Mapping users' expectations regarding extended-range forecasts

Ervasti, Tiina; Gregow, Hilppa; Vajda, Andrea; Laurila, Terhi K.; Mäkelä, Antti

doi:10.5194/asr-15-99-2018

Cited by 6 publications

(9 citation statements)

References 8 publications

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“…As the ensemble size of the reforecasts, m, was only 11, and the ensemble size of the operational forecasts of the ECMWF's IFS, M, was 51, the expected CRPS, namely the CRPS RF of the ECMWF's reforecast was calculated for 51 members using Eq. (26) in Ferro et al (2008) as follows:…”

Section: Skill Scores Of the Forecastsmentioning

confidence: 99%

“…In an academic project called the CLImate services supporting Public mobility and Safety (CLIPS), climatic impact outlooks and early warnings of extremes (i.e. CLIPS forecasts) were developed by employing the ERF data sets (Ervasti et al, 2018). The CLIPS forecasts were co-designed with the general public in Finland and experimented with during a 1 year pilot phase.…”

Section: Introductionmentioning

confidence: 99%

“…As many industries, e.g. energy and food production, and users from the general public considered that they could use and would benefit from reliable ERFs (Ervasti et al, 2018), the development of more skilful ERFs is clearly needed.…”

Section: Introductionmentioning

confidence: 99%

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Adding value to extended-range forecasts in northern Europe by statistical post-processing using stratospheric observations

et al. 2020

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Abstract. The strength of the stratospheric polar vortex influences the surface weather in the Northern Hemisphere in winter; a weaker (stronger) than average stratospheric polar vortex is connected to negative (positive) Arctic Oscillation (AO) and colder (warmer) than average surface temperatures in northern Europe within weeks or months. This holds the potential for forecasting in that timescale. We investigate here if the strength of the stratospheric polar vortex at the start of the forecast could be used to improve the extended-range temperature forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) and to find periods with higher prediction skill scores. For this, we developed a stratospheric wind indicator (SWI) based on the strength of the stratospheric polar vortex and the phase of the AO during the following weeks. We demonstrate that there was a statistically significant difference in the observed surface temperature in northern Europe within the 3–6 weeks, depending on the SWI at the start of the forecast. When our new SWI was applied in post-processing the ECMWF's 2-week mean temperature reforecasts for weeks 3–4 and 5–6 in northern Europe during boreal winter, the skill scores of those weeks were slightly improved. This indicates there is some room for improving the extended-range forecasts, if the stratosphere–troposphere links were better captured in the modelling. In addition to this, we found that during the boreal winter, in cases where the polar vortex was weak at the start of the forecast, the mean skill scores of the 3–6 weeks' surface temperature forecasts were higher than average.

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Section: Skill Scores Of the Forecastsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Adding value to extended-range forecasts in northern Europe by statistical post-processing using stratospheric observations

et al. 2020

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“…The CLIPS forecasts were co-designed with the general public in Finland and experimented during a one year living lab. As many industries, e.g., energy and food production as well as users from the general public considered they could use and would benefit from reliable ERFs (Ervasti et al 2018), development of more skillful ERFs is clearly needed.…”

mentioning

confidence: 99%

Adding value to Extended-range Forecasts in Northern Europe by Statistical Post-processing Using Stratospheric Observations

Korhonen¹,

Hyvärinen²,

Kämäräinen³

et al. 2019

Preprint

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Abstract. The skill scores of the Extended-Range Forecasts (ERF) of the European Centre for Medium-Range Weather Forecasts (ECMWF) are still quite modest for the forecast weeks 3–6 in Northern Europe. As there are known stratospheric precursors impacting the surface weather with potential to improve ERFs, we aim to quantify the effect of these predictors and post-process the ERFs with them. During boreal winter the quasi-biennial oscillation (QBO) affects the stratospheric polar vortex; the easterly (westerly) QBO often coincides with weaker (stronger) than average polar vortex. Consequently, the weaker (stronger) than average stratospheric polar vortex is connected to negative (positive) Arctic Oscillation (AO) and colder (warmer) than average surface temperatures in Northern Europe. We developed a stratospheric wind indicator, SWI, based on the previous months' stratospheric wind observations and the phase of the AO during the following weeks. We demonstrate that there was a statistically significant difference in the observed surface temperature within the 3–6 weeks depending on the SWI at the start of the forecast. These temperature anomalies were underestimated by the ECMWF's reforecasts. When our new SWI was applied in post-processing the ECMWF's two-week mean temperature reforecasts for weeks 3–4 and weeks 5–6 in Northern Europe during boreal winter, the skill scores of those weeks were slightly improved. This indicates there is some room to improve the ERFs, if the stratosphere-troposphere links were better captured in the modelling.

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“…warnings of extremes (CLIPS forecasts) were developed by employing the ERF datasets (Ervasti et al 2018). The CLIPS forecasts were co-designed with the general public in Finland and experimented during a one year living lab.…”

Section: Simulation Of the European Population 30-13 Ky Ago Using Largermentioning

confidence: 99%

Assessing Impacts of Climate Variations and Change on Different Time Scales

Korhonen¹

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Climate change refers to a change in the mean state of the climate that persists for an extended period, typically 30 years or longer. The natural inter-annual variability of climate refers to internal variation of the climate system in shorter timescales. In this thesis I have studied the climate of the last glacial and its impact on human population sizes in Europe during the end of the last glaciation, the change in forest fire danger and strong winds in Europe under the ongoing human-induced climate change, and the relationship between the stratospheric winds and the phase of the Arctic Oscillation in present climate. A regression model was developed to downscale low-resolution dynamical EMIC simulations to regional scale. The regression model was calibrated by gridded data of regional scale resolution observations of present day climate and simulations of glacial climate. The downscaled climate was used in estimating the size of human population in Europe during the end of the last glaciation, between 30,000 and 13,000 years ago. The simulated changes in human population size correlated significantly with an independent archeological data of changes in human population size. The change in the forest fire danger in Europe was investigated by ERA-Interim and ERA-40 reanalysis. The forest fire danger was found to have increased in Southern and Eastern Europe during the period 1980-2012, whilst no significant trend was found elsewhere in Europe. The projected changes in the geostrophic wind speeds under human-induced climate change in Northern Europe during the current century were explored from simulations of nine general circulation models. According to the simulations, the changes in mean and extreme wind speeds are going to be small; in parts of northwestern Russia and southern Baltic Sea the winds might increase by 2-4% and over the Norwegian Sea the winds might decrease by 2-8%. In this thesis the connection between the stratospheric winds and surface Arctic Oscillation was studied statistically. The found stratospheric connection was applied in post-processing the European Centre for Medium-Range Weather Forecasts two-week mean temperature reforecasts for weeks 3-4 and weeks 5-6 in Northern Europe during boreal winter, and the skill scores of those weeks were slightly improved.

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Mapping users' expectations regarding extended-range forecasts

Cited by 6 publications

References 8 publications

Adding value to extended-range forecasts in northern Europe by statistical post-processing using stratospheric observations

Adding value to extended-range forecasts in northern Europe by statistical post-processing using stratospheric observations

Adding value to Extended-range Forecasts in Northern Europe by Statistical Post-processing Using Stratospheric Observations

Assessing Impacts of Climate Variations and Change on Different Time Scales

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