Data Validation and Mesoscale Assimilation of Himawari-8 Optimal Cloud Analysis Products
Data Validation and Mesoscale Assimilation of Himawari-8 Optimal Cloud Analysis Products
复制标题
Himawari-8 最佳云分析产品的数据验证和中尺度同化
DOI：
10.1175/jtech-d-20-0015.1
复制
发表时间：
2021
影响因子：
2.2
通讯作者：
and Ko Koizumi
中科院分区：
文献类型：
--
作者：
Michiko Otsuka;Hiromu Seko;Masahiro Hayashi;and Ko Koizumi
Himawari-8 optimal cloud analysis（OCA）利用先进的Himawari成像仪的全部16个通道，提供云的特性，如云相、顶压、光学厚度、有效半径和水路径。通过使用OCA，可以以高时空分辨率和广泛的覆盖范围推断水汽分布，包括海洋，这对于改善用于预测日本频繁发生的暴雨的初始状态是有用的。OCA产品首先通过将其与不同类型的数据集（地面、探空仪和云高计观测值）以及模型输出进行比较来评估，以确定其数据特征。总体而言，OCA数据与低至中层中等光学厚度水云的观测结果一致。其次，伪相对湿度数据来自OCA产品，并利用同化试验的几个暴雨的情况下，进行了与日本气象厅的非静力模式为基础的变分资料同化系统。OCA伪相对湿度的同化导致水汽场的初始条件与对照相比有显着差异，特别是在OCA云被检测到的地方，其影响持续时间相对较长的预报小时数。同化对风速等其他变量的影响也被看到。当OCA数据成功地代表了来自海洋上空的低空流入时，它们在延长的预测时间内对降水预测产生了积极影响。
Himawari-8optimal cloud analysis (OCA), which employs all 16 channels of the Advanced Himawari Imager, provides cloud properties such as cloud phase, top pressure, optical thickness, effective radius, and water path. By using OCA, the water vapor distribution can be inferred with high spatiotemporal resolution and with a wide coverage, including over the ocean, which can be useful for improving initial states for prediction of the torrential rainfalls that occur frequently in Japan. OCA products were first evaluated by comparing them with different kinds of datasets (surface, sonde, and ceilometer observations) and with model outputs, to determine their data characteristics. Overall, OCA data were consistent with observations of water clouds with moderate optical thicknesses at low to midlevels. Next, pseudorelative humidity data were derived from the OCA products, and utilized in assimilation experiments of a few heavy rainfall cases, conducted with the Japan Meteorological Agency’s nonhydrostatic model–based Variational Data Assimilation System. Assimilation of OCA pseudorelative humidities caused there to be significant differences in the initial conditions of water vapor fields compared to the control, especially where OCA clouds were detected, and their influence lasted relatively long in terms of forecast hours. Impacts of assimilation on other variables, such as wind speed, were also seen. When the OCA data successfully represented low-level inflows from over the ocean, they positively impacted precipitation forecasts at extended forecast times.