{"id":8885,"date":"2025-08-18T12:02:37","date_gmt":"2025-08-18T17:02:37","guid":{"rendered":"https:\/\/permafrostnet.ca\/?p=8885"},"modified":"2026-07-22T08:19:50","modified_gmt":"2026-07-22T13:19:50","slug":"parameter-optimization-for-global-soil-carbon-simulations-not-a-simple-problem","status":"publish","type":"post","link":"https:\/\/permafrostnet.ca\/fr\/blog\/parameter-optimization-for-global-soil-carbon-simulations-not-a-simple-problem\/","title":{"rendered":"Parameter optimization for global soil carbon simulations: Not a simple problem"},"content":{"rendered":"<h2 id=\"wp-block-themeisle-blocks-advanced-heading-e990b683\" class=\"wp-block-themeisle-blocks-advanced-heading wp-block-themeisle-blocks-advanced-heading-e990b683\">Soils store large amounts of organic carbon that could be released into the atmosphere due to climate change, but future projections from numerical models of soil organic carbon dynamics remain highly uncertain.&nbsp;<\/h2>\n\n\n\n<p>Une \u00e9tude r\u00e9cente de <a href=\"https:\/\/permafrostnet.ca\/fr\/people\/charles-gauthier\/\">Charles Gauthier<\/a> used Bayesian optimization techniques and global sensitivity analysis to better constrain the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) model\u2019s soil organic carbon parameters.<\/p>\n\n\n\n<p>Getting a handle on how soil stores and releases carbon is critical for modeling climate change, yet global simulations face many challenges due to uncertain parameters and sparse data. The team explored different sets of parameters and tested two types of loss functions, finding that this choice can greatly influence model outcomes.<\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large\"><img decoding=\"async\" width=\"1024\" height=\"612\" src=\"https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0001-m-1024x612.jpg\" alt=\"\" class=\"wp-image-8888\" srcset=\"https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0001-m-1024x612.jpg 1024w, https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0001-m-300x179.jpg 300w, https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0001-m-768x459.jpg 768w, https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0001-m-1536x918.jpg 1536w, https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0001-m-18x12.jpg 18w, https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0001-m.jpg 1920w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Schematic representation of the optimization workflow.<\/figcaption><\/figure>\n<\/div>\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>The best parameter set resulted in a 12% improvement when compared to observations and matched well with global estimates of soil carbon stocks, particularly at high latitudes. However, the study also points out that certain regions\u2014like the vast needle-leaf forests of Siberia\u2014remain poorly observed and contribute to ongoing uncertainty. By flagging these gaps, the research not only offers a more accurate model but also calls for more targeted data collection and optimization approaches going forward, aiming to close the loop on carbon-climate feedbacks for better future predictions.<\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-large is-resized\"><img decoding=\"async\" width=\"1024\" height=\"377\" src=\"https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0007-m-1024x377.jpg\" alt=\"\" class=\"wp-image-8890\" style=\"width:1024px;height:auto\" srcset=\"https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0007-m-1024x377.jpg 1024w, https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0007-m-300x110.jpg 300w, https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0007-m-768x283.jpg 768w, https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0007-m-1536x566.jpg 1536w, https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0007-m-18x7.jpg 18w, https:\/\/permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0007-m.jpg 1920w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\">Top meter soil organic carbon (SOC) content across the Northern Circumpolar Soil Carbon Database domain obtain with the default parameterization (SDEF) and the two optimized parameter sets (S2EO and SPMO). SOC content is averaged over the 1950\u20132000 period.<\/figcaption><\/figure>\n<\/div>\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p>Gauthier,&nbsp;C. B.,&nbsp;&nbsp;Melton,&nbsp;J. R.,&nbsp;&nbsp;Meyer,&nbsp;G.,&nbsp;&nbsp;Raj Deepak,&nbsp;S. N., &amp;&nbsp;&nbsp;Sonnentag,&nbsp;O.&nbsp;(2025).&nbsp;&nbsp;<strong>Parameter optimization for global soil carbon simulations: Not a simple problem<\/strong>.&nbsp;Journal of Advances in Modeling Earth Systems,&nbsp;&nbsp;17, e2024MS004577.&nbsp;<a href=\"https:\/\/doi.org\/10.1029\/2024MS004577\">https:\/\/doi.org\/10.1029\/2024MS004577<\/a><\/p>\n\n\n\n<div style=\"height:44px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><\/p>","protected":false},"excerpt":{"rendered":"<p>A recent study by Charles Gauthier used Bayesian optimization techniques and global sensitivity analysis to better constrain the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) model\u2019s soil organic carbon parameters. Getting a handle on how soil stores and releases carbon is critical for modeling climate change, yet global simulations [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":8889,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_EventAllDay":false,"_EventTimezone":"","_EventStartDate":"","_EventEndDate":"","_EventStartDateUTC":"","_EventEndDateUTC":"","_EventShowMap":false,"_EventShowMapLink":false,"_EventURL":"","_EventCost":"","_EventCostDescription":"","_EventCurrencySymbol":"","_EventCurrencyCode":"","_EventCurrencyPosition":"","_EventDateTimeSeparator":"","_EventTimeRangeSeparator":"","_EventOrganizerID":[],"_EventVenueID":[],"_OrganizerEmail":"","_OrganizerPhone":"","_OrganizerWebsite":"","_VenueAddress":"","_VenueCity":"","_VenueCountry":"","_VenueProvince":"","_VenueState":"","_VenueZip":"","_VenuePhone":"","_VenueURL":"","_VenueStateProvince":"","_VenueLat":"","_VenueLng":"","_VenueShowMap":false,"_VenueShowMapLink":false,"_themeisle_gutenberg_block_has_review":false,"footnotes":""},"categories":[36,35,118],"tags":[172,158,173,174,175,176],"class_list":["post-8885","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","category-news","category-publications","tag-bayesian-optimization","tag-classic","tag-land-surface-model","tag-sensitivity-analysis","tag-soil-organic-carbon","tag-soil-respiration"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Parameter optimization for global soil carbon simulations: Not a simple problem &#8211; PermafrostNet<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.permafrostnet.ca\/news\/parameter-optimization-for-global-soil-carbon-simulations-not-a-simple-problem\/\" \/>\n<meta property=\"og:locale\" content=\"fr_CA\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Parameter optimization for global soil carbon simulations: Not a simple problem &#8211; PermafrostNet\" \/>\n<meta property=\"og:description\" content=\"A recent study by Charles Gauthier used Bayesian optimization techniques and global sensitivity analysis to better constrain the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) model\u2019s soil organic carbon parameters. Getting a handle on how soil stores and releases carbon is critical for modeling climate change, yet global simulations [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.permafrostnet.ca\/news\/parameter-optimization-for-global-soil-carbon-simulations-not-a-simple-problem\/\" \/>\n<meta property=\"og:site_name\" content=\"PermafrostNet\" \/>\n<meta property=\"article:published_time\" content=\"2025-08-18T17:02:37+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-07-22T13:19:50+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.permafrostnet.ca\/wp-content\/uploads\/2025\/10\/jame70159-fig-0005-m.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1920\" \/>\n\t<meta property=\"og:image:height\" content=\"1015\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"Tristan MacLean\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@PermafrostNet\" \/>\n<meta name=\"twitter:site\" content=\"@PermafrostNet\" \/>\n<meta name=\"twitter:label1\" content=\"\u00c9crit par\" \/>\n\t<meta name=\"twitter:data1\" content=\"Tristan MacLean\" \/>\n\t<meta name=\"twitter:label2\" content=\"Estimation du temps de lecture\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/www.permafrostnet.ca\\\/news\\\/parameter-optimization-for-global-soil-carbon-simulations-not-a-simple-problem\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/www.permafrostnet.ca\\\/news\\\/parameter-optimization-for-global-soil-carbon-simulations-not-a-simple-problem\\\/\"},\"author\":{\"name\":\"Tristan MacLean\",\"@id\":\"https:\\\/\\\/www.permafrostnet.ca\\\/#\\\/schema\\\/person\\\/70e67e64ed65de9f0559f2a871467859\"},\"headline\":\"Parameter optimization for global soil carbon simulations: Not a simple problem\",\"datePublished\":\"2025-08-18T17:02:37+00:00\",\"dateModified\":\"2026-07-22T13:19:50+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/www.permafrostnet.ca\\\/news\\\/parameter-optimization-for-global-soil-carbon-simulations-not-a-simple-problem\\\/\"},\"wordCount\":319,\"publisher\":{\"@id\":\"https:\\\/\\\/www.permafrostnet.ca\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/www.permafrostnet.ca\\\/news\\\/parameter-optimization-for-global-soil-carbon-simulations-not-a-simple-problem\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/permafrostnet.ca\\\/wp-content\\\/uploads\\\/2025\\\/10\\\/jame70159-fig-0005-m.jpg\",\"keywords\":[\"bayesian optimization\",\"CLASSIC\",\"land surface model\",\"sensitivity analysis\",\"soil organic carbon\",\"soil respiration\"],\"articleSection\":[\"Blog\",\"News\",\"Publications\"],\"inLanguage\":\"fr-CA\"},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.permafrostnet.ca\\\/news\\\/parameter-optimization-for-global-soil-carbon-simulations-not-a-simple-problem\\\/\",\"url\":\"https:\\\/\\\/www.permafrostnet.ca\\\/news\\\/parameter-optimization-for-global-soil-carbon-simulations-not-a-simple-problem\\\/\",\"name\":\"Parameter optimization for global soil carbon simulations: Not a simple problem &#8211; 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