Estimations of Land Surface Characteristic Parameters and Turbulent Heat Fluxes over the Tibetan Plateau Based on FY-4A/AGRI Data

Abstract

Accurate estimates of land surface characteristic parameters and turbulent heat fluxes play an important role in the understanding of land-atmosphere interaction. In this study, Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI) satellite data and the China Land Data Assimilation System (CLDAS) meteorological forcing dataset CLDAS-V2.0 were applied for the retrieval of broadband albedo, land surface temperature (LST), radiation flux components, and turbulent heat fluxes over the Tibetan Plateau (TP). The FY-4A/AGRI and CLDAS-V2.0 data from 12 March 2018 to 30 April 2018 were first used to estimate the hourly turbulent heat fluxes over the TP. The time series data of in-situ measurements from the Tibetan Observation and Research Platform were divided into two halves—one for developing retrieval algorithms for broadband albedo and LST based on FY-4A, and the other for the cross validation. Results show the root-mean-square errors (RMSEs) of the FY-4A retrieved broadband albedo and LST were 0.0309 and 3.85 K, respectively, which verifies the applicability of the retrieval method. The RMSEs of the downwelling/upwelling shortwave radiation flux and downwelling/upwelling longwave radiation flux were 138.87/32.78 W m⁻² and 51.55/17.92 W m⁻², respectively, and the RMSEs of net radiation flux, sensible heat flux, and latent heat flux were 58.88 W m⁻², 82.56 W m⁻² and 72.46 W m⁻², respectively. The spatial distributions and diurnal variations of LST and turbulent heat fluxes were further analyzed in detail.

摘要

地表特征参数和湍流热通量的准确估算对地–气相互作用研究至关重要。利用FY-4A/AGRI卫星数据(2018年3月12日至2018年4月30日)和CLDAS-V2.0气象驱动数据进行青藏高原地区地表宽波段反照率、地表温度、辐射四分量和湍流热通量的估算,首次得到基于FY-4A的小时尺度地表热通量数据。基于青藏高原观测研究平台实测数据的交叉验证表明,地表宽波段反照率和地表温度的均方根误差分别为0.0309和3.85 K。下行/上行短波辐射通量、下行/上行长波辐射通量、净辐射通量、感热通量和潜热通量的均方根误差分别为138.87/32.78 W m−2,51.55/17.92 W m−2,58.88 W m−2,82.56 W m−2和72.46 W m−2。在此基础上,进一步详细分析了地表温度和湍流热通量的日变化和空间分布特征。