Abstract

Abstract. We introduce a new method to detect and monitor sudden stratospheric warming (SSW) events using Global Navigation Satellite System (GNSS) radio occultation (RO) data at high northern latitudes and demonstrate it for the well-known January–February 2009 event. We first construct RO temperature, density, and bending angle anomaly profiles and estimate vertical-mean anomalies in selected altitude layers. These mean anomalies are then averaged into a daily updated 5∘ latitude × 20∘ longitude grid over 50–90∘ N. Based on the gridded mean anomalies, we employ the concept of threshold exceedance areas (TEAs), the geographic areas wherein the anomalies exceed predefined threshold values such as 40 K or 40 %. We estimate five basic TEAs for selected altitude layers and thresholds and use them to derive primary-, secondary-, and trailing-phase TEA metrics to detect SSWs and to monitor in particular their main-phase (primary- plus secondary-phase) evolution on a daily basis. As an initial setting, the main phase requires daily TEAs to exceed 3×106 km2, based on which main-phase duration, area, and overall event strength are recorded. Using the January–February 2009 SSW event for demonstration, and employing RO data plus cross-evaluation data from analysis fields of the European Centre for Medium-Range Weather Forecasts (ECMWF), we find the new approach has strong potential for detecting and monitoring SSW events. The primary-phase metric shows a strong SSW emerging on 20 January, reaching a maximum on 23 January and fading by 30 January. On 22–23 January, temperature anomalies over the middle stratosphere exceeding 40 K cover an area of more than 10×106 km2. The geographic tracking of the SSW showed that it was centered over east Greenland, covering Greenland entirely and extending from western Iceland to eastern Canada. The secondary- and trailing-phase metrics track the further SSW development, where the thermodynamic anomaly propagated downward and was fading with a transient upper stratospheric cooling, spanning until the end of February and beyond. Given the encouraging demonstration results, we expect the method to be very suitable for long-term monitoring of how SSW characteristics evolve under climate change and polar vortex variability, using both RO and reanalysis data.

Highlights

  • Sudden stratospheric warming events (SSWs) are strong and highly dynamic phenomena that often occur in the northern polar stratosphere (McInturff et al, 1978; Butler et al, 2015, Butler et al, 2018)

  • We introduced a new approach to detect and monitor SSW events based on radio occultation (RO) temperature, density, and bending angle anomaly profiles over 50–90◦ N and demonstrated it for the well-known January–February 2009 event

  • Based on constructed anomaly profiles for the three variables temperature, density, and bending angle, we employed the concept of threshold exceedance area (TEA), which is the geographic area wherein absolute or relative anomaly values exceed predefined threshold values, as the basis for formulating SSW metrics

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Summary

Introduction

Sudden stratospheric warming events (SSWs) are strong and highly dynamic phenomena that often occur in the northern polar stratosphere (McInturff et al, 1978; Butler et al, 2015, Butler et al, 2018) Such events are characterized by a rapid increase of temperature (>30 to 40 K) in the middle and upper stratosphere, accompanied by vortex displacements or even splits (Charlton and Polvani, 2007). Past research studies mainly used radiosonde, rocketsonde, conventional satellite, or reanalysis data to study SSWs (McInturff et al, 1978; Charlton and Polvani, 2007; Manney et al, 2008, 2009; Hitchcock and Shepherd, 2013) Both radiosondes and rocketsondes cannot provide evenly distributed observations due to their mostly land-limited properties.

Radio occultation data
ECMWF analysis data
SSW detection and monitoring method
Results and discussion
Polar-cap mean anomalies
Spatial and temporal variations of RO anomalies
SSW detection and monitoring results
Conclusions

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