Correction of Satellite-Derived DNI Time Series Using Locally-Resolved Aerosol Data
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1 Correction of Satellite-Derived DNI Time Series Using Locally-Resolved Aerosol Data Tomas Cebecauer, PhD Marcel Suri PhD GeoModel Solar Bratislava, Slovakia Conference SolarPACES 2012, 12 September 2012, Marrakech, Morocco Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [1]
2 Major factors influencing DNI 1) cloud attenuation 2) aerosols 3) water vapour DNI high temporal variability cloud attenuation change of AOD = 40% decrease of DNI DNI daily profile for different aerosol loads DNI daily profile for different water vapour content Influence on GHI is several times lower Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [2]
3 Requirements for AOD data high time resolution - at least daily continuous in time, no gaps homogeneous spatial coverage no regions without data high spatial resolution, site specific AOD in satellite radiation databases Chemical transport models (MACC, GOCARD, MATCH ) Satellite derived products (MODIS, MERA, OMI, ) Local (nearby) measurements (AERONET, DNI derived, visibility) Common AOD problems Regional bias (models, satellite) Low resolution ( km) not site specific (models, satellite) Missing data (satellite, local measurements) Old radiation databases use monthly AOD data Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [3]
4 Monthly vs. daily aerosol data MACC AOD monthly average monthly climatology daily values Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [4]
5 Monthly vs. daily aerosol data Site in Gujarat, India BLU: monthly averaged AOD data RED: data with daily variability of AOD (SolarGIS data) Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [5]
6 AOD problems low resolution of database Sede Boqer (Israel) DNI BIAS Sede Boqer Complex geography, terrain, sea (low res MACC data do not describe inter-pixel variability) GEMS AOD pixel 1.125x1.125 deg. Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [6]
7 AOD problems missing data Satellite (MODIS-Terra) AOD data coverage for 3 September 2012 Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [7]
8 Problems of DNI due to aerosols - Inaccurate day-by-day variability - Systematic over/under-estimation Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [8]
9 AOD database used in SolarGIS model Chemical transport model MACC - operated by ECMWF, reanalysis data + operational model deg resolution (original resolution 0.8 deg) - period hourly time step reduced to daily data - Gaps free Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [9]
10 Adaptation of satellite time series to local measurements Inputs - Time series of irradiance data derived from satellite data (10+ years) - Ground measurements of DNI and GHI (high quality, 12+ months) Output - Time series of irradiance data with reduced uncertainty Aim - Remove systematic deviation from satellite data - Decrease bias, RMSE - Improve distribution of values Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [10]
11 Standard method to reduce systematic deviation Statistical approach, postprocessing (CDF fit, rescale) input data (satellite, AOD, WV, altit., ) satellite based radiation model GHI, DNI on-site measurements adaptation of GHI, DNI final GHI, DNI Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [11]
12 Proposed method to remove systematic deviations Adaptation of inputs correction of source of bias (AOD correction) on-site measurements adaptation of AOD input data (satellite, AOD, WV, altit., ) satellite based radiation model final GHI, DNI Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [12]
13 Correction of aerosols Example:Geraldton, Australia - monthly correction factor derived from local ground measurements - applied to the daily aerosol data from MACC model - correction in the range of to Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [13]
14 Results of site adaptation original DNI data DNI with AOD adaptation Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [14]
15 Results of site adaptation BIAS RMSE KSI ORIGINAL DATA % 26 % 156 CDF FIT % 25 % 26 AOD adaptation -0.2 % 25 % 29 Both methods provide significant improvements of all measures Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [15]
16 Results of site adaptation CDF fit Cumulative distribution original data AOD adaptation Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [16]
17 Results of site adaptation Coherence of GHI and DNI original data CDF fit CDF fit - destroys GHI/DNI coherence - does not follow physical principles AOD adaptation preserves GHI/DNI coherence AOD adaptation Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [17]
18 Use of AOD correction for improvement of SolarGIS database - Regional adaptation of the AOD database used in SolarGIS model - Based on the AERONET data and ground measurements - Aim: identify and remove regional bias of the MACC AOD database, reduce DNI uncertainty Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [18]
19 Regional AOD correction - Pre-selection and validation of the data of heterogeneous quality - Analyzing regional patterns of the systematic AOD bias - Analysis of seasonal pattern of the AOD bias - Analysis of outliers, specific local AOD conditions - Derivation of regional correction factor - Harmonization of clusters of sites - Barrier effect of the mountain ridges and other geographical features Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [19]
20 Time period with available AERONET data All AERONET sites: ~650 More than 15 days of data: 460 site More than 365 days of data: 235 sites Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [20]
21 Average deviation AERONET MACC data - Overall slight overestimation by MACC - Regions with higher overestimation : Arabic peninsula, N. India,China, SW US Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [21]
22 Results: - Reduced uncertainty of DNI and GHI data Regions with available AOD or DNI ground data - DNI uncertainty 5-8 % - Reduction of uncertainty is not as high as for site specific AOD correction, but regional problems were mitigated SolarGIS DNI Conference SolarPACES 2012, 13 September 2012, Marrakech, Morocco [22]
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