CM SAF - Satellite-based climatology
Satellite Application Facilities (SAFs) are centres for processing satellite data, and form an integral part of the EUMETSAT Application Ground Segment. MeteoSwiss has been a partner in the "Satellite Application Facility on Climate Monitoring" project (CM SAF) since 2004.
The SAF on Climate Monitoring generates climate datasets from satellite data on cloud physical parameters, surface radiation and radiation budget at the edge of the atmosphere, as well as water vapour in the atmosphere.
Within the Continuous Development and Operations Phase 2 (CDOP 2, 2012-2017) MeteoSwiss derives a cloud mask from Meteosat covering the satellite's visible disc. These climate data records will be based on data from Meteosat first and second generation satellites (1983-present) and will span a climatological period of 30 years or more.
The cloud mask dataset is a valuable source of climate information and can extend or complement eye-based observations (SYNOP) in regions with sparse ground observation coverage or in regions with high spatial variability of cloud cover, such as mountainous or coastal regions. Additionally, cloud information are often needed as input in the derivation of physical parameters from satellite data such as land and ocean surface properties, surface radiation fluxes or atmospheric state variables like moisture and temperature.
The cloud mask algorithm will be based on continuous cloudiness scores instead of the traditional binary decision tree approach. The scores are calculated for different channels as well as for different spatial and temporal statistical quantities. Each score yields a probability for the pixel's cloud cover (cloudy: score > 0; cloud free: score < 0). The final result, the cloud cover probability, is obtained by summing up all available scores taking into account the varying performance of the scores during day and night and over snow.
Land Surface Temperature
The radiative land surface temperature (LST) is an important land surface state variable for monitoring drought and crop productivity since soil moisture anomalies amplify the atmospherically induced LST variations when vegetation becomes moisture limited. Additionally LST is effective to constrain land surface parameterizations of weather, climate and crop models and thus increases the realism of climate and weather predictions.
During the current project phase MeteoSwiss derives a land surface temperature climate data record from Meteosat data. The final time series will extend over 30 years by using data from Meteosat first and second generation satellites (1983-present). This activity is carried out in close cooperation with the Land Surface Analysis Satellite Applications Facility (LSA SAF). The operating experience of the LSA SAF to derive real-time LST products and the strong CM SAF expertise to generate climate data records incorporate into the product development.
The land surface temperature dataset itself is a valuable source of climate information. LST is an important component of the surface radiation budget and a key variable for a wide range of applications such as model evaluations, hydrological applications and environmental monitoring. Many of those application require a wide spatial coverage combined with a high temporal repetition rate which can only be achieved through the use of satellite data.
Within the last previous project phase (2007-2012) MeteoSwiss contributed climate data records of global radiation (= incoming solar radiation at the earth's surface) and its components. Global radiation data are especially valuable for the planning and operation of solar energy plants as well as for the design of buildings and the estimation of crop yields. Furthermore, long, high quality time series of global radiation are essential in climate science.
The dataset is based on data from the Meteosat first generation satellites (1983-2005) and covers the satellite's visible disc (centered at the equator at 0°E/W). An extension of the dataset with data from Meteosat Second generations satellites (2004-present) available from CM SAF.
The dataset is based on data from Meteosat first-generation satellites (1983-2005) and covers the area of the earth's surface that is visible from the satellite (centred around the equator at 0° E/W). An expansion of the dataset with data from Meteosat second-generation satellites (2004 to date) is available from CM SAF.
MeteoSwiss contributed to the CM SAF climate datasets for global (= incoming solar radiation) and direct radiation on the earth's surface, as well as the effective cloud albedo (also cloud index). This also involves the validation and improvement of data retrieval for global radiation on the earth's surface, particularly where such complex terrain as the Alps is concerned, where it is particularly important to take the radiative effect of snow into account. Making a distinction between snow and clouds is one of the biggest challenges in this process, which involves making the appropriate allowances for the radiative characteristics of snow (i.e. additional reflection).
The climate dataset for surface radiation is freely available on the CM SAF website, and covers the operative phase of the Meteosat first-generation satellites from 1983 to 2005.
The current efforts of MeteoSwiss are focused on expanding the dataset for surface radiation with data from the second-generation Meteosat satellites that are currently in operation (since 2004).
Posselt, R., Mueller, R., Stöckli, R., Trentmann, J., Liniger, M.A. (2014) A surface radiation climatology across two Meteosat satellite generations, Remote Sensing of Environment, 142, 103-110; http://dx.doi.org/10.1016/j.rse.2013.11.007
Posselt, R., R. Müller, J. Trentmann, and R. Stöckli (2012). Remote sensing of solar surface radiation for climate monitoring -- the CM-SAF retrieval in international comparison, Remote Sensing of Environment, 118, 186-198; doi:10.1016/j.rse.2011.11.016
Posselt, R., R. Müller, R. Stöckli, and J. Trentmann (2011). Spatial and Temporal Homogeneity of Solar Surface Irradiance across Satellite Generations, Remote Sensing, 3, 1029-1046; doi:10.3390/rs3051029
Mueller R., J. Trentmann, C. Träger-Chatterjee, R. Posselt, R. Stöckli (2011). The Role of the Effective Cloud Albedo for Climate Monitoring and Analysis. Remote Sensing, 3, 2305-2320; doi:10.3390/rs3112305
Dürr, B.; Zelenka, A.; Müller, R. & Philipona, R. (2010). Verification of CM-SAF and MeteoSwiss satellite based retrievals of surface shortwave irradiance over the Alpine region International Journal of Remote Sensing, 2010, 31, 4179 - 4198
Dürr, B. & Zelenka, A. (2009). Deriving surface global irradiance over the Alpine region from METEOSAT Second Generation data by supplementing the HELIOSAT method, International Journal of Remote Sensing 30(22), 5821 - 5841.
Schulz, J.; Albert, P.; Behr, H. D.; Caprion, D.; Deneke, H.; Dewitte, S.; Dürr, B.; Fuchs, P.; Gratzki, A.; Hechler, P.; Hollmann, R.; Johnston, S.; Karlsson, K. G.; Manninen, T.; Mueller, R.; Reuter, M.; Riihela, A.; Roebeling, R.; Selbach, N.; Tetzlaff, A.; Thomas, W.; Werscheck, M.; Wolters, E. & Zelenka, A. (2009). Operational climate monitoring from space: the EUMETSAT Satellite Application Facility on Climate Monitoring (CM-SAF), Atmos Chem Phys 9(5), 1687 - 1709.