{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T22:11:41Z","timestamp":1766182301349,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T00:00:00Z","timestamp":1711065600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Ministry of Science","award":["PID2021-126436OB-C22"],"award-info":[{"award-number":["PID2021-126436OB-C22"]}]},{"name":"\u201cERDF A way of making Europe\u201d of the \u201cEuropean Union\u201d","award":["PID2021-126436OB-C22"],"award-info":[{"award-number":["PID2021-126436OB-C22"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Currently, it remains a challenge to effectively monitor areas experiencing intense precipitation and the associated atmospheric conditions on a global scale. This challenge arises due to the limitations on both active and passive remote sensing methods. Apart from the lack of observations in remote areas, the quality of some observations deteriorates when heavy precipitation is present, making it difficult to obtain highly accurate measurements of the thermodynamic parameters driving these weather events. However, there is a promising solution in the form of the Global Navigation Satellite System (GNSS) Polarimetric Radio Occultation (PRO) technique. This approach provides a way to assess the large-scale bulk-hydrometeor characteristics of regions with heavy precipitation and the meteorological conditions associated with them. PRO offers vertical profiles of atmospheric variables, including temperature, pressure, water vapor pressure, and information about hydrometeors, all in a single fine-vertical resolution observation. To continue validating the PRO technique, we make use of polarimetric weather data from Next Generation Weather Radars (NEXRAD), focusing on comparing specific differential phase shift (Kdp) structures to PRO observable differential phase shift (\u0394\u03a6). We have seen that PAZ and NEXRAD exhibit a good agreement on the vertical structure of the observable \u0394\u03a6 and that their combination could be useful for enhancing our understanding of the microphysics underlying heavy precipitation events.<\/jats:p>","DOI":"10.3390\/rs16071118","type":"journal-article","created":{"date-parts":[[2024,3,22]],"date-time":"2024-03-22T10:58:02Z","timestamp":1711105082000},"page":"1118","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Evaluating the Polarimetric Radio Occultation Technique Using NEXRAD Weather Radars"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5299-7941","authenticated-orcid":false,"given":"Ant\u00eda","family":"Paz","sequence":"first","affiliation":[{"name":"Institute of Space Sciences, 08193 Barcelona, Spain"},{"name":"Institute for Space Studies of Catalonia, 08034 Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2058-3779","authenticated-orcid":false,"given":"Ramon","family":"Padull\u00e9s","sequence":"additional","affiliation":[{"name":"Institute of Space Sciences, 08193 Barcelona, Spain"},{"name":"Institute for Space Studies of Catalonia, 08034 Barcelona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8908-0972","authenticated-orcid":false,"given":"Estel","family":"Cardellach","sequence":"additional","affiliation":[{"name":"Institute of Space Sciences, 08193 Barcelona, Spain"},{"name":"Institute for Space Studies of Catalonia, 08034 Barcelona, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3217","DOI":"10.1029\/JZ070i013p03217","article-title":"The Bistatic Radar-Occultation Method for the Study of Planetary Atmospheres","volume":"70","author":"Fjeldbo","year":"1965","journal-title":"J. Geophys. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"23429","DOI":"10.1029\/97JD01569","article-title":"Observing Earth\u2019s atmopshere with radio occultation measurements using the Global Positioning System","volume":"102","author":"Kursinski","year":"1997","journal-title":"J. Geophys. Res. Atmos."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"L3804","DOI":"10.1029\/2004GL020806","article-title":"Forecast impact experiment with GPS radio occultation measurements","volume":"32","author":"Healy","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1109\/TGRS.2014.2320309","article-title":"Sensitivity of PAZ LEO Polarimetric GNSS Radio-Occultation Experiment to Precipitation Events","volume":"53","author":"Cardellach","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1024","DOI":"10.1029\/2018GL080412","article-title":"Sensing Heavy Precipitation With GNSS Polarimetric Radio Occultations","volume":"46","author":"Cardellach","year":"2019","journal-title":"Geophys. Res. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1299","DOI":"10.5194\/amt-13-1299-2020","article-title":"Calibration and validation of the Polarimetric Radio Occultation and Heavy Precipitation experiment aboard the PAZ satellite","volume":"13","author":"Ao","year":"2020","journal-title":"Atmos. Meas. Tech."},{"key":"ref_7","first-page":"1727","article-title":"Interpretation of the Precipitation Structure Contained in Polarimetric Radio Occultation Profiles Using Passive Microwave Satellite Observations","volume":"38","author":"Turk","year":"2021","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_8","first-page":"1","article-title":"Sensing Horizontally Oriented Frozen Particles With Polarimetric Radio Occultations Aboard PAZ: Validation Using GMI Coincident Observations and Cloudsat a Priori Information","volume":"60","author":"Cardellach","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2199","DOI":"10.5194\/acp-23-2199-2023","article-title":"On the global relationship between polarimetric radio occultation differential phase shift and ice water conten","volume":"23","author":"Cardellach","year":"2023","journal-title":"Atmos. Chem. Phys."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1002\/2014RG000476","article-title":"A review of the remote sensing of lower tropospheric thermodynamic profiles and its indispensable role for the understanding and the simulation of water and energy cycles","volume":"53","author":"Wulfmeyer","year":"2015","journal-title":"Rev. Geophys."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4633","DOI":"10.1109\/TGRS.2018.2831600","article-title":"Separability of systematic effects in polarimetric GNSS radio occultations for precipitation sensing","volume":"56","author":"Cardellach","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","unstructured":"Padull\u00e9s, R., Cardellach, E., and Oliveras, S. (2024, March 18). resPrf [Dataset]. Available online: https:\/\/digital.csic.es\/handle\/10261\/348253."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1175\/1520-0477(1993)074<1293:ADOTIS>2.0.CO;2","article-title":"A Description of the Initial Set of Analysis Products Aivailable from the NEXRAD WSR-88D System","volume":"74","author":"Klazura","year":"1993","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1175\/1520-0434(1998)013<0253:AUOTNP>2.0.CO;2","article-title":"An Update on the NEXRAD Program and Future WSR-88D Support to Operations","volume":"13","author":"Crum","year":"1998","journal-title":"Weather Forecast."},{"key":"ref_15","unstructured":"NOAA National Weather Service (NWS) Radar Operations Center (1991). NOAA Next Generation Radar (NEXRAD) Level 2 Base Data."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e25","DOI":"10.5334\/jors.119","article-title":"The Python ARM Radar Toolkit (Py-Art), a library for working with weather radar data in the Python programmin language","volume":"4","author":"Helmus","year":"2016","journal-title":"J. Open Res. Softw."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1175\/JAMC-D-10-05024.1","article-title":"On the use of dual-polarized C-band radar for operational rainfall retrieval in mountainous areas","volume":"51","author":"Vulpiani","year":"2012","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"4681","DOI":"10.5194\/amt-8-4681-2015","article-title":"Characterization of Meditarranean hail-bearing storms using an operational polarimetric X-band radar","volume":"8","author":"Vulpiani","year":"2015","journal-title":"Atmos. Meas. Tech."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"587","DOI":"10.1175\/JTECH-D-20-0060.1","article-title":"Evaluation of Kdp Estimation Algorithm Performance in Rain Using a Known-Truth Framework","volume":"38","author":"Reimel","year":"2021","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1175\/JAMC-D-17-0033.1","article-title":"A Polarimetric Analysis of Ice Microphysical Processes in Snow, Using Quasi-Vertical Profiles","volume":"57","author":"Griffin","year":"2018","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Bringi, V.N., and Chandrasekar, V. (2001). Polarimetric Doppler Weather Radar: Principles and Applications, Cambridge University Press.","DOI":"10.1017\/CBO9780511541094"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2565","DOI":"10.1175\/2009JTECHA1358.1","article-title":"Algorithm for Estimation of the Specific Differential Phase","volume":"26","author":"Wang","year":"2009","journal-title":"J. Atmos. Ocean. Technol."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/7\/1118\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:18:17Z","timestamp":1760105897000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/7\/1118"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,22]]},"references-count":22,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["rs16071118"],"URL":"https:\/\/doi.org\/10.3390\/rs16071118","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2024,3,22]]}}}