{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:21:19Z","timestamp":1760242879943,"version":"build-2065373602"},"reference-count":55,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2016,10,11]],"date-time":"2016-10-11T00:00:00Z","timestamp":1476144000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["91437214","71461010701"],"award-info":[{"award-number":["91437214","71461010701"]}],"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>Based on a widely used satellite precipitation product (TRMM Multi-satellite Precipitation Analysis 3B43), we analyzed the spatiotemporal variability of precipitation over the Pacific Ocean for 1998\u20132014 at seasonal and interannual timescales, separately, using the conventional empirical orthogonal function (EOF) and investigated the seasonal patterns associated with El Ni\u00f1o\u2013Southern Oscillation (ENSO) cycles using season-reliant empirical orthogonal function (SEOF) analysis. Lagged correlation analysis was also applied to derive the lead\/lag correlations of the first two SEOF modes for precipitation with Pacific Decadal Oscillation (PDO) and two types of El Ni\u00f1o, i.e., central Pacific (CP) El Ni\u00f1o and eastern Pacific (EP) El Ni\u00f1o. We found that: (1) The first two seasonal EOF modes for precipitation represent the annual cycle of precipitation variations for the Pacific Ocean and the first interannual EOF mode shows the spatiotemporal variability associated with ENSO; (2) The first SEOF mode for precipitation is simultaneously associated with the development of El Ni\u00f1o and most likely coincides with CP El Ni\u00f1o. The second SEOF mode lagged behind ENSO by one year and is associated with post-El Ni\u00f1o years. PDO modulates precipitation variability significantly only when ENSO occurs by strengthening and prolonging the impacts of ENSO; (3) Seasonally evolving patterns of the first two SEOF modes represent the consecutive precipitation patterns associated with the entire development of EP El Ni\u00f1o and the following recovery year. The most significant variation occurs over the tropical Pacific, especially in the Intertropical Convergence Zone (ITCZ) and South Pacific Convergence Zone (SPCZ); (4) Dry conditions in the western basin of the warm pool and wet conditions along the ITCZ and SPCZ bands during the mature phase of El Ni\u00f1o are associated with warm sea surface temperatures in the central tropical Pacific, and a subtropical anticyclone dominating over the northwestern Pacific. These findings may be useful for prediction of seasonal precipitation anomalies over the Pacific Ocean during El Ni\u00f1o years and recovery years.<\/jats:p>","DOI":"10.3390\/rs8100833","type":"journal-article","created":{"date-parts":[[2016,10,11]],"date-time":"2016-10-11T11:27:28Z","timestamp":1476185248000},"page":"833","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Seasonal to Interannual Variability of Satellite-Based Precipitation Estimates in the Pacific Ocean Associated with ENSO from 1998 to 2014"],"prefix":"10.3390","volume":"8","author":[{"given":"Xueyan","family":"Hou","sequence":"first","affiliation":[{"name":"State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China"}]},{"given":"Di","family":"Long","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China"}]},{"given":"Yang","family":"Hong","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China"},{"name":"School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73070, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3516-1210","authenticated-orcid":false,"given":"Hongjie","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Geological Sciences, University of Texas at San Antonio, San Antonio, TX 78204, USA"}]}],"member":"1968","published-online":{"date-parts":[[2016,10,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2786","DOI":"10.1175\/1520-0442(2000)013<2786:EIBOPO>2.0.CO;2","article-title":"ENSO Indices Based on Patterns of Satellite-Derived Precipitation","volume":"13","author":"Curtis","year":"2000","journal-title":"J. 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