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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 7, issue 6
Atmos. Meas. Tech., 7, 1605–1617, 2014
https://doi.org/10.5194/amt-7-1605-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Atmos. Meas. Tech., 7, 1605–1617, 2014
https://doi.org/10.5194/amt-7-1605-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 06 Jun 2014

Research article | 06 Jun 2014

The large-scale spatio-temporal variability of precipitation over Sweden observed from the weather radar network

A. Devasthale and L. Norin A. Devasthale and L. Norin
  • Atmospheric Remote Sensing Unit, Research and Development Department, Swedish Meteorological and Hydrological Institute (SMHI), Norrköping, Sweden

Abstract. Using measurements from the national network of 12 weather radar stations for the 11-year period 2000–2010, we investigate the large-scale spatio-temporal variability of precipitation over Sweden. These statistics provide useful information to evaluate regional climate models as well as for hydrology and energy applications. A strict quality control is applied to filter out noise and artifacts from the radar data. We focus on investigating four distinct aspects: the diurnal cycle of precipitation and its seasonality, the dominant timescale (diurnal versus seasonal) of variability, precipitation response to different wind directions, and the correlation of precipitation events with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO). When classified based on their intensity, moderate- to high-intensity events (precipitation > 0.34 mm/3 h) peak distinctly during late afternoon over the majority of radar stations in summer and during late night or early morning in winter. Precipitation variability is highest over the southwestern parts of Sweden. It is shown that the high-intensity events (precipitation > 1.7 mm/3 h) are positively correlated with NAO and AO (esp. over northern Sweden), while the low intensity events are negatively correlated (esp. over southeastern parts). It is further observed that southeasterly winds often lead to intense precipitation events over central and northern Sweden, while southwesterly winds contribute most to the total accumulated precipitation for all radar stations. Apart from its operational applications, the present study demonstrates the potential of the weather radar data set for studying climatic features of precipitation over Sweden.

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