全球月均地表温度数据集（2003-2019）

地表温度（Land Surface Temperature，LST）是地表能量平衡研究的关键参数，被广泛用于气象、气候、水文、农业和生态等领域研究。月均地表温度（Monthly Mean Land Surface Temperature，MMLST）反映了更稳定的年内和年际温度变化，其不仅用作地表模型的输入参数，还用作一般气候趋势研究的重要指标，一种可靠的MMLST产品在全球气候研究和应用中具有重要的实际价值。本数据采用广义三角帽方法（Generalized Three-Cornered Hat，TCH）和极大似然估计（Maximum Likelihood Estimation，MLE）融合由不同的研究团队或机构使用不同的算法生成的四种MMLST产品，这四种MMLST产品分别是：①占文凤生产的2003年-2019年全球逐日1km分辨率地表温度日均温产品数据集（https://cstr.cn/15732.11.nesdc.ecodb.2016YFA0600200.01.005）、②陈学龙生产的2000年-2020年全球月平均地表温度（https://cstr.cn/18406.11.Meteoro.tpdc.271180）、③刘向阳生产的2000年-2020年全球月平均地表温度（https://doi.org/10.5281/zenodo.6618442）、以及④ERA5-Land提供的全球月均地表温度（https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land-monthly-means）。利用2003-2019年期间的AmeriFlux和SURFRAD网络的25个站点的地面实测地表温度评估融合后的月均地表温度产品的精度，其均方根误差（RMSE）约为1.6 K，相比单一的月均地表温度产品，融合后的地表温度产品的精度提高了0.2-1.0 K。Land Surface Temperature (LST) is a critical parameter for surface energy balance research, and is widely utilized in studies across meteorological, climatic, hydrological, agricultural and ecological fields. Monthly Mean Land Surface Temperature (MMLST) captures more stable intra-annual and inter-annual temperature fluctuations, serving not only as an input parameter for surface models but also as a key indicator for general climate trend investigations. A reliable MMLST product holds substantial practical value in global climate research and applications. This dataset fuses four source MMLST products generated by distinct research teams or institutions using different algorithms via the Generalized Three-Cornered Hat (TCH) method and Maximum Likelihood Estimation (MLE). The four products are listed as follows: 1. Global daily 1 km-resolution daily mean land surface temperature product dataset spanning 2003–2019, produced by Zhan Wenfeng (https://cstr.cn/15732.11.nesdc.ecodb.2016YFA0600200.01.005) 2. Global monthly mean land surface temperature product spanning 2000–2020, produced by Chen Xuelong (https://cstr.cn/18406.11.Meteoro.tpdc.271180) 3. Global monthly mean land surface temperature product spanning 2000–2020, produced by Liu Xiangyang (https://doi.org/10.5281/zenodo.6618442) 4. Global monthly mean land surface temperature product provided by ERA5-Land (https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land-monthly-means) The accuracy of the fused MMLST product was validated using in-situ measured land surface temperatures collected from 25 sites within the AmeriFlux and SURFRAD networks during 2003–2019. The product exhibits a Root Mean Square Error (RMSE) of approximately 1.6 K, and its accuracy is improved by 0.2–1.0 K relative to individual MMLST products.

搜集汇总

背景与挑战

背景概述

该数据集是全球月均地表温度数据（2003-2019），通过融合四种不同来源的产品，采用广义三角帽方法和极大似然估计技术，显著提升了精度，均方根误差约为1.6 K，相比单一产品提高了0.2-1.0 K。数据具有月时间分辨率和1km-10km空间分辨率，以GEOTIFF格式存储，便于在多种软件和编程语言中使用，适用于气象、气候、水文等领域的研究。