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An Objective High-Resolution Hail Climatology of the Contiguous United States

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  • 1 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and National Severe Storms Laboratory, Norman, Oklahoma
  • | 2 National Severe Storms Laboratory, Norman, Oklahoma
  • | 3 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and National Severe Storms Laboratory, Norman, Oklahoma
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Abstract

The threat of damaging hail from severe thunderstorms affects many communities and industries on a yearly basis, with annual economic losses in excess of $1 billion (U.S. dollars). Past hail climatology has typically relied on the National Oceanic and Atmospheric Administration/National Climatic Data Center’s (NOAA/NCDC) Storm Data publication, which has numerous reporting biases and nonmeteorological artifacts. This research seeks to quantify the spatial and temporal characteristics of contiguous United States (CONUS) hail fall, derived from multiradar multisensor (MRMS) algorithms for several years during the Next-Generation Weather Radar (NEXRAD) era, leveraging the Multiyear Reanalysis of Remotely Sensed Storms (MYRORSS) dataset at NOAA’s National Severe Storms Laboratory (NSSL). The primary MRMS product used in this study is the maximum expected size of hail (MESH). The preliminary climatology includes 42 months of quality controlled and reprocessed MESH grids, which spans the warm seasons for four years (2007–10), covering 98% of all Storm Data hail reports during that time. The dataset has 0.01° latitude × 0.01° longitude × 31 vertical levels spatial resolution, and 5-min temporal resolution. Radar-based and reports-based methods of hail climatology are compared. MRMS MESH demonstrates superior coverage and resolution over Storm Data hail reports, and is largely unbiased. The results reveal a broad maximum of annual hail fall in the Great Plains and a diminished secondary maximum in the Southeast United States. Potential explanations for the differences in the two methods of hail climatology are also discussed.

Current affiliation: Cooperative Institute of Meteorological Satellite Studies, Madison, Wisconsin.

Corresponding author address: John L. Cintineo, CIMSS, University of Wisconsin—Madison, 1225 W. Dayton St., Madison, WI 53706. E-mail: john.cintineo@ssec.wisc.edu

A comment/reply has been published regarding this article and can be found at http://journals.ametsoc.org/doi/abs/10.1175/WAF-D-13-00020.1

Abstract

The threat of damaging hail from severe thunderstorms affects many communities and industries on a yearly basis, with annual economic losses in excess of $1 billion (U.S. dollars). Past hail climatology has typically relied on the National Oceanic and Atmospheric Administration/National Climatic Data Center’s (NOAA/NCDC) Storm Data publication, which has numerous reporting biases and nonmeteorological artifacts. This research seeks to quantify the spatial and temporal characteristics of contiguous United States (CONUS) hail fall, derived from multiradar multisensor (MRMS) algorithms for several years during the Next-Generation Weather Radar (NEXRAD) era, leveraging the Multiyear Reanalysis of Remotely Sensed Storms (MYRORSS) dataset at NOAA’s National Severe Storms Laboratory (NSSL). The primary MRMS product used in this study is the maximum expected size of hail (MESH). The preliminary climatology includes 42 months of quality controlled and reprocessed MESH grids, which spans the warm seasons for four years (2007–10), covering 98% of all Storm Data hail reports during that time. The dataset has 0.01° latitude × 0.01° longitude × 31 vertical levels spatial resolution, and 5-min temporal resolution. Radar-based and reports-based methods of hail climatology are compared. MRMS MESH demonstrates superior coverage and resolution over Storm Data hail reports, and is largely unbiased. The results reveal a broad maximum of annual hail fall in the Great Plains and a diminished secondary maximum in the Southeast United States. Potential explanations for the differences in the two methods of hail climatology are also discussed.

Current affiliation: Cooperative Institute of Meteorological Satellite Studies, Madison, Wisconsin.

Corresponding author address: John L. Cintineo, CIMSS, University of Wisconsin—Madison, 1225 W. Dayton St., Madison, WI 53706. E-mail: john.cintineo@ssec.wisc.edu

A comment/reply has been published regarding this article and can be found at http://journals.ametsoc.org/doi/abs/10.1175/WAF-D-13-00020.1

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