Supplementary data for "Satellite Residual Two-stage Convolutional Neural Network Heating (R2CH) Algorithm for Retrieving Latent Heat between Rain Top and Cloud Top"

This dataset is the supplementary data for "Satellite Residual Two-stage Convolutional Neural Network Heating (R2CH) Algorithm for Retrieving Latent Heat between Rain Top and Cloud Top". The dataset contains R2CH and CNNH retrievals of WRF and GPM DPR, CTH from Himawari-8 satellite. This work utilized the Advanced Research WRF model Version 3.4 to perform cloud simulations in the study area (31°N - 51°N,107°E - 131°E). The WRF model simulation used two nested domains, with internal and external spatial resolutions of 3km and 9km, respectively, and the output data have a total of 55 vertical layers (vertical resolution is 0.25km below 5km). LH at each layer was derived from the calculations of water phase transition among associated hydrometeors based on WRF standard outputs. Contact: For further questions please contact Xuanye Xu ([e-mail]).本数据集为论文《卫星残差两阶段卷积神经网络加热（R2CH）算法反演雨顶与云顶间潜热》的配套补充数据。本数据集包含WRF与GPM DPR的R2CH及CNNH反演结果，以及向日葵8号（Himawari-8）卫星的云顶高度（Cloud Top Height, CTH）数据。本研究采用高级研究版WRF模式（Advanced Research WRF Model）3.4版本，对研究区域（31°N - 51°N，107°E - 131°E）开展云模拟。WRF模式模拟采用双重嵌套区域，内外层空间分辨率分别为3km与9km，输出数据共包含55层垂直分层（5km以下垂直分辨率为0.25km）。基于WRF标准输出结果，通过相关水凝物的水相转变过程计算，可得到各层的潜热（Latent Heat, LH）数据。联系方式：如有进一步疑问，请联系徐轩晔（Xuanye Xu），邮箱：[e-mail]。