The application of satellite-derived SST, sea Ice and other parameters in global modelling

The application of satellite-derived SST, sea Ice and other parameters in global modelling Craig Donlon, National Centre for Ocean Forecasting, Met Office, Exeter, United Kingdom craig.donlon@metoffice.gov.uk ABSTRACT A variety of data derived from active and passive instruments carried by satellite platforms in different orbit configurations are available today. Observations delivered by these systems have an increasingly important role in operational numerical weather prediction systems and more recently, in operational oceanographic forecasts as boundary specifications and by assimilation systems. Satellite systems of today and the advanced capability promised through advances in satellite instrumentation in the coming years have the potential to significantly improve forecast outputs. The proliferation of new satellite instruments data formats, delivery mechanisms, delays in commissioning (for example) is hard to manage from an end-user perspective where considerable investment in handling and monitoring a new data stream is required. For some space-systems, satellite-derived observations are available in an operational manner making their application in operational models relatively simple. For others, often viewed as non-operational (research) systems, application of derived observations can is more difficult even though positive impact on forecasts could reasonably be expected. Perhaps a new paradigm is required to make the most of satellite observations that is more in tune to the ever changing infrastructure offered by satellite instruments. The increasing importance of satellite-derived observations for NWP and operational oceanography and the limitations of operational monolithic data provision systems that include validation requirements, study of tandem operations at crossover, the impact of unpredictable failure, the large volume of observations and associated low bias requirements need to be considered in an end to end capacity. The EUMETSAT OSI- SAF system provides a good example in these respects and should maintain a diversity of approach that uses both operational and research satellite systems to provide the user community with the best available data products that make the most of satellite data sets ands the investment made to operate these stystems. 1 INTRODUCTION On 1st April 1960, the polar-orbiting satellite TIROS-1 was launched. The spacecraft operated for only 78 days but the impact of the images (Figure 1) derived from the satellite instruments was immense even though they were primitive compared to the image data available from more recent instruments. Figure 1. The first image obtained by the TIROS-1 satellite on April 1, 1960. Today a wide variety of spacecraft imagers and sounders are available, some operating in a research mode and others operating in an operational context employing various measurement technologies and techniques both active and passive sensing, utilising a wide range of the electromagnetic spectrum. A wealth of information describing the state of the atmosphere and oceans can, and is, derived from active and passive satellite instruments revealing water vapour, sea surface temperature, surface wind speed, sea ice, land cover and vegetation, biological activity of the oceans, atmospheric chemistry and composition to name but a few. These observations are routinely used in day-to-day ocean and atmosphere analyses and forecasts

and following quality control, are now forming the future climate observation record. From the early pioneering days of the TIROS-1, technology, tools and techniques have been rapidly developed by groups all over the world to provide a prototype earth system monitoring capability. from TIROS-N April 1 1960 evolution of annual mean forecast skill for the ECMWF Figure 2. The impact of satellite observations on 3, 5 and 7-day weather forecast accuracies during the 1980 s and 1990 s. Impact is greatest particularly for the Southern hemisphere where traditional observations are relatively sparse. (European Space Agency/European Centre or Medium Range Weather Forecasting) The primary driver for satellite derived information is, at the top level, to save lives, property and our environment. This is achieved through global monitoring and forecasting applications ranging from short term, seasonal forecasting through to advanced state of the art climate forecast models. Figure 2 shows the significant impact of satellite observations on the percentage evolution of mean forecast skill at the European Centre for Medium Range Weather Forecasting (ECMWF). In reality, only 60, or around a third of the missions planned for the next 15 years, could be described as having meteorology as a primary objective and even less for oceanography. The other 110 missions will be applied to a diverse range of research, operational and commercial activities (CEOS, 2005). One thing in common to all these applications is the need for accurate observations having global comprehensive coverage required for initialisation and assimilation, development of climatology, verification and diagnostics and process studies for better parameterisation specification. While the infrastructure costs necessary to provide satellite derived information is extremely high, the derived observations are unique, being accurate and consistent, providing near global coverage from polar orbiting systems and high temporal resolution observations from geostationary systems. Many observations are available in near real time and with relatively short delays from most research instruments. The typical constraints applicable to satellite derived observations include the conversion from measured quantity to that which is required by a user community, the quality of calibration and geophysical algorithms, accessibility to appropriate data products (geophysical vs radiance/reflectance) and the length and inter/cross-calibration of the historical satellite record. This paper briefly reviews the impact of some EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF) products and considers how to provide user communities with the best possible observations from satellite systems today and for future applications. 2 THE USER REQUIREMENT The user community for satellite derived ocean and sea ice information is large and varied. It resides in large operational national Meteorological Services (NMH s), Government agencies, Universities, research laboratories, the industrial sector, education and media. For ocean and sea ice applications the major application is to provide observations, scientific information and forecasts to improve: response to search & rescue and oil slicks management of water quality, ecosystem and fisheries coupled forecasts (sea-breeze, fog, hurricanes) support for wind farms, oil exploration

extreme wave forecasts for shipping warnings of coastal flooding (including risk of tsunamis) tactical edge for defence An example of a new generation user community is the recently opened National Centre for Ocean Forecasting (NCOF, see http://www.ncof.gov.uk) which federates several UK universities, research laboratories and the Met Office across the UK to provide a better more joined up approach to these applications. User drivers and constraints on satellite observations for NWP and operational oceanography include: the timeliness of observations provision of accurate observations together with dynamic uncertainty estimates data available through appropriate channels (e.g., ranging from simple ftp through to GTS reporting) available in a variety of formats that consider large scale programs (WMO, GODAE, GHRSST-PP etc) and with global daily coverage In general, most operational satellite observations are optimised for NWP applications and while operational oceanography, as a relatively new application and potentially the most significant from the position of the OSI-SAF, has tended to make use of these data, they are not optimal. Operational oceanography requirements need to be more fully explored in parallel with the developing discipline which is sometimes difficult due to the long lead-time for satellite launches. For climate and seasonal forecasting applications, the accuracy and uncertainty of observations must be stable across the entire multi-satellite record. Multisatellite in this context refers to satellites of both the same genre and also complementary instruments on other spacecraft having more diverse spectral wavebands, calibration systems, coverage and orbit, amongst other things), the length of the available record, the quality of the record and data products (including reanalysis products) and a need for global daily coverage. The stringent demands of the climate community mean that climate quality user requirement are a useful target to work towards as these will undoubtedly satisfy most of the user requirements across other sectors (except perhaps timeliness and resolution issues). It is clear that there is a significant effort required to properly work with user communities in order to define properly a set of requirements that will satisfy most applications through a series of necessary compromise decisions; we cannot do everything. Particularly difficult is the fact that user requirements change no more so than in the last decade where the power of computing and data storage technology has revolutionised the way in which we can now work with satellite data. Users are people and to work effectively with people a personal dialog between data provider and user personalities is necessary to obtain an adequate knowledge of the application scenarios applicable to the OSI-SAF of today and those expected tomorrow. Agencies providing satellite derived information must adopt a workable but flexible approach to data provision in a manner that empowers the user community to make the most of the data sets that are available. More often than not, user applications (both R&D and operational) obtain the best results based on research and development systems (such as ENVISAT) as opposed to the baseline operational systems which are of course necessary as they provide the reliable, stable data feeds demanded by operational applications. But, it is critical that the successes and lessons learned from activities utilising R&D data streams are pulled through to operations such as that of the OSI-SAF if progress is to be made. It is encouraging to note that this type of activity is now taking place within the European Space Agency as it prepares for the development of the Sentinel series of operational missions planned for 2010/11 in the form of a Roadmap study for Operational Oceanography. The objective of this study was to develop the underlying rationale and plan for development of a long-term ocean satellite mission, capable of supporting and sustaining developing operational services (see http://ocean.cls.fr/html/roadmap_free/roadmap_free_en.html). The main findings of for Earth Observation based oceanographic services and product requirements for operational oceanography are that Sea level, Sea Surface Temperature (SST), Ocean Colour (OC) (although less mature) and winds form the backbone prognostic quantities required for operational oceanography. These data are needed to constrain the ocean models (SST, Sea level, ocean colour) and to provide the surface momentum forcing (winds). Sea Surface Salinity is also a very important parameter that should be ultimately monitored from space (e.g., SMOS and the US Aquarius mission). Synthetic Aperture Radar (SAR) images are required to study mesoscale ocean phenomena, for regular sea ice validation studies and coastal applications at high resolution. Surface wave modelling/forecasting requires access to surface wind fields as well as satellite observations of sea state as provided from altimeters (Significant Wave Height) and SAR (wave spectra). In the context of the OSI-SAF,

the Roadmap for Operational Oceanography should be considered as a major input to the development and evolution of not only the OSI-SAF, but other EUMETSAT SAF activities that could work together to address the user requirements in a more joined up manner. 3 EXAMPLE IMPACT OF OSI-SAF PRODUCTS A new generation of sea surface temperature (SST) products are now available through Global Ocean Data Assimilation Project (GODAE) High Resolution SST Pilot Project (GHRSST-PP) that include products based on OSI-SAF operational satellite data products (see the paper describing the GHRSST-PP in this volume). It is interesting to note that the GHRSST-PP is trying to utilise a variety of available satellite SST products and has chosen to provide a common data interface to the user community. By adopting this position, the boundaries between operational data feeds and R&D data feeds is blurred. Although it is true that the GHRSST-PP relies on the operational OSI-SAF outputs as a backstop, these data are seen as complementary to all available products. The point is that the GHRSST-PP user community is eager to access SST from multiple satellite systems both R&D and operational and the key to satisfying this need is to provide a common flexible data interface in this case netcdf format that can be served in a number of ways ranging from web-based live access servers to direct ftp with full metadata embedded within the data file itself. An example of the impact that OSI-SAF SEVIRI SST and other R&D SST GHRSST-PP products inputs to assimilation systems can be taken from the recent (February 2005) beta test phase of the ESA Medspiration project (see http://medserve.soton.ac.uk). Medspiration takes OSI-SAF LML SEVIRI SST data and adds value in the form of error estimates for each pixel value and additional auxiliary fields to prepare observational products for use in data assimilation systems. Figure 3 shows the impact of Medspiration SST data on a 1 month test parallel run of the National Centre for Ocean Forecasting (NCOF) Forecasting Ocean Assimilation Model (FOAM) in February 2005. The GHRSST-PP data that were assimilated include SST from AMSR-E (R&D), TMI (R&D), MSG-SEVIRI (OSI-SAF, operational), AVHRR (OSI-SAF, operational), ENVISAT AATSR (R&D). The impact of the satellite observations was assessed by comparison to colocated in situ observations, and while limited in extent, there is an improvement in the 24 hour forecast bias and RMS error. The comparison is limited by the short 1 month beta-test duration and ideally 6 months to 1 year is typically required for operational trials. However, the initial results are encouraging. Figure 3. Validation and impact of North Atlantic 1/9 Forecasting Ocean Assimilation Model (FOAM) forecasts using enhanced satellite SST derived by the ESA Medspiration project based on OSI-SAF SST and standard operational run (A. Hines). What is important here is that a consistent delivery of data in a common internationally agreed data format has meant that all SST observations from both R&D and operational satellite systems could be used relatively easily. In this sense, it is important for the OSI-SAF is to continue working with both operational (MSG, EPS) and R&D mode (ENVISAT AATSR) satellite data as part of its on-going work during the FOP as these two types of data are complementary to each other.

From February 1st 2005 new global coverage OSI-SAF sea ice products have been initiated. These provide high resolution (10km) global coverage and will be operationally available in early September 2005. This development is a welcome addition to the OSI-SAF portfolio of output maintaining the OSI-SAF products at forefront of sea ice analysis. Improvements to these products will stem from better weather filtering, which remains a key issue for these products as strong winds and rain over the ocean and other certain conditions can be incorrectly flagged as ice using (for example) SSM/I data. Furthermore, it remains a challenge to make a good sea ice measurement near coastlines due to the large field of view typical of microwave radiometers (like the SSM/I) and associated side lobe contamination. These are areas that require further development together with constant output assessment. The best ways to do this is to engage a user application community to apply the sea ice products in near real time and to actively seek user feedback. This can be a time consuming endeavour but in almost all cases, this process ultimately results in a better set of products. Red line: Control run Blue line: Assimilation run i f a t p t Figure 4. Forecast impact, ice concentration: Root Mean Square error over 9 months Positive bias means that MI-IM shows a tendency to freeze too much ice the positive impact is lost after about 5 days forecast (Jon Albretsen and Lars-Anders Breivik). The impact of OSI-SAF sea ice products assimilated by the MI-IM model is shown in Figure 4 for a period of 9 months (April to December 2002). The impact on the prognosis time is positive out to ~5 days. The bias increases, as expected, during prognosis time and a positive bias indicates that MI-IM shows a tendency to freeze too much ice. As in the case of SST, there is a need to maintain access and use of both operational and R&D satellite data sets for sea ice processing if the OSI-SAF is to provide the best data products to the user community and this should be encouraged throughout the FOP. It is worth considering the next generation of ocean models that are now being implemented through projects such as the Nucleus for European Modelling of the Ocean (NEMO), the EC MERSEA integrated project and at a host of national laboratories and Universities. A current challenge is to include a functional ecosystem component within these models which demand a new type of satellite data product derived from ocean colour. While arguably satellite ocean colour and the derivation of accurate geophysical products is complicated and relatively immature compared to surface wind speed and SST, there is a growing user demand for parameters such as Chlorophyll-a (the physical parameter on which solar transmission in the ocean most heavily depends) and primary productivity estimates from space. The combination of in situ and satellite data plays a key role in ecosystem (Nutrient - Phytoplankton - Zooplankton - Detritus (NPZD)) model validation, particularly at high resolutions. This can potentially be achieved through the use of data products derived from ocean colour satellite sensors. It is clear that the use of high resolution coupled physicalbiogeochemical models will underpin future ocean biology and fisheries research, and allow better targeting of in situ and satellite observation programmes. Applications include:

the accurate mapping of carbon sinks and sources which requires high resolution global coverage and accurate measurements of the ocean biological state in the upper water layers. estimation of carbon and nitrogen budgets & export production at global and regional scales (biogeochemical provinces) investigation of the interactions between the physical and biogeochemical components of model systems at different horizontal and vertical resolutions development of assimilation systems capable of assimilating Ocean Colour & other Earth Observation data into the coupled, general circulation physical-biogeochemical carbon cycle model Figure 5. Early results from the coupled FOAM and Hadley Centre Ocean Carbon Cycle (HadOCC) model at 1 and 1/3 resolution. Model derived chlorophyll is compared to corresponding SeaWIFS derived chlorophyll-a map for 2-11 th May 2000. Mesoscale features not well resolved in global model but there is a reasonable good fit to SeaWIFS observations (Rosa M. Barciela) R&D ocean colour satellite systems are already available and are widely used today. In the future, Europe, through the ESA Sentinel series (and following the ESA Roadmap study for Operational Oceanography) is now discussing how to fly an operational series of ocean colour satellite sensors to address these applications in a more sustained manner. In terms of the OSI-SAF, some form of ocean colour activity should be present in the OSI-SAF portfolio preferably as a stand alone component of the OSAI-SAF activities but at a minimum, to consider properly the impact of ocean biology on the diurnal variability of SST. Similar arguments can be made for altimetery which has a significant impact on ocean forecasting models and surface waves a notable omission from the OSI-SAF portfolio. While not yet a component of the OSI-SAF, as the EPS develops there may be a requirement to explore these systems at the OSI-SAF in the future. 4 THE FUTURE OBSERVING SYSTEM AND THE OSI-SAF The combination of in situ and satellite data plays a key role in OSI-SAF product development, validation and underpins the ultimate credibility of the OSI-SAF data products themselves. But the observing system is changing both in the space segment and in situ component. The changing shape of the satellite segment is a characteristic of space systems which are few in number but nearly always have a high impact. The impact of system loss can be large (e.g., the Japanese ADEOS-II program) and the continued use of R&D instruments eases the burden of maintaining product lines and services following this type of catastrophic event. The OSI-SAF is particularly good at bringing new operational instruments into the processing systems as demonstrated by the recent commissioning of the MSG and is actively preparing for the ESP challenge. However, there is still need to consider how best to make the most of the wide number of R&D instruments that could have a significant impact on OSI-SAF products through complementary activities. For example, the use of passive microwave observations from the TRMM TMI and EOS AQUA AMSRE on SST and sea ice products. In the case of in situ measurements, there is a need for the OSI-SAF to clearly define its own user requirements to the groups that procure and manage the in situ network rather than passively using what is available. The strength of any satellite geophysical data set is underpinned by the breadth and quality of the validation study that establishes confidence limits making it imperative that high quality properly distributed in situ observations are available. Without these data, the considerable investment committed to the satellite systems is undermined through a poor validation capability users can only use data most effectively when proper error estimates for that data are available. For example, the in situ fleet of volunteer observing ships is changing rapidly in terms of coverage and scope such that the uncertainty of measurement is now greater than 20 years ago. The irony here is that the in situ measurements are much improved in terms of technology, accuracy and robustness but there are fewer systems available and those that are reporting are

reporting on a more frequent basis. A higher proportion of these are hourly reports from automatic systems where successive reports are highly correlated and, as a result, the estimated error in gridded air temperature datasets is rising. Uncertainty estimation for satellite data products is an important issue that the OSI-SAF must continue to refine and develop throughout the FOP. For the work of the OSI-SAF, a mixed observing system (ships, buoys, drifters, satellites) is essential and there is a need to ensure that OSI-SAF requirements are properly articulated so that changes in the observing system are made with a proper assessment of the likely impacts on OSI-SAF applications that make use of the data. The OSI-SAF should consider the Observing System Experiments (OSE) to asses the correct blend of in situ and satellite observations fro a given output product specification satellite data are the matrix that fill the gaps between a sparse in situ (truth) network providing unique and complementary information to the in situ observing system. Much can be learned about the accuracy of the in situ and satellite data set in terms of consistency and coverage when this type of comparison is made on a regular basis. For well established products (such as SST) this is general practice but it is less clear for ice parameters, SSI and winds where other satellite observations (SAR, IR, VIS) are often the only source of independent information with any coverage. While this is a difficult and expensive area of work, nevertheless, it is fair to say that the OSI-SAF has made significant progress in coupling in situ and satellite data. 5 SUGGESTIONS TO THE OSI-SAF The OSI-SAF is in good shape and is delivering products that are used in a wide variety of applications both in an operational environment and in a research mode, as demonstrated that this workshop. For the future, there is a need for the OSI-SAF to continue to work with a blend of satellite and in situ data to provide the best data to its user community. As noted by Mr. Schueller, the SAF Network Scientific Coordinator, SAFs use inputs from meteorological (and other) satellites in both geostationary and polar orbits during the development phase including data from any suitable satellite system and research missions and it is argued here that this practice should be continued within the Operational Phase albeit with an emphasis towards EUMETSAT Geostationary and Polar systems. Many of the impacts shown at the OSI-SAF workshop stem from OSI-SAF products and research satellite data streams; for example the ENVISAT AATSR provides an accurate global SST complementary to the MSG and AVHRR (as it is aerosol robust) data that could be used in validation studies and as a calibration source potentially freeing in situ observations for independent validation work. Presently and in the near future, there are a number of new instruments that could be used by the OSI-SAF to support work on operational products including innovative spectroradiometers (such as AIRS, CHRIS) and in particular the METOP IASI instrument that could provide a fiducial calibration for other instruments. The microwave measurements from TRMM-TMI, AMSR-E and WindSat could all make a contribution today. There is a need to think about the operational definitions for satellite instruments today and a degree of flexibility should be maintained in the OSI-SAF operational phase so that operations can be continued in the unfortunate instance where a satellite system is lost. The SAF should not simply be about a operational or research systems but question the boundaries between R&D and operations and thus provide an operational service to a user community that delivers the best data products for a given purpose; and to do this means using all information available in a sensible synergy. There is a clear user demand for high resolution SST derived from METOP. The GHRSST-PP requests that 1km resolution global coverage data are processed and made available from the EPS AVHRR/3. Furthermore, there is a need to provide full resolution (5km) SEVIRI data at hourly or better temporal frame in order to study diurnal SST variability. As computing power and storage space continue to increase, at a falling cost, users are able to manipulate these high resolution data sets in ways not foreseen some years ago. In this respect, the potential for innovative applications and product feedback by a diverse user community to the OSI-SAF should not be underestimated. One aspect of OSI-SAF products that sets them apart from other data providers is the use of uncertainty estimates at a pixel level which can be further refined in partnership with the application community. Data format issues need to be considered from a user perspective. For example BUFR encoding of satellite data versus a more flexible approach using hierarchical data formats (already pioneered by the OSI-SAF) provides a natural way to explore and work with new users. The International GHRSST-PP Project Office, on behalf of the GHRSST-PP Science Team invites the OSI-SAF to consider the production of GHRSST-PP L2P format by OSI-SAF for SST. This format demands integration of several fields including SSI, AOD, sea ice, SST, winds and is requested by a large user community. Such a product provides a near perfect opportunity to cross link SAF operations and have a better dialog with users leading to products that are based on user needs.

There is a need for consistent processing and re-processing of SST and sea ice observations for climate studies and again, this could be considered as a cross-saf activity. In the case of sea ice, it is suggest that a year of excellent ice state analysis could be used as a reference to define validation metrics and to push methodology for better weather and land flagging techniques. In this case, the emphasis is to define better error analysis correlation lengths and variances. Systematic access to SAR (e.g., G-MODE ENVISAT ASAR, RADARSAT, RADARSAT-2) needs to be configured for an on-going pre-operational systematic inter-comparisons. Low resolution SAR (pre-processed) could give ice concentration and ice edge estimates at 10km which would be extremely helpful for assimilation and verification applications such as investigation of sea-ice concentration in boundary conditions in ocean models and the impact on ATOVS retrievals where a better ice concentration estimate should lead to better sounding. Finally, there is a need for sea ice thickness information which remains a significant challenge from satellite. As state of the art sea ice thickness models offer a sensible approach the OSI-SAF should try to work more closely with this user community. Information derived from ocean colour satellite sensors is increasingly required for the present and next generation of ocean model systems for a variety of applications. The emerging user requirement is for this type of data product slowly emerging is for operational availability at a timeliness within ~12 hours of acquisition and for derived quantities such as Chl-a. The OSI-SAF should cultivate a basic capability for ocean colour work (potentially through the new ESA project GlobColour) and take advantage of this resource as a means to provide aerosol optical depth observations (important for their impact on atmospheric transmission) and for a better understanding of the impact of ocean biology on SST data the user community requirements. For the EPS AVHRR/3 and SEVIRI, such information will be critical to providing the user community with a properly qualified data product during Saharan dust outbursts in certain areas and seasons. Much could be achieved at the OSI-SAF by making use of ocean colour R&D sensor outputs. The OSI-SAF is encouraged to consider the GCOS (WMO, 2003) climate monitoring principles as part of its every-day work in order to operate and maintain satellite data sets to climate quality in near real time. The climate monitoring principles are designed to ensure that effective monitoring systems for climate. It is argued that while these can be demanding in some aspects, they provide a sound common sense basis to monitor both the long and short-term products produced by the OSI-SAF. Furthermore, considering climate applications as the most demanding in terms of accuracy, by adopting the Climate Monitoring Principles, all other users will benefit from a consistent higher quality output. The OSI-SAF and EUMETSAT approach is already very good with satellite systems having well planned and executed overlaps (dual operations on MSG are planned), cross and inter instrument comparisons, integrated validation, operational management and deployment of similar characteristic systems, follow on missions etc. and, as noted by Mr Schueller, the OSI SAF is now considering the production of GCOS Essential Climate Variables (ECV). EUMETSAT and the OSI-SAF should encourage other operators to adopt this stance. Finally, as the user community further refines an ever changing set of requirements based on their own developing systems and applications, the OSI-SAF must maintain a flexible approach to take advantage of non-operational R&D systems (e.g., AATSR, SAR and other radar systems such as altimeters, Ocean Colour, Microwave SST). Ultimately, the OSI-SAF is not only developing data products and services, but developing interactions with the user communities helping to explore better and more innovative aspects of data production and application that are not possible in a fully operational system today. The potential for pull through of these activities into the operational systems of tomorrow is one of the great benefits of the OSI-SAF approach but access and flexibility must be preserved within the OSI-SAF mandate. However, the excellent operational data provision must also be maintained and the OSI-SAF is encouraged to actively monitor the way in which users apply data products so that products can easily evolve alongside user needs. This demands flexibility in approach and a full appreciation of the effort required to work effectively with the user community. It also takes time and a considerable effort on the part of the OSI-SAF; users need to be actively contacted on a regular basis and feedback provided/encouraged/solicited in both directions. The fact is that users are people and in any good relationship it is necessary to make friends and talk to each other recognising from the initial conversation, that everyone wants success. References Committee on Earth Observation Satellites (CEOS), (2005), The CEOS Earth Observation Handbook, prepared by the European Space Agency (ESA), available from http://www.eohandbook.com/.

WMO, (2003), The second report on the adequacy of the global observing systems for climate in support of the UNFCCC, GCOS-82, WMO TD 1143, available from the World Meteorological Organization, Geneva, Switzerland, pp 85.