Assessing the Skill of Updated Precipitation-Type Diagnostics for the Rapid Refresh with mPING

Tomer Burg National Weather Center Research Experiences for Undergraduates Program, Norman, Oklahoma, and University at Albany, State University of New York, Albany, New York

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Kimberly L. Elmore Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and National Oceanic and Atmospheric Administration/National Severe Storms Laboratory, Norman, Oklahoma

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Heather M. Grams Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, and National Oceanic and Atmospheric Administration/National Severe Storms Laboratory, Norman, Oklahoma

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Abstract

Previous work has shown that the Rapid Refresh (RAP) model severely underrepresents ice pellets in its grid, with a skill near zero and a very low bias. An ice pellet diagnostic upgrade was devised at the Earth System Research Laboratory (ESRL) to resolve this issue. Parallel runs of the experimental ESRL-RAP with the fix and the operational NCEP-RAP without the fix provide an opportunity to assess whether this upgrade has improved the overall performance and the performance of the individual precipitation types of the ESRL-RAP. Verification was conducted using the mobile Phenomena Identification Near the Ground (mPING) project. The overall Gerrity skill score (GSS) for the ESRL-RAP was improved relative to the NCEP-RAP at a 3-h lead time but degraded with increasing lead time; the difference is significant at p < 0.05. Whether this difference is practically significant for users is unknown. Some improvement was found in the bias and skill scores of ice pellets and snow in the ESRL-RAP, although the model continues to underrepresent ice pellets, while rain and freezing rain were generally the same or slightly worse with the fix. The ESRL-RAP was also found to depict a more realistic spatial distribution of precipitation types in transition zones involving ice pellets and freezing rain.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/WAF-D-16-0132.s1.

Additional affiliation: NOAA/National Severe Storms Laboratory, Norman, Oklahoma.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Dr. Kimberly L. Elmore, kim.elmore@noaa.gov

Abstract

Previous work has shown that the Rapid Refresh (RAP) model severely underrepresents ice pellets in its grid, with a skill near zero and a very low bias. An ice pellet diagnostic upgrade was devised at the Earth System Research Laboratory (ESRL) to resolve this issue. Parallel runs of the experimental ESRL-RAP with the fix and the operational NCEP-RAP without the fix provide an opportunity to assess whether this upgrade has improved the overall performance and the performance of the individual precipitation types of the ESRL-RAP. Verification was conducted using the mobile Phenomena Identification Near the Ground (mPING) project. The overall Gerrity skill score (GSS) for the ESRL-RAP was improved relative to the NCEP-RAP at a 3-h lead time but degraded with increasing lead time; the difference is significant at p < 0.05. Whether this difference is practically significant for users is unknown. Some improvement was found in the bias and skill scores of ice pellets and snow in the ESRL-RAP, although the model continues to underrepresent ice pellets, while rain and freezing rain were generally the same or slightly worse with the fix. The ESRL-RAP was also found to depict a more realistic spatial distribution of precipitation types in transition zones involving ice pellets and freezing rain.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/WAF-D-16-0132.s1.

Additional affiliation: NOAA/National Severe Storms Laboratory, Norman, Oklahoma.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Dr. Kimberly L. Elmore, kim.elmore@noaa.gov

Supplementary Materials

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