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