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

Natalia Korhonen,David S Richardson,Matti Kämäräinen,Hilppa Gregow,Heikki Järvinen,Otto Hyvärinen

doi:10.5194/acp-20-8441-2020

Abstract

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.

Highlights

Extended-range forecasts (ERFs; lead time up to 46 d) by dynamical models have been developed since the 1990s with the aim to fill the gap between the medium-range weather forecasts and the seasonal forecasts
We study the mean surface temperature anomalies observed in northern Europe at 1–2, 3–4, and 5–6 weeks after SWI was defined as negative (SWIneg) in comparison to SWIplain, and we utilise these anomalies in postprocessing the temperature forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) reforecasts
Based on ECMWF’s extended-range reforecasts for the period 1997–2016, we found that the weekly mean surface temperature forecasts over northern Europe were, on average, significantly better than just the climatological forecast in weeks 1–6, in weeks 4–6, the CRPSSs were quite low and mostly between 0 and 0.1

Summary

Introduction

Extended-range forecasts (ERFs; lead time up to 46 d) by dynamical models have been developed since the 1990s with the aim to fill the gap between the medium-range weather forecasts and the seasonal forecasts. It is known that ERF skills are still rather modest in forecast weeks 3–6 especially in the northern latitudes. If the skill of the forecasts improves, ERFs have the potential to become an essential element in climate services, for example, in the form of early warnings of climatic extremes. 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. 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

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Conclusion