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

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 Dat...

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Veröffentlicht in:Weather and forecasting 2012-10, Vol.27 (5), p.1235-1248
Hauptverfasser: CINTINEO, John L, SMITH, Travis M, LAKSHMANAN, Valliappa, BROOKS, Harold E, ORTEGA, Kiel L
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container_issue 5
container_start_page 1235
container_title Weather and forecasting
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creator CINTINEO, John L
SMITH, Travis M
LAKSHMANAN, Valliappa
BROOKS, Harold E
ORTEGA, Kiel L
description 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.
doi_str_mv 10.1175/WAF-D-11-00151.1
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source American Meteorological Society; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection
subjects Algorithms
Climate
Climate change
Climatic data
Climatology
Data centers
Datasets
Earth, ocean, space
Economic impact
Economic indicators
Exact sciences and technology
External geophysics
Hail
Hail damage
Meteorological radar
Meteorology
Neural networks
Population density
Radar
Remote sensing
Servers
Severe storms
Severe thunderstorms
Spatial discrimination
Spatial resolution
Storm data
Storms
Studies
Temporal resolution
Thunderstorms
Velocity
Warm seasons
Water in the atmosphere (humidity, clouds, evaporation, precipitation)
Weather forecasting
Weather radar
title An Objective High-Resolution Hail Climatology of the Contiguous United States
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