{"id":3269,"date":"2024-11-25T10:37:03","date_gmt":"2024-11-25T02:37:03","guid":{"rendered":"https:\/\/changjinyuan.com\/?p=3269"},"modified":"2026-05-02T18:46:35","modified_gmt":"2026-05-02T10:46:35","slug":"%e6%9d%8e%e6%99%a8%e9%be%99-hu-y-2024-analysis-of-the-spatiotemporal-velocity-of-annual-precipitation-based-on-random-field-communications-in-statistics-theory-and-methods-in-press","status":"publish","type":"post","link":"https:\/\/changjinyuan.com\/index.php\/publications\/publications-all\/3269\/","title":{"rendered":"\u674e\u6668\u9f99, &#038; Hu, Y. (2025). Analysis of the spatiotemporal velocity of annual precipitation based on random field. Communications in Statistics \u2013 Theory and Methods, 54, 1232-1249."},"content":{"rendered":"<p>Changes in precipitation directly impact river runoff volume, subsequently influencing food production, and the security of downstream urban areas. In this study, we introduce a random velocity field (RVF)capable of performing multi-step predictions while providing interpretable insights into precipitation variations. The RVF leverages the gradient of a Gaussian random field to learn spatiotemporal velocity patterns and employs a predictive process to reduce dimensionality and enable multi-step forecasting. Bayesian parameter estimation is obtained using the Markov Chain Monte Carlo (MCMC) method. Our analysis reveals a noticeable shifting trend in annual precipitation based on diverse real datasets. This trend serves as a valuable foundation for further exploration of urban flood control and agricultural development strategies.<\/p>\r\n\r\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" style=\"width: 100%; height: 600px;\" data=\"https:\/\/changjinyuan.com\/wp-content\/uploads\/2026\/05\/Analysis-of-the-spatiotemporal-velocity-of-annual-precipitation-based-on-random-field.pdf\" type=\"application\/pdf\" width=\"300\" height=\"150\" aria-label=\"\u5d4c\u5165 1.Analysis of the spatiotemporal velocity of annual precipitation based on random field\"><\/object><a id=\"wp-block-file--media-14afabd7-e9df-448c-b53d-e8000fe7a365\" href=\"https:\/\/changjinyuan.com\/wp-content\/uploads\/2026\/05\/Analysis-of-the-spatiotemporal-velocity-of-annual-precipitation-based-on-random-field.pdf\">1.Analysis of the spatiotemporal velocity of annual precipitation based on random field<\/a><a class=\"wp-block-file__button wp-element-button\" href=\"https:\/\/changjinyuan.com\/wp-content\/uploads\/2026\/05\/Analysis-of-the-spatiotemporal-velocity-of-annual-precipitation-based-on-random-field.pdf\" download=\"\" aria-describedby=\"wp-block-file--media-14afabd7-e9df-448c-b53d-e8000fe7a365\">\u4e0b\u8f7d<\/a><\/div>\r\n","protected":false},"excerpt":{"rendered":"<p>Changes in precipitation directly impact river runoff volume, subsequently influencing food production, and the security of downstream urban areas. In this study, we introduce a random velocity field (RVF)capable of performing multi-step predictions while providing interpretable insights into precipitation variations. The RVF leverages the gradient of a Gaussian random field to learn spatiotemporal velocity patterns and employs a predictive process to reduce dimensionality and enable multi-step forecasting. Bayesian parameter estimation is obtained using the Markov Chain Monte Carlo (MCMC) method. Our analysis reveals a noticeable shifting trend in annual precipitation based on diverse real datasets. This trend serves as a valuable foundation for further exploration of urban flood control and agricultural development strategies.<\/p>\n","protected":false},"author":1,"featured_media":5740,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[15],"tags":[],"class_list":["post-3269","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publications-all"],"acf":[],"lang":"cn","translations":{"cn":3269,"en":3279},"pll_sync_post":[],"_links":{"self":[{"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/posts\/3269","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/comments?post=3269"}],"version-history":[{"count":12,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/posts\/3269\/revisions"}],"predecessor-version":[{"id":5741,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/posts\/3269\/revisions\/5741"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/media\/5740"}],"wp:attachment":[{"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/media?parent=3269"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/categories?post=3269"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/changjinyuan.com\/index.php\/wp-json\/wp\/v2\/tags?post=3269"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}