{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:32:30Z","timestamp":1760146350242,"version":"build-2065373602"},"reference-count":57,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T00:00:00Z","timestamp":1729814400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFC3003903","2023LASW-B26","BMBKJ202402003"],"award-info":[{"award-number":["2022YFC3003903","2023LASW-B26","BMBKJ202402003"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Grants of the State Key Laboratory of Severe Weather","award":["2022YFC3003903","2023LASW-B26","BMBKJ202402003"],"award-info":[{"award-number":["2022YFC3003903","2023LASW-B26","BMBKJ202402003"]}]},{"name":"Beijing Meteorological Service Science and Technology Program","award":["2022YFC3003903","2023LASW-B26","BMBKJ202402003"],"award-info":[{"award-number":["2022YFC3003903","2023LASW-B26","BMBKJ202402003"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A wind profiler radar detects fine spatiotemporal resolution dynamical information, enabling the capture of meso- and micro-scale systems. Experience gained from observing system experiments (OSEs) studies confirms that reasonable profiler assimilation techniques can achieve improved short-term forecasts. This study further applies the adjoint-based forecast sensitivity to observation (FSO) method to investigate the quantitative impact of a profiler data assimilation strategy on short-term forecasts, and the results are consistent with those obtained from OSEs, further demonstrating that FSO and OSEs can be used to evaluate the effect of data assimilation techniques from different perspectives. Considering the unique advantage that the FSO can quantify the interactions between various observing systems and the impact on improving the model forecasts according to specific needs without costly additional calculations, we further diagnose in detail the observation impacts from multiple perspectives, including the observation platform, observation variables, and spatial distribution. And the results show that dynamical variables are more significant in improving forecasts compared to the other observed variables. Meanwhile, the dense profiler observations resulted in a more significant impact when radiosonde observations were not detected. The upper-level single winds monitored by profiler radars play a more important role in improving forecast skill. The FSO method measures the impact of an individual observing system, which can be used to enrich the evaluation of data assimilation schemes, efficiently calculate the impacts of multisource observations, and contribute to future development in adaptive observation, observation quality control, and observation error optimization.<\/jats:p>","DOI":"10.3390\/rs16213964","type":"journal-article","created":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T03:46:04Z","timestamp":1729827964000},"page":"3964","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Using Adjoint-Based Forecast Sensitivity to Observation to Evaluate a Wind Profiler Data Assimilation Strategy and the Impact of Data on Short-Term Forecasts"],"prefix":"10.3390","volume":"16","author":[{"given":"Cheng","family":"Wang","sequence":"first","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"},{"name":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing 100081, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6372-5998","authenticated-orcid":false,"given":"Xiang-Yu","family":"Huang","sequence":"additional","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}]},{"given":"Min","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}]},{"given":"Yaodeng","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster of Ministry of Education (KLME)\/Joint International Research Laboratory of Climate and Environment Change (ILCEC)\/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China"}]},{"given":"Jiqin","family":"Zhong","sequence":"additional","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}]},{"given":"Jian","family":"Yin","sequence":"additional","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1038\/nature14956","article-title":"The quiet revolution of numerical weather prediction","volume":"525","author":"Bauer","year":"2015","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1871","DOI":"10.1175\/BAMS-85-12-1871","article-title":"The Value of Wind Profiler Data in U.S. Weather Forecasting","volume":"85","author":"Benjamin","year":"2004","journal-title":"Bull. 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