ࡱ>  ~uvwxyz{|}a &jbjbA]A] .+?+?]t!QQQ8QD:R!v*S(RShShShS{T{T{T,Rd1Q{TwT{T{T{T1E_hShSE_E_E_{ThShSE_D0{TE_E_&WS eQW>d`vk|&E_&E_!!,M!!MThe Case for Maintaining Surface Meteorological Data Collection from Voluntary Observing Ships Dr E. Kent, Mr S. Woodruff, Mr D. Berry, Ms E Gowland, Prof. S. Gulev, Dr C. Hahn, Dr S. Josey, Dr. J. Kennedy, Ms N. Rayner, Dr R. Reynolds, Ms N. Scott, Mr S. Smith, Mr V. Swail, Dr P. Taylor and Dr S. Warren Reviewed by Mr. G. Ball; Chair, JCOMM Ship Observations Team, and Ms J. Fletcher; Chair, Voluntary Observing Ship Panel Summary and Purpose of Document This document describes the contribution of the Voluntary Observing Ship (VOS) Scheme to the Global Climate Observing System (GCOS). Several serious threats to the continued delivery of climate-quality datasets from VOS are described and recommendations are made as to how the situation can be improved. ACTION PROPOSED The panel is invited to review the information presented. In particular the panel is requested to make a decision whether recommendations on the future of the VOS should be made to the World Climate Research Program (WCRP) Observation and Assimilation Panel (WOAP) for consideration at their 3rd Meeting (29th September to 3rd October 2008). The Case for Maintaining Surface Meteorological Data Collection from Voluntary Observing Ships Executive Summary and Recommendations The importance of data from Voluntary Observing Ships (VOS) in the Global Climate Observing System (GCOS) is highlighted. Despite the many applications of VOS data in climate research and monitoring, and the lack of available alternative sources of information for many of the parameters reported by VOS, the quantity of data has declined in recent years. The reasons for this are described and include operational difficulties, resource constraints, a lack of mechanisms for the climate community to influence the data collection, and outdated perceptions of data quality. Among the areas that will suffer if the provision of VOS data does not improve include: climate change monitoring, air-sea interaction studies, satellite calibration and validation, and reanalysis. Some examples are also shown where newly-developed datasets with improved resolution are likely to increase the number of applications of VOS data. Recommendations 1) A wide ranging review of user requirements for marine meteorological observations should be conducted including potential revision to the GCOS Implementation Plan. 2) Robust adequacy assessments of the marine meteorological observing system should be made operationally against the user requirements identified under (1). 3) The support system for the ship network including Port Meteorological Officers should be improved. 4) The provision of timely, accurate and complete metadata to accompany all in situ observations should become a priority and be appropriately resourced. 5) Clearer responsibilities are required within international bodies for ongoing assessment and implementation of the marine meteorological observing system, and of the costs and benefits of future design changes. 6) Investment is required in climate data management for VOS and other ODAS to ensure that climate archives (e.g. ICOADS) are as complete as possible, and incorporate and disseminate the latest information on data quality. Improved quantitative demonstrations of the value of adding delayed mode data and metadata are desirable. 7) Support the activities of the VOS Panel, a sub-panel of the SOT and responsible for coordinating the VOS Scheme, in (a) transferring the benefits and experience gained from VOSClim to the wider VOS, and (b) raising awareness of the VOS Scheme within IMO and the Marine Community at large. These activities will contribute to enhancing the VOS Scheme as a core element of GCOS. 1. Introduction Mariners have recorded meteorological information for centuries, originally in their logbooks, and later in nationally designed weather logbooks or forms. These activities currently fall under the JCOMM Voluntary Observing Ship (VOS) Scheme. The meteorological reports have been collated in the International Comprehensive Ocean-Atmosphere Data Set (ICOADS, Woodruff et al. 1998, Worley et al. 2005) and have formed the foundation for the definitive studies of marine climate variability and change during the last century and also of present climatic changes. The observations have been collected in recent decades largely in support of Numerical Weather Prediction (NWP), and the VOS Scheme is run operationally by National Meteorological and Hydrological Services (NMHS). The observations are transmitted in real time to the NMHS, and most of the data are shared with other Services using the Global Telecommunications System (GTS). A minority of reports are withheld, considered too sensitive to share widely. While the basic technologies behind the VOS Scheme are generally fairly simple, the entire system is expensive to operate. Some of the instruments used are surprisingly costly, and infrastructure costs must be borne by individual maritime nations. These costs include maintaining networks of Port Meteorological Officers (PMOs), and the expenses associated with INMARSAT transmission since the weather observations are also part of the Safety Of Life At Sea (SOLAS) Convention. However, the quality of weather forecasts has become increasingly driven by data from satellites and drifting buoys. Some NMHS have questioned the need to maintain the VOS Scheme in the face of rising costs and increasing difficulty in recruiting ships. Experiments such as THe Observing System Research and Predictability EXperiment (THORPEX) have shown how to target observations in "sensitive areas" to improve short-range weather forecasts. Such targeting is however inefficient or impractical to achieve with a voluntary scheme such as the VOS, which depends on ships of opportunity. Inevitably support for the VOS from sponsoring nations, whose national VOS Programs are often operated by the same NMHS that are becoming less interested in using the data, has declined over recent years. Fewer reports are now received from ships. This decline in support, due to both the changing data requirements for short-range forecasts and increasing operational challenges, has generally ignored the needs of the climate change community. A community which is striving to define and quantify what is, arguably, one of the greatest challenges facing mankind. There is now a real divergence in the requirements for ship weather reports between the operators of national VOS programs and the downstream users of the data for climate research and other non-NWP activities. The operators in forecast centres require limited information, particularly atmospheric pressure and sea surface temperature (SST) and are encouraging the use of simple automatic systems recording a limited number of parameters (usually atmospheric pressure and air temperature or wind speed) but making more frequent observations. This has meant that the number of ships making the full marine report (containing wind speed and direction, atmospheric pressure, air and sea temperature, humidity, cloud information, wave parameters, weather codes and possibly ice information) is declining along with the spatial coverage of data. The effect of this decline on our ability to monitor the ocean is yet to be assessed. This situation was highlighted in a short article in CLIVAR Exchanges (Kent et al. 2006). If nothing is done, the VOS Scheme will likely continue its decline as the operators have little incentive to continue making observations when there are other priorities with proven benefit for NWP. Some intervention will be required to reverse the decline and improve the quality of datasets based on the VOS to serve the needs of climate research and assessment. We therefore need to confirm why such effort is vital, and what form the intervention must take. This report reviews the VOS Scheme and its role within the Global Climate Observing System (GCOS) in Section 2. The extensive use of VOS data and products for climate and other research is discussed in Section 3. Section 4 discusses the outlook for VOS data, including the many challenges facing the Scheme. Section 5 contains a summary and recommendations. 2. The VOS Scheme within the GCOS 2.1 VOS Scheme Operation (See Appendix A for additional background) 2.1.1 VOS Scheme Management The VOS Scheme is overseen by the Ship Observations Team (SOT) in the Observations Programme Area (OPA) of JCOMM. The requirements for ship data for forecasts and warnings are specified by the World Weather Watch of WMO, which is managed by the WMO Commission for Basic Systems (CBS). CBS also currently has responsibility for implementing the GTS through which the data are distributed. Ships are usually recruited to the VOS by a PMO. Ships are recruited to each national VOS Fleet on the basis of the willingness of the ships' officers to perform the observations, the regular route followed by the ship and the regularity with which the ship visits ports in the country concerned. PMOs visit VOS calling at their ports to check and calibrate the instrumentation, supply consumables, and discuss any observational problems. The activities of PMOs are essential to maintain the quality and quantity of data from ships. The quality of VOS reports is monitored by several meteorological centres, as well as by some NMHS for ships in their national fleet. The results of the monitoring are provided to PMOs, who can take follow-up actions to correct deficiencies. 2.1.2 The Observations VOS make observations of surface wind speed and direction, sea surface temperature (SST), air temperature, humidity, atmospheric pressure, cloud (including types) and wave parameters and weather information. Of these SST, air temperature and humidity as well as atmospheric pressure are measured in situ by meteorological instruments, while waves, clouds and weather information are estimated visually. Wind reports represent a mixture of measurements and visual data. Limited observation metadata are transmitted in the real time report and extensive metadata collected ashore which can often be related to individual observations. Preferred methods of measurement change over time and electronic logbooks are increasingly replacing paper versions. Electronic logbook software is used to format manual observations, calculate derived parameters (e.g. the true wind) and perform simple quality control. As marine instruments have become more robust an increasing number of automated weather systems (AWS) are being installed on VOS. A full high-quality AWS is expensive and some national services install lower cost AWS making only a small subset of the normal range of observations, typically atmospheric pressure and one or two other variables. Although the reporting of some metadata relating to AWS has been possible since 2002, it is only since 2007 that details about the AWS have become available. Some elements of the VOS report require manual input, for example the cloud, wave and weather reports. It has proved a challenge to convince observers that supplementing the report with this vital information is worthwhile and the introduction of AWS has led to a decline in the proportion of reports containing these parameters. Additionally adding the capability for manual input to AWS adds to both the cost and complexity of the system and is not always judged to be cost-effective. There has never been a systematic attempt to recruit research vessels using their own instruments to the VOS. This is because unknown instrument quality and calibration, irregular time at sea and changing personnel have led to a lack of continuity. Some research vessels carry dual instrumentation, a sophisticated set of research instruments, and the standard meteorological service instruments which are used for the VOS observations. These issues may in the future be addressed by the Shipboard Automated Meteorological and Oceanographic System Initiative (SAMOS: http://samos.coaps.fsu.edu/html/). 2.1.3 Data Flow Observations are transmitted as soon as they are made, usually by INMARSAT but increasingly using a variety of technologies. Observations received at a NMHS are shared with other services using the GTS. The longstanding character-based formats used for ship-to-shore transmission (currently FM-13, see Appendix A) and GTS data exchange are currently in transition prior to the WMO-mandated transition to Table Driven Codes (TDCs) (at least for GTS transmission) by 2012, which effectively seems to mandate use of the existing, but extremely complex, BUFR format. Rising transmission costs have already seen some VOS operators move to compressed ship messages. The implementation of these changes requires careful management as it has implications for the consistency of the ship climate record. Observations circulated on the GTS are available to NMHS for assimilation into NWP models and for other real-time applications. Some NMHS also keep an archive of data extracted from the GTS. Due to the vagaries of the real time transmission system, each historical archive will contain different data. Reasons for differences might include: different approaches to quality control and assurance, including the possible combination of fragmentary near duplicate reports; different methods of interrogating the GTS; different timeliness criteria and differences in data conversion and storage formats. Data collected in delayed mode (e.g. from the hard disks of electronic logbooks or digitised from paper logbooks) are sent in IMMT format (see Appendix A) at approximately three-month intervals, to JCOMM global collecting centres (GCCs). Delayed mode data have a slightly extended format and are typically used for climate applications. These reports, archived as part of the JCOMM Marine Climatological Summaries Scheme, form an important part of the climate archive but resource limitations mean that delayed mode data collected after 1997 have not been incorporated into ICOADS (see Appendix B). Limited metadata describing methods of measurement are transmitted with the observation in FM-13 format, and slightly more metadata elements can be conveyed in delayed mode as part of the IMMT format. However, more extensive metadata are available for climate applications in the WMO List of selected, supplementary and auxiliary ships (Pub. 47, see Kent et al. 2007). Key metadata elements in Pub. 47 include heights (or depth) of measurement for winds and temperatures, and measurement methods for air temperature, humidity and SST. To associate the corresponding metadata from Pub. 47 with each ship report there needs to be a valid callsign. For climate research and monitoring it is therefore essential that we can identify reports from individual platforms; any report with a blank or generic callsign cannot have height corrections or other metadata-dependent adjustments properly applied. Timeliness of metadata delivery has long been an issue. Currently the metadata is only one quarter late, but Pub. 47 metadata available from the WMO website (http://www.wmo.ch/pages/prog/www/ois/pub47/pub47-home.htm) has been more than a year out of date. The development of new initiatives such as a new pilot project to integrate marine meteorological and other appropriate oceanic observations into the WMO Global Observing Systems (WIGOS), have the potential to forge closer links between JCOMM and other WMO activities including the WMO Information System (WIS) and the Commission for Instruments and Methods of Observations (CIMO), and thus ultimately the Global Earth Observation System of Systems (GEOSS). 2.2 VOS Data Quality 2.2.1 Near Real Time Monitoring The monitoring of data quality for NWP applications is performed using comparisons of observations with model forecast information, climatology and other nearby observations. Information from the monitoring, carried out at NMHSs, for example the UK Met Office (http://www.metoffice.gov.uk/research/nwp/observations/monitoring/marine/index.html), is used to advise PMOs of data quality issues requiring their attention and provide information on data quality for use in NWP, for example the construction of "suspect lists" indicating observations of particular parameters from individual ships which might be considered for exclusion from NWP data assimilation schemes. 2.2.2 Climate Applications The quality of ship data has been the subject of a considerable amount of research. Some concluded that the observations were not suitable for use in climate research (e.g. Wright 1986, Peterson and Hasse 1987) and some concluded that the observations required adjustment (e.g. Folland and Parker 1995, Cardone et al. 1999). Quality issues have been discussed for decades, for example Kent and Taylor (2006) review studies published since the 1920s. This has led to a perception that the VOS data quality is low. However, all this research, combined with new methods of dataset construction, means that VOS datasets have been amongst the first to be fully characterised with meaningful estimates of data uncertainty (e.g. Gulev et al. 2003, Rayner et al. 2006, Berry and Kent 2008). VOS data contain fairly large random uncertainties, but in many regions the mean uncertainty due to poor sampling is much larger (Kent and Berry 2005, Gulev 2007). In well-sampled regions the random uncertainties in gridded datasets will be small as many observations can be averaged. Sampling by multiple platforms gives the potential for extensive quality assurance, including near neighbour "buddy checks" and analysis of outliers. Random uncertainty can be considered to have two components, that within observations from a single platform, and that amongst observations from different platforms. Typically VOS grid box averages contain observations from multiple platforms, allowing both components of the random uncertainty to be reduced by the averaging process. For observations which can be fully characterised (i.e. from a known platform which can be linked to Pub. 47 metadata) adjustments can be made for biases, or data rejected in environmental conditions where a particular measurement method performs badly. In recognition of the sometimes variable or poor quality of VOS data taken as a whole the VOS Climate Project (VOSClim) was devised as a mechanism to improve the quality of VOS data, initially for a subset of ships, but in the longer term to raise data quality across the VOS. VOSClim was originally envisaged as providing a high quality dataset suitable for climate studies, and for the calibration and validation of a range of model and satellite products. The VOSClim project also offered an opportunity to act as a reference model for ordinary VOS, to define and spread good observing practice, and to test out potential VOS improvements. VOSClim is erroneously seen by some as the sole provider of VOS data for climate applications. VOSClim data is currently under-utilised and the goals and outputs from VOSClim could be more widely advertised within the Climate community. 2.3 VOS in the Multi-Platform Observing System The composition of the GCOS is evolving rapidly. Increasingly weather forecasters are relying more heavily on the information provided by satellites and drifting buoys. The sheer volume of information from these sources has played a large part in the recent improvement of weather forecasts and there are now an order of magnitude more observations from buoys as from ships in ICOADS (Figure 1). The observations provided by each of the main types of observing platform (moored buoys, drifting buoys, ships, near-surface information from oceanographic profiles and satellites) each have a different character and each make an important contribution to the observing systems. For example, research at the Met Office has shown that the contribution of VOS to the SST observing system is equivalent to that of drifting buoys, despite the much smaller numbers of VOS observations. Moored buoys have the potential to provide high quality observations of a wide range of meteorological variables. For the best quality data we need the data from the buoys to be monitored and effective calibration and sensor replacement programs must be in place. The metadata required to make best use of these data are typically not readily available. The difficulties of maintaining surface moored buoys means that there can often be data gaps of many months before faulty sensors can be replaced. Moored buoys are expensive to maintain and cannot be reliably deployed in harsh environments. Oceanographic profiles provide information some of which is high quality, but with a fairly sparse distribution. Drifting buoys typically provide observations of a very narrow range of meteorological variables, some only measure sea surface temperature (SST) and position, others additionally report atmospheric pressure, air temperature or wind speed. The data quality is reasonably good for SST and atmospheric pressure, less good for air temperature and winds. As drifting buoys are often deployed in data sparse regions the opportunities for data intercomparisons and quality checks are often limited. Unfortunately, Argo floats do not provide acceptable near surface sampling of SST. Satellites are particularly useful for providing information on SST, winds and waves. However, satellite instruments have systematic biases which change as instruments age and orbital parameters change. VOS and other in situ observations are needed to correct these biases (e.g. Reynolds et al. 2007). Humidity and air temperature are much more difficult to retrieve from remotely sensed data and in situ data for ground truth and calibration of all satellite-derived meteorological variables are essential. For some variables, e.g. waves, information is only available directly below the satellite making global sampling sparse. Data from VOS are therefore our main source of air temperature, humidity, atmospheric pressure and wave information distributed over the ocean. Ships can provide observations of all the basic meteorological variables and their data can be used to estimate the air-sea exchange of heat and water. They make visual estimates of cloud cover which can be used to estimate the long- and short-wave radiation at the sea surface and report the prevailing and past weather conditions which can be used to make precipitation estimates. VOS observations are of major importance to climate researchers because of their long period of record which allows study of multi-decadal climate change. Satellite observations in contrast typically only cover the last two decades. In addition, it should be noted that atmospheric model reanalyses which are widely used for climate analysis are heavily dependent on the assimilation of ship observations. 3. VOS in Climate Research 3.1 VOS-based datasets The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is the primary climate archive of surface marine meteorological data, presently covering 1784 to mid-2007. ICOADS uses real time data from NCEP and prior to 1998 also incorporated data from the delayed mode. Resource limitations have meant that delayed mode VOS data from the last decade have not been added to ICOADS, priority having being given to data filling gaps in the very early record and data sparse periods such as the two World Wars. However, ICOADS also includes extensive delayed mode collections of moored and drifting buoy data for recent decades, as well as of near surface observations from oceanographic profiles. ICOADS also produces some simple gridded files of statistics (including mean, median, standard deviation, 1st and 5th sextiles, number of reports, number of daytime reports) for each variable (sea surface temperature, air temperature, scalar wind, wind components, sea level atmospheric pressure, cloudiness, specific and relative humidity) and further flux-related derived parameters. These summary statistics have been extensively used in climate research. However many researchers have sought to develop improved gridded datasets using the individual observations, using a variety of different methods of data selection, quality assurance, bias adjustment and dataset construction methodologies. Many papers have been published documenting the shortcomings of the VOS observations themselves, the derived datasets and the lack of sampling in some regions. However datasets and analyses based on ICOADS are highly cited in the literature and form an key resource for climate researchers, especially those interested in large-scale estimates of ocean-atmosphere exchange of heat, freshwater and momentum and multi-decadal climate variability. ICOADS and other important VOS-based datasets, in most cases building on the basic ICOADS observations or gridded summaries, are listed in Table 1. Table 1: Examples of VOS-based datasets ICOADS (http://icoads.noaa.gov/) - see also Appendix B. Individual reports and gridded summary products 1784 to 2007. (Woodruff et al. 1987, 1993, 1998, 2005, Worley et al. 2005). Over 1000 citations. SST HadISST1 - Globally complete sea-ice and SST 1870 to present (Rayner et al. 2003, http://www.hadobs.org/) HadSST2 - Uninterpolated sea-surface temperature 1850 to present (Rayner et al. 2006) Kaplan SST - Near-global monthly mean SST anomalies for 1856 to 1991 interpolated using reduced space optimal smoother (RSOS, Kaplan et al. 1998). NOAA Extended Reconstructed Sea Surface Temperature (ERSST) 1854 to present (Smith and Reynolds 2004) Merged Surface Temperatures - Globally complete SST and land surface temperatures 1870 to present (Smith et al. 2005). Pressure HadSLP2 - Monthly gridded sea-level atmospheric pressures 1850 to 2004 (Allan and Ansell 2006). EMSLP Daily gridded sea-level pressures in the Europe and North Atlantic region from 1850-2003 (Ansell et al. 2006). Kaplan Pressure - Near-global monthly mean sea level atmospheric pressure anomalies 1854 to 1992, interpolated using reduced space optimal interpolation (RSOI, Kaplan et al. 2000). Air Temperature and Humidity HadNMAT - Uninterpolated night marine air temperature 1856 to present (Rayner et al. 2003). HadCRUH Monthly gridded relative and specific humidity from 1973 to 2003. (Willett, 2007) Surface Fluxes NOCS Surface Flux datasets v1 & v2 - gridded monthly mean surface fluxes (v1, 1980 to 1993: Josey et al. 1999 & v2, 1970 to 2006: Berry and Kent 2008) UWM/COADS - da Silva gridded monthly mean surface fluxes 1945 to 1993 (da Silva et al. 1994). FSU - historical gridded tropical wind products ~1960 to ~2000 (Smith et al. 2004) and gridded monthly turbulent surface fluxes for 1978 to 2004 (method based on Bourassa et al. 2005) Clouds Climatic Atlas of Clouds Over Land and Ocean - gridded climatology of cloud parameters based on marine data from 1954 to 1997 (soon to be updated to 2007, Hahn and Warren 2007, www.atmos.washington.edu/CloudMap/) Waves Global Atlas of Ocean Waves - Wave atlas for 1958 to 2005 (Gulev et al. 2003). Significant wave height for the period 1900 2004 (Gulev and Grigorieva 2004).3.2 Applications of VOS-based Datasets 3.2.1 Assessment and Monitoring of climate change International assessments of climate change; for example the Intergovernmental Panel on Climate Change (IPCC) use VOS SST data in the vital assessment of global mean surface temperature. In many regions VOS are the only source of in situ SST information. Importantly, confidence in the marine surface temperature trend is increased by its consistency with the marine surface air temperature trend which is an independent quantity. VOS are the major source of air temperature information over the ocean. VOS also make a major contribution to the day-to-day monitoring of climate change, for example in the bias-adjustment of infrared satellite estimates of SST (e.g., Reynolds et al. 2007). Furthermore, VOS observations have been decreasing in number in the last two decades, while buoy observations have been increasing. Collocated global differences between VOS and buoy SSTs show that VOS SSTs are roughly 0.14C warmer than buoys (Reynolds, personal communication, 2008). A further reduction in VOS SSTs would make it even more difficult to monitor VOS and buoy differences. Changes in clouds in response to global warming are the biggest source of uncertainty in prediction of future climate. Cloud observations from VOS are essential to monitoring of cloud changes over the ocean. The synoptic code defining the cloud types (and the present weather, also needed to identify some types of clouds) has not changed since 1949, so we have a long period of record over which to examine changes. Continued monitoring using the same visual method and code is essential, as climate changes are expected to be more rapid in the near future. The IPCC also presents results from a century-long analysis of VOS wave information following Gulev and Grigorieva (2004) Importantly VOS wave data is the only source of independent separate estimates of sea and swell over the Global Ocean. VOS data were extensively used for the analysis of the variability of the intensity of synoptic processes and its climate variability (Zorita et al. 1992) and for the derivation of storm track intensity indices (Chang 2007). The continuing move to produce data products in a timely manner from VOS data should allow an enhanced climate monitoring role for the VOS, if sampling can be maintained or improved. 3.2.2 Reanalysis The Atmospheric Reanalyses are a heavily-used climate resource and VOS data are one of the major assimilation inputs. Each reanalysis assimilates different elements of the VOS reports. Bengtsson et al. (2004) showed the significant role of the assimilation of marine meteorology in NWP products such as reanalyses for the reliable representation of atmospheric dynamics. It is important that reanalyses are able to utilise the best data available, taking advantage of all research into quality assurance, bias adjustment and quantification of random uncertainty. One proposed initiative, tentatively called "Climate ICOADS", is aimed at addressing this requirement by incorporating the results of disparate research efforts to understand the VOS data into the ICOADS (see Section 4.1.3 for more information). Historical surface reanalyses also rely on VOS data (Compo et al. 2006). Figure 2 shows correlations among different monthly mean wind speed datasets in the North Atlantic. The correlation between the NCEP reanalysis (NCEP1, Kalnay et al. 1996) and the satellite wind speed dataset of Zhang et al. (2006) shows bands of poor agreement, particularly in the tropics. Agreement is better between the satellite winds and the ECMWF reanalysis (ERA40, Uppala et al. 2005), probably at least partly because ERA40 assimilates much of the same satellite data. However correlations between each reanalysis and a VOS-based data also show similar features, in regions where VOS sampling is adequate. This indicates that the higher correlations shown between ERA40 reanalysis and the satellite data are due to improved realisation of the winds in ERA40 compared to NCEP1. This 4-way comparison of datasets shows the value of multiple datasets and independent realisations of the same quantity - in this case only the VOS and satellite data are independent of each other. VOS cloud data have also been used to show biases in reanalysis estimates of cloud cover (Bedacht et al. 2007). 3.2.3 Calibration and Validation VOS datasets are currently under-utilised for calibration and validation. Historically, gridded datasets have contained monthly mean data. This makes understanding of any differences between data sources difficult as the number of data points for comparison is relatively small and any synoptic variability cannot be captured. New datasets at finer temporal resolution are now becoming available which should have wide applications for calibration and validation. Figure 3 compares daily mean air temperature from a VOS-only dataset (Berry and Kent 2008) with data from an operational moored buoy in the North Pacific. Problems with the buoy air temperature in 1982/3 are clear by comparison with the VOS data as are long gaps in the buoy operations. Figure 4 shows a comparison of VOS specific humidity estimates with a recent satellite-based humidity dataset; "Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data V3" (HOAPS3, http://www.hoaps.zmaw.de/). There are large differences between the monthly mean humidity from the two data sources in the period 1988 to 2005. Estimates of the uncertainty in the VOS product are shown and it is clear that many of the large differences are in areas well-sampled by the VOS suggesting the problem may be with the satellite retrievals. This suspicion is reinforced by the time series of daily estimates for a location in the North Atlantic in 2005. There are significant differences between the VOS and satellite estimates which fall well outside the 1-sigma uncertainty limits for the VOS dataset. The NCEP reanalysis data compares fairly well with the VOS data, although there are also periods of quite large differences requiring investigation. Figure 4 shows the importance of having a variety of different datasets for intercomparison, especially when the datasets are characterised with realistic uncertainty estimates. Daily estimates of marine surface humidity from the VOS should be a valuable resource for the improvement of existing satellite humidity datasets, and in the development of humidity datasets from the new generation of satellite-based atmospheric sounders. Improved in situ datasets, if available with minimal delay, could also prove an important validation source for NWP. 3.2.4 Air-sea Interaction VOS data have been essential for the development of multi-decadal air-sea interaction datasets (e.g. da Silva et al. 1994, Josey et al. 1999, Bourassa et al. 2005, Berry and Kent 2008). Figure 5 compares a VOS-based estimate of sensible heat flux (Berry and Kent 2005) with that from the OAFlux product (Yu et al. 2008). OAFlux is a flux dataset synthesised from a combination of reanalysis output (NCEP1&2 and ERA40) with satellite data (winds, SST, humidity). The upper panel in Figure 5 shows the correlation between the monthly means sensible heat flux estimates from the two datasets over the period 1970 to 2006. The lower panel shows the uncertainty estimate for the VOS dataset for the same period. It should be noted that although OAFlux does contain estimates of uncertainty it is not yet clear how valuable they are. For example there is little difference in OAFlux uncertainty estimates in the pre-satellite and satellite periods. Correlations between the flux estimates are invariably low in regions where the VOS sampling is poor and hence the VOS uncertainty estimates are large. However in well-sampled regions there are some interesting regions of low correlations, for example off the west coast of the USA. New daily VOS flux estimates in well sampled regions should help us understand the reasons for these differences and eventually lead to improved flux estimates from all sources. 3.2.5 Other Applications Real time applications include: assimilation into NWP; satellite SST bias removal; preparation of warnings for ship routing and avoidance of severe weather conditions; the preparation of forecasts and warnings for offshore industries. Delayed mode applications of climatological information from the VOS are used for the design criteria for ships and marine structures. The VOS data are used in design criteria, both directly (e.g. Hogben and Lumb 1967), and indirectly through more modern techniques of wind and wave hindcasting, which combines VOS data and numerical models. The VOS data represent a critical component of the hindcast process, especially for winds, but also for air and sea temperatures, pressure, and wave observations. Datasets based on ICOADS have been used in a variety of applications beyond climate variability and change, including fisheries, changes in coastal geological features, and assessments of global anthropogenic emissions from ships (see Worley et al. 2005 and references therein). New and emerging applications include providing broad-scale context for process studies, NWP validation, validation of climate models, climate change attribution, decadal prediction, seasonal forecasting, quantifying uncertainties in model prediction and ground truth for pre-instrumental proxy data. 3.3 Requirements for GCOS VOS are an important component of the GCOS, reporting several of the Essential Climate Variables (ECVs, GCOS 2004) including air temperature, atmospheric pressure, wind speed and direction, water vapour, SST and sea state. VOS also provide cloud information which can be used in parameterisations of the surface radiation budget, and weather codes which can be used to estimate precipitation. Several reports have considered the desirable observational network for climate monitoring purposes including GCOS 2004, Koblinsky and Smith 2001, OCEANOBS 1999, OOSDP 1995 and Weller and Taylor 1993. Despite the VOS providing information on many of the GCOS Essential Climate Variables (GCOS 2004), there are currently no targets for VOS data collection, or monitoring of VOS observations against GCOS requirements, or in the JCOMM OPA Strategic Workplan. The nature of the VOS makes the quantification of adequacy of their observations difficult, but recently progress has been made towards this (e.g. Kent and Berry 2008). This research showed that typically for the construction of climate datasets it is important to obtain data from a variety of different platforms (e.g. from a range of different ships), appropriately separated in space and time (see Appendix C for more information). In summary the desirable features of a surface marine observing system are: a large number (presently being quantified through continuing research) of observations adequately sampling in space and time; known (and preferably high) data quality; a large number of identifiable platforms with known measurement methods and sufficient metadata; monitoring and analysis of data quality; wide range of variables; consistency with (or quantifiable differences from) past observations; feedback of monitoring and analysis results to VOS operators and observers. 4. Outlook 4.1 Challenges for the VOS Scheme 4.1.1 Poor Understanding of VOS Data Many find it hard to understand how VOS data with their well-documented biases and noise can be used for climate applications where high quality and consistency are required. VOS data are therefore sometimes discounted as a climate resource by those planning the GCOS, despite the efforts of the many climate researchers who devote significant effort to understanding and analysing the data and producing high-quality datasets from the observations. Within GCOS the responsibility for surface marine data is split between the ocean (SST, sea state and sea ice) and the atmosphere (near surface air temperature, humidity, winds, and atmospheric pressure, precipitation, clouds and radiation) which is not ideal. Users of VOS data for climate applications have, through past organisational structure, been isolated from the operators responsible for collecting the data; a far from ideal situation. In the past climate datasets were typically updated every three years, although either monthly or annual updates are now more likely. 4.1.2 Operational Challenges The many operational challenges for the VOS are described in AOPC-XIV/Doc. 27. These include: the difficulty of recruiting to VOS; the reluctance of VOS with AWS to keep reporting manual observations such as clouds, weather and wave information; problems with metadata collection and delivery, and ship security and commercial concerns. Automation of VOS has the potential to be extremely valuable for GCOS. However many of the AWS installed on VOS are of low cost, reporting a limited range of variables. Even high quality systems, such as the Canadian AVOS, which have the potential to provide complete ship reports have lead to a reduction in the number of cloud, weather and wave observations. This is because, despite the system allowing the simple recording of cloud and weather information via a touch screen, the observers are often reluctant to supplement the automatic measurements with manual observations. Additionally automatic systems may report more frequently than manual systems, but this short time interval results in the observations being highly correlated with preceding and succeeding reports; the extra information provided is less than might at first appear. While this may be helpful for NWP data assimilation systems, which can utilise time-dependent information, the impact of such highly correlated data on the uncertainty of gridded climate datasets is much smaller than for more widely-spaced observations. For climate applications it is essential that the quality and completeness of the report, the availability of metadata and the available sampling are all accounted for in any assessment of data adequacy. The transition to BUFR is causing concern that the consistency of the climate record may suffer. The ultimate responsibility for the production of BUFR and other data format templates within WMO seems to fall under the CBS Expert Team on Data Representation and Codes (ET/DRC). Although some interaction has occurred between this group and JCOMM bodies and projects such as SOT and the Expert Team on Marine Climatology of the JCOMM Data Management Program Area (DMPA), it is not clear that an effective and rigorous assessment of the proposed templates has occurred, partly due to the complexity of BUFR and the wide gulf in experience between the JCOMM groups responsible for making the observations or assessing climatological impacts, and the highly technical CBS groups. For example, a SOT Task Team reviewed the existing BUFR templates for the VOS and made many recommendations but there has been no follow-up communication from the ET/DRC. In recognition of these issues JCOMM (2008) recommended that Enhanced interaction between JCOMM and CBS or other appropriate WMO committees is needed to expand the scope of Table Driven Codes (TDCs) to more fully incorporate JCOMM considerations, including software reliability, human readability, and the archival and exchange of historical and delayed-mode data in its originally reported form. Moreover, the recently concluded Third Session of the JCOMM Data Management Coordination Group recommended that a single organizational focus across JCOMM program areas be developed for interaction with CBS on these issues. The availability of VOS observations on public websites has caused concern amongst ship operators. Initially concerns were in the area of ship security, but later spread to include commercial sensitivity and the availability of data in delayed mode. This has lead to a variety of solutions being implemented (AOPC-XIV/Doc. 27). It is hoped that the identification of data from individual ships which is essential for both quality checking and the association of metadata will continue to be possible. This will require the proper implementation of short-term masking methods endorsed by SOT, the maintenance of a secure database containing ship masking information and the provision of the original (unaltered) data to monitoring centres by secure methods. It is essential that this information is made available in the climate archive, on timescales that do not compromise ship security. If this does not happen then there will be problems for data adjustment and quality assurance for climate datasets. Resource limitations mean that the size of the PMO network has declined in recent years, alongside a diversification of PMO responsibilities. Often VOS is one of a number of responsibilities for VOS operators and workloads are typically high. Increasing internationalisation of shipping operations means it is hard to find ships suitable for recruitment. VOS is directly affected by the highs and lows of world shipping and the economic climate and constant changes and volatility in trading patterns has led to ships being lost from national lists Also as noted above, Pub. 47 metadata delivery by WMO has long been erratic, causing difficulties for ship operators, PMOs and climate researchers alike. WMO needs to allocate sufficient resources to address these problems, or else other solutions to making metadata available in timely fashion need to be developed within JCOMM (e.g., separating rapid metadata delivery from formal WMO publication, which could follow later). 4.1.3 Delayed Mode and Data Archival Resource pressures in recent years, due to the prioritisation of operational real time data management within NOAA, have led to an under funding of ICOADS activities within NOAA/ESRL and NCAR. Therefore, recent ICOADS updates for periods after 1997 exclusively rely on GTS data for the VOS component. Many important data sources, including delayed mode VOS data from the GCCs, the results of digitisation efforts for historical data sources and data collected by research vessels are yet to be incorporated into the ICOADS archive. See Appendix B for more information. The need to store corrections developed for VOS observations within ICOADS has been raised in the climate community. Through extensive research efforts, the climate community has developed corrections that include (but are not limited to) diurnal ship heating, Beaufort wind adjustments, and adjustment for instrument height and known instrument types (e.g., bucket vs. intake SST). Discussions began in 2008 toward develop a set of individual marine reports from ICOADS that are corrected in a manner that best represents our current state-of-the-art. As possible, the known corrections (and associated uncertainty estimates) would be included in the ICOADS for the entire 1784-2007 data record. The planners anticipate that the corrections would vary in time (e.g., ship heating rates would be different for metal vs. wooden ships). The outcome of the proposed activity would be master marine climate data set that includes bias correction and uncertainty measures, tentatively labeled Climate ICOADS. The product would be the marine equivalent of efforts by world climate centers to create land-based data sets that adjust for station moves and instrumentation changes. The Climate ICOADS would pull together research efforts into VOS biases from the past several decades to create a global community resource that would be available for current and future generations of scientists. The Climate ICOADS set would be ideal to develop new surface flux datasets, new or enhanced Monthly Summary Statistics (MSS), and enhanced marine climate indices. 4.2 A Possible New Approach Relying on the established VOS data delivery systems for climate-quality data has placed restrictions on content of the reports. An alternative approach for the future may be to more clearly distinguish between the real time data, which serves the NWP community and the delayed mode data, which serves GCOS and climate research. This was the model in the past when the GTS reports were a subset of the more comprehensive keyed logbook data. The distinction between the two streams is now blurred and consequently some countries do not currently contribute to the delayed mode. There could be a variety of advantages in an approach which clearly distinguishes between NWP and climate user requirements. For example, ship operators might be keen to contribute to GCOS to improve their environmental credentials. In delayed mode the ship report could be extended to include extra variables, and precision and metadata important for climate quality; ships with automatic weather stations (AWS) could log additional reports for delayed transmission; and ship security and commercial issues would be ameliorated. Overall, we would have more ability to plan and manage for greatest efficiency in the observing system for climate. There are also potential benefits to NWP if high-quality datasets (with error characterisation) become available within a few weeks for model validation. However there may also be disadvantages: VOS operators may be unwilling to play a part in a climate observing system, the benefits of making observations for a forecast are perhaps more immediately obvious; the delayed mode infrastructure would require modernising and reinvigorating; it would be more difficult to associate reports with model output for quality control and assurance and additional resources would be required for monitoring, data analysis and maintenance of climate archives. Currently the vast majority of VOS reports are available in real time. JCOMM, through its Task Team on Delayed Mode VOS, are currently investigating the possibilities for improving the data flow and stewardship for climate applications. 4.3 The Future for VOS Reversing the decline in the number of ship observations will require finding new resources, despite increasingly tight national and international budgets. In support of such efforts, it will be critical to review and define user requirements for a wide range of applications and to make adequacy assessments using those requirements. The support systems for the ships (for example the PMO network) are also declining and will require bolstering if we are to maintain the quality of observations from VOS. New observation sources such as automated systems on VOS and the integration of research vessels into the observing system through, for example, the SAMOS Initiative may prove part of the answer. But any transition must be well-planned and address the homogeneity requirements of climate assessments. It is clear that to characterise the marine atmosphere, to even the same standards as achieved 20 years ago, requires the maintenance of a more distributed system than that which we now have. ODAS are not presently the answer as moored buoys cannot monitor the global ocean, and drifters do not meet the multi-variate accuracy requirements of the climate community. The VOS have served us well and should be recognised as making a valuable and ongoing contribution to the marine record. We must ensure that this contribution is maintained and enhanced until we are sure that any candidate systems to replace the VOS fulfil the Global Climate Observing System Monitoring Principles (GCOS, 2004). 5. Summary The VOS Scheme and its predecessors have provided climate information going back centuries, but this important observing programme is under threat resulting in a perceived divergence of requirements between NWP and climate applications. The VOS Scheme operates from within NMHSs and resource pressures have caused operators to focus on the operational elements of the VOS Scheme with applications in forecasting and warning, arguably to the detriment of VOS as a climate resource. Surface meteorological observations of wind speed and direction, sea surface temperature (SST), air temperature, humidity, atmospheric pressure, cloud and wave parameters and weather information are made by many different ships, recruited to the VOS Scheme by a range of different countries. These observations are transmitted in real time for NWP applications, and an extended report is recovered in delayed mode for climate applications as a contribution to GCOS. Limited observation metadata are transmitted in the real time report and extensive metadata collected ashore which can be related to individual observations using the ship callsign. The VOS Scheme has been operating with limited resources whilst costs and the complexity of the Scheme have been increasing. Recent challenges include ship security concerns leading to data loss and anonymous observations, lack of up-to-date metadata available at WMO and the decline of the PMO network (see AOPC-XIV/Doc. 27). VOS report GCOS ECVs including air temperature, atmospheric pressure, wind speed and direction, water vapour, SST and sea state. VOS also provide cloud information which can be used to give estimates of the surface radiation budget, and weather codes which can be used to estimate precipitation. VOS are our major sources of air temperature, humidity and atmospheric pressure information over the ocean and provide all the variables required to calculate heat, freshwater and momentum fluxes. The diversity of the observations, in terms of data quality, types of instruments and observing practice, and changing composition over time is both an asset and a challenge. The range of different observations allows intercomparison of data from different sources, there is a significant body of literature describing the characteristics of different observation types. Some observation types contain biases which can be corrected if the associated metadata are available to identify those observations which require adjustment. A wide variety of datasets for climate applications have been developed using VOS data, most recent datasets are based on ICOADS the most complete archive of surface marine data. Important multi-decadal datasets include SST, atmospheric pressure, air temperature, surface fluxes and atlases of cloud and wave parameters. Applications for these datasets include: climate change detection, variability and air-sea interaction studies and the calibration and validation of reanalyses, operational data and satellite datasets. Improvements in dataset construction techniques, for example new higher resolution datasets, will allow further exploitation of the VOS data. The role and benefits of monitoring and clearly defined user requirements is outlined. The complex and somewhat random nature of VOS sampling, combined with the diversity of ships contributing to the VOS Scheme mean that quality assessments are hard to make. However recent progress toward understanding the data requirements for VOS has been made, showing clearly the advantages of the VOS multi-platform sampling. 6. Recommendations 1) A wide ranging review of user requirements for marine meteorological observations should be conducted including potential revision to the GCOS Implementation Plan. 2) Robust adequacy assessments of the marine meteorological observing system should be made operationally against the user requirements identified under (1). 3) The support system for the ship network including Port Meteorological Officers should be improved. 4) The provision of timely, accurate and complete metadata to accompany all in situ observations should become a priority and be appropriately resourced. 5) Clearer responsibilities are required within international bodies for ongoing assessment and implementation of the marine meteorological observing system, and of the costs and benefits of future design changes. 6) Investment is required in climate data management for VOS and other ODAS to ensure that climate archives (e.g. ICOADS) are as complete as possible, and incorporate and disseminate the latest information on data quality. Improved quantitative demonstrations of the value of adding delayed mode data and metadata are desirable. 7) Support the activities of the VOS Panel, a sub-panel of the SOT and responsible for coordinating the VOS Scheme, in (a) transferring the benefits and experience gained from VOSClim to the wider VOS, and (b) raising awareness of the VOS Scheme within IMO and the Marine Community at large. These activities will contribute to enhancing the VOS Scheme as a core element of GCOS. Figures  Figure 1. Annual numbers of marine reports in ICOADS, stratified by platform type for 1936 to 2005. (Ship photo courtesy of www.ShipPhotos.co.uk.) Figure adapted from: Woodruff et al. 2008.  Figure 2. (top row) Correlation coefficients for monthly mean wind speeds from reanalysis (NCEP1, Kalnay et al. 1996, and ECMWF, Uppala et al. 2005), satellites (Zhang et al. 2006); (lower row) correlations of the same reanalysis with an Optimal Interpolation (OI) analysis of VOS data (Berry and Kent 2008). The period is 1970 to 2006. Note that ECMWF winds end in mid 2002 and the satellite winds start in mid 1987. VOS winds are masked to only include regions where the sampling is judged to be adequate for use in the comparison. The annual cycle is included in the correlation calculation..  Figure 3. Air temperature (C) comparison of NOCS VOS derived OI dataset with NDBC buoy 46006 (SE PAPA, 40.9N 137.5W). The buoy data show large data gaps and a calibration offset in 1982/83.  Figure 4. Specific humidity difference (gkg-1) HOAPS3 Satellite estimates - VOS-based NOCS OI Dataset (upper left panel). Monthly mean specific humidity total uncertainty (gkg-1) from NOCS OI Dataset (upper right panel). Time series of specific humidity at 20W, 20N from NOCS OI Dataset (black, grey shading indicates 1 standard deviation from OI error estimates), HOAPS3 Satellite estimates (red) and NCEP1 (green) (lower panel).  Figure 5. Correlation between monthly mean sensible heat flux (Wm-2) from NOCS VOS OI Dataset and OAFlux for the period 1970 to 2006 (upper panel). Monthly mean total uncertainty (Wm-2) from NOCS OI Dataset (lower panel). Acknowledgements Some text has been copied from the SOT ( HYPERLINK "http://www.jcommops.org/sot/" http://www.jcommops.org/sot/) and VOS ( HYPERLINK "http://www.bom.gov.au/jcomm/vos/" http://www.bom.gov.au/jcomm/vos/) websites. Buoy data in Figure 3 was provided by NOAAs National Data Buoy Center. The OAFlux dataset was downloaded from the Objectively Analyzed air-sea Fluxes Project (OAFlux) website: http://oaflux.whoi.edu/. The HOAPS-3 dataset was downloaded from the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) website: http://www.hoaps.zmaw.de/. ECMWF ERA-40 data have been obtained from the ECMWF data server. 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Thomas, B. R., E. C. Kent, V. R. Swail and D. I. Berry, 2007: Analysis of Monthly Mean Marine Winds Adjusted for Observation Method and Height, International Journal of Climatology, DOI: 10.1002/joc.1570. Uppala SM, et al. 2005. The ERA-40 re-analysis, Quarterly Journal of the Royal Meteorological Society 131: 2961-3012, DOI: 10.1256/qj.04.176. Weller, R.A. and P.K. Taylor, 1993: Surface Conditions and Air-sea Fluxes, CCC0-JSC Ocean Observing System Development Panel, 131pp, Texas A&M University, College Station, TX 77843-3146, 131pp. Willett, K. W., 2007: Creation and Analysis of HadCRUH: a New Global Surface Humidity Dataset, PhD Thesis, University of East Anglia, 199pp. WMO, 1956: International Cloud Atlas. 62 pp. + 72 plates. WMO, Geneva. WMO Guide to Meteorological Instruments and Methods Of Observation (CIMO Guide) draft SEVENTH EDITION (2006): http://www.wmo.ch/pages/prog/www/IMOP/publications/WMO-8-Guide-contents.html Woodruff, S.D. R.J. Slutz, R.L. Jenne, P.M. Steurer, 1987: Bulletin of the American Meteorological Society, 68(10), 1239-1250. Woodruff, S.D., S.J. Lubker, K. Wolter, S.J. Worley and J.D. Elms, 1993: Comprehensive Ocean-Atmosphere Data Set (COADS) release 1a: 1980-92. Earth System Monitor, 4(1), 4-8. Woodruff, S.D., H.F. Diaz, J.D. Elms, and S.J. Worley, 1998: COADS Release 2 Data and Metadata Enhancements for Improvements of Marine Surface Flux Fields. Physics and Chemistry of the Earth, 23, 517-527. Woodruff, S.D., H.F. Diaz, S.J. Worley, R.W. Reynolds, and S.J. Lubker, 2005: Early ship observational data and ICOADS. Climatic Change, 73, 169-194. Worley SJ, Woodruff SD, Reynolds RW, Lubker SJ, Lott N (2005) ICOADS Release 2.1 data and products. Int. J. Climatol. 25: 823-842 Wright PB. 1988. On the reality of climatic changes in wind over the Pacific. Journal of Climatology 8: 521-527. Yu, L., X. Jin, and R. A. Weller, 2008: Multidecadal Global Flux Datasets from the Objectively Analyzed Air-sea Fluxes (OAFlux) Project: Latent and sensible heat fluxes, ocean evaporation, and related surface meteorological variables. Woods Hole Oceanographic Institution, OAFlux Project Technical Report. OA-2008-01, 64pp. Woods Hole. Massachusetts. Zhang, H.-M., J.J. Bates, and R.W. Reynolds, 2006: "Assessment of composite global sampling: Sea surface wind speed". Geophysical Research Letters, VOL. 33, L17714, doi:10.1029/2006GL027086. Zorita, E., V. Kharin and H. Von Storch, 1992: The Atmospheric Circulation and Sea Surface Temperature in the North Atlantic Area in Winter: Their Interaction and Relevance for Iberian Precipitation. Journal of Climate, 5, 1097-1108. Appendix A: Additional Voluntary Observing Ship (VOS) Scheme Background Introduction Early observations of the weather recorded in ships logbooks form a unique climate record (Woodruff et al. 2005). For example, logbooks kept by officers from the 17th century until 1850 and held in the archives of Britain, Holland, France and Spain were digitised in the Climatological Database for the World's Oceans (CLIWOC) project (Garca-Herrera et al. 2005). In August-September 1853, a Maritime Conference was convened in Brussels by Lt. Matthew Fontaine Maury of the US Navy for the purpose of "establishing a uniform system of meteorological observations at sea, and of concurring in a general plan of observation on the winds and currents of the ocean." This was the first international meteorological conference and led to the establishment, 20 years later, of the International Meteorological Organization, the predecessor of WMO. As such, it was a key milestone in the development of present-day operational meteorology and oceanography. Early in the twentieth century observations from ships started to be transmitted in real time via wireless telegraphy for use in weather forecasting. It also became possible for meteorological offices ashore to transmit warnings of dangerous conditions to the ships. At the 1929 meeting of the SOLAS Convention, provision was made for the international encouragement of meteorological work at sea. Met. Services of most maritime countries made arrangements with ships regularly visiting their shores to take marine meteorological observations and transmit them to shore at no cost to the ship. The observations themselves still are usually provided free of charge by shipping companies in return for the instrumentation and the forecasting and warning service. Currently ship observations are taken as part of the VOS Scheme, an international programme comprising member countries of the WMO that recruit ships to take, record and transmit weather observations whilst at sea, as well as encourage the delayed-mode submission of paper or increasingly electronic logbook reports. The VOS (http://www.bom.gov.au/jcomm/vos/) Scheme is a core observing programme of the Ship Observations Team (SOT: http://www.jcommops.org/sot/) in the Observations Programme Area of JCOMM. It should be noted that participation in VOS is voluntary; the observers are generally not paid to take weather observations, nor are they experts in taking weather observations,and it must be emphasised that their primary role is the safe navigation of the ship. The requirements for forecasts and warnings are specified by the World Weather Watch of WMO, which is managed by the Commission for Basic Systems (CBS). CBS also currently has responsibility for implementing the Global Telecommunications System (GTS) through which the data are distributed. It is anticipated that the GTS will transition to become part of the WMO Information System (WIS: http://www.wmo.int/pages/prog/www/WIS-Web/home.html). Most VOS participate as "Selected Ships" in that they are equipped with sufficient certified meteorological instruments for making observations, transmit regular weather reports and enter the observations in meteorological logbooks. Selected Ships should have at least a calibrated barometer, a thermometer for sea-surface temperature, a psychrometer and a barograph. Other VOS are either "Supplementary" or "Auxiliary" and take more limited observations. Auxiliary Ships usually report from data-sparse areas outside the regular shipping lanes. Ships are recruited by Met. Services, usually through a PMO, who recruits ships of all flags, not just those on the national register, into the national VOS Fleet. Ships are recruited on the basis of the willingness of the ships' officers to perform the observations, the regular route followed by the ship and the regularity the ship visits ports in the country concerned. The PMO is a representative of the NMHS and is the primary contact with local maritime authorities and the maritime community at large. Without the dedication and enthusiasm of the PMO the quality and quantity of data from ships would be adversely affected. PMOs visit VOS calling at their ports to check the instrumentation, calibrate the barometer, supply stationery such as barograph charts or logbooks as required, and discuss any observational problems with the Master and officers. The quality of VOS reports is monitored by several major meteorological centres, primarily the Met Office, United Kingdom as WMO-designated lead centre for monitoring the quality of surface marine data. Results of this monitoring are compiled and distributed at monthly and six-monthly intervals to PMOs, who are expected to take follow-up actions to correct deficiencies. Technology The instruments typically carried by the VOS are described in WMO Publication No. 8 (Guide to meteorological instruments and methods of observation, 2006) and in national publications. Details of the instruments carried by individual ships are given in WMO Publication No. 47 (List of selected, supplementary and auxiliary ships; see Kent et al. 2007). The VOS have always used a variety of instruments, although this introduces inhomogeneity into the dataset, it also allows intercomparison of measurements made using different methods, which can give insight into the characteristics of the observations (e.g. Kent et al. 1993). The instruments used by the VOS include: wet and dry bulb thermometers exposed in marine screens or sling psychrometers; a range of different types of anemometer; barometers and barographs. Methods of measurement have tended to change over time, for example visual observations of wind parameters are being replaced by measurements from anemometers (Thomas et al. 2007) and bucket measurements of SST by engine intake or hull sensors (Kent and Taylor 2006). Remote reading technology has allowed instruments to be located in positions remote from the bridge which can be better exposed (Berry and Kent 2005). It is expected that in the basic VOS (i.e. those without automated systems) there will be a move to digital instruments as existing autographic and analogue instruments become harder to maintain. In order to reduce the workload on ships' officers, several means of automation of the observations have been developed. In one form, such as the TurboWin electronic logbook, the observations are still taken manually but then entered into a personal computer which then calculates the true wind, the mean sea level atmospheric pressure (correcting for the height of the bridge) and the dew point. The computer can perform simple quality control, code the observations in a manner ready for transmission by INMARSAT, and format the observation in logbook format for digitisation. As marine instruments have become more robust an increasing number of automated weather systems (AWS) are being installed on VOS. However this poses a number of problems. It is not always easy to find well-exposed locations for the sensors and air flow distortion may be a problem (Moat et al. 2005). A full high-quality AWS is expensive and some national services install lower cost AWS making only a small subset of the normal range of observations, typically atmospheric pressure and one or two other variables. Unfortunately the metadata have only recently become available to identify which ships carry AWS and the type. Despite the wide range of instruments used by VOS, there has never been a systematic attempt to recruit research vessels using their own instruments to the VOS. The view has been taken that any instruments should be installed and checked by PMOs. Indeed some research vessels carry dual instrumentation, a sophisticated set of research instruments, and the standard meteorological service instruments which are used for the VOS observations. The Shipboard Automated Meteorological and Oceanographic System Initiative (SAMOS: http://samos.coaps.fsu.edu/html/) aims to co-ordinate and improve meteorological observations from ships and is working with the JCOMM Ship Observations Team (SOT) on these issues. Manual Observations Manual observations have always been an important part of the ship data. Ship's officers make visual estimates of the wind speed from sea state, wave parameters, cloud amounts and types, weather information and ice parameters. Clouds are important in the Earth's climate system because of their effects on solar radiation, terrestrial radiation, and precipitation. These effects depend on cloud height, thickness, horizontal extent, horizontal variability, water content, phase (liquid or ice), and sizes of droplets and crystals. It is therefore useful to distinguish different types of clouds. The visual appearance of clouds is often taken to indicate characteristic atmospheric dynamical processes, so the traditional classification by weather observers of cloud types based on their appearance (WMO, 1956) continues to be a useful classification in studies of cloud processes (Houze, 1993). Data Flow Real Time Contemporary ship's observations are usually reported at the standard synoptic hours of 0000, 0600, 1200 and 1800 UTC and are sent to a meteorological service as soon as they are made. Observations received at a NMHS are shared with other services using the GTS. Currently observations are circulated on the GTS using the plain text ship code format known as FM-13. This is usually the same format used by the ship to transmit the observation from ship to shore. From 2012 the WMO has mandated the use of TDCs (such as Binary Universal Form for the Representation of meteorological data (BUFR)) for all GTS transmission. Rising transmission costs have already seen some VOS operators move to compressed ship messages. BUFR messages are larger than FM-13. BUFR templates for the data formats are still under development and there are concerns that this radical change of format will have implications for the consistency of the ship climate record, concerns heightened by the current lack of certified encoding and decoding software, and insufficient validation to ensure the full preservation of originally reported data details. In the run-up to the implementation of BUFR the content of the FM-13 ship message was frozen and no changes were allowed. This means that the implementation of BUFR is required for any additional elements, or improved resolution for selected elements to be added to the ship message. The observations received directly by Met. Services are combined with others extracted from the many marine data types circulated on the GTS. Some Met. Services only keep a rolling archive of recent data, while others keep a full historical archive of data extracted from the GTS. Due to the vagaries of the real time transmission system, each historical archive will contain different data. Reasons for differences might include: different approaches to quality control and assurance, including the possible combination of fragmentary near duplicate reports; different methods of interrogating the GTS; different timeliness criteria and differences in data conversion and storage formats. Delayed Mode Marine meteorological observations are recorded on board ships either in special logbooks provided by national Met. Services or electronic logbooks such as TurboWin (http://www.knmi.nl/turbowin/), SEAS (http://seas.amverseas.noaa.gov/seas/) and others. Data are stored in a standard, internationally agreed, format by the electronic logbook and may be collected by the PMO of the recruiting country on magnetic media, or in some cases transmitted direct to the NMHS from the ship. These data are then sent, at approximately three-month intervals, to JCOMM global collecting centres in Germany (http://www.dwd.de/gcc) and the United Kingdom (http://www.metoffice.gov.uk/research/interproj/gcc/index.html). These centres ensure that minimum quality control has been applied to the data and forward the data to 8 "Responsible Members" who archive the data and have responsibility for the preparation of regional climatological summaries: the Marine Climatological Summaries Scheme (MCSS). The JCOMM Expert Team on Marine Climatology (ETMC: http://icoads.noaa.gov/etmc/) currently has a Task Team developing a plan to modernise and streamline operation of the MCSS. The format used for this data exchange is International Maritime Meteorological Tape (IMMT) format, the most recent version is IMMT-3 (see http://icoads.noaa.gov/etmc/j2-rec9.pdf for more information). Metadata The need for metadata, data about data, to accompany VOS reports has long been recognised. Climate researchers need to know as much information as possible about the data and the ships or other automated Ocean Data Acquisition Systems (ODAS), which produce the data. Some of this information can be transmitted with the report, such as the ship callsign and methods of SST and wind measurement. Additionally a list of all VOS and their instrumentation is included in the WMO Pub. 47, on the basis of information supplied by participating NMHS. Pub. 47 is available digitally from 1973 onwards (1973-1997 as annual files, quarterly thereafter). More information is given by Kent et al. (2007). The importance of these metadata to climate research is demonstrated by the US National Climatic Data Center (NCDC) agreeing to fund the digitisation of the metadata from 1955 to 1972 as part of its Climate Database Modernization Program (CDMP). Key metadata elements in Pub. 47 include heights of measurement for winds and temperatures, and measurement methods for air temperature, humidity and SST. To associate the corresponding metadata from Pub. 47 with each ship report there needs to be a valid callsign included with the report (similar requirements apply to ODAS). For climate research and monitoring it is therefore essential that we can identify reports from individual platforms; any report with a blank callsign, or generic callsign such as SHIP, cannot have height corrections properly applied or a full range of measurement methods assigned. Timeliness of metadata delivery has long been an issue. Currently the Pub. 47 metadata available from the WMO website (http://www.wmo.ch/pages/prog/www/ois/pub47/pub47-home.htm) is a year out of date. Appendix B: Additional International Comprehensive Ocean-Atmosphere Data Set (ICOADS) Background The International Comprehensive Ocean-Atmosphere Data Set (ICOADS) is the primary climate archive of surface marine meteorological data, presently covering 1784 to mid-2007. ICOADS grew out of datasets held by the US National Climatic Data Center and has been supplemented over the years by data from the Japanese Kobe Collection, the US Maury Collection, the UK Met Office Marine Data Bank, the Russian MARMET marine archive and many others. A major new historical update is planned to incorporate a wide variety of new or updated sources (~1662-2007). These will include the Climatological Database for the World's Oceans (CLIWOC 1662-1855, http://www.ucm.es/info/cliwoc/, Garca-Herrera et al. 2005), near-surface data from the World Ocean Database 2005 (~1772-2005), Deutscher Wetterdienst ships (1876-1914), US Marine Met. Journals (1878-94), Japanese Kobe Collection (2003 Ed., 1889-1940) and Whaling Data (1946-84), Russian Research Vessels (R/V; 1936-2000), UK Royal Navy Ship's Logs (1938-47), a portion of the UK Marine Data Bank (1950-79), 19th-20th Century Antarctic Expedition Logbooks, and Center for Ocean-Atmospheric Prediction Studies (COAPS) R/V Data (1980-98). ICOADS uses real time data from NCEP and prior to 1998 also incorporated data from the delayed mode (see sec. 3.1). Resource limitations have meant that delayed mode VOS data from the last decade have not been added to ICOADS, priority having being given to the historical data. ICOADS also includes extensive moored and drifting buoy data for recent decades. Combining data from many sources requires extensive duplicate checking. The report expected to be of highest quality and more complete is used in ICOADS, a decision generally based partly on the source of the data and partly on quality control (QC) results. Sometimes elements from duplicate data from different sources are combined. ICOADS performs fairly basic QC flagging based on expected climatological ranges, a process referred to as "trimming," plus additional checks back on NCDC procedures designed many years ago. For VOS reports that can be linked to ships reporting metadata in Pub. 47, selected metadata elements can be downloaded alongside the observations. One key area planned for improvements is continuing work towards regular ICOADS update extensions (potentially monthly). These improvements require the resolution of complex international issues such as call sign masking for security and commercial concerns, and the transition to table driven code forms (e.g., BUFR) under the WMO Information System (WIS). The International Maritime Meteorological Archive (IMMA) format, which is widely used for ICOADS and is also being advanced internationally by ETMC (JCOMM, 2007) is a flexible and extensible ASCII format designed for archival and exchangeof both historical and contemporary marine dataplus convenient data access by users. The convention adopted for standardized representation of data within the format uses a fixed-field approach (in contrast to a delimited format, or a binary format such as BUFR) similar to IMMT. The fields presently composing IMMA have been organised into two different types of format components: the corecontaining the most universal and commonly used marine data elements (e.g., reported time and location, temperatures, wind, atmospheric pressure, cloudiness, and sea state)and attachments (att), which contain additional, less universal data elements. The core forms the common front-end for all IMMA data, and by itself forms a relatively concise record type that can satisfy many end-user requirements. Additional record types are constructed by appending to the core one or more att, and this flexibility is anticipated to allow expansion of the format to include additional metadata (e.g., ODAS), bias adjustments, and new data elements bridging the gap between oceanography and marine meteorology (e.g., sea surface salinity). Appendix C: Preliminary Assessment of VOS Data Requirements and Monitoring Background The definition of user requirements for the marine observing system is not a simple process. Sometimes there is not enough information or data at the outset to do more than guess at the requirement. There are also pragmatic considerations. The importance of well-characterised user requirements is easy to demonstrate. Those observing programs that have clear user requirements, particularly when those requirements can be stated simply, have prospered in the developing GCOS. Examples are the Argo program of ocean profiling floats and the drifting buoy network for observing SST. The clear definition of user requirements, and in particular the point at which a particular component of the GCOS can be considered complete, has allowed funding agencies to target resources at these projects and to easily report back on the impact that their funding has had. Even more desirable is the ability to prove that the investment is reaping rewards, for example that the money spent on operational satellite programs can be demonstrated to have improved weather forecasting in a quantitative way. The assessment of observing system adequacy against user requirements is made easier when the contributing observing platforms sample regularly and predictably and the characteristics of the uncertainty in the components of the measurement system is known. Particularly difficult to assess are observing systems made up of a large number of observing platforms, where the characteristics of those observing platforms are variable and sometimes unknown, where details of the sampling is unpredictable, where the spatial and temporal characteristics of the observed field are poorly known and the signal to noise ratio is not particularly favourable. These are the characteristics of the marine surface meteorological observing system, currently made up of contributions from VOS, a network of moored and drifting buoys and satellite observations. Here only the in situ component of the marine surface meteorological observing system will be considered. It should be remembered that the satellite observing system contributes substantially to observations of SST, winds, cloud and precipitation. All of the satellite-derived parameters require in situ ground truth for calibration, validation or bias correction. Surface air temperature, humidity and heat fluxes are examples of parameters which cannot be derived with usable accuracy from space-based platforms. The need to consider all users of the VOS data and the importance of defining user requirements was recognised by JCOMM (2005). "[The Commission] asked the [JCOMM] Management Committee ensure that an appropriate group of experts undertook a scientific review of the requirements for the VOSClim and VOS Schemes, for use in both numerical weather prediction and in climate studies, and reported back to the next session of the Commission." First Steps Toward the Assessment of Data Adequacy A recent Met Office-funded project (Kent and Berry 2008) provided a preliminary set of metrics for use assessing the quality and adequacy of climate information from the surface marine observing system, including VOS. The assessment is non-trivial, requiring information on the quality and characteristics of individual reports including estimates of true bias and biases between different platforms, the variability and autocorrelation of the data fields being constructed, the autocorrelation of errors in data from the same platform and the effects of sampling. It was concluded that further research was needed in almost all areas. Further research is also needed to determine whether the combinations of temporal and spatial resolutions requested by users are appropriate. It was noted that user requirements need to include estimates of both target and usable uncertainties. Preliminary Metrics Suitable for the Assessment of Data Adequacy for Monthly Mean Datasets of Surface Meteorological Parameters The diurnal cycle should be adequately sampled. Fairly even sampling on the 4 synoptic hours (00, 06, 12, 18) should be adequate to avoid aliasing the diurnal cycle. Even sampling every 3, or preferably 1 hour(s) would be needed to resolve the diurnal cycle. Fortunately diurnal variations are small over most of the ocean, particularly when compared to the situation over land. For applications where there is a strong requirement for very low bias and/or very high stability over time (e.g. Hadley Centre datasets, Allen and Ansell 2006, Rayner et al. 2003, 2006) only observations from known platforms with known measurement methods (and heights where applicable) and with supporting environmental information should be given a high weight. In well sampled regions only such observations should be included in adequacy assessments. An estimate of the inter and intra platform random uncertainties can be associated with each individual report depending on metadata and environmental conditions. These uncertainties can be reduced with further research. Sufficient co-located observations are required to make effective quality checks on the data for both numerical weather prediction and climate applications. The global uncertainty estimates for the Hadley Centre, and other similar, datasets should be monitored. For present sampling characteristics the gridbox uncertainty is well constrained by requirements on the number of days sampled and the details of the platforms. The health of the observing system should be monitored using the percentage of ocean gridboxes meeting sampling requirements indicative of the best quality data obtainable from the observing system (see e.g. Table A3). VariableNumber of days sampled (per month)Number of platformsNumber of moored buoysNumber of drifting buoysIndicative gridbox uncertainty (1 - 10)SSTe" 4-6e" 4or e" 1or e" 20.4 - 0.2 CAir temperaturee" 4-6e" 4or e" 10.4 - 0.3 CSurface pressuree" 4-6e" 4or e" 1or e" 20.5 - 0.4 mbCloud covere" 4-6e" 40.4 - 0.2 octasWind speede" 4-6e" 4or e" 10.7 - 0.5 ms-1Dewpointe" 4-6e" 40.5 - 0.3 CTable A3: Summary of metrics suitable for monitoring the surface meteorological observing system for the construction of gridded monthly mean datasets. It should be noted that metrics assume that the current characteristics of the VOS data do not change. These metrics are preliminary, further research is required to improve the analysis on which these metrics are based.  Since 1999, the marine activities of the World Meteorological Organization (WMO) as well as those of the Intergovernmental Oceanographic Commission (IOC) of UNESCO, have been coordinated by the Joint WMO/IOC Technical Commission for Oceanography and Marine Meteorology (JCOMM).  http://www.jcomm.info/index.php?option=com_oe&task=viewDocumentRecord&docID=1878  http://www.wmo.ch/pages/prog/gcos/aopcXIV/27_VOS_Issues.pdf     p.  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