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

Abstract

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.

Assimilation of atmospheric infrasound data to constrain tropospheric and stratospheric winds

“…Moreover, the lid of several atmospheric model products has been raised into the mesosphere (Polavarapu et al, 2005) and it has been demonstrated that this can improve numerical weather and climate models (Orsolini et al, 2011;Charlton-Perez et al, 2013;Kidston et al, 2015). But the full potential of high-top models can only be unlocked if middle atmospheric winds are better represented (Baker et al, 2014;Korhonen et al, 2019;Lee et al, 2019). Hence, it is timely to explore novel datasets and assimilation approaches that can constrain the upper-stratospheric dynamics in atmospheric model products.…”

Review of nhess-2024-75

“…The data of Figs. 1-6 are available at https://fmi.b2share.csc.fi/records/8ceb3da6ce144180b5304ad080af88af (Korhonen, 2024).…”

Assimilating atmospheric infrasound data to constrain atmospheric winds in a two‐dimensional grid

“…However, the observational coverage of these two layers is nowhere near as dense as that of the troposphere. Some of the largest uncertainties in current reanalyses occur in these levels, leading the wind representation of mesospheric winds to lag behind other areas (Baker et al, 2014;Korhonen et al, 2019). For instance, Duruisseau et al (2017) compared high-altitude (pressure less than 20 hPa) ERA-Interim values against wind measurements taken from a balloon radiosonde and noted that the standard deviations of the differences were greater than 5 m⋅s −1 in some cases.…”