Advancements and Characteristics of Gauge Ingest and Quality Control within the Multi-Radar Multi-Sensor System

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  • 1 Cooperative Institute for Mesoscale Meteorological Studies, The University of Oklahoma, and NOAA/OAR National Severe Storms Laboratory, Norman, Oklahoma
  • 2 National Weather Center Research Experience for Undergraduates, Norman, Oklahoma and Central Michigan University, Mt. Pleasant, Michigan
  • 3 NOAA/OAR National Severe Storms Laboratory, Norman, Oklahoma
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Abstract

This study describes recent advancements in the Multi-Radar Multi-Sensor (MRMS) automated gauge ingest and quality control (QC) processes. A data latency analysis for the combined multiple gauge collection platforms provided guidance for a multiple-pass generation and delivery of gauge-based precipitation products. Various advancements to the gauge QC logic were evaluated over a 21-month period, resulting in an average of 86% of hourly gauge observations per hour being classified as useful. The fully-automated QC logic was compared to manual human QC for a limited domain, which showed a > 95% agreement in their QC reasoning categories. This study also includes an extensive evaluation of various characteristics related to the gauge observations ingested into the MRMS system. Duplicate observations between gauge collection platforms highlighted differences in site coordinates; moreover, errors in Automated Surface Observing System (ASOS) station site coordinates resulted in > 79% of sites being located in a different MRMS 1-km grid cell. The ASOS coordinate analysis combined with examinations of other limitations regarding gauge observations highlight the need for robust and accurate metadata to further enhance the quality control of gauge data.

Corresponding author address: Steven Martinaitis, National Weather Center, 120 David L. Boren Blvd., Norman, OK 73072-7303. Email: steven.martinaitis@noaa.gov

Abstract

This study describes recent advancements in the Multi-Radar Multi-Sensor (MRMS) automated gauge ingest and quality control (QC) processes. A data latency analysis for the combined multiple gauge collection platforms provided guidance for a multiple-pass generation and delivery of gauge-based precipitation products. Various advancements to the gauge QC logic were evaluated over a 21-month period, resulting in an average of 86% of hourly gauge observations per hour being classified as useful. The fully-automated QC logic was compared to manual human QC for a limited domain, which showed a > 95% agreement in their QC reasoning categories. This study also includes an extensive evaluation of various characteristics related to the gauge observations ingested into the MRMS system. Duplicate observations between gauge collection platforms highlighted differences in site coordinates; moreover, errors in Automated Surface Observing System (ASOS) station site coordinates resulted in > 79% of sites being located in a different MRMS 1-km grid cell. The ASOS coordinate analysis combined with examinations of other limitations regarding gauge observations highlight the need for robust and accurate metadata to further enhance the quality control of gauge data.

Corresponding author address: Steven Martinaitis, National Weather Center, 120 David L. Boren Blvd., Norman, OK 73072-7303. Email: steven.martinaitis@noaa.gov
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