20130607 arecs web_forecast_video_spring_sun

Climate Forecasting Unit

SPRINGSeasonal Forecasts for Global Solar PV Energy

Melanie Davis, Francisco Doblas-Reyes, Fabian Lienert


Fig. S1.1.1: Spring solar GHI availability from 1981-2011 (ERA-Interim)

m/s

Stage A: Solar GHI (Global Horizontal Irradiance) Resource Assessment Solar PV energy potential: Where is it the sunniest?

Dark red regions of this map shows where global solar GHI is highest in spring, and lighter yellow regions where it is lowest. N.b. This information is based on reanalysis* data (ERA-Interim) not direct observations.

* Reanalysis information comes from an objective combination of observations and numerical models that simulate one or more aspects of the Earth system, to generate a synthesised estimate of the state of the climate system and how it changes over time.

SPRING Solar PV Forecasts(March + April + May)


Fig. S1.1.2: Spring solar GHI inter-annual variability from 1981-2011 (ERA-Interim)

m/s

Stage A: Solar GHI Resource Assessment Solar PV energy volatility: Where does the solar radiation vary the greatest?

Darker red regions of this map show where global solar GHI varies the most from one year to the next in spring, and lighter yellow regions where it varies the least.

N.b. This information is based on reanalysis* data (ERA-Interim) not direct observations.



Europe

Spring solar GHI availability Spring solar GHI inter-annual variabilitym/s

Areas of interest: N.

Continent

S.Sahal/ Zimbabwe/Zambia/Mozambique

S.E.Continent/N.E.Pakistan/N.E.Afghanistan/Tajikistan

N-N.E. Australia

S.America Africa Asia Australia

N.E.Mexico/W.USA

N.America

France/N.W.Spain

Stage A: Solar GHI Resource Assessment Where is solar PV energy resource potential and variability highest?

By comparing both the spring global solar GHI resource availability and inter-annual variability, it can be seen that there 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 of greatest interest for seasonal forecasting in spring.



Fig. S2.1.1: Spring solar GHI ensemble mean correlation(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)

time

forecast + 1.0

obs. forecast - 1.0

forecast example 1

forecast - 1.0

example 2

example 3

Stage B: Solar GHI Forecast Skill Assessment1St validation of the climate forecast system:

The skill of a climate forecast system, to predict global solar GHI variability in spring 1 month ahead, is partially shown in this map. Skill is assessed by comparing the mean of a spring solar GHI forecast, made every year since 1981, to the reanalysis “observations” over the same period. If they follow the same variability over time, the skill is positive. This is the case even if their magnitudes are different (see example 1 and 2).

Perfect Forecast

Same as Climatology

Worse than

Clima-tology


Can the solar forecast mean tell us about the solar GHI resource variability at a specific time?

Sol

ar G

HI


Fig. S2.1.1: Spring solar GHI ensemble mean correlation

(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)

Stage B: Solar GHI Forecast Skill Assessment1St validation of the climate forecast system:

Dark red regions of the map show where the climate forecast system demonstrates the highest skill in spring seasonal forecasting, with a forecast issued 1 month in advance. White regions show where there is no available forecast skill, and blue regions where the climate forecast system performs worse than a random prediction. A skill of 1 corresponds to a climate forecast that can perfectly represent the past “observations”.

Perfect Forecast

Same as Climatology

Worse than

Clima-tology


Can the solar forecast mean tell us about the solar GHI resource variability at a specific time?


Fig. S2.1.2: Spring solar GHI CR probability skill score(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)

time

forecast + 1.0

obs. forecast - 1.0

forecast example 1

forecast - 1.0

example 2

example 3

Stage B: Solar GHI Forecast Skill Assessment2nd validation of the climate forecast system:

The skill of a climate forecast system, to predict global solar GHI variability in spring 1 month ahead, is fully shown in this map. Here, skill is assessed by comparing the full distribution (not just the mean value as in the previous map) of a spring solar GHI forecast, made every year since 1981, to the “observations” over the same period. If they follow the same magnitude of variability over time, the skill is positive (example 2).

Perfect Forecast

Same as Climatology

Worse than

Clima-tology


Can the solar forecast distribution tell us about the magnitude of the solar GHI resource variability and its uncertainty at specific time?

Sol

ar G

HI


Fig. S2.1.2: Spring solar GHI CR probability skill score(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)

Stage B: Solar GHI Forecast Skill Assessment2nd validation of the climate forecast system:

Dark red regions of the map show where the climate forecast system demonstrates the highest skill in spring seasonal forecasting, with a forecast issued 1 month in advance. White regions show where there is no available forecast skill, and blue regions where the climate forecast system performs worse than a random prediction. A skill of 1 corresponds to a climate forecast that can perfectly represent the past “observations”.

Perfect Forecast

Same as Climatology

Worse than

Clima-tology


Can the solar forecast distribution tell us about the magnitude of the solar GHI resource variability and its uncertainty at specific time?


EuropeAreas of interest:

E.Chile/S.SE Argentina/N.E.Brasil

Indonesia/W.Philippines/Cambodia/Thailand/Vietnam/UAE/Oman/S.Pakistan/S.Iran/Afghanistan

N.Australia/Pacific Isles

S.America AfricaAsia

AustraliaE.USAN.America

North Sea/S.France/E.Europe

Spring solar GHI magnitude, and its uncertainty forecast skill

Spring solar GHI variability forecast skill

Solar GHI variability forecast skill only

Solar GHI magnitude and its uncertainty forecast skill

S.Moz-ambique

Stage B: Solar GHI Forecast Skill Assessment

Where is solar GHI forecast skill highest?

By comparing both the spring global solar GHI forecast skill assessments, it can be seen that there are several key areas (listed above) where solar GHI forecasts are skilful in assessing its variability, magnitude and uncertainty. These regions show the greatest potential for the use of operational spring wind forecasts, and are therefore of greatest interest to seasonal solar GHI forecasting in spring.



Stage B: Solar GHI Forecast Skill AssessmentMagnitude and uncertainty forecast skillVariability forecast skill

m/sm/sm/s

SPRING Wind Forecasts

These four maps compare the seasonal spring solar GHI global forecast skill maps (bottom) alongside the spring global solar GHI availability and inter-annual variability map (top). It can be seen that there are several key areas (highlighted above) where the forecast skill is high in assessing its variability, magnitude and uncertainty, and the solar GHI is both abundant and highly variable. These regions demonstrate where spring seasonal solar GHI forecasts have the greatest value and potential for operational use.

EuropeAreas of Interest:(Forecast skill)

E.BrazilIndonesia/W.Philippines/Cambodia/Thailand/Vietnam/UAE/Oman/S.Pakistan/S.Iran/Afghanistan

W.

S.America AfricaAsia

Australia

Mexico/S.Canada

N.America

North Sea/S.France/E.Europe

S.Moz- ambique

Europe S.America Africa Asia AustraliaN.America

S.E.Continent/N.E.Pakistan/N.E.Afghanistan/Tajikistan

France/N.W.Spain

Areas of Interest: (Resources)

N-N.E.Australia

Solar GHI resource inter-annual variability Solar GHI resource availabilityStage A: Solar GHI Resource Assessment

Variability forecast skillWhere is solar GHI forecast skill highest?

Where is solar resource potential + volatility highest?


N.E.Mexico/W.USA

N.Continent

S.Sahal/ Zimbabwe/Zambia/Mozambique

E.Chile/S.SE Argentina/N.E.Brasil

N.Australia/Pacific Isles

E.USA


%

Areas of Interest Identified:(Resources and Forecast Skill)

S.America

E.BrasilE.Brasil

W.

Australia

N.Australia

S.America

Fig. S3.1.1: Probabilistic forecast of (future) spring 2011, solar GHI most likely tercile(ECMWF S4, 1 month forecast lead time)

Stage C: Operational Solar GHI Forecast

This operational solar forecast shows the probability of global solar GHI to be higher (red), lower (blue) or normal (white) over the forthcoming spring season, compared to their mean value over the past 30 years. As the forecast season is spring 2011, this is an example of solar GHI forecast information that could have been available for use within a decision making process in February 2011.


Europe

S.France

Africa

S.Mozambique

Indonesia/ W.Philippines/Cambodia/ Thailand/Vietnam/ N.E.Afghanistan

Asia


%



The key areas of highest interest are shown, identified in the stages A and B of the forecast methodology. These regions demonstrate where spring seasonal solar GHI forecasts have the greatest value and potential for operational use. The areas that are blanked out either have lower forecast skill in spring (Stage B) and/or lower solar GHI availability and inter-annual variability (Stage A).



S.America

E.BrasilE.Brasil

W.

Australia

N.Australia

S.America Europe

S.France

Africa

S.Mozambique


Asia


%



This does not mean that the blanked out areas are not useful, only that the operational solar GHI forecast for these regions should be used within a decision making process with due awareness to their corresponding limitations. The primary limitations to a climate forecast are either the forecast skill and/or the low risk of variability in solar GHI for a given region. See the “caveats” webpage for further limitations.



S.America

E.BrasilE.Brasil

W.

Australia

N.Australia

S.America Europe

S.France

Africa

S.Mozambique


Asia


The research leading to these results has received funding from 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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20130607 arecs web_forecast_video_spring_sun