Abstract

Weather forecasting in the Southern Ocean and Antarctica is a challenge above all due to the rarity of observations to be assimilated in numerical weather prediction (NWP) models. As observations are expensive and logistically challenging, it is important to evaluate the benefit that additional observations could bring to NWP. Atmospheric soundings applying unmanned aerial vehicles (UAVs) have a large potential to supplement conventional radiosonde sounding observations. Here, we applied UAV and radiosonde sounding observations from an RV Polarstern cruise in the ice-covered Weddell Sea in austral winter 2013 to evaluate the impact of their assimilation in the Polar version of the Weather Research and Forecasting (Polar WRF) model. Our experiments revealed small to moderate impacts of radiosonde and UAV data assimilation. In any case, the assimilation of sounding data from both radiosondes and UAVs improved the analyses of air temperature, wind speed, and humidity at the observation site for most of the time. Further, the impact on the results of 5-day-long Polar WRF experiments was often felt over distances of at least 300 km from the observation site. All experiments succeeded in capturing the main features of the evolution of near-surface variables, but the effects of data assimilation varied between different cases. Due to the limited vertical extent of the UAV observations, the impact of their assimilation was limited to the lowermost 1–2-km layer, and assimilation of radiosonde data was more beneficial for modeled sea level pressure and near-surface wind speed.

Highlights

  • Observations from the Southern Ocean and AntarcticaASSIMILATION OF SOUNDING DATA IN POLAR Weather Research and Forecasting (WRF)VOLUME 37 the profiles of atmospheric pressure, temperature, moisture and wind

  • Results for mean sea level pressure (MSLP) are slightly positively impacted by assimilation of small unmanned meteorological observer (SUMO) observations in the three cases compared with CTRL (Fig. 3, second row; blue dots indicate the SUMO observation times)

  • SUMOE and RSE are slightly better than CTRL in the simulation of relative and specific humidity, especially at times when observations are assimilated

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Summary

Introduction

VOLUME 37 the profiles of atmospheric pressure, temperature, moisture and wind. These are important for initialization of NWP models (Bromwich et al, 2005), for which near-surface observations from weather stations and buoys alone are not sufficient. Sato et al (2017) showed that campaign-based radiosonde observations from the Arctic, assimilated in an NWP model, reduced analysis errors in the upper troposphere, and improved forecast skill and reduced uncertainties of predicted weather extremes in remote locations. Benefits from assimilation of radiosonde and wind profiler data have been detected for short-range forecasts for Central Europe (Federico, 2013), and studies on temperature and humidity retrievals from satellite and ground-based microwave radiometers and their assimilation into NWP system have been made (e.g., Knupp et al, 2009; Guedj et al, 2010; Caumont et al, 2016). The aim of this study was to find out, for the first time, what the benefit is of radiosonde and UAV observations for an NWP model over the Southern Ocean in winter

SUMO soundings
Radiosonde soundings on Polarstern
Observations from automatic weather stations
Polar WRF model
Data assimilation strategy
Impacts on local analyses
Impacts on the 5-day model experiments along the track of RV Polarstern
Impacts on model results on the regional scale
Discussion and conclusions
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