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Climate Forecasting Unit
SPRING
Seasonal Forecasts for
Global Wind Energy
Melanie Davis, Francisco Doblas-Reyes, Fabian Lienert
Climate Forecasting Unit
Fig. W1.1.1: Spring 10m wind resource (speed, m/s) availability from 1981-2011 (ERA-Interim)
m/s
Stage A: Wind Resource Assessment
Wind energy potential: Where is it the windiest?
Dark red regions of this map show where global 10m wind resource (speed, m/s) 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 Wind Forecasts
(March + April + May)
Climate Forecasting Unit
Fig. W1.1.2: Spring 10m wind resource inter-annual variability from 1981-2011 (ERA-Interim)
m/s
Stage A: Wind Resource Assessment
Wind energy volatility: Where does the wind vary the greatest?
Darker red regions of this map show where global 10m wind resource 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.
SPRING Wind Forecasts
(March + April + May)
Climate Forecasting Unit
Europe
Spring 10m wind resource availability Spring 10m wind resource inter-annual variabilitym/s
m/s
Areas of
interest: Patagonia/
E.Brasil
Central
Sahara/
Sahel
China/
Mongolia/
N. Russia
W.
Australia/
Tasmania
S.America Africa Asia Australia
N.Mexico/
N.Canada
N.America
UK/
Baltic Sea
Stage A: Wind Resource Assessment
Where is wind resource potential and variability (volatility) highest?
By comparing both the spring 10m global wind resource availability and inter-annual variability, it can be seen
that there are several key areas (listed above) where wind speed is both abundant and highly variable.
These regions are most vulnerable to wind resource variability over climate timescales, and are therefore of
greatest interest for seasonal forecasting in spring.
SPRING Wind Forecasts
(March + April + May)
Climate Forecasting Unit
Fig. W2.1.1: Spring 10m wind resource ensemble mean correlation
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
time
windspeed
forecast
+ 1.0
obs. forecast
- 1.0
forecast
example 1
forecast
- 1.0
example 2
example 3
SPRING Wind Forecasts
(March + April + May)
Stage B: Wind Forecast Skill Assessment
1St
validation of the climate forecast system:
The skill of a climate forecast system, to predict global wind speed variability in spring 1 month ahead, is
partially shown in this map. Skill is assessed by comparing the mean of a spring wind 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 wind forecast mean tell us about the
wind resource variability at a specific time?
Climate Forecasting Unit
Fig. W2.1.1: Spring 10m wind speed ensemble mean correlation
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
Stage B: Wind 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 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
SPRING Wind Forecasts
(March + April + May)
Can the wind forecast mean tell us about the
wind resource variability at a specific time?
Climate Forecasting Unit
Fig. W2.1.2: Spring 10m wind resource CR probability skill score
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
time
windspeed
forecast
+ 1.0
obs. forecast
- 1.0
forecast
example 1
forecast
- 1.0
example 2
example 3
Stage B: Wind Forecast Skill Assessment
2nd
validation of the climate forecast system:
The skill of a climate forecast system, to predict global wind resource 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 wind 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).
SPRING Wind Forecasts
(March + April + May)
Perfect
Forecast
Same as
Climatology
Worse
than
Clima-
tology
Can the wind forecast distribution tell us about
the magnitude of the wind resource variability,
and its uncertainty at a specific time?
Climate Forecasting Unit
Fig. W2.1.2: Spring 10m wind resource CR probability skill score
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
Stage B: Wind 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 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”.
SPRING Wind Forecasts
(March + April + May)
Perfect
Forecast
Same as
Climatology
Worse
than
Clima-
tology
Can the wind forecast distribution tell us about
the magnitude of the wind resource variability,
and its uncertainty at a specific time?
Climate Forecasting Unit
Europe
Areas of
interest: E.Brasil/
N.Chile
Indonesia/
W.India
W.
Australia
S.America Africa Asia Australia
Mexico/
S.Canada
N.America
N.Spain/
S.E Europe
Spring 10m wind resource variability
magnitude, and its uncertainty forecast skill
Spring 10m wind resource variability
forecast skill
Wind resource variability
forecast skill only
Wind resource magnitude and its uncertainty forecast skill
Kenya/
Somalia
Stage B: Wind Forecast Skill Assessment Where is wind forecast skill highest?
By comparing both the spring 10m global wind resource forecast skill assessments, it can be seen that there
are several key areas (listed above) where wind resource 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 wind forecasting in spring.
SPRING Wind Forecasts
(March + April + May)
Climate Forecasting Unit
Stage B: Wind Forecast Skill Assessment
Magnitude and uncertainty forecast skillVariability forecast skill
m/sm/sm/s
SPRING Wind Forecasts
These four maps compare the seasonal spring 10m wind resource global forecast skill maps (bottom)
alongside the spring 10m global wind resource availability and inter-annual variability maps (top). It can be
seen that there are several key areas (highlighted above) where the forecast skill is high assessing its
variability, magnitude and uncertainty, and the wind resource is both abundant and highly variable. These
regions demonstrate where spring seasonal wind forecasts have the greatest potential for operational use.
EuropeAreas of
Interest:
(Forecast skill)
E.Brazil
N.Chile
Indonesia/
W.India
W.
S.America Africa Asia Australia
Mexico/
S.Canada
N.America
N.Spain/
S.E Europe
Kenya/
Somalia
Mexico E.Brasil/Mexico/ W.Australia
Europe S.America Africa Asia AustraliaN.America
Patagonia/
E.Brazil
C.Sahara/
Sahel
China/ Mongolia/
N.Russia
W.Australia/
Tasmania
N.Mexico/
N.Canada
UK/
Baltic Sea
Areas of
Interest:
(Resources)
N.Mexico/
E.Brasil
W.Australia
Where is wind resource potential and volatility highest?
Wind resource inter-annual variabilityWind resource availability
Stage A: Wind Resource Assessment
Variability forecast skill
Where is wind forecast skill highest?
SPRING Wind Forecasts
(March + April + May)
Climate Forecasting Unit
%
N.America
MexicoMexico
Areas of Interest Identified:
(Resources and Forecast Skill)
S.America
E.BrasilE.Brasil
W.
Australia
W.Australia
S.America
Fig. W3.1.1: Probabilistic forecast of (future) spring 2011,10m wind resource most likely tercile
(ECMWF S4, 1 month forecast lead time)
Stage C: Operational Wind Forecast
This operational wind forecast shows the probability of global 10m wind resource 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 wind forecast information that could have
been available for use within a decision making process in February 2011.
SPRING Wind Forecasts
(March + April + May)
Climate Forecasting Unit
%
N.America
MexicoMexico
Areas of Interest Identified:
(Resources and Forecast Skill)
S.America
E.BrasilE.Brasil
W.
Australia
W.Australia
S.America
Stage C: Operational Wind Forecast
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 10m wind 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 wind resource availability and inter-annual variability (Stage A).
SPRING Wind Forecasts
(March + April + May)
Fig. W3.1.1: Probabilistic forecast of (future) spring 2011,10m wind resource most likely tercile
(ECMWF S4, 1 month forecast lead time)
Climate Forecasting Unit
%
N.America
MexicoMexico
Areas of Interest Identified:
(Resources and Forecast Skill)
S.America
E.BrasilE.Brasil
W.
Australia
W.Australia
S.America
Stage C: Operational Wind Forecast
This does not mean that the blanked out areas are not useful, only that the operational wind 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 the wind resource for a given region. See the “caveats” webpage for further limitations.
SPRING Wind Forecasts
(March + April + May)
Fig. W3.1.1: Probabilistic forecast of (future) spring 2011,10m wind resource most likely tercile
(ECMWF S4, 1 month forecast lead time)
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)

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20130607 arecs web_forecast_video_spring_wind

  • 1. Climate Forecasting Unit SPRING Seasonal Forecasts for Global Wind Energy Melanie Davis, Francisco Doblas-Reyes, Fabian Lienert
  • 2. Climate Forecasting Unit Fig. W1.1.1: Spring 10m wind resource (speed, m/s) availability from 1981-2011 (ERA-Interim) m/s Stage A: Wind Resource Assessment Wind energy potential: Where is it the windiest? Dark red regions of this map show where global 10m wind resource (speed, m/s) 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 Wind Forecasts (March + April + May)
  • 3. Climate Forecasting Unit Fig. W1.1.2: Spring 10m wind resource inter-annual variability from 1981-2011 (ERA-Interim) m/s Stage A: Wind Resource Assessment Wind energy volatility: Where does the wind vary the greatest? Darker red regions of this map show where global 10m wind resource 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. SPRING Wind Forecasts (March + April + May)
  • 4. Climate Forecasting Unit Europe Spring 10m wind resource availability Spring 10m wind resource inter-annual variabilitym/s m/s Areas of interest: Patagonia/ E.Brasil Central Sahara/ Sahel China/ Mongolia/ N. Russia W. Australia/ Tasmania S.America Africa Asia Australia N.Mexico/ N.Canada N.America UK/ Baltic Sea Stage A: Wind Resource Assessment Where is wind resource potential and variability (volatility) highest? By comparing both the spring 10m global wind resource availability and inter-annual variability, it can be seen that there are several key areas (listed above) where wind speed is both abundant and highly variable. These regions are most vulnerable to wind resource variability over climate timescales, and are therefore of greatest interest for seasonal forecasting in spring. SPRING Wind Forecasts (March + April + May)
  • 5. Climate Forecasting Unit Fig. W2.1.1: Spring 10m wind resource ensemble mean correlation (ECMWF S4, 1 month forecast lead time, once a year from 1981-2010) time windspeed forecast + 1.0 obs. forecast - 1.0 forecast example 1 forecast - 1.0 example 2 example 3 SPRING Wind Forecasts (March + April + May) Stage B: Wind Forecast Skill Assessment 1St validation of the climate forecast system: The skill of a climate forecast system, to predict global wind speed variability in spring 1 month ahead, is partially shown in this map. Skill is assessed by comparing the mean of a spring wind 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 wind forecast mean tell us about the wind resource variability at a specific time?
  • 6. Climate Forecasting Unit Fig. W2.1.1: Spring 10m wind speed ensemble mean correlation (ECMWF S4, 1 month forecast lead time, once a year from 1981-2010) Stage B: Wind 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 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 SPRING Wind Forecasts (March + April + May) Can the wind forecast mean tell us about the wind resource variability at a specific time?
  • 7. Climate Forecasting Unit Fig. W2.1.2: Spring 10m wind resource CR probability skill score (ECMWF S4, 1 month forecast lead time, once a year from 1981-2010) time windspeed forecast + 1.0 obs. forecast - 1.0 forecast example 1 forecast - 1.0 example 2 example 3 Stage B: Wind Forecast Skill Assessment 2nd validation of the climate forecast system: The skill of a climate forecast system, to predict global wind resource 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 wind 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). SPRING Wind Forecasts (March + April + May) Perfect Forecast Same as Climatology Worse than Clima- tology Can the wind forecast distribution tell us about the magnitude of the wind resource variability, and its uncertainty at a specific time?
  • 8. Climate Forecasting Unit Fig. W2.1.2: Spring 10m wind resource CR probability skill score (ECMWF S4, 1 month forecast lead time, once a year from 1981-2010) Stage B: Wind 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 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”. SPRING Wind Forecasts (March + April + May) Perfect Forecast Same as Climatology Worse than Clima- tology Can the wind forecast distribution tell us about the magnitude of the wind resource variability, and its uncertainty at a specific time?
  • 9. Climate Forecasting Unit Europe Areas of interest: E.Brasil/ N.Chile Indonesia/ W.India W. Australia S.America Africa Asia Australia Mexico/ S.Canada N.America N.Spain/ S.E Europe Spring 10m wind resource variability magnitude, and its uncertainty forecast skill Spring 10m wind resource variability forecast skill Wind resource variability forecast skill only Wind resource magnitude and its uncertainty forecast skill Kenya/ Somalia Stage B: Wind Forecast Skill Assessment Where is wind forecast skill highest? By comparing both the spring 10m global wind resource forecast skill assessments, it can be seen that there are several key areas (listed above) where wind resource 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 wind forecasting in spring. SPRING Wind Forecasts (March + April + May)
  • 10. Climate Forecasting Unit Stage B: Wind Forecast Skill Assessment Magnitude and uncertainty forecast skillVariability forecast skill m/sm/sm/s SPRING Wind Forecasts These four maps compare the seasonal spring 10m wind resource global forecast skill maps (bottom) alongside the spring 10m global wind resource availability and inter-annual variability maps (top). It can be seen that there are several key areas (highlighted above) where the forecast skill is high assessing its variability, magnitude and uncertainty, and the wind resource is both abundant and highly variable. These regions demonstrate where spring seasonal wind forecasts have the greatest potential for operational use. EuropeAreas of Interest: (Forecast skill) E.Brazil N.Chile Indonesia/ W.India W. S.America Africa Asia Australia Mexico/ S.Canada N.America N.Spain/ S.E Europe Kenya/ Somalia Mexico E.Brasil/Mexico/ W.Australia Europe S.America Africa Asia AustraliaN.America Patagonia/ E.Brazil C.Sahara/ Sahel China/ Mongolia/ N.Russia W.Australia/ Tasmania N.Mexico/ N.Canada UK/ Baltic Sea Areas of Interest: (Resources) N.Mexico/ E.Brasil W.Australia Where is wind resource potential and volatility highest? Wind resource inter-annual variabilityWind resource availability Stage A: Wind Resource Assessment Variability forecast skill Where is wind forecast skill highest? SPRING Wind Forecasts (March + April + May)
  • 11. Climate Forecasting Unit % N.America MexicoMexico Areas of Interest Identified: (Resources and Forecast Skill) S.America E.BrasilE.Brasil W. Australia W.Australia S.America Fig. W3.1.1: Probabilistic forecast of (future) spring 2011,10m wind resource most likely tercile (ECMWF S4, 1 month forecast lead time) Stage C: Operational Wind Forecast This operational wind forecast shows the probability of global 10m wind resource 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 wind forecast information that could have been available for use within a decision making process in February 2011. SPRING Wind Forecasts (March + April + May)
  • 12. Climate Forecasting Unit % N.America MexicoMexico Areas of Interest Identified: (Resources and Forecast Skill) S.America E.BrasilE.Brasil W. Australia W.Australia S.America Stage C: Operational Wind Forecast 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 10m wind 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 wind resource availability and inter-annual variability (Stage A). SPRING Wind Forecasts (March + April + May) Fig. W3.1.1: Probabilistic forecast of (future) spring 2011,10m wind resource most likely tercile (ECMWF S4, 1 month forecast lead time)
  • 13. Climate Forecasting Unit % N.America MexicoMexico Areas of Interest Identified: (Resources and Forecast Skill) S.America E.BrasilE.Brasil W. Australia W.Australia S.America Stage C: Operational Wind Forecast This does not mean that the blanked out areas are not useful, only that the operational wind 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 the wind resource for a given region. See the “caveats” webpage for further limitations. SPRING Wind Forecasts (March + April + May) Fig. W3.1.1: Probabilistic forecast of (future) spring 2011,10m wind resource most likely tercile (ECMWF S4, 1 month forecast lead time)
  • 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)