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20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
20130607 arecs web_forecast_video_autumn_sun
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20130607 arecs web_forecast_video_autumn_sun

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  • 1. Climate Forecasting UnitAUTUMNSeasonal Forecasts forGlobal Solar PV EnergyMelanie Davis, Francisco Doblas-Reyes, Fabian Lienert
  • 2. Climate Forecasting UnitFig. S1.3.1: Autumn solar GHI availability from 1981-2011 (ERA-Interim)m/sStage A: Solar GHI (Global Horizontal Irradiance) Resource AssessmentSolar PV energy potential: Where is it the sunniest?Dark red regions of this map shows where global solar GHI is highest in autumn, and lighter yellow regionswhere it is lowest.N.b. This information is based on reanalysis* data (ERA-Interim) not direct observations.* Reanalysis information comes from a objective combination of observations and a numerical models that simulate one or more aspects of the Earth system, togenerate a synthesised estimate of the state of the climate system and how it changes over time.AUTUMN Solar PV Forecasts(September + October + November)
  • 3. Climate Forecasting UnitFig. S1.3.2: Autumn solar GHI inter-annual variability from 1981-2011 (ERA-Interim)m/sStage A: Solar GHI Resource AssessmentSolar PV energy volatility: Where does solar radiation vary the greatest?The darker red regions of this map shows where global solar GHI varies the most from one year to the next inautumn, and lighter yellow regions where it varies the least.N.b. This information is based on reanalysis* data (ERA-Interim) not direct observations.AUTUMN Solar PV Forecasts(September + October + November)
  • 4. Climate Forecasting UnitEuropeAutumn solar GHI availability Autumn solar GHI inter-annual variabilitym/sAreas ofinterest: WholeContinentS.AfricanContinentS.E.MainlandAsia/Philippines/IndonesiaE.Australia/Papua NewGuineaS.America Africa Asia AustraliaN.Mexico/S.E. USAN.AmericaSpain/Portugal/MediterraneanStage A: Solar GHI Resource AssessmentWhere is solar PV energy resource potential and variability highest?By comparing both the autumn global solar GHI availability and inter-annual variability, it can be seen thatthere are several key areas (listed above) where solar GHI is both abundant and highly variable.These regions are most vulnerable to solar GHI variability over climate timescales, and are therefore ofgreatest interest for seasonal forecasting in autumn.AUTUMN Solar PV Forecasts(September + October + November)
  • 5. Climate Forecasting UnitFig. S2.3.1: Autumn solar GHI ensemble mean correlation(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)timeSolarGHIforecast+ 1.0obs. forecast- 1.0forecastexample 1forecast- 1.0example 2example 3Stage B: Solar GHI Forecast Skill Assessment1Stvalidation of the climate forecast system:Can the forecast mean predict thevariability of the solar GHI observations?The skill of a climate forecast system, to predict global solar GHI variability in autumn 1 month ahead, ispartially shown in this map. Skill is assessed by comparing the mean of a autumn solar GHI forecast, madeevery year since 1981, to the reanalysis “observations” over the same period. If they follow the same variabilityover time, the skill is positive. This is the case even if their magnitudes are different (see example 1 and 2).PerfectForecastSame asClimatologyWorsethanClima-tologyAUTUMN Solar PV Forecasts(September + October + November)
  • 6. Climate Forecasting UnitFig. S2.3.1: Autumn solar GHI ensemble mean correlation(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)Stage B: Solar GHI Forecast Skill Assessment1Stvalidation of the climate forecast system:Can the forecast mean predict thevariability of the solar GHI observations?Dark red regions of the map show where the climate forecast system demonstrates the highest skill in autumnseasonal forecasting, with a forecast issued 1 month in advance. White regions show where there is noavailable forecast skill, and blue regions where the climate forecast system performs worse than a randomprediction. A skill of 1 corresponds to a climate forecast that can perfectly represent the past “observations”.PerfectForecastSame asClimatologyWorsethanClima-tologyAUTUMN Solar PV Forecasts(September + October + November)
  • 7. Climate Forecasting UnitFig. S2.3.2: Autumn solar GHI CR probability skill score(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)Can the forecast distribution predict themagnitude and the variability of thesolar GHI observations?timeSolarGHIforecast+ 1.0obs. forecast- 1.0forecastexample 1forecast- 1.0example 2example 3Stage B: Solar GHI Forecast Skill Assessment1Stvalidation of the climate forecast system:The skill of a climate forecast system, to predict global solar GHI variability in autumn 1 month ahead, is fullyshown in this map. Here, skill is assessed by comparing the full distribution (not just the mean value as in theprevious map) of an autumn solar GHI forecast, made every year since 1981, to the “observations” over thesame period. If they follow the same variability and magnitude over time, the skill is positive (example 2).PerfectForecastSame asClimatologyWorsethanClima-tologyAUTUMN Solar PV Forecasts(September + October + November)
  • 8. Climate Forecasting UnitFig. S2.3.2: Autumn solar GHI CR probability skill score(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)Can the forecast distribution predict themagnitude and the variability of thesolar GHI observations?Stage B: Solar GHI Forecast Skill Assessment1Stvalidation of the climate forecast system:Dark red regions of the map show where the climate forecast system demonstrates the highest skill in autumnseasonal forecasting, with a forecast issued 1 month in advance. White regions show where there is noavailable forecast skill, and blue regions where the climate forecast system performs worse than a randomprediction. A skill of 1 corresponds to a climate forecast that can perfectly represent the past “observations”.PerfectForecastSame asClimatologyWorsethanClima-tologyAUTUMN Solar PV Forecasts(September + October + November)
  • 9. Climate Forecasting UnitEuropeAreas ofinterest:N.Patagonia/N.E.Coast(variability skill only)Indonesia/Malaysia/SingaporeN.E.AustraliaS.America Africa Asia AustraliaN.USA/CaribbeanN.AmericaUK/SpainPortugal/Sardinia/CorsicaAutumn solar GHI magnitude and variabilityforecast skillAutumn solar GHI variability forecast skillSolar GHI variabilityforecast skill onlyBoth solar GHI variability and magnitude forecast skillTanzania/KenyaCoastStage B: Solar GHI Forecast Skill Assessment Where is solar GHI forecast skill highest?By comparing both the autumn global solar GHI forecast skill assessments, it can be seen that there areseveral key areas (listed above) where solar GHI forecasts are skilful in both its variability and magnitude.These regions show the greatest potential for the use of operational autumn wind forecasts, and are thereforeof greatest interest to seasonal solar GHI forecasting in autumn.AUTUMN Solar PV Forecasts(September + October + November)
  • 10. Climate Forecasting UnitMexico/S.CanadaStage B: Solar GHI Forecast Skill AssessmentMagnitude + variability forecast skillVariability forecast skillm/sm/sm/sSPRING Wind ForecastsThese four maps compare the seasonal autumn solar GHI global forecast skill maps (bottom) alongside theautumn global solar GHI availability and inter-annual variability map (top). It can be seen that there are severalkey areas (highlighted above) where the forecast skill is high in both its variability and magnitude, and thesolar GHI is both abundant and highly variable. These regions demonstrate where autumn seasonal solar GHIforecasts have the greatest value and potential for operational use.EuropeAreas ofInterest:(Forecast skill)Indonesia/Malaysia/SingaporeW.S.America Africa Asia AustraliaN.AmericaXXCOASTN.Patagonia/N.E.CoastN.E.AustraliaEurope S.America Africa Asia AustraliaN.AmericaWholeContinentS.AfricaContinentS.E.Mainland AsiaPhilippines/IndonesiaW.Australia/TazmaniaN.Mexico/S.E. USASpain/Portugal/MediterraneanAreas ofInterest:(Resources)E.AustraliaSolar GHI inter-annual variabilitySolar GHI availabilityStage A: Solar GHI Resource AssessmentVariability forecast skillWhere is solar GHI forecast skill highest?Where is solar resource potential + volatility highestAUTUMN Solar PV Forecasts(September + October + November)IndonesiaN.USA/CaribbeanIndonesiaUK/SpainPortugal/Sardinia/CorsicaTanzania/KenyaCoast
  • 11. Climate Forecasting Unit%EuropeSpain/Portugal/SicilyAreas of Interest Identified:(Resources and Forecast Skill)W.AustraliaE.AustraliaFig. S3.3.1: Probabilistic forecast of (future) autumn 2011, solar GHI most likely tercile(ECMWF S4, 1 month forecast lead time)Stage C: Operational Solar GHI ForecastThis operational solar forecast shows the probability of global solar GHI to be higher (red), lower (blue) ornormal (white) over the forthcoming autumn season, compared to their mean value over the past 30 years. Asthe forecast season is autumn 2011, this is an example of solar GHI forecast information that could have beenavailable for use within a decision making process in August 2011.AUTUMN Solar PV Forecasts(September + October + November)AsiaIndonesiaAfricaTanzania/KenyaCoastS.AmericaN.PatagoniaN.E.CoastS.America
  • 12. Climate Forecasting Unit%Stage C: Operational Solar GHI ForecastThe key areas of highest interest are shown, identified in the stages A and B of the forecast methodology.These regions demonstrate where autumn seasonal solar GHI forecasts have the greatest value and potentialfor operational use. The areas that are blanked out either have lower forecast skill in autumn (Stage B) and/orlower solar GHI availability and inter-annual variability (Stage A).Fig. S3.3.1: Probabilistic forecast of (future) autumn 2011, solar GHI most likely tercile(ECMWF S4, 1 month forecast lead time)AUTUMN Solar PV Forecasts(September + October + November)Fig. S3.3.1: Probabilistic forecast of (future) autumn 2011, solar GHI most likely tercile(ECMWF S4, 1 month forecast lead time)EuropeSpain/Portugal/SicilyAreas of Interest Identified:(Resources and Forecast Skill)W.AustraliaE.AustraliaAsiaIndonesiaAfricaTanzania/KenyaCoastS.AmericaN.PatagoniaN.E.CoastS.America
  • 13. Climate Forecasting Unit%Stage C: Operational Solar GHI ForecastThis does not mean that the blanked out areas are not useful, only that the operational solar GHI forecastinformation for these regions should be used within a decision making process with due awareness to theircorresponding limitations. The primary limitations to a climate forecast are either the forecast skill and/or thelow risk of variability in solar GHI for a given region. See the “caveats” webpage for further limitations.Fig. S3.3.1: Probabilistic forecast of (future) autumn 2011, solar GHI most likely tercile(ECMWF S4, 1 month forecast lead time)AUTUMN Solar PV Forecasts(September + October + November)Fig. S3.3.1: Probabilistic forecast of (future) autumn 2011, solar GHI most likely tercile(ECMWF S4, 1 month forecast lead time)EuropeSpain/Portugal/SicilyAreas of Interest Identified:(Resources and Forecast Skill)S.AmericaN.PatagoniaN.E.CoastW.AustraliaE.AustraliaS.AmericaAsiaIndonesiaAfricaTanzania/KenyaCoast
  • 14. Climate Forecasting UnitThe research leading to these results has received fundingfrom the European Union Seventh Framework Programme(FP7/2007-2013) under the following projects:CLIM-RUN, www.clim-run.eu (GA n° 265192)EUPORIAS, www.euporias.eu (GA n° 308291)SPECS, www.specs-fp7.eu (GA n° 308378)

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