1. Evaluation and applications of a new satellite-based surface solar radiation data set for climate analysis
Jörg Trentmann1, Richard Müller1, Christine Träger-Chatterjee1, Rebekka Posselt2, Reto Stöckli2
Satellite Application Facility on Climate Monitoring (CM SAF) 1Deutscher Wetterdienst, 2MeteoSwiss

2. Motivation Surface Solar Irradiance highly relevant:
Climate Monitoring and Climate Analysis
Solar Energy
Available data sets (ISCCP, GEWEX, ERA-Interim) agree well on the mean
Differ substantially in the temporal evolution
Coarse spatial resolution

3. The CM SAF approach
Retrieve surface solar irradiance (SIS) from the geostationary Meteosat satellites (1983 – today)
Apply a well-established method:
Heliosat (Cano et al.,1986, Hammer et al., 2003)
Provide the data at high temporal and spatial resolution
Free and easy accessible
Validate the data with BSRN surface station data
Evaluate the data with alternative data sets

4. Fundamental Assumptions
The Heliosat method
Fundamental Assumptions
The clear-sky surface radiation can be accurately calculated (information on the water vapor and aerosol is required)
For each satellite pixel and time slot the minimum reflectance of each months represents clear-sky conditions (i.e., effect of Rayleigh scattering + surface albedo on the reflectance)
The cloud optical depth is related to the cloud-reflected solar radiation (= brightness of the visible satellite channel)
The degradation of sensor sensitivity can be monitored with bright cloud targets (maximum reflectance)

5. The Heliosat method
Surface irradiance (global radiation) is retrieved for each satellite pixel / time slot (30 min) between 1983 and 2005.
Average and interpolate to hourly / daily / monthly means on a 0.03o-lon-lat-grid.
Data is freely available in CF-netcdf-format:
Additionally, the direct surface irradiance and the cloud index are provided.
Scripts to visualize and analyse the data using open-source software (cdo, R) are provided.

6. Validation
Monthly means surface irradiance at 14 BSRN stations

7. Validation

8. Validation Temporal Stability Hovmöller Diagram
Temporal evolution of the bias to BSRN surface stations
Apply standard techniques to detect change points (ongoing project, University Frankfurt)

9. Evaluation
CM SAF data about 2-3 Wm-2 higher than alternative data sets
Temporal evolution of CM SAF consistent with alternative data sets, exception 1991 (Pinatubo??)

10. Applications Close-up Views Germany Amazon Mediterranean West Africa
Tanzania

11. Applications Surface Irradiance, Mean July, CM SAF
GEWEX
Topography
Surface Irradiance, Mean July, CM SAF
No validation with DWD surface network available.
Excellent correspondence with topographic features.
GEWEX SRB data misses details due to coarse resolution.

12. Applications Close-up Views Germany Amazon Mediterranean West Africa
Tanzania

13. Applications Mean Surface Radiation, Tanzania
No surface network available
Correspondence of surface irradiance with topographic features.
Tanzania is mountainous in the northeast, where Mount Kilimanjaro,[22] Africa's highest peak, is situated. To the north and west are the Great Lakes of Lake Victoria (Africa's largest lake) and Lake Tanganyika (Africa's deepest lake, known for its unique species of fish). Central Tanzania comprises a large plateau, with plains and arable land. The eastern shore is hot and humid, with the island of Zanzibar lying just offshore.
Cooperation with Jörg Bendix, University Marburg

14. Applications Surface Radiation at Mt. Kilimanjaro
Substantially reduced surface radiation around Kilimanjaro due to enhanced cloud cover

15. Applications Time Series of Surface Radiation 37.5° E, 3.1° S

16. Linear Trend in Surface Radiation (W/m2/dec)
Applications
Linear Trend in Surface Radiation (W/m2/dec)
There are significant trends in the surface radiation at Mt. Kilimanjaro between 1983 and 2005
Strong increase of surface radiation (more than 15 W/m2/dec) over the summit (> 3000 m)
Decrease along the northern and southern slopes

17. Summary
Heliosat Method is applied to Meteosat Satellites to derive solar surface irradiance from 1983 to 2005
Validation with BSRN surface measurements shows high quality of the CM SAF satellite-derived data set.
Temporal (hourly) and spatial (0.03o) resolution of the data set is unique.
Spatial resolution allows detailed local studies: Strong contrast in temporal trends of surface irradiance at the summit (increase) and the foothills (decrease) of Mt. Kilimanjaro, Tanzania.
The Data Set is freely available in CF-netcdf-format at software tools are also provided
Processing of the global AVHRR satellite data (1982 – 2009) ongoing (see Poster XY 220, F. Kaspar et al.)

19. Extra Slides

20. The Heliosat method Reflectivity, 12 UTC, 2 Sept 2008
Min. Reflectivity, Rmin, 12 UTC, Sept 2008

21. The Heliosat method
Max. reflectance, Rmax: 95 % percentile of counts during one month in the reference region
Reflectivity, 12 UTC, 2 Sept 2008
Temporal evolution of Rmax

22. The Heliosat method The definition of the Cloud Index n:
Cloud Index, 11 UTC, 1 July 2005

23. The Heliosat method
The cloud index, n, is related to the clear-sky index, k.
The clear-sky index, k, is the ratio between the all-sky surface irradiance, G, and the clear-sky surface irradiance, Gclear
clear sky index
cloud index

24. The Heliosat method k = 1  n G = k * Gclear
Gclear can be calculated by radiation transfer calculations using the fast and accurate clear-sky model gnu-MAGIC (Mesoscale Atmospheric Global Irradiance Code, Mueller et al., 2009,
The cloud index, n, is related to the clear-sky index, k:
The clear-sky index, k, is the ratio between the all-sky surface irradiance, G, and the clear-sky surface irradiance, Gclear:
G = k * Gclear
k = 1  n

25. Validation Monthly means SIS from 14 BSRN stations
Measures: Bias, Variance, Correlation Coefficient of Anomalies, Fraction of months with bias above 15 Wm-2