![]() Rain gauge observations provide critical information for various hydrometeorological needs, ranging from flood operations to water resource management. 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. ![]() 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. ![]() This study also includes an extensive evaluation of various characteristics related to the gauge observations ingested into the MRMS system. 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. 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. 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. This study describes recent advancements in the Multi-Radar Multi-Sensor (MRMS) automated gauge ingest and quality control (QC) processes.
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