measuring the benefits of climate forecasts

Measuring the skill benefits of climate forecasts in predicting

PV power productionMatteo De Felice, Andrea Alessandri and Maurizio

Pollino

Solar Power and Climate• Today we have plenty of weather/climate datasets of

solar radiation (satellites, reanalyses, NWP, climate forecasts)

• Here we focus on seasonal predictability of solar radiation

• The aim of this paper is an assessment of the skills of seasonal forecasts to predict solar radiation over Europe

• May the information provided by climate forecasts help the solar power sector to improve their decision-making?

EGU2016-18336 - Climate Services - Underpinning Science Session

Skill of seasonal forecasts

ECMWF System4 vs Heliosat (SARAH) - Summer, 1983-2013

EGU2016-18336 - Climate Services - Underpinning Science Session

Is this enough?

More information sources

• Skill of seasonal forecasts in predicting PV power output

• PV Solar Installed capacity

• Solar radiation inter-annual variability

• Using land-cover to mask areas not-suitable for PV

EGU2016-18336 - Climate Services - Underpinning Science Session

Measuring the benefitsEGU2016-18336 - Climate Services - Underpinning Science Session

And now the long story…

What is a good forecast?Allan Murphy in 1993 categorised the “goodness” of a forecast in…

1 Consistency Correspondence between forecasts and judgements

2 Quality Correspondence between forecasts and observations

3 Value Incremental benefits of forecasts to users

EGU2016-18336 - Climate Services - Underpinning Science Session

“Quality” means “value”?

• A. Murphy underlined that forecasts do not have an intrinsic value but instead they gain it when they have a positive influence on on the decisions made by users of the forecasts.

• Value of a forecast is strictly linked with its quality but their relationship is rarely linear

EGU2016-18336 - Climate Services - Underpinning Science Session

Information layersHere we assume that the benefit of a climate forecast of solar power is affected by the following three factors:

1. Statistical Skill (e.g. BSS): the more the better

2. Installed Capacity: good forecast will have a greater impact in areas with high installed capacity

3. Inter-annual variability: a forecast can help to cope with the high variability of solar radiation

EGU2016-18336 - Climate Services - Underpinning Science Session

(1/3) Statistical skill

ECMWF System4 vs Heliosat (SARAH)

1983-2013 Lower tercile upper part: DJF - MAM lower part: JJA - SON

EGU2016-18336 - Climate Services - Underpinning Science Session

(1/3) Statistical skill

ECMWF System4 vs Heliosat (SARAH)

1983-2013 Upper tercile upper part: DJF - MAM lower part: JJA - SON

EGU2016-18336 - Climate Services - Underpinning Science Session

(1/3) Statistical skill

Modelled PV production of ECMWF System4 vs

Heliosat (SARAH) + EOBS

1983-2013 Lower tercile upper part: DJF - MAM lower part: JJA - SON

EGU2016-18336 - Climate Services - Underpinning Science Session

(1/3) Statistical skill

Modelled PV production of ECMWF System4 vs

Heliosat (SARAH) + EOBS

1983-2013 Upper tercile upper part: DJF - MAM lower part: JJA - SON

EGU2016-18336 - Climate Services - Underpinning Science Session

PV Suitability• Map of suitability of PV

derived by the work by Hansen & Thorn (PV potential and potential PV rent in European regions)

• Based on the Corine Land Cover 2006 (CLC2006)

• Used to mask out grid points from analysis

EGU2016-18336 - Climate Services - Underpinning Science Session

(2/3) Installed Capacity• PV cumulative installed capacity in 2014 (Data

extrapolated from the Solar-Power Europe Global Market Outlook)

EGU2016-18336 - Climate Services - Underpinning Science Session

(3/3) Inter-annual variability

Relative Std. Dev. Heliosat (SARAH)

1983-2013 Lower tercile upper part: DJF - MAM lower part: JJA - SON

EGU2016-18336 - Climate Services - Underpinning Science Session

(3/3) Inter-annual variability

Relative Std. Dev. Heliosat (SARAH)

1983-2013 Lower tercile upper part: DJF - MAM lower part: JJA - SON

EGU2016-18336 - Climate Services - Underpinning Science Session

Putting things togetherA matrix of this type should be designed in

collaboration with the end-user

EGU2016-18336 - Climate Services - Underpinning Science Session

Measuring the benefitsEGU2016-18336 - Climate Services - Underpinning Science Session

Comments

• We should focus not only on skill but on all the factors influencing the decisions

• When providing a service focus on value and not (only) on quality

EGU2016-18336 - Climate Services - Underpinning Science Session