全球海气通量格点数据产品

本数据集由中科院海洋大科学研究中心共建单位中科院南海海洋研究所王鑫研究员和张荣望副研究员牵头研制，主要基于卫星遥感和再分析数据，以中国近海浮标、海上平台和通量塔等观测数据为训练数据，采用目标深度神经网络集合平均模型和改进后的COARE 3.5算法等技术研发，有效克服了大气比湿偏差引起的潜热通量低估和海表冷皮效应造成的潜热通量误差等突出问题。与国际主流海气通量产品对比，该产品在中国近海具有显著的区域优势和性能指标优势。

This dataset was developed under the leadership of Researcher Wang Xin and Associate Researcher Zhang Rongwang from the South China Sea Institute of Oceanology (SCSIO), Chinese Academy of Sciences (CAS), a co-established unit of the CAS Ocean Science Research Center. It is primarily developed based on satellite remote sensing and reanalysis data, with in-situ observational data such as buoys, offshore platforms and flux towers in the China Seas serving as its training dataset. Core technologies adopted include the targeted deep neural network ensemble average model and the improved COARE 3.5 algorithm. This dataset effectively addresses key challenges including the underestimation of latent heat flux under moderate atmospheric specific humidity conditions and latent heat flux errors induced by the sea surface skin effect. Compared with internationally mainstream air-sea flux products, this dataset exhibits significant regional and performance advantages in the China Seas.

搜集汇总

背景与挑战

背景概述

该数据集是一个全球海气通量格点数据产品，由中国科学院南海海洋研究所研发，基于卫星遥感和再分析数据，采用深度神经网络和改进算法，有效解决了潜热通量误差问题。数据覆盖1988年1月至2024年12月，水平分辨率为0.25°×0.25°，提供日和月时间分辨率的潜热通量、海表风速等要素，格式为NetCDF，在中国近海具有显著的区域优势。