{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T01:49:30Z","timestamp":1764812970781,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2021,8,12]],"date-time":"2021-08-12T00:00:00Z","timestamp":1628726400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Precipitation estimation by weather radars in Alaska is challenging. In this study, we investigate National Weather Service (NWS) precipitation products that are produced from the seven NEXRAD radar sites in Alaska. The NWS precipitation processing subsystem generates stages of data at each NEXRAD site which are then input to the weather forecast office to generate a regionwide precipitation product. Data from the NEXRAD sites and the operational rain gauges in the weather forecast region are used to produce this regionwide product that is then sent to the National Centers for Environmental Prediction (NCEP) to be included in the NCEP Stage IV distribution. The NCEP Stage IV product for Alaska has been available since 2017. We use the United States Climate Reference Network (USCRN) data from Alaska to compare to the NCEP Stage IV data. Given that the USCRN can be used in the production of the NCEP Stage IV data for Alaska, we also used the NEXRAD Digital Precipitation Array (DPA) that is generated at the site for comparison of the radar-only products. Comparing the NEXRAD-based data from Alaska to the USCRN gauge estimates using the USCRN site information on air temperature, we are able to condition the analysis based on the hourly or 6-hourly average air temperature. The estimates in the frozen phase of precipitation largely underestimate as compared to the gauge, and the correlation is low with larger errors as compared to other phases of precipitation. In the mixed phase the underestimation of precipitation improves, but the correlation is still low with relatively large errors as compared to the rain phases of precipitation. The difficulties in precipitation estimation in cold temperatures are well known and we show the evaluation for the NCEP Stage IV regional data for Alaska and the NEXRAD site specific Digital Precipitation Array (DPA) data. Results show the challenges of estimating mixed-phase and frozen precipitation. However, the DPA data shows somewhat better performance in the mixed precipitation phase, which suggests that the NWS Precipitation Processing Subsystem (PPS) is tuned to the climatology as it relates to precipitation in Alaska.<\/jats:p>","DOI":"10.3390\/rs13163202","type":"journal-article","created":{"date-parts":[[2021,8,12]],"date-time":"2021-08-12T10:54:41Z","timestamp":1628765681000},"page":"3202","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["An Investigation of NEXRAD-Based Quantitative Precipitation Estimates in Alaska"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1479-6367","authenticated-orcid":false,"given":"Brian R.","family":"Nelson","sequence":"first","affiliation":[{"name":"NOAA National Environmental Satellite, Data, and Information Service (NESDIS), Asheville, NC 28801, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9289-5723","authenticated-orcid":false,"given":"Olivier P.","family":"Prat","sequence":"additional","affiliation":[{"name":"Cooperative Institute for Satellite Earth System Studies, North Carolina State University, Asheville, NC 28801, USA"}]},{"given":"Ronald D.","family":"Leeper","sequence":"additional","affiliation":[{"name":"Cooperative Institute for Satellite Earth System Studies, North Carolina State University, Asheville, NC 28801, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"478","DOI":"10.2166\/nh.2014.023","article-title":"Reflecting on the Status of Precipitation Data Collection in Alaska: A Case Study","volume":"46","author":"Kane","year":"2014","journal-title":"Hydrol. 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Clim."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3202\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:44:56Z","timestamp":1760165096000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/16\/3202"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,12]]},"references-count":27,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2021,8]]}},"alternative-id":["rs13163202"],"URL":"https:\/\/doi.org\/10.3390\/rs13163202","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2021,8,12]]}}}