2. Climate Forecasting Unit
Fig. S1.2.1: Summer 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 summer, 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 a objective combination of observations and a 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.
SUMMER Solar PV Forecasts
(June + July + August)
3. Climate Forecasting Unit
Fig. S1.2.2: Summer solar GHI inter-annual variability from 1981-2011 (ERA-Interim)
m/s
Stage A: Solar GHI Resource Assessment
Solar 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 in
summer, and lighter yellow regions where it varies the least.
N.b. This information is based on reanalysis* data (ERA-Interim) not direct observations.
SUMMER Solar PV Forecasts
(June + July + August)
4. Climate Forecasting Unit
Europe
Summer solar GHI availability Summer solar GHI inter-annual variability
m/s
Areas of
interest:
N.Continent/
C-N.Chile-
Argentina
border
Central
Continent
S.W.Continent/
C-C.E.
Continent/
W-N.W.
Continent
Papua New
Guinea
S.America Africa Asia Australia
N.C.America/
S.W.Canada
N.America
UK/Norway/
Sweden/
S.Finland/
N.Mainland
Europe
Stage A: Solar GHI Resource Assessment
Where is solar PV energy resource potential and variability highest?
By comparing both the summer 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 summer.
SUMMER Solar PV Forecasts
(June + July + August)
5. Climate Forecasting Unit
Fig. S2.2.1: Summer solar GHI ensemble mean correlation
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
time
SolarGHI
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 forecast mean predict the
variability of the solar GHI observations?
The skill of a climate forecast system, to predict global solar GHI variability in summer 1 month ahead, is
partially shown in this map. Skill is assessed by comparing the mean of a summer 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
SUMMER Solar PV Forecasts
(June + July + August)
6. Climate Forecasting Unit
Fig. S2.2.1: Summer 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:
Can the forecast mean predict the
variability of the solar GHI observations?
Dark red regions of the map show where the climate forecast system demonstrates the highest skill in
summer 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”.
SUMMER Solar PV Forecasts
(June + July + August)
Perfect
Forecast
Same as
Climatology
Worse
than
Clima-
tology
7. Climate Forecasting Unit
Fig. S2.2.2: Summer solar GHI CR probability skill score
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
Can the forecast distribution predict the
magnitude and the variability of the
solar GHI observations?
time
SolarGHI
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:
The skill of a climate forecast system, to predict global solar GHI variability in summer 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 summer solar GHI forecast, made every year since 1981, to the “observations” over the
same period. If they follow the same variability and magnitude over time, the skill is positive (example 2).
Perfect
Forecast
Same as
Climatology
Worse
than
Clima-
tology
SUMMER Solar PV Forecasts
(June + July + August)
8. Climate Forecasting Unit
Fig. S2.2.2: Summer solar GHI CR probability skill score
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
Can the forecast distribution predict the
magnitude and the variability of the
solar GHI observations?
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
summer 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
SUMMER Solar PV Forecasts
(June + July + August)
9. Climate Forecasting Unit
Europe
Areas of
interest:
N.Brasil?/
E.Brasil/N.Chile/
N.Argentina
C-C.E.Indone-
sia/W.China/
UAE/S.E.Saudi
Arabia
C.W.
Australia/
Pacific Isles
S.America Africa
Asia
Australia
S.E.Canada/
Caribbean
Isles
N.America
Spain/Portugal/Medite-
rranean/S.E.Europe/
W.Great Britain/
S.Norway/S.Sweden/
N.Finland?
Summer solar GHI magnitude and variability
forecast skill
Summer solar GHI variability forecast skill
Solar GHI variability
forecast skill only
Both solar GHI variability and magnitude forecast skill
S-S.Africa/
N.Mozambi-
que/Ethiopia
Stage B: Solar GHI Forecast Skill Assessment Where is solar GHI forecast skill highest?
By comparing both the summer 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 both its variability and magnitude.
These regions show the greatest potential for the use of operational summer wind forecasts, and are therefore
of greatest interest to seasonal solar GHI forecasting in summer.
SUMMER Solar PV Forecasts
(June + July + August)
10. Climate Forecasting Unit
Stage B: Solar GHI Forecast Skill Assessment
Magnitude + variability forecast skillVariability forecast skill
m/sm/sm/s
SPRING Wind Forecasts
These four maps compare the seasonal summer solar GHI global forecast skill maps (bottom) alongside the
summer 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 both its variability and magnitude, and
the solar GHI is both abundant and highly variable. These regions demonstrate where summer seasonal solar
GHI forecasts have the greatest value and potential for operational use.
Areas of
Interest:
(Forecast skill)
Areas of
Interest:
(Resources)
Solar GHI inter-annual variabilitySolar GHI availability
Stage A: Solar GHI Resource Assessment
Variability forecast skill
Where is solar GHI forecast skill highest?
Where is solar resource potential + volatility highest
SUMMER Solar PV Forecasts
(June + July + August)
Europe
N.Brasil?/
E.Brasil/N.Chile/
N.Argentina
C-C.E.Indone-
sia/W.China/
UAE/S.E.Saudi
Arabia
C.W.
Australia/
Pacific Isles
S.America Africa Asia Australia
S.E.Canada/
Caribbean
Isles
N.America
Spain/Portugal/Medite-
rranean/S.E.Europe/
W.Great Britain/
S.Norway/S.Sweden/
N.Finland?
S-S.Africa/
N.Mozambi-
que/Ethiopia
Europe
N.Continent/
C-N.Chile-
Argentina
border
Central
Continent
S.W.Continent/
C-C.E.
Continent/
W-N.W.
Continent
Papua New
Guinea
S.America Africa Asia Australia
N.C.America/
S.W.Canada
N.America
UK/Norway/
Sweden/
S.Finland/
N.Mainland
Europe
11. Climate Forecasting Unit
%
Areas of Interest Identified:
(Resources and Forecast Skill)
S.America
N.Brasil?/
E.Brasil/C-N.
Chile-Argentina
border
S.America
Fig. S3.2.1: Probabilistic forecast of (future) summer 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 summer season, compared to their mean value over the past 30 years.
As the forecast season is summer 2011, this is an example of solar GHI forecast information that could have
been available for use within a decision making process in May 2011.
SUMMER Solar PV Forecasts
(June + July + August)
Europe
W.Great Britain/
S.Norway/
S.Sweden
Africa
Ethiopia W.China
Asia
12. Climate Forecasting Unit
%
Areas of Interest Identified:
(Resources and Forecast Skill)
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 summer 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 summer (Stage
B) and/or lower solar GHI availability and inter-annual variability (Stage A).
Fig. S3.2.1: Probabilistic forecast of (future) summer 2011, solar GHI most likely tercile
(ECMWF S4, 1 month forecast lead time)
SUMMER Solar PV Forecasts
(June + July + August)
S.America
N.Brasil?/
E.Brasil/C-N.
Chile-Argentina
border
S.AmericaEurope
W.Great Britain/
S.Norway/
S.Sweden
Africa
Ethiopia W.China
Asia
13. Climate Forecasting Unit
%
Areas of Interest Identified:
(Resources and Forecast Skill)
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
information 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. S3.2.1: Probabilistic forecast of (future) summer 2011, solar GHI most likely tercile
(ECMWF S4, 1 month forecast lead time)
SUMMER Solar PV Forecasts
(June + July + August)
S.America
N.Brasil?/
E.Brasil/C-N.
Chile-Argentina
border
S.AmericaEurope
W.Great Britain/
S.Norway/
S.Sweden
Africa
Ethiopia W.China
Asia
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)
