{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T12:09:03Z","timestamp":1767182943204,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"20","license":[{"start":{"date-parts":[[2020,10,20]],"date-time":"2020-10-20T00:00:00Z","timestamp":1603152000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000192","name":"National Oceanic and Atmospheric Administration","doi-asserted-by":"publisher","award":["NA18NWS4680053."],"award-info":[{"award-number":["NA18NWS4680053."]}],"id":[{"id":"10.13039\/100000192","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper explores the capability of high frequency microwave measurements at vertical and horizontal polarizations in detecting snowfall over land. Surface in-situ meteorological data were collected over Conterminous US during two winter seasons in 2014\u20132015 and 2015\u20132016. Statistical analysis of the in-situ data, matched with Global Precipitation Measurement (GPM) Microwave Imager (GMI) measurements on board NASA\/JAXA Core Observatory, showed that the polarization difference at 166 GHz had the highest correlation to measured snowfall rate compared to the single channel high frequency measurements and the polarization difference at 89 GHz. A logistic regression model applied to the match-up data, using the polarization difference at 166 and 89 GHz as predictors, yielded an overall snowfall classification rate of 69.0%, with the largest contribution coming from the polarization difference at 166 GHz. Logistic regression using the four single channels as predictors (at 89 and 166 GHz, horizontal and vertical polarizations) further indicated that the horizontal polarization at 166 GHz was the most important contributor. An overall classification rate of 73% was achieved by including the 183.31 \u00b1 3 GHz and 183.31 \u00b1 7 GHz vertical polarization channels in the final logistic regression model. Evaluation of the final algorithm demonstrated skill in snowfall detection of two significant events.<\/jats:p>","DOI":"10.3390\/rs12203441","type":"journal-article","created":{"date-parts":[[2020,10,20]],"date-time":"2020-10-20T09:28:23Z","timestamp":1603186103000},"page":"3441","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Ground-based Assessment of Snowfall Detection over Land Using Polarimetric High Frequency Microwave Measurements"],"prefix":"10.3390","volume":"12","author":[{"given":"Cezar","family":"Kongoli","sequence":"first","affiliation":[{"name":"Earth System Science Interdisciplinary Center (ESSIC), University of Maryland College Park, College Park, MD 20740, USA"},{"name":"National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service (NESDIS), College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huan","family":"Meng","sequence":"additional","affiliation":[{"name":"National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service (NESDIS), College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Dong","sequence":"additional","affiliation":[{"name":"Earth System Science Interdisciplinary Center (ESSIC), University of Maryland College Park, College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8393-7135","authenticated-orcid":false,"given":"Ralph","family":"Ferraro","sequence":"additional","affiliation":[{"name":"National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data, and Information Service (NESDIS), College Park, MD 20740, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,10,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13987","DOI":"10.1029\/96JD03090","article-title":"Precipitation Characteristics in Greenland-Iceland-Norwegian Seas Determined by Using Satellite Microwave Data","volume":"102","author":"Liu","year":"1997","journal-title":"J. Geophys. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2322","DOI":"10.1109\/36.868889","article-title":"Precipitation Observations Near 54 and 183 GHz using the NOAA-15 Satellite","volume":"38","author":"Staelin","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1109\/TGRS.2002.808322","article-title":"AIRS\/AMSU\/HSB precipitation estimates","volume":"41","author":"Chen","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1756","DOI":"10.1029\/2003GL017177","article-title":"A New Snowfall Detection Algorithm Over Land Using Measurements from the Advanced Microwave Sounding Unit (AMSU)","volume":"30","author":"Kongoli","year":"2003","journal-title":"Geophys. Res. Lett."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1047","DOI":"10.1109\/TGRS.2004.825585","article-title":"A Physical Model to Determine Snowfall Over Land by Microwave Radiometry","volume":"42","author":"Kim","year":"2004","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","first-page":"D22216","article-title":"Development of a Snowfall Retrieval Algorithm at High Microwave Frequencies","volume":"111","author":"Noh","year":"2006","journal-title":"J. Geophys. Res."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1376","DOI":"10.1002\/jgrd.50172","article-title":"Detecting Snowfall Over Land by Satellite High-Frequency Microwave Observations: The Lack of Scattering Signature and a Statistical Approach","volume":"118","author":"Liu","year":"2013","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1036","DOI":"10.1109\/TGRS.2004.843249","article-title":"NOAA Operational Hydrological Products Derived from the AMSU","volume":"43","author":"Ferraro","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Surussavadee, C., Blackwell, W.J., Entekhabi, D., and Leslie, R.V. (2012, January 22\u201327). A Global Precipitation Retrieval Algorithm for Suomi NPP ATMS. Proceedings of the Geoscience and Remote Sensing Symposium (IGARSS), Munich, Germany.","DOI":"10.1109\/IGARSS.2012.6351128"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1918","DOI":"10.1002\/2014JD022427","article-title":"A Snowfall Detection Algorithm Over Land Utilizing High-Frequency Passive Microwave Measurements\u2014Application to ATMS","volume":"120","author":"Kongoli","year":"2015","journal-title":"JGR-Atmos."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1002\/qj.3270","article-title":"A Hybrid Snowfall Detection Method from Satellite Passive Microwave Measurements and Global Weather Forecast Models","volume":"144","author":"Kongoli","year":"2018","journal-title":"Q. J. R. Meteorol. Soc."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6520","DOI":"10.1002\/2016JD026325","article-title":"A 1DVAR-Based Snowfall Rate Retrieval Algorithm for Passive Microwave Radiometers","volume":"122","author":"Meng","year":"2017","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1175\/JHM-D-16-0190.1","article-title":"Quantifying the Snowfall Detection Performance of the GPM Microwave Imager Channels over Land","volume":"18","author":"You","year":"2017","journal-title":"J. Hydrometeor."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Panegrossi, G., Rysman, J.-F., Daniele, C., Marra, A., Sano, P., and Kulie, M. (2017). CloudSat-Based Assessment of GPM Microwave Imager Snowfall Observation Capabilities. Remote Sens., 9.","DOI":"10.3390\/rs9121263"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1175\/JCLI-D-18-0293.1","article-title":"Analysis of the Global Microwave Polarization Data of Clouds","volume":"32","author":"Zeng","year":"2019","journal-title":"J. Clim."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"6154","DOI":"10.1002\/2017GL073451","article-title":"Microwave Retrievals of Terrestrial Precipitation Over Snow-Covered Surfaces: A Lesson from the GPM Satellite","volume":"44","author":"Ebtehaj","year":"2017","journal-title":"Geophys. Res. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"6145","DOI":"10.1002\/2015JD023158","article-title":"Polarization Signatures and Brightness Temperatures Caused by Horizontally Oriented Snow Particles at Microwave Bands: Effects of Atmospheric Absorption","volume":"120","author":"Xie","year":"2015","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_18","unstructured":"(2005, September 27). Iowa Environmental Mesonet. Available online: https:\/\/mesonet.agron.iastate.edu\/docs\/nexrad_mosaic\/."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1576","DOI":"10.1002\/hyp.6720","article-title":"Enhancements to, and Forthcoming Developments in the Interactive Multisensor Snow and Ice Mapping System (IMS)","volume":"21","author":"Helfrich","year":"2007","journal-title":"Hydrol. Proc."},{"key":"ref_20","unstructured":"Carroll, T., Cline, D., Fall, G., Nilsson, A., Li, L., and Rost, A. (2001, January 16\u201319). NOHRSC Operations and the Simulation of Snow Cover Properties for the Conterminous, U.S. Proceedings of the 69th Annual Meeting of the Western Snow Conference, Sun Valley, ID, USA."},{"key":"ref_21","unstructured":"Lin, Y., and Mitchell, K.E. (2005, January 9\u201313). The NCEP Stage II\/IV Hourly Precipitation Analyses: Development and Applications, preprints. Proceedings of the 19th Conf. on Hydrology, American Meteorological Society, San Diego, CA, USA."},{"key":"ref_22","unstructured":"Wilks, D.S. (2011). Statistical Methods in the Atmospheric Sciences, Elsevier."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/20\/3441\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:24:28Z","timestamp":1760178268000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/20\/3441"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,20]]},"references-count":22,"journal-issue":{"issue":"20","published-online":{"date-parts":[[2020,10]]}},"alternative-id":["rs12203441"],"URL":"https:\/\/doi.org\/10.3390\/rs12203441","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2020,10,20]]}}}