Enhancing Land Surface Net Radiation Simulations in Arid Regions via Surface Albedo Data Assimilation

Enhancing Land Surface Net Radiation Simulations in Arid Regions via Surface Albedo Data Assimilation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Enhancing Land Surface Net Radiation Simulations in Arid Regions via Surface Albedo Data Assimilation Wenjing Ma, Wanni Ma, Hongyu Su, Pei Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8093599/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Accurate simulation of surface net radiation (Rn) is essential for understanding land-atmosphere interactions and managing agricultural water and energy budgets. This study develops an Ensemble Kalman Filter (EnKF)-based albedo assimilation system, integrated with an energy-balanced Soil–Plant–Atmosphere Continuum (SPAC) model, to improve Rn simulations in the Heihe River Basin, a typical arid and semi-arid agricultural region. The system dynamically updates surface albedo through Bayesian inference, optimizing vegetation and soil reflectance parameters using multi-source observational data. Results demonstrate that the assimilation framework significantly enhances Rn simulation accuracy: the coefficient of determination increased by 16–45%, with the most pronounced improvements observed in alpine meadow and cropland ecosystems. The RMSE decreased by up to 45.7% at the Arou station, and systematic biases in farmland radiation simulations were effectively corrected. The proposed method outperformed single-variable assimilation approaches, particularly in heterogeneous landscapes, and successfully captured diurnal variations in albedo. A novel stratification scheme, which explicitly separates vegetation and soil albedo components, improved physical consistency and sensitivity to leaf area index (LAI) and soil moisture dynamics. These advancements provide a robust foundation for enhancing ecohydrological modeling in arid regions. Future efforts will focus on integrating multi-sensor data fusion and thermal inertia corrections to further improve sub-daily simulation capabilities. surface albedo net radiation ensemble Kalman filter SPAC model arid region agriculture Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8093599","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":549857081,"identity":"a9333bb8-a12c-45ce-949c-1eff348b5eb7","order_by":0,"name":"Wenjing Ma","email":"","orcid":"","institution":"Beijing Normal University","correspondingAuthor":false,"prefix":"","firstName":"Wenjing","middleName":"","lastName":"Ma","suffix":""},{"id":549857082,"identity":"2a47e1ee-f02a-4f3c-92c2-e3438b8a0cb7","order_by":1,"name":"Wanni Ma","email":"","orcid":"","institution":"Beijing Normal 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