Daily surface all-wave net radiation over global land (1981—2019) from AVHRR data
收藏资源简介：
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.
地表净辐射（surface net radiation）作为地表辐射能量平衡的核心表征，与蒸散发、光合作用、湍流通量及传导热通量等多项陆地物理过程密切相关。再分析产品（reanalysis products）可提供长期序列的地表净辐射数据，但其空间分辨率偏粗糙且存在较大不确定性，制约了其在区域尺度上的精细化应用。卫星遥感产品同样包含高精度的地表净辐射反演结果，但这类产品（如GLASS产品）的时间序列跨度较短，无法满足长期气候变化研究的需求。因此，本研究采用深度学习方法，对全球分布式观测站点采集的原位实测数据进行空间尺度升尺度处理，基于1981—2019年先进甚高分辨率辐射计（Advanced Very High Resolution Radiometer, AVHRR）数据，生成了空间分辨率为0.05°的逐日地表净辐射数据集产品。经多维度综合验证，该AVHRR地表净辐射产品的均方根误差（Root Mean Square Error, RMSE）约为26 W·m⁻²，整体性能优于当前部分主流再分析产品与卫星反演产品。
