MeteoSwiss - CM SAF: Data and Methods

Data

Data from EUMETSAT's geostationary Meteosat satellites of the First and Second Generation (MFG=Meteosat 2-7 and MSG=Meteosat 8-9) are used. The satellites are located directly over the equator at a longitude of 0° at an altitude of about 36'000 km. The resulting visible disc reaches up to 80°N/S and 80°E/W, respectively.

The satellites of the first generation (Meteosat 2-7, in operation 1982-2005) had a radiometer with 3 spectral bands in the visible (VIS) and infrared (IR) range (MVIRI – Meteosat Visible and InfraRed Imager). One scan of the visible disc was accomplished within 30 min at a horizontal resolution of around 2.5 km.

The recent geostationary satellites of the second generation (Meteosat 8-9, in operation since 2004, see also Schmetz et al, 2002) carry a radiometer that measures in 12 different spectral bands in the visible and infrared (SEVIRI - Spinning Enhanced Visible and InfraRed Imager) at a horizontal resolution of around 3 km every 15 min. Additionally, there is a high resolution visible (HRV) channel with a spatial resolution of around 1 km.

Methods

The full-disc climatological global radiation dataset will employ all available satellite data starting with Meteosat 2 in 1982. Different channel specifications between the satellite generations neccesitate an algorithm only based on the visible channel which is available for both generations. An additional regional surface radiation dataset utilize only the MSG satellite data which in turn allows for an algorithm that incorporates several of the available channels is the visible and the infrared range.

The derivation of the surface radiation is based on the Heliosat algorithm (Cano et al. 1986, Beyer et al., 1996; Hammer et al., 2003) which is used by CM SAF. The algorithm is based on an empirical correlation between a satellite derived cloud index and the radiation at the surface and exploits the relationship between top of the atmosphere albedo and the atmospheric transmittance. The standard algorithm, however, is not able to distinguish snow and clouds. This would lead to an underestimation of the surface radiation on a clear-sky day because the wrongly detected clouds cause a reduction of the incoming radiation and the additional reflections of the snow are not considered. Modifications of the algorithm by Dürr and Zelenka (2009) have introduced a snow detection and have verified its results (Dürr et al. 2010). The final climate data record and its processing has been documented and verified in Posselt et al. (2011) and Posselt et al (submitted).

The path from the satellite picture to the global radiation data is illustrated in Figure 1 using the example of a global surface radiation field for Switzerland.

Depending on the product, one or more VIS and IR channels are used to obtain information about the state of the atmosphere and the surface for each pixel. This information is then used to calculate the cloud index (~0: no clouds, ~1: overcast) that accounts for radiation reflected from snow in addition to attenuated radiation due to clouds. The surface radiation is then calculated by scaling the expected clear sky radiation with the cloud index. The clear sky radiation depends on the sun’s elevation, surface altitude and the atmospheric turbidity. The latter describes the radiative impact of water vapour, atmospheric aerosols, ozone, etc. on the atmospheric transmission. Furthermore, corrections for effects of the surrounding terrain such as shadowing can be applied. A digital elevation model is used to determine the topography and the horizon of each pixel.

Figure 1: Schematic of algorithm to determine global radiation.

Cloudindex: the darker the colour the more clouds
Clear sky and global radiation: the darker the colour the higher the radiation

Larger_version_of_schematic.pdf, 2.9 MB

References

Beyer, H. G., C. Costanzo, and D. Heinemann (1996). Modifications of the Heliosat procedure for irradiance estimates from satellite images, Solar Energy, 56, 207 - 212.

Cano, D.; Monget, J. M.; Albuisson, M.; Guillard, H.; Regas, N. & Wald, L. (1986). A method for the determination of the global solar-radiation from meteorological satellite data, Solar Energy, 37, 31 - 39.

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, 31, 4179 - 4198

Dürr, B. and A. Zelenka (2009). Deriving surface global irradiance over the Alpine region from METEOSAT Second Generation data by supplementing the HELIOSAT method International Journal of Remote Sensing, 2009, 30, 5821 - 5841

Hammer, A., D. Heinemann, C. Hoyer, R. Kuhlemann, E. Lorenz, R. Müller, and H. Beyer (2003). Solar energy assessment using remote sensing technologies, Remote Sens. Environ., 86 (3), 423 - 432.

Posselt, R.; Müller, R.; Stöckli, R. & Trentmann, J. (2011). Spatial and Temporal Homogeneity of Solar Surface Irradiance across Satellite Generations Remote Sensing, 3, 1029-1046

Posselt, R.; Trentmann, J.; Stöckli, R. & Müller, R. (submitted). The CM SAF surface radiation climate data set Remote Sensing of Environment

Schmetz, J., P. Pili, S. Tjemkes, D. Just, J. Kerkmann, S. Rota, and A. Ratier (2002). An Introduction to Meteosat Second Generation (MSG), Bull. Amer. Meteor. Soc., 83 (7), 977 - 992.