Toward a Polarimetric Radar Classification Scheme for Coalescence Dominant Precipitation: Application to Complex Terrain

Toward a Polarimetric Radar Classification Scheme for Coalescence Dominant Precipitation:... AbstractAccurate quantitative precipitation estimation over mountainous basins is of great importance because of their susceptibility to natural hazards. It is generally difficult to obtain reliable precipitation information over complex areas, due to the scarce coverage of ground observations, the limited coverage from operational radar networks and high elevation of the study sites. Warm-rain processes have been observed in several flash flood events in complex terrain regions. While they lead to high rainfall rates from precipitation growth due to collision-coalescence of droplets in the cloud liquid layer, their characteristics are often difficult to identify. X-band mobile dual-polarization radars located in complex terrain areas provide fundamental information at high-resolution and at low atmospheric levels. This study analyzes a dataset collected during the IPHEx (North Carolina, US) field campaign in 2014 over a mountainous basin where the NOAA/National Severe Storm Laboratory's NOXP X-band dual-polarization radar was deployed. Polarimetric variables are used to isolate collision-coalescence microphysical processes. This work lays the basis for classification algorithms able to identify coalescence dominant precipitation by merging the information coming from polarimetric radar measurements. The sensitivity of the proposed classification scheme is tested with different rainfall rate retrieval algorithms and compared to rain gauge observations. Results show the inadequacy of rainfall estimates when coalescence identification is not taken into account. This work highlights the necessity of a correct classification of collision-coalescence processes, which can lead to improvements in quantitative precipitation estimation. Future studies will aim at generalizing this scheme making use of space-borne radar data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Hydrometeorology American Meteorological Society

Toward a Polarimetric Radar Classification Scheme for Coalescence Dominant Precipitation: Application to Complex Terrain

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1525-7541
D.O.I.
10.1175/JHM-D-17-0016.1
Publisher site
See Article on Publisher Site

Abstract

AbstractAccurate quantitative precipitation estimation over mountainous basins is of great importance because of their susceptibility to natural hazards. It is generally difficult to obtain reliable precipitation information over complex areas, due to the scarce coverage of ground observations, the limited coverage from operational radar networks and high elevation of the study sites. Warm-rain processes have been observed in several flash flood events in complex terrain regions. While they lead to high rainfall rates from precipitation growth due to collision-coalescence of droplets in the cloud liquid layer, their characteristics are often difficult to identify. X-band mobile dual-polarization radars located in complex terrain areas provide fundamental information at high-resolution and at low atmospheric levels. This study analyzes a dataset collected during the IPHEx (North Carolina, US) field campaign in 2014 over a mountainous basin where the NOAA/National Severe Storm Laboratory's NOXP X-band dual-polarization radar was deployed. Polarimetric variables are used to isolate collision-coalescence microphysical processes. This work lays the basis for classification algorithms able to identify coalescence dominant precipitation by merging the information coming from polarimetric radar measurements. The sensitivity of the proposed classification scheme is tested with different rainfall rate retrieval algorithms and compared to rain gauge observations. Results show the inadequacy of rainfall estimates when coalescence identification is not taken into account. This work highlights the necessity of a correct classification of collision-coalescence processes, which can lead to improvements in quantitative precipitation estimation. Future studies will aim at generalizing this scheme making use of space-borne radar data.

Journal

Journal of HydrometeorologyAmerican Meteorological Society

Published: Oct 16, 2017

References

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