1 / 25

Evaluation and Applications of a New Satellite-based Surface Solar Radiation Data Set for Climate Analysis

This study evaluates a new satellite-based data set for surface solar radiation and explores its applications in climate analysis, solar energy, and other studies. The data set, retrieved using the Heliosat method from geostationary Meteosat satellites, provides high temporal and spatial resolution and is freely accessible. Validation with surface station data and comparison with alternative data sets show promising results. The data set is particularly useful for studying regional variations and temporal trends in surface radiation.

davidcole
Download Presentation

Evaluation and Applications of a New Satellite-based Surface Solar Radiation Data Set for Climate Analysis

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  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 temporalevolution • 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. 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 / timeslot (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: www.cmsaf.eu • 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. Germany Amazon Mediterranean West Africa Tanzania Applications Close-up Views

  11. Topography GEWEX Applications 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. Germany Amazon Mediterranean West Africa Tanzania Applications Close-up Views

  13. Applications Mean Surface Radiation, Tanzania • No surface network available • Correspondence of surface irradiance with topographic features. 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 37.6° E, 3.1° S

  16. 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 www.cmsaf.eu, software tools are also provided • Processing of the global AVHRR satellite data (1982 – 2009) ongoing (see Poster XY 220, F. Kaspar et al.)

  18. Extra Slides

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

  20. 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

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

  22. 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

  23. 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: 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, http://sourceforge.net/projects/gnu-magic/) The Heliosat method

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

More Related