1) The document analyzes seasonal forecasts for global solar photovoltaic (PV) energy in winter by assessing solar irradiance resource potential, variability, and forecast skill. 2) It identifies key regions where solar irradiance is abundant and highly variable, and where forecast models demonstrate the highest skill in predicting irradiance variability, magnitude, and uncertainty. 3) These regions, including parts of South America, Africa, Asia, and Australia, show the greatest potential for operational winter solar irradiance forecasts to inform decision-making.

1. Climate Forecasting Unit
WINTER
Seasonal Forecasts for
Global Solar PV Energy
Melanie Davis, Francisco Doblas-Reyes, Fabian Lienert

2. Climate Forecasting Unit
Fig. S1.4.1: Winter 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?
Darker red regions of this map show where global solar GHI is highest in winter, 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.
WINTER Solar PV Forecasts
(December + January + February)

3. Climate Forecasting Unit
Fig. S1.4.2: Winter 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 wind vary the greatest?
Darker red regions of this map show where global solar GHI varies the most from one year to the next in
winter, and lighter yellow regions where it varies the least.
N.b. This information is based on reanalysis* data (ERA-Interim) not direct observations.
WINTER Solar PV Forecasts
(December + January + February)

4. Climate Forecasting Unit
Europe
Winter solar GHI availability Winter solar GHI inter-annual variability
m/s
Areas of
interest: Whole
Continent
S.
Continent
S.E.
Continent/
E.India
Australia/
New Zealand/
Papua New
Guinea/
Pacific Isles
S.America Africa Asia Australia
S.Continent
N.America
S.Iberian
Peninsular/
Mediterranean
Stage A: Solar GHI Resource Assessment
Where is solar PV energy resource potential and variability highest?
By comparing both the winter global solar GHI 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 winter.
WINTER Solar PV Forecasts
(December + January + February)

5. Climate Forecasting Unit
Fig. W2.4.1: Winter 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 Assessment
1St
validation of the climate forecast system:
Can the solar forecast mean tell us about
the solar GHI resource variability
at a specific time?
The skill of a climate forecast system, to predict global solar GHI variability in winter 1 month ahead, is partially
shown in this map. Skill is assessed by comparing the mean of a winter 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
WINTER Solar PV Forecasts
(December + January + February)
SolarGHI

6. Climate Forecasting Unit
Fig. W2.4.1: Winter solar GHI ensemble mean correlation
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
Stage B: Solar GHI Forecast Skill Assessment
1St
validation of the climate forecast system:
Dark red regions of the map show where the climate forecast system demonstrates the highest skill in winter
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
WINTER Solar PV Forecasts
(December + January + February)
Can the solar forecast mean tell us about
the solar GHI resource variability
at a specific time?

7. Climate Forecasting Unit
Fig. S2.4.2: Winter solar GHI CR probability skill score
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
Can the solar forecast distribution tell us
about the magnitude of the solar GHI
resource variability and its uncertainty at
specific time?
time
forecast
+ 1.0
obs. forecast
- 1.0
forecast
example 1
forecast
- 1.0
example 2
example 3
Stage B: Solar GHI Forecast Skill Assessment
2nd
validation of the climate forecast system:
The skill of a climate forecast system, to predict global solar GHI variability in winter 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 winter 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
WINTER Solar PV Forecasts
(December + January + February)
SolarGHI

8. Climate Forecasting Unit
Fig. S2.4.2: Winter 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 Assessment
2nd
validation of the climate forecast system:
Dark red regions of the map show where the climate forecast system demonstrates the highest skill in winter
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
WINTER Solar PV Forecasts
(December + January + February)
Can the solar forecast distribution tell us
about the magnitude of the solar GHI
resources variability and its uncertainty
at specific time?

9. Climate Forecasting Unit
Europe
Areas of
interest:
N.Brasil/
N.E.Coast/
N.W.Coast
Indonesia/
N.Philippines/
S.Korea/
S.Japan/
Vietnam
W. Australia/
S.New Zealand/
Papua New
Guinea/Pacific
Isles
S.America Africa
Asia Australia
Caribbean/Gulf of
California/
C.S.W.USA/
N.W.Coast Canada
N.America
N.UK/N.Sea/
S.Baltic Sea and
surrounding land
Winter solar GHI magnitude, and its uncertainty
forecast skill
Winter solar GHI variability forecast skill
Solar GHI variability
forecast skill only
Solar GHI magnitude and its uncertainty forecast skill
E.Penins-
ular/
E.Namibia
Stage B: Solar GHI Forecast Skill Assessment Where is solar GHI forecast skill highest?
By comparing both the winter 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 winter wind forecasts, and
are therefore of greatest interest to seasonal solar GHI forecasting in winter.
WINTER Solar PV Forecasts
(December + January + February)

10. Climate Forecasting Unit
Stage B: Solar GHI Forecast Skill Assessment
Magnitude and uncertainty forecast skillVariability forecast skill
m/sm/sm/s
SPRING Wind Forecasts
These four maps compare the seasonal winter solar GHI global forecast skill maps (bottom) alongside the
winter 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 winter
seasonal solar GHI forecasts have the greatest value and potential for operational use.
Areas of
Interest:
(Forecast skill)
Areas of
Interest:
(Resources)
Solar GHI resource inter-annual variabilitySolar GHI resource availability
Stage A: Solar GHI Resource Assessment
Variability forecast skill
Where is solar GHI forecast skill highest?
WINTER Solar PV Forecasts
(December + January + February)
Where is solar resource potential + volatility highest?
Europe
Whole
Continent
S.
Continent
S.E.
Continent/
E.India
Australia/
New Zealand/
Papua New
Guinea/
Pacific Isles
S.America Africa Asia Australia
S.Continent
N.America
S.Iberian
Peninsular/
Mediterranean
Europe
N.Brasil/
N.E.Coast/
N.W.Coast
Indonesia/
N.Philippines/
S.Korea/
S.Japan/
Vietnam
W. Australia/
S.New Zealand/
Papua New
Guinea/Pacific
Isles
S.America Africa Asia Australia
Caribbean/Gulf
of California/
C.S.W.USA/
N.W.Coast Canada
N.America
N.UK/N.Sea/
S.Baltic Sea and
surrounding land
E.Penins-
ular/
E.Namibia

11. Climate Forecasting Unit
%
Fig. S3.4.1: Probabilistic forecast of (future) winter 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 resource to be higher (red), lower
(blue) or normal (white) over the forthcoming winter season, compared to their mean value over the past 30
years. As the forecast season is winter 2011, this is an example of solar GHI forecast information that could
have been available for use within a decision making process in November 2011.
WINTER Solar PV Forecasts
(December + January + February)
N.Brasil/
N.E.Coast/
N.W.Coast
Indonesia/
N.Philippines/
S.Korea/S.Japan/
Vietnam
W. Australia/
S.New Zealand/
Papua New
Guinea/Pacific
Isles
S.America
Asia
Australia
Carribbean/Gulf
of California/
C.S.W.USA/
N.America
Africa
E.Peninsular/
E.Namibia
Areas of Interest Identified:
(Resources and Forecast Skill)

12. Climate Forecasting Unit
%
Stage C: Operational Solar GHI Forecast
The key areas of highest interest are shown, identified in the stages A and B of the forecast methodology.
These regions demonstrate where winter 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 winter (Stage B) and/or
lower solar GHI availability and inter-annual variability (Stage A).
Fig. S3.4.1: Probabilistic forecast of (future) winter 2011, solar GHI most likely tercile
(ECMWF S4, 1 month forecast lead time)
WINTER Solar PV Forecasts
(December + January + February)
N.Brasil/
N.E.Coast/
N.W.Coast
Indonesia/
N.Philippines/
S.Korea/S.Japan/
Vietnam
W. Australia/
S.New Zealand/
Papua New
Guinea/Pacific
Isles
S.America
Asia
Australia
Carribbean/Gulf
of California/
C.S.W.USA/
N.America
Africa
E.Peninsular/
E.Namibia
Areas of Interest Identified:
(Resources and Forecast Skill)

13. Climate Forecasting Unit
%
Stage C: Operational Solar GHI Forecast
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.
Fig. S3.4.1: Probabilistic forecast of (future) winter 2011, solar GHI most likely tercile
(ECMWF S4, 1 month forecast lead time)
WINTER Solar PV Forecasts
(December + January + February)
N.Brasil/
N.E.Coast/
N.W.Coast
Indonesia/
N.Philippines/
S.Korea/S.Japan/
Vietnam
W. Australia/
S.New Zealand/
Papua New
Guinea/Pacific
Isles
S.America
Asia
Australia
Carribbean/Gulf
of California/
C.S.W.USA/
N.America
Africa
E.Peninsular/
E.Namibia
Areas of Interest Identified:
(Resources and Forecast Skill)

14. Climate Forecasting Unit
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)