Beyond skill scores: exploring sub‐seasonal forecast value through a case‐study of French month‐ahead energy prediction

Dorrington, Joshua; Finney, Isla; Palmer, Tim; Weisheimer, Antje

doi:10.1002/qj.3863

Cited by 15 publications

(9 citation statements)

References 29 publications

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“…Although the approach for calculating the model climatology is different from the one used for the ERA‐Interim climatology (using ensemble mean instead of running mean), it allows for a similarly strong smoothing and eliminates (lead‐time‐dependent) model drifts. In this study, we focus on month‐ahead anomalies as a particularly relevant time‐scale for the energy industry (e.g., Dorrington et al ., 2020). In addition, predictability on sub‐seasonal time‐scales is generally higher for temporally and spatially aggregated fields compared to instantaneous fields (e.g., Buizza and Leutbecher, 2015).…”

Section: Methodsmentioning

confidence: 99%

Stratospheric influence on ECMWF sub‐seasonal forecast skill for energy‐industry‐relevant surface weather in European countries

Büeler

Beerli

Wernli

et al. 2020

Quart J Royal Meteoro Soc

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Meteorologists in the energy industry increasingly draw upon the potential for enhanced sub-seasonal predictability of European surface weather following anomalous states of the winter stratospheric polar vortex (SPV). How the link between the SPV and the large-scale tropospheric flow translates into forecast skill for surface weather in individual countries-a spatial scale that is particularly relevant for the energy industry-remains an open question. Here we quantify the effect of anomalously strong and weak SPV states at forecast initial time on the probabilistic extended-range reforecast skill of the European Centre for Medium-Range Weather Forecasts (ECMWF) in predicting countryand month-ahead-averaged anomalies of 2 m temperature, 10 m wind speed, and precipitation. After anomalous SPV states, specific surface weather anomalies emerge, which resemble the opposing phases of the North Atlantic Oscillation. We find that forecast skill is, to first order, only enhanced for countries that are entirely affected by these anomalies. However, the model has a flow-dependent bias for 2 m temperature (T2M): it predicts the warm conditions in Western, Central and Southern Europe following strong SPV states well, but is overconfident with respect to the warm anomaly in Scandinavia. Vice versa, it predicts the cold anomaly in Scandinavia following weak SPV states well, but struggles to capture the strongly varying extent of the cold air masses into Central and Southern Europe. This tends to reduce skill (in some cases significantly) for Scandinavian countries following strong SPV states, and most pronounced, for many Central, Southern European, and Balkan countries following weak SPV states. As most of the weak SPV states are associated with sudden stratospheric warmings (SSWs), our study thus advices particular caution when interpreting sub-seasonal regional T2M forecasts following SSWs. In contrast, it suggests that the model benefits from enhanced predictability for a considerable part of Europe following strong SPV states.

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Section: Methodsmentioning

confidence: 99%

Stratospheric influence on ECMWF sub‐seasonal forecast skill for energy‐industry‐relevant surface weather in European countries

Büeler

Beerli

Wernli

et al. 2020

Quart J Royal Meteoro Soc

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“…A long-term ambition is to exploit microbarom infrasound datasets to enhance the representation of stratospheric dynamics in atmospheric model products and hence increase the accuracy of both medium-range weather forecasting and sub-seasonal climate modeling (Büeler et al, 2020;Dorrington et al, 2020;Domeisen et al, 2020a, b). In addition to prospective numerical weather prediction improvements, the suggested vespagram-based approach may be applied in multi-technology studies of atmospheric dynamics, for example initiatives building on the Atmospheric dynamics Research InfraStructure in Europe (ARISE) projects (Blanc et al, 2018(Blanc et al, , 2019.…”

Section: 2)mentioning

confidence: 99%

Microbarom radiation and propagation model assessment using infrasound recordings: a vespagram-based approach

Vorobeva

Carlo

Pichon

et al. 2020

Preprint

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Abstract. This study investigates the use of a vespagram-based approach as a tool for multi-directional comparison between simulated microbarom soundscapes and infrasound data recorded at ground-based array stations. Data recorded at the IS37 station in northern Norway during 2014–2019 have been processed to generate vespagrams (velocity spectral analysis) for five frequency bands between 0.1 and 0.6 Hz. The back-azimuth resolution between vespagrams and a microbarom model is harmonized by smoothing the modelled soundscapes along the back-azimuth axis with a kernel corresponding to the frequency-dependent array resolution. An estimate of similarity between the output of a microbarom radiation and propagation model and infrasound observations is then generated based on the image processing approach of mean-square difference. The analysis revealed that vespagrams can monitor seasonal variations in the microbarom azimuth distribution, amplitude, and frequency, as well as changes during sudden stratospheric warming. The vespagram-based approach is computationally inexpensive, can uncover microbarom source variability, and has potential for near-real-time stratospheric diagnostics and atmospheric model assessment.

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“…This is possibly consistent with the perceived difficulty of extracting predictable signals from extended-range forecasts (Soares and Dessai, 2016). However, recent advances in forecasting have begun to result in skilful longer-range predictions for European demand (De Felice et al, 2015;Clark et al, 2017;Thornton et al, 2019;Dorrington et al, 2020), wind power generation (Lynch et al, 2014;Beerli et al, 2017;Soret et al, 2019;Torralba et al, 2017;Lledó et al, 2019;Bett et al, 2019;Lee et al, 2019), solar power generation (Bett et al, 2019) and hydropower generation (Arnal et al, 2018), which can consequently lead to improvements in awareness, preparedness and decision-making from a user perspective (Goodess et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Sub-seasonal forecasts of demand and wind power and solar power generation for 28 European countries

Bloomfield

Brayshaw

Gonzalez

et al. 2021

Earth Syst. Sci. Data

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Abstract. Electricity systems are becoming increasingly exposed to weather. The need for high-quality meteorological forecasts for managing risk across all timescales has therefore never been greater. This paper seeks to extend the uptake of meteorological data in the power systems modelling community to include probabilistic meteorological forecasts at sub-seasonal lead times. Such forecasts are growing in skill and are receiving considerable attention in power system risk management and energy trading. Despite this interest, these forecasts are rarely evaluated in power system terms, and technical barriers frequently prohibit use by non-meteorological specialists. This paper therefore presents data produced through a new EU climate services programme Subseasonal-to-seasonal forecasting for Energy (S2S4E). The data correspond to a suite of well-documented, easy-to-use, self-consistent daily and nationally aggregated time series for wind power, solar power and electricity demand across 28 European countries. The data are accessible from https://doi.org/10.17864/1947.275 (Gonzalez et al., 2020). The data include a set of daily ensemble reforecasts from two leading forecast systems spanning 20 years (ECMWF, an 11-member ensemble, with twice-weekly starts for 1996–2016, totalling 22 880 forecasts) and 11 years (NCEP, a 12-member lagged-ensemble, constructed to match the start dates from the ECMWF forecast from 1999–2010, totalling 14 976 forecasts). The reforecasts contain multiple plausible realisations of daily weather and power data for up to 6 weeks in the future. To the authors’ knowledge, this is the first time a fully calibrated and post-processed daily power system forecast set has been published, and this is the primary purpose of this paper. A brief review of forecast skill in each of the individual primary power system properties and a composite property is presented, focusing on the winter season. The forecast systems contain additional skill over climatological expectation for weekly-average forecasts at extended lead times, though this skill depends on the nature of the forecast metric considered. This highlights the need for greater collaboration between the energy and meteorological research communities to develop applications, and it is hoped that publishing these data and tools will support this.

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Beyond skill scores: exploring sub‐seasonal forecast value through a case‐study of French month‐ahead energy prediction

Cited by 15 publications

References 29 publications

Stratospheric influence on ECMWF sub‐seasonal forecast skill for energy‐industry‐relevant surface weather in European countries

Stratospheric influence on ECMWF sub‐seasonal forecast skill for energy‐industry‐relevant surface weather in European countries

Microbarom radiation and propagation model assessment using infrasound recordings: a vespagram-based approach

Sub-seasonal forecasts of demand and wind power and solar power generation for 28 European countries

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