20130607 arecs web_forecast_video_spring_wind

Climate Forecasting Unit

SPRINGSeasonal Forecasts for

Global Wind Energy Melanie Davis, Francisco Doblas-Reyes, Fabian Lienert


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)


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.



Europe

Spring 10m wind resource availability Spring 10m wind resource inter-annual variabilitym/sm/s

Areas of interest: Patagonia/

E.BrasilCentral 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.



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

wind speed

forecast + 1.0

obs. forecast - 1.0

forecast example 1

forecast - 1.0

example 2

example 3


Stage B: Wind Forecast Skill Assessment1St 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?


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 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 wind forecast mean tell us about the wind resource variability at a specific time?


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

wind speed

forecast + 1.0

obs. forecast - 1.0

forecast example 1

forecast - 1.0

example 2

example 3

Stage B: Wind Forecast Skill Assessment2nd 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).


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?


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 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 wind forecast distribution tell us about the magnitude of the wind resource variability, and its uncertainty at a specific time?


EuropeAreas of interest: E.Brasil/

N.ChileIndonesia/W.India

W. 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.



Stage B: Wind Forecast Skill AssessmentMagnitude 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.BrazilN.Chile

Indonesia/W.India

W.


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 variability Wind resource availabilityStage A: Wind Resource Assessment

Variability forecast skillWhere is wind forecast skill highest?



%

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.



%

N.America

MexicoMexico


S.America

E.BrasilE.Brasil

W.

Australia

W.Australia

S.America


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).




%

N.America

MexicoMexico


S.America

E.BrasilE.Brasil

W.

Australia

W.Australia

S.America


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.




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