ࡱ> ` 0 bjbjss <PPPPPPP(,{:p>>>vB ߜ3ܢ$hP$,rv$,$,PP>>4*HHH$,x P>P>ߜH$,ߜHH9 PPŖ> MMN6Y<C?<{0`FNxŖPӖp#H&D(>Gp{$,$,$,$,$  PPPPPP  WORLD METEOROLOGICAL ORGANIZATION ________________________  INTERGOVERNMENTAL OCEANOGRAPHIC COMMISSION (OF UNESCO) ________________________ JOINT WMO-IOC TECHNICAL COMMISSION FOR OCEANOGRAPHY AND MARINE METEOROLOGY (JCOMM) MANAGEMENT COMMITTEE SEVENTH SESSION MELBOURNE, AUSTRALIA, 8 TO 12 DECEMBER 2008MAN-VII/Doc. 4.3(1) (24.XI.2008) __________ ITEM 4.3 Original: ENGLISH Satellite (aligned with the JCOMM Operating Plan) (Submitted by the Secretariat) Summary and Purpose of Document This document provides for proposals from the JCOMM Cross Cutting Team on Satellite Data Requirements for aligning JCOMM Operating Plan with the WMO and IOC Strategic Planning in terms of (i) deliverables and/or achievements planned for presentation to JCOMM-III, (ii) satellite work plan for the remaining intersessional period, and (iii) satellite work plan for the next intersessional period. The document also addresses issues and opportunities that need action or discussion by the Management Committee to be recommended to both WMO and IOC Executive Bodies, as well as other issues to be discussed by the Management Committee. ACTION PROPOSED The Management Committee is invited to: Review and agree on deliverables and/or achievements planned for presentation to JCOMM-III; Review and agree on OPA work plan for the remaining intersessional period; Review and agree on OPA work plan for the next intersessional period; Address issues and opportunities that need action or discussion by the Management Committee to be recommended to both WMO and IOC Executive Bodies; Recommend updating the JCOMM OPA Strategic workplan to address WMO & IOC Strategic planning, and include requirements expressed in the JCOMM Statement of Guidance for Ocean Applications Provide guidance regarding the integrated (space and in situ) observing strategy document Make recommendations regarding establishing better links with CBS Make recommendations regarding integration of satellites in the WIGOS Pilot Project for JCOMM ______________________ Appendices: A. Deliverables and/or Achievements planned for presentation to JCOMM-III B. Programme Area work plan for the remaining intersessional period Programme Area work plan for the next intersessional period CBS Expert Team on Satellite Systems (ET-SAT) CBS Expert Team on Satellite Utilization and Products (ET-SUP) Statement of Guidance for Ocean Applications Statement of Guidance for Global Numerical Weather Prediction Statement of Guidance for Regional Numerical Weather Prediction Statement of Guidance for Synoptic Meteorology Statement of guidance for Seasonal and Inter-Annual (SIA) forecasts DISCUSSION 1. Updating the JCOMM OPA Strategic workplan 1.1 The priority satellite observation requirements in support of JCOMM applications are detailed in the JCOMM Observations Programme Area strategic workplan for building a sustained Global Ocean Observing System in support of the Global Earth Observation System of Systems. The priority variables (Essential Climate Variables) include at the time being: sea surface temperature, sea surface height, surface vector winds, ocean colour, and sea ice. 1.2 The plan needs to be updated to reflect the WMO and IOC Strategic planning. In particular, WMO as engaged in the WMO Integrated Global Observing Systems (WMO ER 4), and a WIGOS Pilot Project for JCOMM established. The integration of satellite observations needs to be properly addressed in this framework (see also paragraph 4 below). 1.3 The gap analysis produced by JCOMM as part of the Statement of Guidance for Ocean Applications (Appendix F) is addressing the requirements for Met-ocean forecasts and services (global and regional wave modelling and forecasting, marine meteorological services, including sea-ice, and ocean mesoscale forecasting). In this context, wave observations and sea level are key variables for which satellite observations are needed. Statements of Guidance for Global Numerical Weather Prediction (Appendix G), Regional Numerical Weather Prediction (Appendix H), Synoptic Meteorology (Appendix I), and Seasonal and Inter-Annual (SIA) forecasts (Appendix J) are also addressing requirements for ocean variables. As these requirements, especially for waves, are not properly reflected in the JCOMM OPA Strategic workplan, the latter ought to be updated accordingly. 2. Integrated (space and in situ) observing strategy document 2.1 As discussed at MAN-VI, Eric Lindstrom was tasked to draft a more comprehensive document on the integrated (space and in situ) observing strategy for a number of geophysical variables including sea surface temperature, sea surface height, ocean vector winds, chlorophyll-a, sea-ice, sea state, and sea surface salinity. The final document should to be delivered to JCOMM-III and will address the integrated (space and in situ) observing strategy for these geophysical variables with emphasis on operational utility and on the integrated nature of the space and in situ observing components. Requirements for wave observations should also be addressed in the document. MAN may wish to discuss the audience for this document and how to most effectively address the space agencies with this guidance. 3. Relationship with CBS 3.1 The fifth Session of the Implementation Coordination Team on the Integrated Observing System (ICT-IOS-5) (Geneva, Switzerland, 15-18 September 2008) noted JCOMMs efforts to develop global wave observing capabilities to address the requirements for Maritime Safety Services (MSS), calibration / validation of satellite wave sensors, the description of the ocean wave climate and its variability on seasonal to decadal time scales, and the role of waves in the coupled ocean-atmosphere system, and their inclusion in weather and climate models. The ICT-IOS invited JCOMM to develop links with the CBS Expert Teams on Satellite Systems (ET-SAT) and Satellite Utilization and Products (ET-SUP) in assessing satellite capabilities for obtaining this information (see TOR of the two Expert Teams in Appendix D and E). 3.2 ICT-IOS-5 recognized that WIGOS concept should foster effective integration of satellite and in-situ observations; however, little involvement of satellite expert groups is seen so far. It proposed that satellite components be incorporated into relevant WIGOS Pilot Projects. 3.3 The ICT-IOS-5 requested that the level of involvement of the WMO Satellite Programme in the WIGOS Pilot Projects be increased, particularly regarding the Hydrology and Marine Pilot Projects. This should be reflected in the Future Plans of the relevant CBS Expert Teams. 4. WIGOS Pilot Project for JCOMM 4.1 The meeting of the joint Steering Group for the IODE Ocean Data Portal and the WIGOS Pilot Project for JCOMM (ODP-WIGOS2) (Geneva, Switzerland, 18-19 September 2008) noted the development of a proposal for an Ocean Surface Vector Wind Virtual Constellation to be established under the Committee on Earth Observing Satellites (CEOS). A draft study report and implementation plan for the OSVW virtual constellation, prepared by Stan Wilson (NOAA, USA), was presented to the Steering Group. The meeting agreed that the proposal connected well with the WIGOS exercise and invited CEOS to consider its integration in the WIGOS framework in line with the WIGOS CONOPS. This study was also presented to the CEOS Strategic Implementation Team (SIT) at its 22nd meeting in Tokyo September 17-18, 2008. 4.2 The ODP-WIGOS2 meeting reviewed the potential partners and data contributors for participating in the WIGOS Pilot Project for JCOMM. It was agreed to place priority on thirteen potential partners who would make specific data sets available through the ODP and/or WIS. Two of them are satellite related: The GODAE High-Resolution SST (GHRSST) Pilot Project, and the Virtual constellation for Ocean Surface Vector winds. 4.3 The document detailed in paragraph 2 above can also be regarded as a contribution to the WIGOS Pilot Project for JCOMM. _____________ Appendices: 6 Deliverables and/or Achievements planned for presentation to JCOMM-III  FORMTEXT Observations Programme Area (Satellites)Deliverables and/or AchievementsSummary of the Activity(ies)Decisions/Actions (if any)Recommendations (if any)Formal Recommendation or Resolution required for JCOMM-III (Y/N; and subject)Contribute to Expected Result(s) (WMO/IOC)OPA Strategic workplanUpdated Strategic Workplan presented to the Session. The plan was updated according to latest developments, including consideration of WIGOS, and new requirements (JCOMM Statement of Guidance)Endorse workplanUrge Members to commit resources towards achieving the implementation targets and sustaining the missionsY; Implementation of the JCOMM OPA Strategic workplanWMO ER 4 IOC HLO 2 (JCOMM)Integrated (space and in situ) observing strategy documentDocument presented to the sessionEndorse documentUrge Members to commit resources towards achieving the implementation targets and sustaining the missions, and develop a strategy for approaching the satellite agencies with this guidance via established channels at the WMO and IOCNWMO ER 4 IOC HLO 1, 2 Programme Area Work Plan for the remaining intersessional period  FORMTEXT Observations Programme Area (Satellites)DeliverablesSummary of the Activity(ies)By whom (Group/Team)Key Performance Target(s) and Indicator(s)Risks (likelihood of occurrence (low, medium, high) and severity of the consequences from non occurrence (low, medium high) Contribute to Expected Result(s) (WMO/IOC)Links with other Programmes in WMO and IOCOPA Strategic workplanOCG-III meeting in 2009 to address: Consideration of WMO & IOC Strategic planning Consideration of JCOMM Statement of GuidanceOPAKPT: Updated workplan KPI: 0 (fail) or 1 (success) Likelihood: High Severity: HighWMO ER4, IOC HLO 2WIGOS CBS (ICT-IOS, ET-EGOS, ET-SUP, ET-SAT) GOOSIntegrated (space and in situ) observing strategy documentEric Lindstrom to draft document Document to be reviewed by JCOMM & CBS experts Final draft approved by JCOMM Co-PresidentsOPAKPT: Document available KPI: 0 (fail) or 1 (success) Likelihood: High Severity: HighWMO ER4, IOC HLO 2WIGOS CBS (ICT-IOS, ET-EGOS, ET-SUP, ET-SAT) GOOS, GCOS, OOPCCompletion and sustainability of the observing systemCoordination undertaken by email mainly for: Assisting in the development of the Virtual constellation of Surface Vector Wind (SVW) Contributing to the development of global wave observing capability (in liaison with ET-SAT, ET-SUP) Contributing to the continued development and sustainability of GHRSST Sustainability of missions (sea level in particular)OPAKPT: Completion of the satellite ocean observing system KPI: Percentage of completionLikelihood: Low Severity: MediumWMO ER4, 5 IOC HLO 1,2WIGOS CBS (ICT-IOS, ET-EGOS, ET-SUP, ET-SAT) GOOSWIGOS Pilot Project for JCOMMOne meeting of the joint Steering Group (late 2009) to coordinate following activities: Providing data sets through GTS and WIS (GHRSST, SVW) Integration/documentation of Best Practices (to feed in appropriate WMO & IOC Manuals and Guides)ODP-WIGOS & OPAKPT: Integrated best practices documented and two data sets feeding into WIS KPI: Best practices documented: success=1; fail=0; plus ratio of data sets contributed to WIS (n/2) Likelihood: Medium Severity: MediumWMO ER4, 5 IOC HLO 2WIGOS, WIS CBS (ICT-IOS, IPET-MI, ET-SUP, ET-SAT) IODE Programme Area Work Plan for the next intersessional period  FORMTEXT Observations Programme Area (Satellites)DeliverablesPriority (low, medium, high)Summary of the Activity(ies)By whom (Group/Team) (Suggest changes on the PA structure if required)Key Performance Target(s) and Indicator(s)TimelinesRisks (likelihood of occurrence (low, medium, high) and severity of the consequences from non occurrence (low, medium high)Contribute to Expected Result(s) (WMO/IOC)Links with other Programmes in WMO and IOC2010201120122013Completion and sustainability of the observing systemHighCoordination by email mainly; participation of JCOMM experts at ET-Sat, ET-SUP, CEOS, CGMS as appropriate Coordination on requirements and provision of information on satellite planning through JCOMMOPS, then OPSC Contribute to the development of the Virtual constellation for Surface Vector Wind (in liaison with ET-SAT, ET-SUP) Contribute to the development of global wave observing capability (in liaison with ET-SAT, ET-SUP) Contribute to the continued development and sustainability of GHRSST Sustainability of missions (sea level in particular)OPAKPT: Completion of the satellite ocean observing system KPI: Percentage of completionxxxXLikelihood: Low Severity: HighWMO ER 4 IOC HLO 1,2WIGOS CBS (ICT-IOS, ET-EGOS, ET-SUP, ET-SAT) GOOS GCOS OOPCIntegration in WIGOSHighOne meeting of the joint Steering Group in 2010 Coordination by email Provide data sets through WIS (Sea level, GHRSST, SVW, Ocean Color, Sea Ice, Waves) Integration/documentation of Best Practices (to feed in appropriate WMO & IOC Manuals and Guides) Contribute to the Business plan for the WIGOS PP for JCOMM OPD-WIGOS & OPAKPT: Integrated best practices documented and two data sets feeding into WIS KPI: Best practices documented: success=1; fail=0; plus ratio of data sets contributed to WIS (n/6)xXxxLikelihood: Medium Severity: HighWMO ER 4, 5 IOC HLO 2WIGOS, WIS CBS (ICT-IOS, IPET-MI, ET-SUP, ET-SAT) IODE  CBS Expert Team on Satellite Systems (ET-SAT) Terms of Reference (a) Provide technical advice with respect to both operational and R&D environmental satellites to assist in the integration of WMO-coordinated observing systems; (b) Advise CBS through ICT-IOS on matters requiring feedback to the WMO Consultative Meetings on High-level Policy on Satellite Matters; (c) Assess the observation, collection, and analysis systems relating to the use of operational and R&D environmental satellites contributing, or with the potential to contribute, to the space-based subsystem of the GOS, and to suggest improvements of system capabilities, particularly with respect to developing countries; (d) Assist CBS in assessing the status of implementation of the space-based subsystem of the GOS and the adequacy of plans for implementation for meeting established requirements for satellite data and products; (e) Make recommendations with respect to the transition of relevant R&D instruments to operational environmental satellites; (f) Coordinate with other relevant CBS teams with a view to making recommendations on matters, such as the exchange, management, and archiving of satellite data and products, radio frequency utilization, as well as education an training and other appropriate capacity-building measures related to satellite meteorology; (g) Identify and assess opportunities and/or problem areas concerning satellite technology and plans of relevant satellite operators, and inform CBS timely and comprehensively through ICT-IOS. ________________ CBS Expert Team on Satellite Utilization and Products (ET-SUP) Terms of Reference In following the rolling requirements review for the Strategy to Improve Satellite System Utilization, analyse the 2006 biennial questionnaire, compile a list of recommended actions based on that analysis and prepare a new technical document, including a summary analysis from the Virtual Laboratory for Satellite Data Utilizations Centres of Excellence; Extend the regional ADM concept and principles to IGDDS for operational and R&D satellites, in close coordination with the CGMS standing working group on this issue and with WIS activities aimed at harmonizing the services to the maximum extent possible; Review present and future R&D satellite data and products including their availability and applications in view of better utilization by WMO Members; Represent WMO Member needs to the Virtual Laboratory for Satellite Data Utilization in relevant areas, including: Organize training events aiming at further increasing the number of staff and their skills in full utilization of satellite data, from both operational and R&D satellite data; Help ensure Members have access to training materials and courses, as well as provide advice on ways to access data, products, and algorithms from both operational and R&D satellites; With the Virtual Library Focus Group, evaluate the success and needs of the Virtual Library components and suggest strategies for improving its performance; Begin preparation for global high profile global training event to take place in 2006 or 2007; Prepare documents to assist Members, summarizing the results from the above activities. ________________ 3.8 STATEMENT OF GUIDANCE FOR OCEAN APPLICATIONS (Updated June 2008) This Statement of Guidance (SOG) was developed through a process of consultation to document the observational data requirements to support ocean applications. This version was based originally on the JCOMM Users Requirement Document, which was prepared by the Chairpersons of the Expert Teams under the JCOMM Services Programme Area. It is expected that the statement will be reviewed at appropriate intervals by the JCOMM Services Programme Area Coordination Group to ensure that it remains consistent with the current state of the relevant science and technology. 3.8.1. Introduction Marine Meteorology and Oceanography have a global role and embraces a wide range of users from international shipping, fishing and other met-ocean activities on the high seas to the various activities, which, take place in coastal and offshore areas and on the coast itself. In preparation of analyses, synopses, forecasts and warnings, knowledge is required of the present state of the atmosphere and ocean. There are three major met-ocean application areas that critically depend on highly accurate observations of met-ocean parameters: (a) Numerical Weather Prediction (NWP); (b) Seasonal to Inter-annual Forecast (SIA); and, (c) Met-Ocean Forecasts and Services (MOFS), including marine services and ocean mesoscale forecasting. The key met-ocean variables to be observed and forecasted in support of NWP and SIA are addressed in the Numerical Weather Prediction and the Seasonal to Inter-annual Forecast Statements of Guidance (SoG). Met-ocean Services which refer to special elements, such waves, storm surges, sea-ice, ocean currents, etc., critically depend on relevant observational data. This Statement of Guidance provides a brief discussion of the key met-ocean observational requirements for Met-Ocean Services, concentrating on those parameters not covered by previous sections of this document. In particular, variables, such precipitation, air temperature, humidity and cloud cover, required for marine services, and surface heat fluxes required for NWP, are addressed in the global and regional NWP SoG. The requirements for met-ocean forecasts and services stipulated here are based on a consensus of the met-ocean modelling and forecasting communities. It builds on the requirements for global and regional wave modelling and forecasting, marine meteorological services, including sea-ice, and ocean mesoscale forecasting, and represents in addition those variables that are known to be important for initialising, testing and validating models and assimilation, as well as for providing services. 3.8.2. Data Requirements The following terminology has been adhered to as much as possible: poor (minimum user requirements are not being met), marginal (minimum user requirements are being met), acceptable (greater than minimum but less than optimum requirements are being met), and good (near optimum requirements are being met). 3.8.2.1 Wind-Wave parameters (significant wave height, dominant wave direction, wave period, 1D frequency spectral wave energy density, and 2-D frequency-direction spectral wave energy density) Global and regional wave models are used to produce short- and medium-range wave forecasts (typically up to 7 days) of the sea state, with a horizontal resolution of typically 30-100 km for global models, and down to 3-4 km for regional models (with a natural progression to higher resolution expected). Marine forecasters use wave model outputs as guidance to issue forecasts and warnings of important wave variables (such as, significant wave height and dominant wave direction) for their area of responsibility and interest, in support of several marine operations. Specific users usually require additional parameters that are obtained from the directional spectrum of wave energy density. The observational requirements for global and regional wave modelling are depended on the applications for which the data are required and based on the need to provide an accurate analysis of the sea state at regular intervals (typically every 6 hours). These includes: (a) assimilation into wave forecast models; (b) validation of wave forecast models; (c) calibration / validation of satellite wave sensors; (d) ocean wave climate and its variability on seasonal to decadal time scales; and, (e) role of waves in coupling. Additionally, wave observations are also required for nowcasting (0 to 2 hours) and issuing / cancelling warnings, and very-short-range forecasting (up to 12 hours) of extreme waves associated with extra-tropical and tropical storms, and freak waves (in this case, in combination with other variables such as ocean currents). Whilst nowcasting is largely based on observational data, very-short range forecasting is being generated based on high-resolution regional wave models. The key model variables for which observations are needed are: (i) significant wave height; (ii) dominant wave direction; (iii) wave period; (iv) 1-D frequency spectral wave energy density; and (v) 2-D frequency-direction spectral wave energy density. Also important are collocated surface wind observations which are advantageous for validation activities. Further additional parameters are of value for use in delayed mode validation (e.g. full time series of sea surface elevation). The geographical coverage of the in situ wave data is still very limited and most measurements are taken in the Northern Hemisphere (mainly in the North America and Western Europe coasts). The majority of these data are provided by in situ non-spectral and spectral buoys and ships with acceptable frequency and marginal accuracy. Limited number of in situ spectral buoys is available around the globe. Current in situ reports are not standardized resulting in impaired utility. Differences in measured waves from different platforms, sensors, processing and moorings are identified. In particular, a systematic 10% bias identified between US and Canadian buoys, the two largest moored buoy networks. Standardized measurements and metadata are essential to ensure consistency between different platforms. In situ measurements are currently too sparse in the open ocean (poor coverage) to be of particular value, but could potentially provide higher accuracy observations to complement and correct for biases in the satellite observations. Validation requirement is for average 1000km spacing requiring a network of around 400 buoys with minimum 10% / 25cm accuracy for wave height and 1 second for wave period. Higher density (horizontal resolution of 500km) would be advantageous for data assimilation. In regions where known non-linear interactions between waves and local dynamic features exist (e.g., Agulhas Current, Gulf Stream, and Kuroshio Current) higher density (horizontal resolution of 100km) would be also advantageous. Satellite altimeters provide information on significant wave height with global coverage and good accuracy. However, horizontal / temporal coverage is marginal. Minimum 20km resolution is required for use in regional wave models. Along track spacing is likely to be adequate to meet this requirement; cross-track spacing is not. Multiple altimeters are therefore required to provide adequate cross-track sampling. Fast delivery (within 6 hours at most) is required with accuracy of 10% / 25cm for wave height, and 1 second for wave period. Long-term, stable time series of repeat observations are required for climate applications. Information on the 2-D frequency-direction spectral wave energy density is provided by SAR instruments with good accuracy but marginal horizontal / temporal resolution. Horizontal resolution of 100km is required for use in regional models, with fast delivery required (within 6 hours). Real aperture radar capability is expected to be available within 5 years. Coastal wave models require different observing methods to those used for the open ocean due not only to their high-resolution, but also due to limitations of the satellite data close to land, hence for these models systems such as coastal HF radar are of particular importance. These radars provide information on significant wave high with limited coverage, good accuracy and acceptable horizontal/temporal resolution. High-resolution observations (up to 100m resolution) are required over coastal model areas. Potential contribution from other technologies and platforms (e.g., navigation radar, other radars, and shipborne sensors such as WAVEX) should be developed where they can contribute to meeting the specified requirements. 3.8.2.2 Sea Level Traditionally, permanent sea level stations around the world have been primarily devoted to tide and mean sea level applications, both non-requiring real or near-real time delivery. This has been the main objective of the Global Sea Level Observing System (GLOSS). Because of this focus, not only are wind-waves filtered out from the records by mechanical or mathematical procedures, but any oscillation between wind-waves and tides (e.g., seiches, tsunamis, storm surges, etc.) has not been considered a priority; in fact, these phenomena are not properly monitored (standard sampling time of more than 5 to 6 minutes). Due to the increased demand for tsunamis, storm surges and coastal flooding forecasting and warning systems, for assimilation of in situ sea level data into ocean circulation models, and for calibration / validation of the satellite altimeter and models, this range of the spectrum should be covered from now on, and it would be necessary to consider this when choosing a new instrument and designing the in situ sea level stations. Additionally, there has been an emphasis on making as many GLOSS gauges as possible deliver data in real and / or near-real time, i.e., typically within an hour. An ongoing issue with these data is sea level measurements have not been well integrated into NHMSs. The aim of any tide gauge recording should be to operate a gauge which is accurate to better than 1cm at all times; i.e., in all conditions of tide, waves, currents, weather, etc. This requires dedicated attention to gauge maintenance and data quality control. In brief, the major requirements for in situ sea level stations are: A sampling of sea level, averaged over a period long enough to avoid aliasing from waves, at intervals of typically 6 or 15 minutes, or even 1 minute or less if the instrument is to be used also for tsunami, storm surges and coastal flooding forecasting and warning; but in all circumstances the minimum sampling interval should be one hour, which these days is an insufficient sampling for most applications marginal accuracy; Gauge timing be compatible with level accuracy, which means a timing accuracy better than one minute (and in practice, to seconds or better, with electronic gauges) marginal accuracy; Measurements must be made relative to a fixed and permanent local tide gauge bench mark (TGBM). This should be connected to a number of auxiliary marks to guard against its movement or destruction. Connections between the TGBM and the gauge zero should be made to an accuracy of a few millimetres at regular intervals (e.g., annually) acceptable accuracy; GLOSS gauges to be used for studies of long term trends, ocean circulation and satellite altimeter calibration / validation need to be equipped with GPS receivers (and monitored possible by other geodetic techniques) located as close to the gauge as possible; The readings of individual sea levels should be made with a target accuracy of 10 mm acceptable accuracy; Gauge sites should, if possible, be equipped for recording tsunami and storm surge signals, implying that the site be equipped with a pressure sensor capable of 15-seconds or 1-minute sampling frequency, and possibly for recording wave conditions, implying 1-second sampling frequency poor accuracy; and, Gauge sites should be also equipped for automatic data transmission to data centres by means of satellite, Internet, etc., in addition to recording data locally on site. Coastal sea level tide gauges are invaluable for refining tsunami warnings, but due to nearshore bathymetry, sheltering, and other localized conditions, they do not necessarily always provide a good estimate of the characteristics of a tsunami. Additionally, the first tide gauges to receive the brunt of a tsunami wave do so without advance verification that a tsunami is under way. In order to improve the capability for the early detection and real-time reporting of tsunamis in the open ocean, some countries have begun deployment of tsunameter buoys in the Pacific, Indian, and Atlantic Oceans and other tsunami-prone basins. Due to cost constrains, the number of DART buoys deployed and maintained is still limited marginal geographic coverage and good accuracy. The geographic coverage of the in situ sea level data is acceptable for studies of long-term trends, but marginal for other applications. Tsunami and storm surge-prone basins (e.g., Bay of Bengal, Gulf of Mexico and Pacific Islands) require higher density of sea level observations. Sea level measurements should be accompanied by observations of atmospheric pressure, and if possible winds and other environmental parameters, which are of direct relevance to the sea level data analysis. Satellite altimeters provide information on sea surface height with global coverage and good accuracy, i.e., within 1cm at a basin scale. However, horizontal / temporal coverage is marginal. The main limitation of the satellite altimeter in reproducing the non-long-term sea level changes is the spatial sampling because the repeat orbit cycle leads to an across-track spacing of about 300km at mid-latitudes. This sampling cannot resolve all spatial scales of mesoscale and coastal signals which have typical wavelengths of less than 100km at mid-latitude. The scales are even shorter at high latitudes (around 50km), but fortunately the ground track separation decreases with latitude. Thus, to cover the whole mesoscale and coastal domain it is necessary to increase the spatial sampling by merging (in an optimal way with cross-calibration) different altimetry data sets. The temporal changes in sea level are usually determined along the repeat tracks of altimetry satellites. In areas close to the coasts (less than 20km) the difficulty is even larger because of the proximity of land which the track spacing is too coarse to resolve the short scales of the sea level changes. Thus, adaptive tracker and / or specific re-tracking of altimeter waveforms and near-shore geophysical corrections (such as coastal tide models and marine boundary layer tropospheric corrections) are needed. 3.8.2.3 Sea-Ice parameters (thickness, coverage / concentration, type / form, and movement) Sea-ice charts containing information of sea-ice thickness, coverage / concentration, type / form and movement are produced in support of marine operations, validation of models and for climatological studies. Although broad knowledge of the extent of sea-ice cover has been totally revolutionized by satellite imagery, observations from shore stations, ships and aircraft are still of great importance in establishing the ground truth of satellite observations. At present, observations of floating ice depend on instrumental and, to lesser extent, on visual observations. The instrumental observations are by conventional aircraft and coastal radar, visible and infra-red airborne and satellite imagery, and more recent techniques, such as passive microwave sensors, laser airborne profilometer, scatterometer, side-looking (airborne) radar (SLAR / SLR) or synthetic aperture radar (SAR, satellite or airborne). Visual observations from coastal settlements, lighthouses and ships provide an ice report several times a day as the ice changes in response to wind and ocean currents, but the total area of ice being reported is very small (e.g., from a ship, observations can cover a radius of only 78 km; from a coastal lighthouse, observations can cover a radius of 20km). In some marine areas, such as the Baltic Sea, visual observations may be present in sufficient numbers that a reasonable proportion of the ice cover can be reported each day by a surface network. In others such as the Gulf of St Lawrence, where the waterways are broad and the shores often unsettled, no shore reporting system can provide data on more than a very small percentage of the total ice cover. Although surface based reports can provide excellent detail about the ice, especially its thickness, it is generally recognized that for most areas, the surface reports are not really adequate to describe ice conditions fully. Surface reports from shore stations, ships and drifting buoys provide accurate information on ice amount, thickness, movement and its deformation over rather small areas. When many vessels and fixed observing points are available accurate information can be provided in restricted waterways. Many areas of the Kattegat and Baltic Sea coastline fall into this category. Reports about the ice coverage taken from the air, i.e., helicopters and fixed-wing aircraft, have the advantage of a much better viewing angle; the platforms flying speed allows a great deal more of the sea-ice to be reported; and problems of remoteness from airports or other suitable landing sites can be overcome by using long-range aircraft. In the various stages of development of sea-ice, estimates its amount; notes its deformation and the snow cover or stage of decay data are provided by visual estimation. Comprehensive aerial reporting has its own particular requirements beginning with an accurate navigational system when out of sight of land. Inclement weather fog, precipitation and low cloud will restrict or interrupt the observations and the usual problems of flying limits at the aircraft base may also be a factor even if the weather over the ice is adequate for observing. Recent advances in technology are now permitting more accurate data to be obtained by aerial observations. SLAR and SAR can provide information, which documents precisely the distribution and nature of the ice in one or two belts along the flight path of the aircraft for distances of up to 100km on each side. Unlike most other sensors, the radar has the capability of monitoring the ice under nearly all weather conditions. When no fog or low clouds are present a laser airborne profilometer can be used to measure the height and frequency of ridges on the ice, and under similar conditions an infra-red airborne scanning system can provide excellent information with regard to floe thickness in the ranges below 30cm. The advent of earth-orbiting meteorological satellites has added a third, and now the most important and predominant mode of observing sea ice but again there are some restrictions. The spectral range of the sensors may be visible, infra-red, passive or active microwave or a combination of these. Satellite coverage may be broad at low resolution or cover a narrow swathe at high-resolution. In the latter case, data from a particular location may be obtained only at temporal intervals of several days. In general, most meteorological satellites provide 1012 passes daily in the Polar Regions, i.e., complete coverage of Polar Regions once or twice a day. These satellites provide visible and infra-red imagery with resolutions of 250m1km; and passive microwave and scatterometer data at coarser resolutions of 670km good horizontal / temporal coverage. Visible and infra-red data do not have cloud-penetrating capability while microwave data are practically cloud independent. Active microwave SAR data are characterized by improved ground resolution (approximately 10100m) but a reduced coverage due to narrow swathes and greater revisit time between exact repeat orbits. Snow cover on the ice and puddles on the floes are other complicating factors. Interpretation of SAR images may be even more difficult due to the ambiguities associated with SAR backscatter from sea-ice features that vary by season and geographic region. Space-borne sensors can provide precise data on the location and type of ice boundary, concentration or concentration amounts (in tenths or percentages) and the presence or absence of leads, including their characteristics, if radar sensors are used. Less accurate information is provided on the stages of development of the sea ice including the FY / MY ratio, forms, with an indication of whether ice is land-fast or drifting, stages of ice melting and ice surface roughness. Flow motion over approximately 1224-hour intervals can often be determined through the use of imagery from sequential orbits. 3.8.2.4 Sea-Surface Temperature (SST) High-resolution sea-surface temperature (SST) observations are required for: (i) NWP (addressed in the global and regional NWP SoGs); (ii) Seasonal to Inter-annual Forecast (addressed in the SIA SoG); (iii) ocean forecasting systems (assimilation in and validation of ocean models); and, (iv) marine services. Coastal and inland seas users are defined as those using SST data products for regional ocean modelling and marine services. SST in the coastal and inland regions have a large variability due to the diurnal cycle of solar radiation, which enhances surface characteristics of the land and sea and forces land-air-sea interactions, i.e., land-sea breezes. Typically, this user group has a requirement for ultra-high resolution SST data sets (1km spatial resolution and <6 hours temporal resolution), with good accuracy (< 0.1 C) and temporal coverage (hourly). The table below specifies the consolidated user requirements for ocean forecasting systems and marine services. Spatial resolution (km)Delivery timeliness (hours)Accuracy (C)TargetThresholdCoastal Ocean< 113< 0.1Open Ocean5-1016< 0.1 Ships and moored and drifting buoys provide observations of sea-surface temperature of good temporal frequency and acceptable accuracy as long as required metadata (e.g., the depth of the measurement is essential for deriving the diurnal cycle and the foundation temperature) are provided. Coverage is marginal or worse over some areas of the ocean globe. There is a requirement for high quality SST in open ocean, ideally with accuracy < 0.1 C on 5km spatial scale, and fast delivery (availability within 1h). In coastal regions, higher density is required (accuracy < 0.1 C on 1km spatial scale). Drifting Buoy and other in situ SST measurements are used for calibration / validation of satellite data, in the error estimation for observations products and in the combined analysis products. They are critically important providing bias correction of these data. Satellite biases can occur from orbit changes, satellite instrument changes and changes in physical assumptions on the physics of the atmosphere (e.g., through the addition of volcanic aerosols). Thus, drifting buoy and other in situ data are needed to correct for any of these changes. Satellite measurements provide high-resolution sea surface temperature data. Both infra-red and microwave satellite data are important. Microwave sea-surface temperature data have a significant coverage advantage over infra-red sea-surface temperature data, because microwave data can be retrieved in cloud-covered regions while infra-red cannot. However, microwave sea-surface temperatures are at a much lower spatial resolution than infra-red. In addition microwave sea-surface temperatures cannot be obtained within roughly 50km of land. A combination of both infra-red and microwave data are needed because they have different coverage and error properties. Instruments on polar satellites provide information with global coverage in principle, good horizontal and temporal resolution and acceptable accuracies (once they are bias-corrected using in situ data), except in areas that are persistently cloud-covered (which includes significant areas of the tropics). High-resolution SSTs (1 km) can be retrieved by the LEO infra-red radiometer and rather degraded resolution SSTs (5 km) from the GEO IR radiometer. However, quantitative detection of the SST diurnal cycle is still challenging subject but drifters can provide high temporal resolution SST data. In contrast, microwave radiometers cannot be used for the coastal applications because of: (a) rather coarse spatial resolution; and, (b) contamination of land signals in the measurement in the coastal sea. 3.8.2.5 Sub-surface Temperature, Salinity and Density Sub-surface temperature, salinity and density observations are required for: (i) Seasonal to Inter-annual Forecast (SIA) (addressed in the SIA SoG); (ii) for testing and validation of ocean models; and, (iii) marine services. The Tropical Atmosphere Ocean (TAO) / TRITON moored buoy network provides data with good frequency and accuracy, and acceptable spatial resolution for the tropical Pacific. The TAO Tropical Moored Buoy Arrays provide data of marginal vertical resolution for marine services applications (~50m down to 500m), which require high vertical resolution data in the mixed layer. The tropical moored network in the Atlantic (PIRATA) is acceptable. The Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) is being developed but is providing only marginal sampling at the moment. Sustained funding for the Tropical Moored Buoy Arrays remains a matter of concern. Ships (XBT profiles) provide temperature profile data of acceptable spatial resolution over many of the targeted frequently repeated and high [horizontal resolution] density lines. However, about half the targeted lines are still poorly sampled. Temporal resolution is marginal, and acceptable in some ship specific lines. XBTs provide data with good vertical resolution (typically 1m) down to 1000m depth in delayed mode, but real-time data are constrained to limitation in the GTS traditional character codes being used at the moment. The Argo profiling floats provide global coverage of temperature and salinity profiles to ~2000 m, mostly with acceptable-to-good vertical (every ~5m) and spatial resolutions, but only marginal temporal resolution, particularly for marine services. The accuracy is acceptable for assimilation in ocean models and for marine services. 3.8.2.6 Ocean Colour Ocean colour observations are required for marine services applications and for validation of ocean models. The ocean colour remote sensing provides images of biological / non-biological parameters with high-spatial resolution (250m to 1km). The ocean colour can detect several types of marine pollutions, harmful algae and red tide plankton blooms. Parameter retrieval algorithm in turbid waters is not established yet, but developments of an observation system based on the Ocean Colour remote-sensing have presented promising results for a future operational observing system. In situ measurements are needed to complement satellite ocean colour observations. These measurements should be accompanied by real-time daily observations of ocean temperature, surface wind and derived dynamic height. 3.8.2.7 3-D Ocean Currents Observations of 3-D ocean currents are required for marine services applications, and for testing and validation of ocean models. Inferred surface currents from drifting buoys are acceptable in terms of spatial coverage and accuracy and marginal temporal resolution. Moored buoys are good in temporal resolution and accuracy, but marginal or worse otherwise. The Acoustic Doppler Current Profiler (ADCP) provides observations of ocean currents over a range of depths, with acceptable accuracy. Coverage is marginal or worse over some areas of the ocean globe, and marginal vertical resolution for marine services applications, which require high vertical resolution data in the mixed layer. Satellite altimetry is being used to infer the distribution of ocean currents (geostrophic velocity). Satellite altimetry provides more homogeneous space and time coverage than in situ observations, but they cannot determine mean currents. Velocities derived from Lagrangian drifters are acceptable in terms of accuracy (2 cm / s) and spatial coverage (5 lat. / lon.), but marginal temporal resolution (typically 1 month). Satellite altimetry permits to derive the ageostrophic motion (e.g., centrifugal, Ekman, ageostrophic submesoscale) and the time-mean motion. Satellite altimetry permits to detect geostrophic eddies. Global mean dynamic topography can be obtained by combining information on the geoid, altimeters, drifters, wind field, and hydrography. These products are poor in terms of timeliness required for marine services applications. HF Radars provide for good temporal and spatial resolution in coastal regions, and marginal accuracy. 3.8.2.8 Bathymetry, Coastal Topography and Shorelines Observations of bathymetry, coastal topography and shorelines are required for ocean and coastal modelling. Very high-resolution data are required due to the gradual changes of the coastline through erosion and accretion processes relating to coastal meteorological and oceanographic phenomena (e.g., waves, storm surges and sea ice). Visible and infrared imagers (i.e., Landsat, Spot), synthetic aperture radar (SAR) and aerial photography provide good information on the coastline and coastal topography. Many sonar techniques have been developed for bathymetry. Satellite altimeters map deep-sea topography by detecting the subtle variations in sea level caused by the gravitational pull of undersea mountains, ridges, and other masses. These provide global coverage and acceptable-to-good accuracy. 3.8.2.9 Surface Wind over the Ocean and Coastal Areas (10m) High-resolution surface wind over the ocean and coastal areas is required as an input field for ocean models (including wave models), and for marine services. The surface wind is a key variable for driving ocean models and to nowcast and forecast marine meteorological and oceanographic conditions. It is strongly influenced by the coastal topography and land-sea surface conditions. Traditional global and regional NWP products do not have enough spatial resolution for marine services applications, as well as for coastal modelling. Voluntary Observing Ships (VOS) and meteorological and oceanographic moored buoys provide observations of acceptable frequency. Accuracy is acceptable. Coverage is marginal or worse over large areas of the ocean globe. The tropical moored buoy network has been a key contributor for surface winds over the last decade, particularly for monitoring and verification, providing both good coverage and accuracy in the equatorial Pacific. Fixed and drifting buoys and VOS outside the tropical Pacific provide observations of marginal coverage and frequency; accuracy is acceptable. Wind observations from drifting buoys are poor. Polar satellites provide information on surface wind, with global coverage, good horizontal resolution, and acceptable temporal resolution and accuracy. The microwave scatterometer has limited spatial resolution (25km), and the wide swath SAR measurement has limited temporal resolution (one measurement every few days) and provides no wind direction. 3.8.2.10 Surface pressure Ships and buoys take standard surface observations of several atmospheric variables, including surface pressure. In relatively shallow waters, oil platforms do the same, but the frequency and spatial coverage are marginal for marine services applications. Mean sea level pressure is vital to detect and monitor atmospheric phenomena over the oceans (e.g., tropical cyclones) that significantly constrain shipping. As stated in the SoG for Synoptic Meteorology, even very isolated stations may play an important role in synoptic forecasting, especially when they point out differences with NWP model outputs. 3.8.2.11 Visibility Poor visibility is a major hazard to all vessels because of the increased danger of collision. Surface visibility observations are made primarily by ships, and at the coastal stations (mainly at harbours, where the VTS (Vessel Track System is usually available)). This parameter can vary substantially over short distances. Accuracy is acceptable in coastal areas and marginal in open ocean. Horizontal / temporal resolution is poor over the most of the global ocean. Visibility is deduced from the output of regional atmospheric models (see regional NWP SoG). 3.8.2.12 Summary of the Statement of Guidance for Ocean Applications The following key points summarize the SoG for Ocean Applications: Satellite data are the only means for providing high-resolution data in key ocean areas where in situ observations are sparse or absent; In general, in situ met-ocean data and observations are insufficient for marine services (in particular, for monitor and warning marine-related hazards) and marginal for assimilation in ocean models, including wave models; Many met-ocean measurements have not been well integrated into NHMSs; and, In general, there is a requirement for fast delivery of met-ocean data. The critical met-ocean variables that are not adequately measured (more accurate and frequent measures and better spatial/temporal resolution are required) by current or planned systems are: Waves parameters; Sea level; and Visibility. ________________ 3.1 Statement of Guidance for Global Numerical Weather Prediction (updated 12 June 2008) Global Numerical Weather Prediction (NWP) models are used to produce short- and medium-range weather forecasts (out to 15 days) of the state of the troposphere and lower stratosphere, with a horizontal resolution of typically 20-100 km and a vertical resolution of ~1km. Forecasters use NWP model outputs as guidance to issue forecasts of important weather variables for their area of interest. To initialize these models, an accurate estimate of the complete atmospheric state is required. Observations from surface-based, airborne and space-based platforms are all used to help define this initial state. The observational requirements for global NWP are based on the need to provide an accurate analysis of the complete atmospheric state at regular intervals (typically every 6 hours). Through a data assimilation system, new observations are used to update and improve an initial estimate of the atmospheric state provided by an earlier short-range forecast. The key model variables for which observations are needed are: 3-dimensional fields of wind, temperature and humidity, and the 2-dimensional field of surface pressure. Also important are boundary variables, particularly sea surface temperature, and ice and snow cover. Of increasing importance in NWP systems are observations of cloud and precipitation. In the latter part of the medium-range, the upper layers of the ocean become increasingly important, and so relevant observations are also needed. Modern data assimilation systems are able to make effective use of synoptic observations. Observations are most easily used when they are direct measurements of the model variables (temperature, wind, etc.), but recent advances have also facilitated the effective use of indirect measurements (e.g., satellite radiances, which are linked in a complex but known way to the model fields of temperature, humidity, etc.) and also the extraction of dynamical information from frequent (e.g. hourly) time series of observations. The highest benefit is derived from observations available in near real-time; NWP centres derive more benefit from observational data, particularly continuously generated a synoptic data (e.g., polar orbiting satellite data), the earlier they are received, with a goal of less than 30 minutes delay for observations of geophysical quantities that vary rapidly in time. However most centres can derive some benefit from data up to 6 hours old. In general, conventional observations have limited horizontal resolution and coverage, but high accuracy and vertical resolution. Satellite data provide very good horizontal resolution and coverage but limited vertical resolution, and they are more difficult to interpret and use effectively. Single in situ observations from remote areas can occasionally be of vital importance. Also, a baseline network of in situ observations is currently necessary for tuning the use of some satellite data. Observations are more important in some areas than in others; it is desirable to make more accurate analyses in areas where forecast errors grow rapidly, (e.g., bar clinic zones). Identifying these areas and targeting observations to them is an active area of research. The following sections provide an assessment, for the main variables of interest, of how well the observational requirements are met by existing or planned observing systems. 3-D wind field (horizontal component) Wind profiles are available from radiosondes over populated land areas, and from aircraft (ascent / descent profiles) and wind profilers over some of these areas. In these areas, horizontal and temporal coverage is acceptable and vertical resolution is good. Over most of the Earth - ocean and sparsely-inhabited land - coverage is marginal or absent. Profile data are supplemented by single-level data from aircraft along main air routes only, and by single-level satellite winds (motion vectors from cloud or humidity tracers in geostationary imagery) over low and mid-latitudes. In these areas, horizontal and temporal resolution is acceptable or good, but vertical coverage is marginal. There are very few in situ wind observations from Polar Regions, but recent advances have provided useful satellite winds at high latitudes from research satellite imagery (MODIS and AVHRR). In the lower stratosphere, only radiosondes provide information. Accuracy is good / acceptable for in situ systems and acceptable / marginal for satellite winds. Extension of AMDAR technology (principally for ascent / descent profiles but also for flight level information) offers the best short-term opportunity for increasing observations of wind, although large areas of the world would still remain uncovered. From satellites, Doppler wind lidar technology is being developed to provide 3-D winds of acceptable coverage and vertical resolution, but thick cloud will provide limitations. Advanced geostationary imager-sounders will offer wind profile information in cloud-free areas through tracking of highly-resolved features in water vapour channels. Surface pressure and surface wind Over ocean, ships and buoys provide observations of acceptable frequency. Accuracy is good for pressure and acceptable / marginal for wind. Coverage is marginal or absent over large areas of the Earth. Polar satellites provide information on surface wind - with global coverage, good horizontal resolution, and acceptable temporal resolution and accuracy - in two ways. Scatterometers give information on wind speed and direction, whereas passive microwave imagers provide information on wind speed (only). Several NWP centres have noted the positive impact from both data types, including the analysis and prediction of tropical cyclones. Passive polarimetric radiometers have recently been demonstrated; in addition to wind speed, they offer directional information but of inferior quality to scatterometers at low wind speed. Over land, surface stations measure pressure and wind with horizontal and temporal resolution which is good in some areas and marginal in others. Measurement accuracy is generally good, though this can be difficult to use (particularly for wind) where surface terrain is not flat, because of the sensitivity of the measurements to small scale circulations that global NWP models do not resolve. Surface pressure is not observed by present or planned satellite systems, with the exception of some contribution from radio occultation data (which has been demonstrated theoretically and merits further study). 3-D temperature field Temperature profiles are available from radiosondes over populated land areas and from aircraft (ascent/descent profiles) over some of these areas. In these areas, horizontal and temporal resolution is acceptable and vertical resolution and accuracy are good. Over most of the Earth - ocean and sparsely-inhabited land - coverage is marginal or absent. Profile data are supplemented by single-level data from aircraft along main air routes, where horizontal and temporal resolution and accuracy are acceptable or good. Polar satellites provide information on temperature with global coverage, good horizontal resolution and acceptable accuracy. Vertical resolution from passive microwave and infra-red filter radiometers is marginal, but advanced infra-red systems have improved (acceptable) vertical resolution. Microwave measurements from AMSU provide considerable information, including in cloudy areas, and strong positive impacts have been demonstrated by several NWP centres, to the extent that this is now the single most important source of observational information for global NWP, even in the Northern Hemisphere. Data from high resolution infra-red sounders (AIRS on EOS-Aqua, IASI on MetOp) have also shown strong positive impact, and similar data will be available from instruments on NPP and NPOESS. Satellite sounding data are currently under-utilised over land, but progress in this area is anticipated in the near future. Radio-occultation measurements now complement other systems through high accuracy and vertical resolution in the stratosphere and upper troposphere. 3-D humidity field Tropospheric humidity profiles are available from radiosondes over populated land areas. In these areas, horizontal and temporal resolution is usually acceptable (but sometimes marginal, due to the high horizontal variability of the field), vertical resolution is good and accuracy is good / acceptable. Over most of the Earth - ocean and sparsely-inhabited land - coverage is marginal or absent. Very few aircraft currently provide humidity measurements, and these data are not generally available, but technical advances in this area are anticipated in the next decade. Polar satellites provide information on tropospheric humidity with global coverage, good horizontal resolution and acceptable accuracy. Vertical resolution from passive microwave and infra-red filter radiometers is marginal, but advanced infra-red systems have improved (acceptable) vertical resolution. Microwave measurements from AMSU-B/MHS have shown significant impacts. Data from high resolution infra-red sounders (AIRS on EOS-Aqua, IASI on MetOp) have started to be used operationally, and similar data will be available from instruments on NPP and NPOESS. Geostationary infra-red radiances, particularly in water vapour channels, are also helping to expand coverage in some regions by making measurements hourly and thus creating more opportunities for finding cloud-free areas. Satellite sounding data are currently under-utilised over land, but progress in this area is anticipated in the near future. Radio-occultation measurements complement other systems by providing information on the humidity profile in the lower troposphere. Over ocean, coverage is supplemented by information on total column water vapour from microwave imagers. Over populated land areas, growth is expected in the availability of total column water vapour data from ground-based GPS measurements. Also over land, total column water vapour information is potentially available from near infra-red imagery (e.g., MODIS, MERIS). Sea surface temperature Ships and buoys provide observations of sea surface temperature of good temporal frequency and accuracy. Coverage is marginal or absent over some areas of the Earth, but recent improvements in the in situ network have enhanced coverage considerably. Infra-red instruments on polar satellites provide information with global coverage, good horizontal resolution and accuracy, except in areas that are persistently cloud-covered. Here data from passive microwave instruments on research satellites has been shown to be complementary. Temporal coverage is adequate for short-medium range NWP but, for seasonal / inter-annual forecasting, observation of the diurnal cycle is required, for which present/planned geostationary satellites offer a capability. Sea-ice Sea-ice cover and type are observed by microwave instruments on polar satellite with good horizontal and temporal resolution and acceptable accuracy. Data interpretation can be difficult when ice is partially covered by melt ponds. Operational ice thickness monitoring will be required in the longer term, but is not currently planned. Ocean sub-surface variables In the latter part of the medium-range (~7-15 days), the role of the sub-surface layers of the ocean becomes increasingly important, and hence observations of these variables become relevant. In this respect the requirements of global NWP are similar to those of seasonal and inter-annual forecasting (see SoG on Seasonal and Inter-annual Forecasting). Snow Over land, surface stations measure snow cover with good temporal resolution but marginal horizontal resolution and accuracy (primarily because of spatial sampling problems). Visible / near infra-red satellite imagery provides information of good horizontal and temporal resolution and accuracy on snow cover (but not on its equivalent water content) in the day-time in cloud-free areas. Microwave imagery offers the potential of more information on snow water content (at lower but still good resolution) but data interpretation is difficult. Snow cover over sea-ice also presents data interpretation problems. Soil moisture Microwave imagery and scatterometer data are sensitive to surface wetness, with a penetration depth dependent on the wavelength of the radiation. It is planned to provide operational soil moisture products from ASCAT on MetOp. Data of acceptable temporal and spatial resolution are expected, with marginal accuracy. Passive microwave imagers on research satellites (e.g., SMOS) also offer considerable potential. Some land surface stations report soil moisture routinely with marginal accuracy, but most do not report. Surface air temperature and humidity Over ocean, ships and buoys provide observations of acceptable frequency and acceptable accuracy (except ship temperatures during the daytime, which currently have poor accuracy). Coverage is marginal or absent over large areas of the Earth. Over land, surface stations measure with horizontal and temporal resolution which is good in some areas and marginal in others. Measurement accuracy is generally good, though this can be difficult to use where surface terrain is not flat, because of the sensitivity of the measurements to local variability that global NWP models does not resolve. Satellite instruments do not observe these variables, or do so only to the extent that they are correlated with geophysical variables that significantly affect the measured radiation (i.e., skin temperature and atmospheric layer-mean temperature and humidity). Land and sea-ice surface skin temperature Satellite infra-red and microwave imagers and sounders provide data containing information on these variables, although retrieval accuracy is affected by cloud detection problems and surface emissivity uncertainties, and interpretation is difficult because of the heterogeneous nature of the emitting surface for many surface types. Otherwise, present / planned instruments offer data of good resolution and frequency. Vegetation type and cover Present-day operational satellite imagery from visible / near infra-red channels offers good resolution and frequency, and marginal accuracy. Research instruments, such as MODIS, offer considerably improved accuracy. Clouds Surface stations measure cloud cover and cloud base with a temporal resolution and accuracy that is acceptable but a horizontal resolution that is marginal in some areas and missing over most of the Earth. Satellite instruments offer a wealth of information on cloud. Infra-red imagers and sounders can provide information on cloud cover and cloud-top height of good horizontal and temporal resolution and good/acceptable accuracy. Microwave imagers and sounders offer information on cloud liquid water of good horizontal resolution and acceptable temporal resolution, with an accuracy that is probably acceptable (though validation is difficult). At present the primary problem is not with the cloud observations themselves but with their assimilation, arising from weaknesses in data assimilation methods and in the parameterisation of clouds and other aspects of the hydrological cycle within NWP models. Substantial improvements in these areas will be needed in order to make more use of the available observations over the next decade. Current and planned visible / infra-red imagers offer some information on cloud drop-size at cloud top. Active microwave instruments are required to give more information on the 3-D distribution of cloud water / ice amounts and cloud-drop size. Some research instruments have been launched and more are planned. Precipitation Surface stations measure accumulated precipitation with a temporal resolution and accuracy that is acceptable but a horizontal resolution that is marginal in some areas and missing over most of the Earth. Ground-based radars measure instantaneous precipitation with good horizontal and temporal resolution and acceptable accuracy, but over a few land areas only. Microwave imagers and sounders offer information on precipitation of marginal horizontal and temporal resolution, and acceptable / marginal accuracy (though validation is difficult). Geostationary infra-red imagers offer some information at much higher temporal resolution through the correlation of surface precipitation with properties of the cloud top, but accuracy is marginal due to the indirect nature of this relationship. Satellite-borne rain radars, together with plans for constellations of microwave imagers, offer the potential for improved observations. Ozone Developments are under way to add ozone as a new NWP model variable. More accurate model ozone fields will improve model radiation calculations and the assimilation of infra-red temperature sounding data. The accuracy of total column ozone obtained from satellite instruments is acceptable and will be improved with the launch of high resolution infra-red sounders and more accurate solar backscatter instruments. However, to maintain realistic vertical distributions of ozone in NWP models, some observations of ozone profiles are also needed at lower horizontal and temporal resolution. A few ozonesondes are launched once a week at widely spaced locations, and their data are available to NWP centres for model validation. Wave height, direction and period Ships and buoys provide observations of acceptable frequency and acceptable / marginal accuracy. Coverage is marginal or absent over large areas of the Earth. Altimeters on polar satellites provide information on significant wave height with global coverage and good accuracy. However, horizontal/temporal coverage is marginal. Information on the 2-D wave spectrum is provided by SAR instruments with good accuracy but marginal horizontal/temporal resolution. 3-D aerosol Assimilation of aerosols is generally immature in global NWP but is likely to increase in importance. Operational visible / near infra-red satellite imagery is used to provide estimates of total column amounts over the ocean with good horizontal resolution and acceptable temporal resolution but marginal accuracy. Advanced imagers such as MODIS have improved accuracy for total column amounts and provided information on aerosol particle size and type, and information over land. However, retrieved quantities are of column totals and means only. Data from radiometers measuring backscattered visible / ultra-violet radiation, such as OMI on Aura, can be used to obtain more accurate estimates of aerosol properties and total column amounts. Geostationary imagers are also useful to monitor the temporal evolution of high-aerosol events (e.g., dust storms). Lidar measurements will be required to provide vertically resolved information; research demonstrations are under way. 3-D wind - vertical component No present or planned capability. Research is required on indirect observation via sequences of geostationary infra-red imagery. Additional observations for model validation Outgoing longwave and shortwave radiation fluxes can be estimated, with varying degrees of accuracy, from several broadband or multi-spectral infra-red and visible satellite radiometers designed primarily for other purposes. Specialised instruments designed to measure accurately some component(s) of the Earths radiation budget include CERES on TRMM, TERRA and Aqua, and GERB on MSG. Horizontal resolution is good. Accuracy is acceptable and depends on the accuracy of the absolute calibration and of the radiance to flux conversions. Advanced infra-red sounders (e.g., AIRS, IASI, CrIS), providing complete or near-complete spectral coverage of the thermal infra-red at high spectral resolution, should offer the opportunity to monitor the infra-red spectrum of surface emissivity with good horizontal resolution and accuracy, although further research is required. Surface albedo can be estimated from shortwave broadband or multi-spectral radiometer measurements with good horizontal resolution. Clouds, aerosols and atmospheric gases affect the accuracy achievable, which is currently marginal / acceptable but should become good as progress is made in interpreting data from high-resolution, multi-spectral instruments. SUMMARY OF STATEMENT OF GUIDANCE FOR GLOBAL NWP Global NWP centres: make use of the complementary strengths of in situ and satellite-based observations; have shown strong positive impact from advanced microwave sounding instruments (such as AMSU-A); are starting to take advantage of high spectral resolution sounders with improved vertical resolution (such as AIRS, IASI, CrIS); are advancing in the use of 4-D data assimilation systems to benefit from more frequent measurements (e.g., from geostationary satellites, from AMDAR) and from measurements of cloud, precipitation, ozone, etc.; would benefit from increased coverage of aircraft data, particularly from ascent / descent profiles; and, would benefit from more timely availability of all observations, in particular satellite data, and from several types of in situ measurement that are made but not currently disseminated globally. The critical atmospheric variables that are not adequately measured by current or planned systems are (in order of priority): wind profiles at all levels; temperature and humidity profiles of adequate vertical resolution in cloudy areas; precipitation; surface pressure; and snow equivalent water content. _____________ 3.2 Statement of Guidance for Regional Numerical Weather Prediction (updated May 2008) Regional numerical prediction models are intended to produce more detailed forecasts than those available from global models. The added detail is made possible by a finer computational grid, more detailed specification of terrain, more sophisticated prescription of physical processes, and, ideally, dense and frequent observations to specify appropriately detailed initial conditions. Because most regional models depend upon global models for their lateral boundary conditions, the duration of regional forecasts is effectively limited by the size of the computational domain. At least one model has global coverage but variable horizontal resolution, with the highest resolution concentrated in the region of interest. Regional models are more likely to cover land areas than ocean, but oceanic buffer zones upstream from heavily populated areas are often included. Like global models, regional models are initialized through the assimilation of observations. Observing systems that report hourly or more often and at high resolution are relatively more important for regional modeling than for global modeling because of the emphasis on correct prediction of mesoscale events such as thunderstorms, lake-effect snows, fog, orographically induced windstorms, or spiral rainbands in a tropical storm. Proper initialization of physical processes requires detailed observations of the standard variables of temperature, moisture, and wind but also of variables that have a direct bearing on physical processes at the surface and in the atmosphere. For initializing boundary fluxes, observations of vegetative cover, soil moisture, snow or ice cover, and surface albedo are important. For initializing diabatic processes, the presence or absence of clouds and precipitation, and information on hydrometeors are important. Not all of the parameters listed above are observable with current systems, let alone with the required resolution. Nonetheless, a variety of observing systems can contribute to mesoscale numerical prediction, provided that progress continues in the assimilation of the more esoteric data sources. The impetus for regional numerical prediction in a particular area is governed primarily by the need to provide enhanced weather services in densely populated areas. Dense and diverse observations are a great aid in mesoscale prediction, but some advantages accrue just from the inclusion of high-resolution topography in the model. Nonetheless, attempts at mesoscale numerical weather prediction in data-poor areas are severely handicapped. Considering only the frequency of observations but not their spatial distribution, the following ground-based or in situ systems are apt for mesoscale prediction: wind profiling radars, dual-frequency GPS receivers for the inference of column water vapour, most automated surface observing systems, automated measurements of cloud base and cloud coverage, scanning Doppler radars, and fully automated aircraft reports. Future observing systems with special application to regional numerical prediction are water vapour sensors on aircraft (as an adjunct to the temperature and wind information already provided), Doppler radars with multiple polarizations, and hourly precipitation estimates from multiple sources. The following space-based observations are apt for mesoscale prediction: cloud images (visible and infrared), winds determined from the drift of features in satellite images, and radiometric data - all from geosynchronous satellites (frequent views); scatterometer data for determination of sea-surface winds and microwave observations for detection of cloud water and cloud ice, so far, available only from polar orbiting satellites. In the future, interferometric data and Doppler lidar data from satellites will contribute toward the prediction of mesoscale events. Because mesoscale forecasts are perishable, it is important to collect the observations and process them very quickly, usually within one hour or less. The assimilation cycle is likely to become less than six hours, which is common practice. Advances in regional modeling are transferable to global models, when faster computers permit finer resolution in global models. 3.2.1 Upper-Air Observations and Regional NWP (Variables observed are listed in the perceived order of their importance for regional NWP). - 3-D wind field Raobs, AMDAR, profilers and Doppler radars all provide useful wind information for regional NWP. In addition, satellite derived wind information is particularly useful where other sources of wind information are lacking. The best short-term opportunity for increasing 3-D wind information is to capitalize on reports available from commercial aircrafts world-wide. Where scanning Doppler radars are available, data assimilation techniques are being perfected to extract information from the very high-resolution radial winds (~1-km resolution along each radial). Long-term needs for more comprehensive wind information might be met by aerosondes (unpiloted aircraft) able to fly for an extended period. They might be met also by the development of a TAMDAR (Tropospheric AMDAR) system producing wind observations from airplanes on a national or regional basis, and at lower levels compared to the AMDAR systems. For wider coverage, wind-finding Doppler lidars, like the one planned for the ESA mission called ADM-AEOLUS, will be experimented. If this demonstration mission is successful, it may open the way to a more systematic wind observation from space, although wind retrieval is not possible within and below thick clouds. - 3-D humidity field From the standpoint of mesoscale numerical weather prediction, the humidity field is marginally sampled practically everywhere in the world. Like clouds and precipitation, the humidity field has strong variability on scales of tens to hundreds of kilometres in the horizontal and, as Raman lidar observations show, on scales of hundreds of metres in the vertical. Any improvement in the density, coverage, or vertical resolution of humidity observations is likely to be helpful for mesoscale prediction. Although raobs are launched only twice a day in most locations and spaced at least a few hundred kilometres apart, they are still the best source of detailed humidity information in the vertical. Different instrument packages have had problems measuring humidity accurately when the atmosphere is either very dry or close to saturation, but the situation is improving. Polar and geostationary satellites provide estimates of total column water vapour probably accurate to within 10-20%. Enough information is collected to infer moisture concentration within several thick layers in the vertical, with good horizontal resolution. The vertical resolution is marginal, at best, for mesoscale prediction, and the infrared information is available only for cloud-free fields of view. The temporal frequency is good for the geosynchronous satellites, marginal for the polar orbiting satellites. The AMSU aboard polar orbiting satellites can extract moisture information in cloudy areas, but the vertical resolution is marginal. Furthermore, no information is easily available in rainy areas and more work is needed to capture this information. Over the oceans, satellites are virtually the only source of moisture information. Humidity measurements have been tried on the AMDAR systems since 2000. In 2008, humidity measurements are tried on several aircrafts, and one can expect these data to become operational soon in the context of the AMDAR observing system. Humidity soundings from aircraft will supplement raob soundings over land. En route humidity measurements in the high troposphere will perhaps be more valuable for climate purposes than for mesoscale numerical prediction. In general, concerning coverage and vertical resolution, one can expect something which would match the current availability of AMDAR temperature and wind measurements. It is expected that measurements of total column water vapour from satellites and ground-based GPS receivers will lead to better mesoscale forecasts. Impact studies have shown some positive impact of the ground-based GPS humidity measurements. The possibility that 3-D moisture information might be extracted from dense GPS networks through analysis of signal delay along slant paths is under investigation. GPS technology is driven by applications in many geophysical sciences besides meteorology. It is, therefore, likely that the number of GPS receivers will steadily grow, thereby improving the chances for dense networks and enhanced opportunities to infer the moisture field. Vertical resolution of moisture soundings in cloud-free areas will be improved with the deployment of advanced infrared sounders or interferometers aboard future satellites. Such instruments will provide the equivalent of thousands of channels as compared with only dozens on todays satellites. Measurements by research aircraft suggest that variations in temperature of 1-2oC and in water vapour mixing ratio of 1-2 g/kg over distances of tens of kilometres can mark the difference between the initiation of deep convection or lack of it. This emphasizes all the more the need for detailed thermodynamic measurements, particularly in the boundary layer, for successful mesoscale forecasts. - 3-D temperature field With regard to raobs, the same comments made under "3-D wind fields" apply here. The raob supplies temperature soundings at good vertical resolution, but the density and frequency of observations is marginal, especially in sparsely populated areas, from the standpoint of mesoscale numerical prediction. The AMDAR systems provide good accuracy temperature measurements. Spatial and temporal coverage at altitude is good over the United States of America and Europe and along a few heavily traveled oceanic routes. Ascent / descent temperature soundings are becoming more numerous as airlines respond to a plea for altitude-dependent reporting during approaches and departures. Manual aircraft reports (AIREP) are still useful and sometimes they are available in some areas of the globe where no other data (like AMDAR) are available: they are then very valuable. The efficacy of satellite temperature information in numerical prediction depends partly upon the physical nature of the measurements and partly upon the sophistication of the data assimilation procedures, which are constantly being improved. Polar orbiting satellites provide information on temperature with global coverage, acceptable accuracy, good horizontal resolution, but marginal temporal frequency and vertical resolution for the purpose of mesoscale prediction. The use of radiances (radiation measurements) over land is still experimental, though recent improvements in assimilating oceanic data have led to better global forecasts. Geosynchronous satellites provide frequent radiance data, but their use over land is still hindered because of the difficulty of estimating surface emissivity. Infrared soundings cannot be made below clouds because all but very thin clouds are opaque to infrared radiation. Polar orbiting satellites have microwave sounders that can penetrate clouds (the Advanced Microwave Sounding Unit-AMSU), but the field of view of this instrument is broader than that for infrared sounders. As with infrared soundings, progress is slow in utilizing them over land. Future methods for measuring 3-D temperature will come from a variety of sources. Augmentation of the program for automated aircraft measurements is probably the best way to increase temperature soundings in the near term. A wind profiler operated in conjunction with a Radio Acoustic Sounding System (RASS) can measure the speed of sound in each range gate and thereby infer a profile of virtual temperature in the boundary layer every few minutes. This is valuable for mesoscale prediction, but such units are few in number and nowhere operational. Moreover, the sounds generated by RASS systems are potentially irritating to anyone nearby. There are at least two ideas for augmenting temperature and moisture soundings with balloons, either by making in situ measurements over a long trajectory (driftsondes) or by floating them in the stratosphere high above the weather (GAINS - Global Air-ocean In situ System). Both systems are being designed to drop compact, lightweight sondes at designated times and locations. Aerosondes have already been mentioned as one way to increase the number of soundings. With regard to satellites, instruments able to measure in large numbers of channels (either advanced radiometers or interferometers) are already available and are also being planned for future satellites. These instruments improve upon the vertical resolution and accuracy of current radiometers. Radio-occultation techniques, whereby signals from a GPS satellite are measured while passing through successively lower layers of the atmosphere, promise to provide temperature information at roughly 1-km vertical resolution from the mid troposphere to the stratosphere. While valuable in other areas of atmospheric science, such measurements have poor horizontal resolution and are not expected to benefit mesoscale prediction, except peripherally. - Clouds and precipitation It is more critical in mesoscale than in global numerical weather prediction to initialize moisture, cloud, and precipitation fields properly. Because mesoscale forecasts are shorter and more detailed, the early hours of the forecast are relatively more important. It is counterproductive to wait many hours until the model spins up. Diabatic processes must be properly initialized in order to minimize spin-up time. Satellites offer detailed information on cloud coverage, type, growth, and motion. It is relatively easy to infer cloud-top height from measurements of cloud-top temperature. The coverage is global for polar orbiting satellites and nearly global for geosynchronous satellites (high latitudes are not viewed). The frequency of cloud images is hourly or better for geosynchronous satellites. Frequency of polar coverage is good for the polar orbiting satellites. Microwave sounders on the polar orbiting satellites give information on cloud liquid water, cloud ice, and precipitation. Because most mesoscale models have sophisticated parameterisations of cloud physics, the microwave information is valuable. Precipitation estimates have been derived from analysis of infrared images, but these have greater accuracy at longer time scales (weeks or months) and are not particularly useful for mesoscale forecasting. Ground based observations are necessary for estimating cloud base. The presence of cloud is a proxy observation for a relative humidity of 100%. Numerical weather prediction has been slow to make quantitative use of satellite cloud information, but the situation is changing. Because satellite cloud images are one of the few sources of truly mesoscale weather information with good coverage, the effective incorporation of cloud information in mesoscale models requires methodological research and is a high priority. Ground-based (remote-sensing) observing technologies are also available and ready for implementation. Their operational usage should be developed according to the WMO User Requirements stated for the cloud and precipitation parameters in the regional NWP application. Precipitation rates inferred from accumulation maps and automated rain gauges are used for diabatic initialization of mesoscale models, but the techniques are neither very accurate nor highly advanced. The problem of diabatic initialization is the subject of active research. Polarization diversity radars, now used exclusively for research, offer promise for identifying hydrometeor type and, in some cases, shape. Such measurements will undoubtedly improve estimates of accumulated precipitation at the ground. Operational benefits in mesoscale prediction are probably several years away. 3.2.2 Surface Observations and Regional NWP - Surface pressure, temperature, humidity, wind, and precipitation Over water, ships and buoys take standard surface observations of temperature, pressure, wind, and humidity. In relatively shallow water, oil rigs do the same, but the frequency and spatial coverage is marginal for mesoscale forecasting except perhaps close to some shorelines. Over many parts of the oceans the buoy data coverage has improved a lot from about 2000, especially for SST measurements. Polar orbiting satellites provide information on sea-surface wind information that has had a beneficial effect on global forecasts, but temporal frequency is marginal for regional mesoscale forecasts. The skin temperature of the sea-surface is inferred from satellites with good horizontal resolution; temporal resolution is also good for geosynchronous satellites. Satellite estimates of short-term precipitation are marginal at best, but satellites are virtually the only source of precipitation information over the oceans. Over land, surface observations have spacing that varies a lot from region to region. Accuracy is generally good. Data from many local meso-networks are not part of national data collections, which is unfortunate. The interpretation of local wind data is complicated in mountainous terrain, where local diurnal circulations are common (e.g., mountain-valley winds or drainage winds). Mesoscale models with high-resolution terrain and good surface boundary physics should be able to explain many of these local wind systems and some are able to get some benefit from assimilating surface winds. Hourly precipitation estimates are valuable for estimating latent heat release at the beginning of a mesoscale forecast. Recording rain gauges are the most accurate source, but they seldom sample the true spatial variability of rainfall, especially convective rainfall. Radar estimates capture the spatial variability of precipitation, but they need to be calibrated with gauge data. Satellite measurements of surface skin temperature are subject to greater error over land than over water because of the complex underlying surface. Surface pressure is not measured by satellite. - Other surface information required for mesoscale modeling Surface boundary conditions strongly affect mesoscale forecasts. They are the reason why lateral boundary conditions do not totally determine conditions in the interior late in the forecast period. Thus, it is vital to know surface conditions: the fluxes of solar and infrared radiation (and their strong modulation by clouds), soil type, soil moisture, surface vegetation, albedo, and presence or absence of snow and ice cover. Cloud observations from the ground are increasingly automated, with a resultant loss of some information formerly available from trained observers. For example, many automated reports do not report ceilings higher than several kilometres above ground, and cloud cover is inferred rather than directly observed. This implies that the ground cloud observations are far from meeting the regional NWP requirements defined in the WMO tables (even the threshold values). Satellites are ideal for observing cloud cover, but they cannot measure cloud thickness. Still, ceiling height observations, where available, are valuable for mesoscale forecasting. Surface visibility observations are made primarily at airports because this information is critical for landing and departing aircraft. The density of such observations is good in heavily populated areas, but this parameter can vary substantially over short distances in complex terrain when the cloud ceiling is low. Visibility is deduced from the output of some regional models. Databases of soil type are available for many regions of the world at high resolution. Soil type determines the water holding capacity and the retention of rainwater. Because microwave radiation emitted at the ground is influenced by surface moisture, satellite microwave observations are proving useful for monitoring soil moisture. Soil moisture can also be estimated by tracking precipitation over many days. Many countries have dense networks of rain gauges, reporting daily, for the climatological record. These 24-hour reports are probably sufficient for tracking soil moisture. In many cases, radar estimates of accumulated precipitation can effectively supplement the climatological network. Databases of land surface (desert, grassland, forest, farmland, urban corridor, etc.) are available for calculating the surface energy budget. This must be supplemented by information on seasonal changes in vegetative cover. Satellites provide various indices on vegetative cover; perhaps the best known is the Normalized Difference Vegetation Index (NDVI). The albedo over water is low and subject to small variability unless ice forms. Over land, surface albedo varies with the geography, but is well described by databases on land surface characteristics. Large and sudden changes in albedo are caused by snowfall and the formation of sea or lake ice. Visible satellite images show well the horizontal extent of snow and ice, and portray the surface albedo during daylight when clouds do not obstruct the view of the ground. Microwave images may hold information on the water content of snow, but this is still a research topic. 3.2.3 Summary of Statement of Guidance for Regional NWP Regional (mesoscale) NWP is motivated mainly by a desire to provide enhanced weather services to large population centres and is aided by the availability of comprehensive observations. Oceanic areas are generally included in the geographical domain for regional weather prediction primarily as a buffer zone upstream from populated land areas, where accuracy is most important, except for models focusing on islands. Lateral boundary conditions supplied by global models eventually govern the forecast in the interior of the domain except for locally forced events. Where observational and computational resources support regional prediction, the following is true: Continental NWP centres rely rather more on surface-based and in situ observing systems than on space-based systems; Weather radars supply the highest resolution information, but the coverage is spatially limited, vertically and horizontally; Satellites supply information at high horizontal resolution; infrared sounding coverage is limited primarily by clouds; Accurate moisture fluxes are critical for good mesoscale forecasts, especially of clouds and precipitation; the forecasts thus rely heavily upon wind and humidity observations; Lower boundary conditions can quickly affect a mesoscale forecast; observations of screen-height (2-metre) air temperature, dew point, wind, and pressure are often good to adequate in coverage and frequency whereas observations of surface conditions, for example, soil moisture, are far from meeting the WMO requirements; and, In many cases, mesoscale observations are not fully exploited in mesoscale prediction, e.g., radar reflectivity, cloud images, and microwave sounders. This is more a problem in data assimilation than in the character or distribution of the observations. The greatest observational needs for regional prediction are: More comprehensive wind and moisture observations, especially in the planetary boundary layer. Enhancement of the AMDAR data collections and the addition of moisture sensors aboard aircraft are recommended. Numerous ground-based GPS receivers need only the addition of simple surface observations to be able to deliver estimates of integrated water vapour. Wind profiles are needed at closer spacing; More accurate and frequent measures of surface and soil properties, in that these influence surface fluxes strongly. More accurate estimates of precipitation are sorely needed. Often these observations are made but not exchanged; and, More comprehensive observations of cloud base, cloud thickness and other cloud _____________ 3.3 Statement of Guidance for Synoptic Meteorology (updated June 2008) Synoptic Meteorology could be defined as the activity performed by a human forecaster when predicting the weather at time scales from one hour to several days, and at related space scales. Numerical Weather Prediction (NWP) output (global, regional and ensembles) play a vital role in forecasting; and information benefiting these models benefits synoptic meteorology. Many uses of the observations in synoptic meteorology are thus related to numerical models: to evaluate the value of model output by comparing the analysis and early frames of a forecast (regarding timing, location and intensity of synoptic-scale features); to take appropriate mitigating action if a mismatch exists between model output and observations; to capture smaller-scale details that are unresolved by the models; and, to verify forecasts a posteriori. This statement of guidance concentrates on uses other than data assimilation and model forecasting, which are already covered in the SOGs for global NWP and regional NWP. Contrary to a NWP data assimilation system, where the goal is to estimate each atmospheric variable on a more or less regular grid, synoptic meteorologists attempt to depict meteorological phenomena in an object-oriented way. Forecasters tend to look at individual observing systems separately, so that the impact of the different observing systems discussed in this SOG by data source rather than by meteorological parameter. 3.3.1 Satellite observations and Synoptic Meteorology Geostationary Satellites Geostationary satellites imagery is the prime source for locating synoptic-scale features and objects in real-time, allowing them to detect any incipient discrepancies between model forecasts and reality at an early stage. This is particularly true over oceanic areas, where conventional data are typically very sparse. Model fields and satellite imagery may be superposed on a workstation screen; a good example is given by the potential vorticity field of the upper-level flow correlated with water vapour satellite images. The horizontal resolution and coverage are good, except over the Polar Regions (60-90N and 60-90S). The vertical resolution is improving with the new generation of geostationary satellites GOES and Meteosat. The steadily improving horizontal and spectral resolution of geostationary satellite instruments leads to improved detection and classification of clouds. Progress has been made on night-time detection of low clouds, which used to be marginal, and on distinction between high-thin and high-thick clouds (e.g., cirrus versus cumulonimbus). Many of the derived products are very useful for nowcasting purposes, and the recently enhanced rapid-scan facility on Meteosat 8 is also beneficial. Quantitative precipitation estimates from geostationary satellites are improving, but are still considered marginal. Polar Orbiting Satellites Polar orbiting satellite infrared and visible images continue to deliver excellent horizontal and spectral resolution, with their use being limited only by the infrequent availability of the data. However, for the high latitudes, where geostationary satellite data are missing, the polar orbiting satellites provide valuable observations with acceptable frequency due to the convergence of tracks. Surface winds over oceans provided either by microwave imagers (wind speed) or scatterometers (speed and direction) are considered accurate, and are widely used, particularly for marine forecasts. The horizontal resolution is good at synoptic scales, while the temporal resolution is marginal to acceptable depending on the swath width of the instrument. The detection of precipitation is poor for microwave imagers and depending on the wavelength of the instrument good to poor for scatterometers. Precipitation estimates derived from satellite measurements are improving. Microwave radiometers, and precipitation radars are capable of estimating precipitation with acceptable accuracy and horizontal resolution. The nature of the phenomenon (short-lived convective cells and rain bands) limits the use of data for quantitative assessments of accumulated precipitation. 3.3.2 In-situ and surface-based remote-sensing observations for Synoptic Meteorology Weather Radar Weather radars are essential for the detection of precipitation in real-time at high-spatial resolution. In areas where radar networks are installed, the horizontal and temporal resolution are excellent, and the accuracy of the quantitative estimation of precipitation is acceptable to good except for complex topography, where obscuration of low-lying areas hidden by higher topography is a limiting factor. Doppler radars are now becoming the standard, so that VAD winds and the identification of line squalls and outflow boundaries are an essential element of the data. Increasingly, polarimetric radars are being used to discern between liquid and solid precipitation, which is highly relevant for all types of traffic and infrastructure forecasts (i.e., aviation, road and rail weather, building industry, etc...). Radiosondes Radiosondes remain the reference observing system for determination of detailed vertical structure in the atmosphere. This is due to their excellent vertical resolution (provided full resolution data are being transmitted instead of standard / significant eel data only) and second to the simultaneous presence of temperature, wind, moisture and pressure measurements (moisture with marginal accuracy, all other parameters with good accuracy). Vertical stability analyses, seeking details which are not necessarily captured by the NWP models, are based mostly on the radiosondes. Moreover, radiosondes remain one of the key observing systems in NWP analyses; the model assessment made by the forecasters relies to a large extent on them. Thus, despite the poor temporal resolution and uneven geographical coverage, radiosondes are of primary importance in synoptic meteorology. Wind profilers (Boundary layer and tropospheric) are still widely regarded as research tools, despite the fact that operational networks have been established in the United States of America, and in Europe. The good temporal resolution of wind profilers and the generally adequate data quality is making them quite useful. However, their geographical coverage is expected to remain marginal to poor except in a few regions of the world. Moreover, the cost of technical maintenance and the difficulty to obtain the necessary frequency bands are limiting their operational implementation. Aircraft data The increasing availability of display software for ADMAR data, particularly for ascent / descent profiles is making these data a highly useful tool for forecasters, particularly in data sparse regions of developing countries. Data quality is generally good, and quality control measures are being put in place to ensure adequate data integrity. Surface data Surface data are quite essential in synoptic meteorology. Their horizontal coverage is generally good over populated land, and marginal to poor over oceanic or desert areas, although oceanic buoys are being deployed in large numbers and improving the situation there. Measurement frequency and data accuracy are good. In addition, forecasters are very familiar with these data and can make best use of them. Over land surface, data from an increasing number of automated stations contains, as a minimum, information on wind, temperature, moisture and mean sea-level pressure, with weather elements such as cloud cover or visibility mostly available from manned and aeronautical stations. Regional efforts are underway to collect, standardize, and quality control data from observing networks from non-NMHS sources such as hydrological services, road networks and private and industrial operators. Over the oceans, fewer parameters are available. Mean sea-level pressure, measured on ships, buoys, and islands is a key tracer of synoptic activity. Even very isolated stations may play an important role in synoptic forecasting, especially when they point out differences with NWP model output. 3.3.3 The special case of tropical cyclones Geostationary satellites provide vital information on the location of a tropical cyclone with a good temporal resolution and a good horizontal coverage; the availability of such information all over the tropical belt is essential. Polar orbiting satellites provide more detailed information on tropical cyclones, but at a coarser temporal resolution. For the surface, wind scatterometers are most useful. They also provide some capability for detecting precipitation. Ground-based precipitation radars have a good horizontal and temporal coverage around land (including islands) areas, but are absent over most oceanic regions. They allow good monitoring of tropical cyclones and landfall, and they contribute quite significantly to nowcasting and very short range forecast, but not to their longer-term forecast. Conventional in situ data provide marginal coverage over tropical cyclones, but measure MSLP with a good accuracy (one of the essential parameters of a tropical cyclone); they also provide measurements of wind with good accuracy. Targeted observations like dropsondes have been used for tropical cyclones, and have proved to be very useful not only for NWP usage but also for direct use by forecasters. 3.3.4 Summary of Statement of Guidance for Synoptic Meteorology NWP models are the most important tool for synoptic prediction, leading to a strong dependence on the same data as identified as sources for NWP. Thus, the SOG for global and regional NWP applies for Synoptic Meteorology as well. Information that best complements these data is found in satellite imagery and weather radar data; their usage is further supported by their good temporal and spatial resolution. Surface data, because of their good representation of the conditions where people are living, are also essential. There still is concern for oceanic areas, where significant phenomena such as cyclogenesis occur, but surface-based data are sparse. Another concern is the quality of cloud cover and base height estimates in remote areas, and especially during the night, some progress is expected in this area from new satellite sensors over the next decade. _____________ 3.5 Statement of guidance for Seasonal and Inter-Annual (SIA) forecasts (updated April 2006, with complement updated April 2008) This Statement of Guidance (SOG) was developed through a process of consultation to document the observational data requirements to support seasonal-to-interannual (SIA) climate prediction. This version was prepared originally by the ET-ODRRGOS with experts from the NWP community, and was subsequently updated in consultation with a number of experts from the climate community through AOPC and by the CBS ET on Infrastructure for Long-Range Forecasting. It is expected that the statement will be reviewed at appropriate intervals by the OPAG on Data Processing Forecasting Systems to ensure that it remains consistent with the current state of the relevant science and technology. 3.5.1. Introduction Coupled atmosphere-ocean models are used to produce seasonal-to-inter-annual forecasts of climate. While empirical and statistical methods are also used to predict climate conditions a season ahead, the present assessment of how well observational requirements are met relates only to the coupled model inputs. It is noted that historical data sets also play an important role in SIA prediction by supporting calibration and verification activities. Whilst such forecasting is still subject to much research and development, many seasonal forecast products are now widely available. The complexity of the component models ranges from simple models to full general-circulation-model representations of both the ocean and atmosphere. There is also large variation in the approach to the assimilation of initial data, with some of the simpler models assimilating only wind information while the more complex models usually assimilate subsurface temperature information and satellite surface topography and temperature data. Indeed, major challenges remain in the development of assimilation techniques that optimise the use of observations in initialising models. The time and space scales associated with seasonal-to-interannual variability (large scale, low frequency) suggest the key information for forecasts will derive mostly from the slow parts of the climate system, in particular the ocean, but also the land surface. When considering impacts such as rainfall deficiencies or increased temperatures over land, however, there are very good reasons for considering variables associated with the land surface conditions. In particular, land surface moisture and vegetation should be specified and predicted. The models should also include up-to-date radiative forcing (e.g. greenhouse forcing), which are important for maximising skill in forecasts of land surface air temperature anomalies relative to recent historical reference-normal periods. In this list of observation needs, the requirements for SIA forecasts are based on a consensus of the coupled atmosphere-ocean modelling community. It builds on the requirements for Global NWP and represents in addition those variables that are known to be important for initialising models or for testing and validating models. For the most part, aspects that remain purely experimental (i.e. unproven) are not included. There is some attempt to capture the impacts aspects; that is, those variables that are needed for downscaling and/or regional interpretation. 3.5.2. Data Requirements The following terminology has been adhered to as much as possible: marginal (minimum user requirements are being met), acceptable (greater than minimum but less than optimum requirements are being met), and good (near optimum requirements are being met). 3.5.2.1 Sea surface temperature Accurate SST determinations, especially in the tropics, are important for SIA forecast models. Ships and moored and drifting buoys provide observations of good temporal frequency and acceptable accuracy, but coverage is marginal or worse over large areas of the Earth. Instruments on polar satellites provide information with global coverage in principle, good horizontal and temporal resolution and acceptable accuracies (once they are bias-corrected using in situ data), except in areas that are persistently cloud-covered (which includes significant areas of the tropics). Geostationary imagers with split window measurements are helping to expand the temporal coverage by making measurements hourly and thus creating more opportunities for finding cloud-free areas and characterising any diurnal variations (known to be up to 4 degrees C in cloud free regions with relatively calm seas). Microwave measurements provide acceptable resolution and accuracy and have the added value of being able to see through clouds. Blended products from the different satellites and in-situ data can be expected to be good for SIA forecasts. There is a requirement for high quality, fast delivery SST (ideally with accuracy < 0.1 deg C on 100 km spatial scale and < 0.25 deg C on 10 km spatial scale, available within 24h ( by SST we mean eg bulk temperature at 2m depth). 3.5.2.2 Ocean wind stress Ocean wind stress is a key variable for driving ocean models. It is important to recognise the complementarity between surface wind and surface topography measurements. Current models use winds derived from Numerical Weather Prediction (NWP), from specialist wind analyses or, in some cases, winds inferred from atmospheric models constrained by current SST fields. The tropical moored buoy network has been a key contributor for surface winds over the last decade, particularly for monitoring and verification, providing both good coverage and accuracy in the equatorial Pacific. Fixed and drifting buoys and ships outside the tropical Pacific provide observations of marginal coverage and frequency; accuracy is acceptable. Satellite surface wind speed and direction measurements are now the dominant source of this information. Currently their data reach SIA models mostly through the assimilated surface wind products of NWP, where their positive impact is acknowledged. Overall, a two-satellite scatterometer system, or its equivalent, would provide good coverage and acceptable frequency, and it would complement the ocean-based systems. At this time, continuity and long-term commitment are a concern. Improved integration of the data streams and operational wind stress products from NWP and other sources will be needed to achieve acceptable or better coverage, frequency and accuracy. High quality scatterometer winds are the best products available at the moment and need to be maintained operationally. Additional data would always be useful. For example data to allow better estimates of heat-fluxes and P-E (precipitation minus evaporation) could help give a better definition of the mixed layer structure. 3.5.2.3 Subsurface temperature Many, but not all, SIA forecast models assimilate subsurface temperature and salinity data, at least in the upper ocean (down to ~500 m depth). The Tropical Atmosphere Ocean (TAO) / TRITON moored buoy network provides data of good frequency and accuracy, and acceptable spatial resolution, of subsurface temperature for the tropical Pacific, at least for the current modeling capability. The tropical moored network in the Atlantic (PIRATA) is better than marginal but does not yet have the long-term resource commitments and stability to be classified as acceptable. There is no array in the Indian Ocean. The Ships-of-Opportunity Programme (SOOP) provides data of acceptable spatial resolution over some regions of the globe but the temporal resolution is marginal. It is noted that SOOP is evolving to provide enhanced temporal resolution along some specific lines. The Argo Project is providing global coverage of temperature and salinity profiles to ~2000 m, mostly with acceptable-to-good spatial resolution, but only marginal temporal resolution in the tropics. In all cases the accuracy is acceptable for SIA purposes. Ocean observation system over Equatorial Atlantic is deficient in moorings. Moorings at and near the equator are important. Equatorial moorings in the Indian Ocean are also useful. 3.5.2.4. Salinity Salinity is becoming an important parameter. Some model are starting to make use of such data in the ocean data assimilation. ARGO is a major source of salinity observations. It provides global coverage of temperature and salinity profiles to ~2000 m, mostly with acceptable-to-good spatial resolution, but only marginal temporal resolution in the tropics. Valuable data also comes from the tropical moorings although data coverage is too limited. Surface salinity will be measured by satellite in the forthcoming research mission. There will be a need for continuity of those measurements. 3.5.2.5 Ocean topography Ocean altimetry provides a measure of the sea surface topography relative to some (largely unknown) geoid (or mean sea surface position) that in turn is a reflection of thermodynamic changes over the full-depth ocean column. In principle, the combination of altimetry, tropical mooring and Argo will provide a useful system for initialising the thermodynamic state of SIA models. Long term commitments for satellite altimetry are required. Research satellites are providing a mix of data with acceptable accuracy and resolution and data with good spatial resolution (along the satellite tracks) but marginal accuracy and frequency. The "synoptic" global coverage, particularly beyond the tropical Pacific, is an important requisite. Ocean altimetry data can currently only be used to look at variability in the sea state. There are plans to make use of geodetic data to obtain information about the geoid and the mean state of the oceans. It is expected that geodetic data will become available from satellites; GRACE and CHAMP are flying missions; GOCE will be an important addition. 3.5.2.6 Surface heat and freshwater fluxes There are a few sites in the tropical ocean where the data on surface heat flux are of value for validation and are required at a number of sites in the tropical oceans. NWP products (derived from analysis from short range forecast), in principle, have good resolution but the accuracy is at best marginal. Satellite data provide prospects for several of the components of heat flux, particularly shortwave radiation, but at present none is used on a routine basis for SIA assimilation. Precipitation estimates are important for validation because of the fundamental role of the hydrological cycle in SIA impacts. They also have importance in initialisation because of the links to salinity. However, there remain significant uncertainties in estimates of rainfall over the oceans. In addition the fresh water run off information from rivers (large estuaries) will become important in coastal areas and regional parts of the oceans, eg the Gulf of Bengal. 3.5.2.7 Ocean current data Models generally do not currently assimilate ocean current data, perhaps in part because data is limited. However, because of the central importance of dynamics and advection, current data are important for testing and validation. For example, experimental fields of surface current for the tropical Pacific and Atlantic are now being produced routinely by blending geostrophic estimates from altimetry with Ekman estimates from remotely-sensed wind observations. Inferred surface currents from drifting buoys are acceptable in terms of accuracy and temporal resolution but marginal in spatial coverage. Satellite altimetry is also being used to infer the distribution of ocean currents. Moored buoys are good in temporal coverage and accuracy, but marginal otherwise. 3.5.2.8 In-situ sea level In-situ sea level measurements provide an additional time-series approach (good temporal resolution and accuracy; marginal spatial coverage), particularly for testing models and validating altimetry. 3.5.2.9 Atmospheric data Since several SIA systems are driven by winds and, in several cases, surface heat flux products from operational analyses, the global (atmospheric) observing system is fundamental for SIA forecasts and their verification. 3.5.2.10. Land surface Snow cover. Snow cover and depth are important, particularly at short lead times (intraseasonal-to-seasonal). Snow depth observations are marginal. Soil moisture and terrestrial properties: Soil moisture use is still very marginal although soil moisture initial conditions are a crucial element in the forecast performance in mid-latitudes spring/summer (Beljaars, 1996) and might extend predictability over land in the monthly to seasonal range (Koster et al., 2004a, b). Soil moisture drifts are ubiquitous in NWP models, due to deficiencies in land surface models and/or the forcing precipitation and radiative fluxes (Viterbo, 1996). Due to its extended memory, the relevant quantity to initialise is the soil water in the root layer. There are no existing or planned direct observation of such quantity with global or even regional coverage. Soil moisture analysis relies on proxy data. Such data cover 3 main groups: Observations related to the surface-atmosphere feedback, or the partitioning of available energy at the surface into sensible and latent heat fluxes (e.g. Screen-level temperature and humidity and early morning evolution of IR radiances in the window channels in geostationary platforms) Observations related to the soil hydrology, such as microwave remote sensing; radiances are sensitive to water in the first top few cm of the soil. Remote sensing observations related to plant phenology, such as leaf area index (LAI), fraction of available photosynthetically active radiation (fAPAR), broadly based in the contrast in reflectances between the visible and NIR. In as much as the phenological evolution of plants depends on available water, there is a soil water related signal in the LAI and/or fAPAR; conversely, assimilation of such quantities will constrain the model evaporation, impacting on the background soil moisture. Without careful constraints, the use of one of the 3 classes of observations presented above will alias information into the analysed soil moisture. A strong synergy is expected from combining observations from each of the 3 classes above, because they sample "complementary directions" in the physical space. Sea Ice cover and thickness Sea ice cover is important for high latitudes. It is implicitly included in the leading SST products. Sea ice thickness is important for fluxes and would be useful for initialisation. Too few ice thickness measurements are presently available. 3.5.2.12 Other data There are many other data sets that may play a role in future-generation SIA forecast models. Because these roles are largely unknown, it is premature to discuss the adequacy of observing systems to meet these needs; generally speaking, they are not expected to rank near the above data in terms of priority. These data sets include: Ocean colour. Ocean transparency is already included in several ocean models and is thought to be a factor in SIA models (helping to determine where radiation is absorbed). Ocean colour measurements provide a means to estimate transparency. Clouds. Poor representation of clouds remains a key weakness of most SIA models. Better data are needed to improve parameterisations but these needs are adequately specified under NWP and elsewhere. Aerosols data such as volcanic ash is also required. Continuity of satellite observations of volcanic aerosols is important. Stratospheric ozone concentration data might be of interest in the future for seasonal forecasting. DATA NEEDS FOR LONG RANGE FORECAST (Updated April 2008) An accurate description of the ocean, land surface, sea ice and atmospheric conditions is the basic need to create the best initial conditions for long-range forecasts. On timescales beyond one or two months, the ocean state has an important role. Land surface conditions play a role during the first two months of the forecast. Although little is known about the predictability of the sea-ice, it has been shown that changes in the ice coverage have the potential of impacting the atmospheric circulation at monthly and seasonal time scales. In general, the quality of LRF is still much affected by model errors, and there is a real need for suitable data to assess and improve models. Ocean initial conditions Sea-Surface Temperature (SST) High-quality, fast delivery SST, ideally with accuracy < 0.1 deg C on 100 km spatial scale, available within 24h (by SST we mean e.g., bulk temperature at 2m depth). Data used to force the ocean model, such as wind stresses. High-quality scatterometer winds are the best products available at the moment and need to be maintained operationally. Additional data would always be useful. For example, data to allow better estimates of heat-fluxes, surface radiation and Precipitation-Evaporation could help give a better definition of the mixed layer structure. High quality, time homogeneous equatorial data: temperature, salinity and velocities. The equatorial mooring arrays, providing homogeneous and continuous time-series of observations are essential. TAO array is a vital backbone for the sub-surface temperature in the Pacific. It could be easily enhanced by providing also salinity measurements. Data at higher vertical resolution, and real-time velocity would also be beneficial. Although the PIRATA array over Equatorial Atlantic is useful, its spatial sampling is still deficient, and the salinity data, measured in real-time, is often not received by the assimilation centres. Temperatures from the recently implemented moorings in the Indian Ocean are being used operationally, and further developments of this array will be welcome. Broad-scale ocean sub-surface Temperature and Salinity data In overall terms the ARGO array has been demonstrated to have a substantial impact in the knowledge of the ocean and in the skill of seasonal forecasts. It is absolutely essential that the sustainability of the ARGO array is maintained for the foreseeable future. The Ships-Of-Opportunity Programme (SOOP) provides data of acceptable spatial resolution, over some region of the globe but the temporal resolution is marginal. It is noted that the SOOP is evolving to provide enhanced temporal resolution along some specific lines. Real-time delivery of satellite derived sea level data. The spatial coverage provided by the Altimeter data has been proved to be valuable. Again, it is important to guarantee the continuity of the altimeter missions without interruptions. A good knowledge of the earths geoid provides essential information for estimating the mean dynamic topography, which has been proven to have a large impact in the ocean state when combined with the altimeter information, although further developments of assimilation methods are needed. There are plans to make use of geodetic data to obtain information about geoid and the mean state of the oceans. It is expected that geodetic data will become available from satellite; GRACE and CHAMP are flying missions; GOCE will be an important addition. Sea-ice data (concentration and thickness) will be helpful. For instance, the significant reductions in Arctic ice cover during the 2007 Northern Hemisphere (NH) summer are not correctly represented in the ECMWF seasonal forecasting system. Experimental results indicate that this anomalous ice cover has an impact on the NH atmospheric circulation suggesting a potential benefit from proper sea-ice treatment in the seasonal forecasting system. However, the predictability of sea ice anomalies in coupled models is still poorly understood, and it is likely that accurate initialization of sea-ice properties is needed to predict such anomalies few months in advance. Satellite derived surface salinity data might prove useful, since it will help to reduce the large uncertainty in the upper ocean salinity field, currently very large due to the precarious knowledge of the fresh water fluxes. Surface salinity information will certainly help to constrain the fresh water balance. Land surface Soil moisture Soil moisture initial conditions are a crucial element in the forecast performance in mid-latitudes spring / summer and might extend predictability over land in the monthly to seasonal range. Soil moisture drifts are ubiquitous in NWP models, due to deficiencies in land surface models and / or the forcing precipitation and radiative fluxes. Due to its extended memory, the relevant quantity to initialise is the soil water in the root layer. There are no existent or planned direct observations of such quantity with global or even regional coverage. Soil moisture analysis relies on proxy data. Such data covers three main groups: Observations related to the surface-atmosphere feedback, or the partitioning of available energy at the surface into sensible and latent heat fluxes (e.g., Screen-level temperature and humidity and early morning evolution of IR radiances in the window channels in geostationary platforms); Observations related to the soil hydrology, such as microwave remote-sensing; radiances are sensitive to water in the first top few cm of the soil; and, Remote-sensing observations related to plant phenology, such as leaf area index (LAI), fraction of available photosynthetically active radiation (fAPAR), broadly based in the contrast in reflectances between the visible and NIR. In as much as the phenological evolution of plants depends on available water, there is a soil water related signal in the LAI and / or fAPAR; conversely, assimilation of such quantities will constrain the model evaporation, impacting on the background soil moisture. It is clear that without stringent caveats and constraints, the use of one of the 3 classes of observations presented above will alias information into the analysed soil moisture. A strong synergy is expected from combining observations from each of the 3 classes above, because they sample "complementary directions" in the physical space. Snow cover, depth and mass. Both for real-time analyses and consistent analyses of the past. Atmospheric initial conditions Thanks to Medium-Range Numerical Weather Prediction systems, an accurate description of the real-time atmospheric initial conditions is already largely available. However, LRF has some needs additional to those for medium range forecast: Time variation in the composition of the atmosphere needs to be known and accounted for: greenhouse gases, tropospheric aerosols, volcanic aerosols, and stratospheric ozone. Near real-time data is needed, and in many cases both horizontal variations and the vertical profile are required. For verification and calibration of model output Global data that can be used to validate the LRF. This is particularly important for rainfall, where high-quality, high-density and readily available data would be of great value both for assessing model quality, and, more importantly, empirical downscaling global model output for local use; Long records of station data will be very useful for calibration and downscaling purposes, and will greatly help the application and usefulness of the seasonal forecasts products; Atmospheric reanalysis should be continued in the real-time. Although the existing atmospheric reanalysis have proved an invaluable contribution to LRF, they usually cover only a fixed period, and in order to complete the validation data set, the reanalysis record is often complemented with operational data. This has the potential of introducing undesired inhomogeneities in the validation data sets; and, Reanalysis should be repeated as the models and data assimilation methods improve, thus guaranteeing that the quality of the data sets is continuously improved. _____________      MAN-VII/Doc. 4.3(1), p.  PAGE 3 MAN-VII/Doc. 4.3(1), Appendix A MAN-VII/Doc. 4.3(1), Appendix B MAN-VII/Doc. 4.3(1), Appendix C MAN-VII/Doc. 4.3(1), Appendix D MAN-VII/Doc. 4.3(1), Appendix E MAN-VII/Doc. 4.3(1), Appendix F, p.  PAGE 3 MAN-VII/Doc. 4.3(1), Appendix F MAN-VII/Doc. 4.3(1), Appendix G, p.  PAGE 6 MAN-VII/Doc. 4.3(1), Appendix H, p.  PAGE 6 MAN-VII/Doc. 4.3(1), Appendix I, p.  PAGE 3 MAN-VII/Doc. 4.3(1), Appendix J, p.  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