A high-resolution near-surface meteorological forcing dataset for arid Xinjiang
收藏科学数据银行2025-11-20 更新2026-04-23 收录
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资源简介：
We present a hybrid framework that combines regional modelling with data assimilation and station-informed bias correction to produce a physically coherent, observation-constrained near-surface meteorological dataset for Xinjiang for 1960–2020. First, a regional modelling system is used to obtain spatially continuous and dynamically consistent fields. Station observations are then employed to estimate and apply gridded bias corrections on a common spatial framework, thereby reducing systematic and locally varying errors while preserving cross-variable physical relationships. The resulting dataset provides gridded fields of six key variables, including 2 m air temperature, relative humidity, 10 m wind speed, surface pressure, downward shortwave radiation and precipitation, at multiple temporal resolutions. It is designed as a unified, well-documented forcing dataset to support dry–wet indices, extreme-event analyses, moisture-transport diagnostics and a wide range of hydrological, ecological, agricultural and human–environment applications over Xinjiang’s complex terrain.
提供机构：
Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research; Centre for Human Settlements, Liaoning Normal University; Department of Natural Resources and the Environment, University of Connecticut, Storrs, CT 06269, USA; School of Geographical Sciences, Liaoning Normal University; Beijing Municipal Climate Center, Beijing Meteorological Service; CongXueping; Hungarian University of Agriculture and Life Sciences, Institute of Landscape Architecture Urban Plannino and Garden Art; University of Chinese Academy of Sciences
创建时间：
2025-11-20
