{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T21:01:58Z","timestamp":1765486918192,"version":"build-2065373602"},"reference-count":36,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,4,29]],"date-time":"2023-04-29T00:00:00Z","timestamp":1682726400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000006","name":"the NSSL Warn-on-Forecast project and the Office of Naval Research","doi-asserted-by":"publisher","award":["N000142012449","42275010"],"award-info":[{"award-number":["N000142012449","42275010"]}],"id":[{"id":"10.13039\/100000006","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["N000142012449","42275010"],"award-info":[{"award-number":["N000142012449","42275010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>By sampling perturbed state vectors from each ensemble forecast at additional time levels shifted by \u00b1\u03c4 (where \u03c4 is a selected time interval) from the analysis time, time-expanded sampling (TES) can not only sample timing errors (or phase errors) but also triple the analysis ensemble size for covariance construction without increasing the forecast ensemble size. In this study, TES was applied to the convection-allowing ensemble-based warn-on-forecast system (WoFS), for four severe storm events, to reduce the computational costs that constrain real-time applications in the assimilation of remote-sensing data from radars and the geostationary satellite GOES-16. For each event, TES was implemented against a 36-member control experiment (E36) by reducing the forecast ensemble size to 12 but tripling the analysis ensemble size to 12 \u00d7 3 = 36 with \u03c4 = 2.5 min, 5 min and 7.5 min in three TES experiments, named E12\u00d73\u03c42.5, E12\u00d73\u03c45 and E12\u00d73\u03c47.5, respectively. A 0\u20136-h forecast was created hourly after the second hour during the assimilation in each experiment. The assimilation statistics were evaluated for each experiment applied to each event and were found to be little affected by the TES, while reducing the computational cost. The forecasts produced in each experiment were verified against multi-sensor observed\/estimated rainfall, reported tornadoes and damaging winds for each event. The verifications indicated that the forecasts produced in the three TES experiments had about the same capability and quality as that in the E36 for predicting hourly rainfall and the probabilities of tornadoes and damaging winds; in addition, the predictive capability and quality were not sensitive to \u03c4, although they were slightly enhanced by selecting \u03c4 = 7.5 min. These results suggest that TES is attractive and useful for cost-saving real-time applications of WoFS in the assimilation of remote-sensing data and the generation of short-term severe-weather forecasts.<\/jats:p>","DOI":"10.3390\/rs15092358","type":"journal-article","created":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T12:10:03Z","timestamp":1682943003000},"page":"2358","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Applying Time-Expended Sampling to Ensemble Assimilation of Remote-Sensing Data for Short-Term Predictions of Thunderstorms"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-4868-7815","authenticated-orcid":false,"given":"Huanhuan","family":"Zhang","sequence":"first","affiliation":[{"name":"Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"},{"name":"Cooperative Institute for Severe and High-Impact Weather Research and Operations, University of Oklahoma, Norman, OK 73072, USA"},{"name":"University of Chinese Academy of Sciences, Beijing 100029, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9999-5455","authenticated-orcid":false,"given":"Jidong","family":"Gao","sequence":"additional","affiliation":[{"name":"NOAA\/OAR\/National Severe Storms Laboratory (NSSL), Norman, OK 73072, USA"}]},{"given":"Qin","family":"Xu","sequence":"additional","affiliation":[{"name":"NOAA\/OAR\/National Severe Storms Laboratory (NSSL), Norman, OK 73072, USA"}]},{"given":"Lingkun","family":"Ran","sequence":"additional","affiliation":[{"name":"Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,29]]},"reference":[{"key":"ref_1","unstructured":"NOAA (2023, April 25). 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