Daily surface all-wave net radiation over global land (1981—2019) from AVHRR data

Surface net radiation, representing surface radiation energy balance, is closely related to several land processes, such as evapotranspiration, photosynthesis, and turbulent and conductive heat fluxes. Reanalysis products can provide a long-term surface net radiation; however, their coarse spatial resolution and large uncertainties hinder us from well applicating the data at a regional scale. Satellite products also include surface net radiation retrievals with high accuracy. The short time span of satellite products (i.e., GLASS product) makes these satellite products not suitable for long-term climate change study. Therefore, we used a deep learning method to upscale in situ measurements collected from global-distributed sites to generate a daily surface net radiation product with 0.05° spatial resolution from AVHRR data (1981-2019). After comprehensive validation, the RMSE of AVHRR net radiation product was ~26 Wm-2, which is generally better than some current reanalysis and satellite products.

搜集汇总

背景与挑战

背景概述

该数据集是一个全球陆地表面净辐射的日数据产品，覆盖1981年至2019年，基于AVHRR数据通过深度学习方法生成，空间分辨率为0.05°。它旨在解决现有产品空间分辨率低、不确定性大和时间跨度短的问题，验证显示RMSE约为26 Wm-2，优于一些再分析和卫星产品，适用于长期气候变化研究。