{"id":46399,"date":"2025-04-28T03:44:59","date_gmt":"2025-04-27T22:14:59","guid":{"rendered":"https:\/\/vajiramandravi.com\/current-affairs\/?p=46399"},"modified":"2025-05-17T21:51:12","modified_gmt":"2025-05-17T16:21:12","slug":"history-and-evolution-of-monsoon-forecasting-in-india","status":"publish","type":"post","link":"https:\/\/vajiramandravi.com\/current-affairs\/history-and-evolution-of-monsoon-forecasting-in-india\/","title":{"rendered":"History and Evolution of Monsoon Forecasting in India | IMD Advances Explained"},"content":{"rendered":"<h2>What\u2019s in Today\u2019s Article?<\/h2>\n<ul>\n<li>Monsoon Forecasting in India Latest News<\/li>\n<li>Early Efforts in Monsoon Forecasting<\/li>\n<li>Post-Independence Challenges and the IMD\u2019s Early Forecasting Models<\/li>\n<li>Recent Improvements in Monsoon Forecasting<\/li>\n<li>Monsoon Forecasting in India FAQs<\/li>\n<\/ul>\n<h2>Monsoon Forecasting in India Latest News<\/h2>\n<ul>\n<li>The India Meteorological Department (IMD) has predicted above-normal rainfall of 105% of the long-period average (LPA) for the June-September southwest monsoon season.\u00a0<\/li>\n<li>Key drivers like the El Ni\u00f1o-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) are favorable for the monsoon.<\/li>\n<li>\u00a0The April 15 forecast is the first of the year, with an updated forecast expected in the last week of May. Long-range forecasts can extend from 30 days to two years.<\/li>\n<\/ul>\n<h2>Early Efforts in Monsoon Forecasting<\/h2>\n<ul>\n<li>A systematic effort to forecast monsoon rainfall began in 1877, following the establishment of the India Meteorological Department (IMD) in 1875.\u00a0<\/li>\n<li>The impetus for this was the Great Famine of 1876-78, which highlighted the critical need to understand monsoon patterns for agriculture, revenue, and public health.\u00a0<\/li>\n<li>British colonial interests, including agricultural production and shipping, relied heavily on the monsoon.<\/li>\n<\/ul>\n<h3>Blanford&#8217;s Contribution (1882-1885)<\/h3>\n<ul>\n<li>The first tentative forecasts were made by Henry Francis Blanford, who analyzed the relationship between Himalayan snow cover and monsoon rainfall.\u00a0<\/li>\n<li>Blanford\u2019s theory suggested that the extent and thickness of snow in the Himalayas influenced rainfall patterns over India, particularly in northwest regions.\u00a0<\/li>\n<\/ul>\n<h3>Eliot&#8217;s Advances (1889)<\/h3>\n<ul>\n<li>Sir John Eliot succeeded Blanford as the first Director General of Indian Observatories in 1889.\u00a0<\/li>\n<li>Eliot expanded on Blanford&#8217;s work by incorporating data on Himalayan snow, local weather conditions, and factors from the Indian Ocean and Australia.\u00a0<\/li>\n<li>Despite these advancements, Eliot\u2019s forecasts were still unable to predict droughts or famines, such as the devastating Indian Famine of 1899-1900.<\/li>\n<\/ul>\n<h3>Sir Gilbert Walker and Global Influences (1904)<\/h3>\n<ul>\n<li>In 1904, Sir Gilbert Walker succeeded Eliot and made significant advancements by incorporating global atmospheric, land, and ocean parameters.\u00a0<\/li>\n<li>Walker identified 28 predictors with stable historical correlations to the Indian monsoon and identified the <strong>Southern Oscillation (SO)<\/strong> as a key global pressure pattern influencing India&#8217;s climate.\u00a0<\/li>\n<li>SO was later linked to El Ni\u00f1o, which was identified by Jacob Bjerknes in the 1960s.\u00a0<\/li>\n<li>Walker also divided India into three subregions\u2014Peninsula, Northeast, and Northwest\u2014for more accurate forecasts.<\/li>\n<\/ul>\n<h2>Post-Independence Challenges and the IMD\u2019s Early Forecasting Models<\/h2>\n<ul>\n<li>After India\u2019s independence, the IMD continued using Walker\u2019s monsoon forecasting model until 1987, but the forecasts were not very accurate.\u00a0<\/li>\n<li>From 1932 to 1987, the average error in predictions was significant, with errors of 12.33 cm for the peninsula and 9.9 cm for Northwest India.\u00a0<\/li>\n<li>The primary issue was that many of Walker\u2019s parameters had lost their relevance over time, leading to poor accuracy despite attempts to improve the model.<\/li>\n<\/ul>\n<h3>Introduction of the Gowariker Model (1988)<\/h3>\n<ul>\n<li>In 1988, the IMD adopted a new model based on power regression, developed by Vasant R Gowariker and his team.\u00a0<\/li>\n<li>This model used <strong>16 atmospheric variables as predictors<\/strong> in statistical relationships with total rainfall.\u00a0<\/li>\n<li>Forecasts for the entire country replaced regional forecasts, though regional predictions were reintroduced in 1999 with modified geographical boundaries.\u00a0<\/li>\n<li>However, the new model still faced issues, and by 2000, four of the 16 parameters had lost their correlation with the monsoon, requiring adjustments.<\/li>\n<\/ul>\n<h3>Failures and Re-evaluation (2000s)<\/h3>\n<ul>\n<li>The Gowariker model faced significant challenges, including its failure to predict the drought of 2002, which followed 14 years of good monsoons.\u00a0<\/li>\n<li>This failure led to a re-evaluation of the model.\u00a0<\/li>\n<li>In 2003, the IMD introduced two new models based on 8 and 10 parameters, along with a two-stage forecast strategy.\u00a0<\/li>\n<li>While the 2003 forecast was accurate, the models again failed to predict the 2004 drought, prompting further refinement.<\/li>\n<\/ul>\n<h3>Development of the Statistical Forecasting System (2007)<\/h3>\n<ul>\n<li>In 2007, the IMD introduced a <strong>Statistical Ensemble Forecasting System (SEFS)<\/strong> to support its two-stage forecasting strategy.\u00a0<\/li>\n<li>This new system reduced the number of parameters in the models, replacing the eight-parameter model with a five-parameter model for the first forecast and the ten-parameter model with a six-parameter model for the update.\u00a0<\/li>\n<li>The aim was to avoid &#8220;overfitting,&#8221; ensuring the models could accurately predict new data.<\/li>\n<li>The IMD also implemented ensemble forecasting, which combined all possible forecasting models based on different predictor combinations to generate a more robust prediction.\u00a0<\/li>\n<li>This new approach significantly improved the accuracy of monsoon forecasts, with the average error decreasing from 7.94% of the long-period average (LPA) between 1995 and 2006 to 5.95% of LPA between 2007 and 2018.<\/li>\n<\/ul>\n<h2>Recent Improvements in Monsoon Forecasting<\/h2>\n<ul>\n<li><strong>Launch of the Monsoon Mission Coupled Forecasting System (MMCFS) &#8211; 2012<\/strong>\n<ul>\n<li>The introduction of the MMCFS in 2012 marked a significant advancement in monsoon prediction.\u00a0<\/li>\n<li>This coupled dynamic model combined data from the ocean, atmosphere, and land to provide more accurate forecasts.\u00a0<\/li>\n<li>The IMD used MMCFS alongside the SEFS for improved predictions.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Multi-Model Ensemble (MME) Approach &#8211; 2021<\/strong>\n<ul>\n<li>In 2021, the IMD further enhanced its forecasting accuracy with the introduction of an MME system.\u00a0<\/li>\n<li>This approach incorporated coupled global climate models (CGCMs) from various global climate prediction and research centers, including India\u2019s own MMCFS.\u00a0<\/li>\n<li>The MME system has significantly improved the accuracy of monsoon predictions.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Notable Improvements in Forecast Accuracy<\/strong>\n<ul>\n<li>Since the introduction of SEFS in 2007 and MME in 2021, the IMD&#8217;s operational forecasts have shown marked improvement.\u00a0<\/li>\n<li>The absolute forecast error in India&#8217;s seasonal rainfall has decreased by about 21% between 2007 and 2024 compared to 1989-2006.\u00a0<\/li>\n<li>IMD&#8217;s April forecasts have also become more precise, with deviations of only 2.27 percentage points in the actual rainfall from 2021-2024, well within the forecast range of 4%.<\/li>\n<\/ul>\n<\/li>\n<li><strong>Scope for Further Improvement<\/strong>\n<ul>\n<li>Despite these advancements, there is still room for further refinement.\u00a0<\/li>\n<li>Experts have suggested that the IMD should improve its dynamical models by addressing systematic errors and biases, as well as enhancing teleconnectivity with global climate modes such as the ENSO.\u00a0<\/li>\n<li>This could further enhance the precision of the IMD&#8217;s monsoon forecasts.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h2>Monsoon Forecasting in India FAQs<\/h2>\n<p><strong>Q1.<\/strong> When did systematic monsoon forecasting begin in India?<\/p>\n<p><strong>Ans.<\/strong> Systematic monsoon forecasting began in 1877 after the establishment of the India Meteorological Department (IMD) in 1875.<\/p>\n<p><strong>Q2.<\/strong> Who introduced global atmospheric parameters into India&#8217;s monsoon forecasts?<\/p>\n<p><strong>Ans.<\/strong> Sir Gilbert Walker introduced global atmospheric, land, and ocean parameters into India&#8217;s monsoon forecasting in 1904.<\/p>\n<p><strong>Q3.<\/strong> What was the purpose of the Gowariker model introduced in 1988?<\/p>\n<p><strong>Ans.<\/strong> The Gowariker model aimed to improve forecast accuracy using 16 atmospheric variables through power regression techniques.<\/p>\n<p><strong>Q4.<\/strong> What is the Monsoon Mission Coupled Forecasting System (MMCFS)?<\/p>\n<p><strong>Ans.<\/strong> MMCFS is a dynamic model introduced in 2012 combining ocean, atmosphere, and land data for improved monsoon prediction.<\/p>\n<p><strong>Q5.<\/strong> How has forecast accuracy improved since 2007?<\/p>\n<p><strong>Ans.<\/strong> Forecast error reduced by about 21% between 2007-2024, aided by SEFS and the Multi-Model Ensemble (MME) approach.<\/p>\n<p>\n<strong>Source: <\/strong><a href=\"https:\/\/indianexpress.com\/article\/explained\/explained-climate\/the-history-and-evolution-of-monsoon-forecasting-in-india-9969292\/\" target=\"_blank\" rel=\"nofollow noopener\">IE<\/a> | <a href=\"https:\/\/indianexpress.com\/article\/india\/chasing-monsoon-150-years-origin-story-india-meteorological-department-9107666\/\" target=\"_blank\" rel=\"nofollow noopener\">IE<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Explore the history, challenges, and recent improvements in India&#8217;s monsoon forecasting, from early British efforts to IMD&#8217;s modern dynamic models.<\/p>\n","protected":false},"author":5,"featured_media":46400,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[18],"tags":[],"class_list":{"0":"post-46399","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-upsc-mains-current-affairs","8":"no-featured-image-padding"},"acf":[],"_links":{"self":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts\/46399","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/comments?post=46399"}],"version-history":[{"count":0,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/posts\/46399\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/media\/46400"}],"wp:attachment":[{"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/media?parent=46399"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/categories?post=46399"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/vajiramandravi.com\/current-affairs\/wp-json\/wp\/v2\/tags?post=46399"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}