{"id":543,"date":"2022-02-25T15:04:55","date_gmt":"2022-02-25T21:04:55","guid":{"rendered":"https:\/\/inside.nssl.noaa.gov\/mrms\/?page_id=543"},"modified":"2023-03-02T17:09:00","modified_gmt":"2023-03-02T23:09:00","slug":"conference-presentations-2022","status":"publish","type":"page","link":"https:\/\/inside.nssl.noaa.gov\/mrms\/conference-presentations-2022\/","title":{"rendered":"Conference Presentations &#8211; 2022"},"content":{"rendered":"<p><strong>Select Conference Presentations and Extended Abstracts Given in 2022<\/strong><\/p>\n<p>Howard, K., and J. Zhang, 2022: Multi-Radar Multi-Sensor System (MRMS). <em>11th European Conf. on Radar in Meteorology and Hydrology<\/em>, MeteoSwiss, NET.P9.<\/p>\n<p>Osborne, A., J. Zhang, M. Simpson, S. Cocks, and K. Howard, 2022: Development of Multi-Radar Multi-Sensor (MRMS) machine learning QPE for complex terrain. <em>11th European Conf. on Radar in Meteorology and Hydrology<\/em>, MeteoSwiss, ORO.T5.<\/p>\n<p>Zhang, J., and W. Hanft, 2022: A dual-pol VPR correction for operational radar QPE. <em>11th European Conf. on Radar in Meteorology and Hydrology<\/em>, MeteoSwiss, QPE2.P11.<\/p>\n<p>Zhang, P., A. Ryzhkov, and S. Cocks, 2022: Rainfall estimation using specific attenuation with a new alpha optimization method. <em>11th European Conf. on Radar in Meteorology and Hydrology<\/em>, MeteoSwiss, QPE2.P13.<\/p>\n<p>Kirstetter, P., M. Simpson, J. Zhang, J. J. Gourlye, S. Martinaitis, and N. Indik, 2022: Probabilistic quantitative precipitation estimation with ground- and space-based radars. <em>11th European Conf. on Radar in Meteorology and Hydrology<\/em>, MeteoSwiss, QPE1.P8.<\/p>\n<p>Cocks, S. B., L. Tang, W. Hanft, C. Langston, J. Zhang, and K. Howard, 2022: Real-time verification\/ evaluation results for the MRMS experimental dual-pol QPE Product during the 2021 warm season. <em>36th Conf. on Hydrology<\/em>, Amer. Meteor. Soc., 437. [<a href=\"https:\/\/ams.confex.com\/ams\/102ANNUAL\/meetingapp.cgi\/Paper\/395587\" target=\"_blank\" rel=\"noopener\">Link<\/a>]<\/p>\n<p>Cocks, S. B., L. Tang, A. Osborne, J. Zhang, and K. Howard, 2022: Impacts of NEXRAD supplemental lower-elevation angles on MRMS quality control and QPE. <em>36th Conf. on Hydrology<\/em>, Amer. Meteor. Soc., 14B.4. [<a href=\"https:\/\/ams.confex.com\/ams\/102ANNUAL\/meetingapp.cgi\/Paper\/395576\" target=\"_blank\" rel=\"noopener\">Link<\/a>]<\/p>\n<p>Grams, H. M., J. Noel, V. Fortin, and L. Fry, 2022: Comparison of operational quantitative precipitation estimates from the U.S. National Weather Service and Environment Canada over the Great Lakes region. <em>36th Conf. on Hydrology<\/em>, Amer. Meteor. Soc., 14B.5. [<a href=\"https:\/\/ams.confex.com\/ams\/102ANNUAL\/meetingapp.cgi\/Paper\/399292\" target=\"_blank\" rel=\"noopener\">Link<\/a>]<\/p>\n<p>Martinaitis, S. M., S. B. Cocks, C. Langston, B. Kaney, J. Zhang, K. Howard, H. M. Grams, M. Hurwitz, and M. Mullusky, 2022: Designing the next-generation Multisensor Precipitation Estimator program for NWS River Forecast Centers. <em>38th Conf. on Environmental Information Processing Technologies<\/em>, Amer. Meteor. Soc., 8B.2. [<a href=\"https:\/\/ams.confex.com\/ams\/102ANNUAL\/meetingapp.cgi\/Paper\/395037\" target=\"_blank\" rel=\"noopener\">Link<\/a>]<\/p>\n<p>Martinaitis, S. M., S. B. Cocks, J. Zhang, S. Lincoln, and D. Schlotzhauer, 2022: A temporal quality control of gauges to improve precipitation processes for MRMS. <em>36th Conf. on Hydrology<\/em>, Amer. Meteor. Soc., 16B.5. [<a href=\"https:\/\/ams.confex.com\/ams\/102ANNUAL\/meetingapp.cgi\/Paper\/395020\" target=\"_blank\" rel=\"noopener\">Link<\/a>]<\/p>\n<p>Osborne, A. P., M. Simpson, J. Zhang, S. B. Cocks, and K. Howard, 2022: Evaluation and interpretation of an MRMS machine learning approach for precipitation estimation in complex terrain. <em>21st Conf. on Artificial Intelligence<\/em>, Amer. Meteor. Soc., 7B.4. [<a href=\"https:\/\/ams.confex.com\/ams\/102ANNUAL\/meetingapp.cgi\/Paper\/394304\" target=\"_blank\" rel=\"noopener\">Link<\/a>]<\/p>\n<p>Reinhart, A. E., H. M. Grams, J. Brogden, K. Cooper, R. Toomey, K. Howard, and A. Gerard, 2022: The Multi-Radar Multi-Sensor (MRMS) cloud computing update. <em>Eighth Symposium on High Performance Computing for Weather, Water, and Climate<\/em>, Amer. Meteor. Soc., 5.5. [<a href=\"https:\/\/ams.confex.com\/ams\/102ANNUAL\/meetingapp.cgi\/Paper\/399392\" target=\"_blank\" rel=\"noopener\">Link<\/a>]<\/p>\n<p>Simpson, M., J.\u00a0 Zhang, and K. Howard, 2022: Deep learning radar-based quantitative precipitation estimates in complex terrain. <em>21st Conf. on Artificial Intelligence<\/em>, Amer. Meteor. Soc., 5B.3. [<a href=\"https:\/\/ams.confex.com\/ams\/102ANNUAL\/meetingapp.cgi\/Paper\/398819\" target=\"_blank\" rel=\"noopener\">Link<\/a>]<\/p>\n<p>Thedens, E., H. M. Grams, R. A. Clark III, S. M. Martinaitis, and M. Simpson; Characterizing errors in MRMS quantitative precipitation estimates over Alaska, Hawaii, and Puerto Rico. <em>36th Conf. on Hydrology<\/em>, Amer. Meteor. Soc., 14B.3. [<a href=\"https:\/\/ams.confex.com\/ams\/102ANNUAL\/meetingapp.cgi\/Paper\/394513\" target=\"_blank\" rel=\"noopener\">Link<\/a>]<\/p>\n<p>Zhang, J., L. Tang, W. Hanft, A. P. Osborne, S. B. Cocks, M. Simpson, S. M. Martinaitis, H. M. Grams, C. Langston, K. Cooper, M. Taylor, A. Arthur, J. Brogden, and K. Howard; MRMS radar QPE updates: 2020\u201321. <em>36th Conf. on Hydrology<\/em>, Amer. Meteor. Soc., 16B.4. [<a href=\"https:\/\/ams.confex.com\/ams\/102ANNUAL\/meetingapp.cgi\/Paper\/393817\" target=\"_blank\" rel=\"noopener\">Link<\/a>]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Select Conference Presentations and Extended Abstracts Given in 2022 Howard, K., and J. Zhang, 2022: Multi-Radar Multi-Sensor System (MRMS). 11th European Conf. on Radar in Meteorology and Hydrology, MeteoSwiss, NET.P9.&#8230; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/inside.nssl.noaa.gov\/mrms\/conference-presentations-2022\/\" class=\"more-link\">Read more \u00bb<\/a><\/p>\n","protected":false},"author":121,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-543","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/mrms\/wp-json\/wp\/v2\/pages\/543","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/mrms\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/mrms\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/mrms\/wp-json\/wp\/v2\/users\/121"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/mrms\/wp-json\/wp\/v2\/comments?post=543"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/mrms\/wp-json\/wp\/v2\/pages\/543\/revisions"}],"predecessor-version":[{"id":561,"href":"https:\/\/inside.nssl.noaa.gov\/mrms\/wp-json\/wp\/v2\/pages\/543\/revisions\/561"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/mrms\/wp-json\/wp\/v2\/media?parent=543"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}