东亚区域0.02°逐小时无缝地表温度数据集（2016-2021）

逐小时空间完整的地表温度产品在冻融状态监测、夏季高温热浪监测等领域具有广泛的应用需求。基于热红外遥感反演的地表温度精度较高，但是容易受到云雾的影响，空间上不连续，这给用户带来诸多不便，也极大地限制了其应用。模式模拟的地表温度虽时空完整，但空间分辨率低，精度差。因此融合遥感反演的地表温度和模式模拟的地表温度，是获取逐小时空间完整地表温度的有效途径。基于此，作者发展了生成东亚区域0.02°逐小时无缝地表温度的融合方法，并制备了相应的数据集（2016-2021）。
本数据集为东亚区域0.02°逐小时无缝地表温度数据集产品（2016-2021年）。首先采用iTES算法反演葵花8/AHI 地表温度，之后对CLDAS LST 进行偏差校正以消除其系统偏差，最后使用多尺度卡尔曼滤波融合葵花8/AHI LST和CLDAS LST，生成0.02°逐小时无缝地表温度数据集。地面验证结果表明，全天地表温度的均方根误差（RMSE）约为3K，精度较好。
本数据集的时间分辨率为1小时，空间分辨率0.02°，时间跨度为2016年-2021年，空间范围为0-60°N，80°E-140°E。

Hourly spatially seamless land surface temperature (LST) products have broad application demands in fields such as freeze-thaw state monitoring and summer high-temperature heatwave monitoring. LST retrieved via thermal infrared remote sensing has high accuracy but is easily affected by clouds and fog, resulting in spatial discontinuity, which brings great inconvenience to users and severely limits its applications. Although LST simulated by numerical models is temporally and spatially complete, it has low spatial resolution and poor accuracy. Therefore, fusing remotely sensed LST and model-simulated LST is an effective way to obtain hourly spatially seamless LST. Based on this, the authors developed a fusion method for generating hourly seamless LST with a spatial resolution of 0.02° over East Asia, and produced the corresponding dataset (2016–2021).

This dataset is an hourly seamless LST product over East Asia with a spatial resolution of 0.02° spanning 2016–2021. First, the iTES algorithm is used to retrieve LST from Himawari-8/AHI data. Then, bias correction is performed on CLDAS LST to eliminate its systematic bias. Finally, multi-scale Kalman filtering is employed to fuse Himawari-8/AHI LST and CLDAS LST, generating the hourly seamless LST dataset with a spatial resolution of 0.02°. Ground validation results show that the root mean square error (RMSE) of all-day LST is approximately 3 K, indicating good accuracy.

The temporal resolution of this dataset is 1 hour, spatial resolution is 0.02°, temporal coverage ranges from 2016 to 2021, and spatial coverage spans 0–60°N and 80°E–140°E.

搜集汇总

背景与挑战

背景概述

该数据集是东亚区域2016年至2021年的逐小时无缝地表温度产品，空间分辨率为0.02°，通过融合葵花8/AHI遥感反演和CLDAS模式模拟数据生成，以解决热红外遥感受云雾影响导致的空间不连续问题。数据集具有较高的时空完整性，全天地表温度的均方根误差约为3K，适用于冻融状态监测、夏季高温热浪监测等领域，数据量达298.49 GB并以开放获取方式共享。