Conference Presentation

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1 Conference Presentation Satellite Derived Irradiance: Clear Sky and All-Weather Models Validation on Skukuza Data INEICHEN, Pierre Abstract Downward short wave incoming irradiances play a key role in the radiation budget at the earth surface. The monitoring of this parameter is essential for the understanding of the basic mechanisms involved in climate change, such as the greenhouse effect, the global dimming, the change in cloud cover and precipitations, etc. Unfortunately, the density of the ground measurement network is insufficient, especially on continents like Africa, or countries in the Near East. To circumvent this lack of measured data, the meteorological satellites are of great help and models converting the satellite images into the different radiation components become increasingly performing. If these converting models are well validated over the United States and Europe, it is not the case over the African continent. A previous study [1] conducted on data covering the year 2006 over 12 sites situated in Western Africa at latitudes from 17 N to 5 S show that the global irradiance retrieved from satellite images is highly dependent on the knowledge of the aerosol optical depth (aod) and the water vapor content of the atmosphere (w). The [...] Reference INEICHEN, Pierre. Satellite Derived Irradiance: Clear Sky and All-Weather Models Validation on Skukuza Data. In: SASEC 2015, Sklukuza (South Africa), mai 2015, 2015 Available at: Disclaimer: layout of this document may differ from the published version.

2 Satellite Derived Irradiance Clear Sky and All-Weather Model Validation on Skukuza Data Dr Pierre Ineichen University of Geneva Institute of Environmental Sciences

3 Solar resource validation Ground data Quality control Model input Atmospheric water vapor content Aerosol optical depth Clear sky model Validation of 7 models Dependence analysis Results for Skukuza All weather satellite models Validation of 3 models Dependence analysis Results for Skukuza

4 Data quality control Ground data quality control (QC and AQC) Ground data from 2001 to 2007 (2008 ->?) Satellite data from 2004 (MSG) Physical limits (should be on-line AQC) Data time stamp assessment: morning/afternoon symmetry Absolute calibration with aod data and clear sky model (aeronet measurements) Calibration coefficient drift: year to year stability

5 Aerosol optical depth From MACC project retrieved by MinesParisTech From ground measurements: Molineaux-Ineichen bmpi model multi-conditions spectral calculations with Modtran and Smarts2, US 1976 standard atmosphere at sea level, 343 Dobson units of ozone broadband cda and w optical depths retrieved form integrated spectral values (see applied optics paper) cda m w 0.16 m R w R aod retrieved by retro-calculation from DNI ground data in daily values aod retrieved by retro-calculation from GHI ground data with Solis clear sky model From Aeronet network (ground measurements) level 2.0 (if not available, level 1.5)

6 Aerosol optical depth and water vapor column Solis retrofit aod versus aeronet aod (daily values) the aod has a low effect on the global irradiance, relatively high dispersion low number of values due to highly variable daily dynamics MACC aod versus aeronet aod (daily values) overestimation of the aod by the MACC model, but good correlation Atmospheric water vapor content or column relatively high dispersion good correlation less impact on the models results

7 Clear sky model validation Validation background McClear, Solis, REST2, CPCR2, Bird, ESRA and Kasten 22 sites, in Europe and Mediterranean region, + Skukuza latitude: 20 -> 60, altitude: 0m -> 1600m validation over 8 years ( ), global, diffuse and normal beam components (Skukuza: only the global component, ) hourly and daily (daily represent the integration of only the clear hourly data) aod input data: MACC project, aeronet and Molineaux-Ineichen (bmpi retrofit model) Almeria (Spain) Bratislava (Slovakia) Cabauw (the Netherlands) Carpentras (France) Davos (Switzerland) Geneva (Switzerland) Kassel (Germany) Mt Kenya (Kenya) Kishinev (Moldavia) Lerwick (Great Britain) Lindenberg (Germany) Madrid (Spain) Nantes (France) Payerne (Switzerland) Sede Boqer (Israel) Skukuza (South Africa) Tamanrasset (Algeria) Toravere (Estonia) Valentia (Ireland) Vaulx-en-Velin (France) Wien (Austria) Zilani (Letonia)

8 Clear sky model validation Solis clear sky aod retrieved from ground measurements aod only for clear days normal distribution McClear clear sky aod from circulation model aod continuous values higher dispersion normal distribution Clearness index clear sky measurements within physical limits

9 Clear sky model validation Bias dependence with the aerosol optical depth higher dispersion with MACC aerosol slight dependence for McClear no specific seasonal dependence too low measurements density in summer Overall results negligible bias GHI: sd = 2.5% - 3% DNI: sd = 3% - 10%

10 Satellite irradiance Validation background Macc Rad, Helioclim 3v5 and SolarGIS Validation over 5 years, from 2004 to 2007, not continuous, global component Hourly, daily and monthly values Satellite models SolarGIS (GeoModel): cloud index retrieved from multi-spectral MSG images analysis and Solis as clear sky model for the normalization, aod from MACC-II Helioclim 3v5 (MinesParisTech): based on calibrated radiances from MSG sensors, ESRA clear sky model with Linke turbidity climatic databanks as input. The v5 is a renormalization with McClear clear sky model MacRad (MinesParisTech): LibRadTran calculated look-up tables normalized by McClear clear sky model, aod from MACC-II

11 Satellite irradiance models Data selection Quality control passed Solar elevation > 1 Daily values obtained from integration of selected pairs of hourly data Monthly values obtained from summation of selected daily pairs Results Good correlation, low bias but relatively high dispersion due to highly variable conditions Same remark for daily and monthly values

12 Satellite irradiance models Model dependence No specific dependence with the sky conditions No specific dependence with the aerosol optical depth Too high dispersion in daily values to point out a seasonal dependence Similar results for the three models Best results mean bias difference: 3% hourly standard deviation: 33% daily standard deviation: 24% monthly standard deviation: 8%

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