Abstract:

Using the matched data between infrared images of the geostationary meteorological satellite Himawari-8 and the product 2AGPROFGMI of Global Precipitation Measurement (GPM), the matched infrared brightness temperature (BT), brightness temperature difference (BTD) and surface precipitation are connected by pixel to pixel. Further more, because of the advantage of the more channels of geostationary meteorological satellite, two-dimensional and three-dimensional lookup tables of rain rate (RR) are established with the matched infrared brightness temperature, brightness temperature difference and surface precipitation. The lookup tables which can identify the rain rate of different grades are found by the retrieval tests. The three-dimensional lookup tables (BT10.4, BTD12.4-10.4, BTD6.2-7.3) show higher probability of detection (POD=0.8817) and lower false alarm rate (FAR=0.4042) when detecting the rain, so it can identify the areas of rainfall.

Key words: satellite remote sensing, brightness temperature, brightness temperature difference, rain rate, retrieval

摘要：

利用静止气象卫星Himawari-8的红外图像数据, 结合全球降雨测量计划的降水产品2AGPROFGMI, 通过将匹配的红外亮温和亮温差数据点与近地面雨强数据点一一对应, 使二者之间建立联系。利用静止气象卫星通道多的优点, 进一步建立多个以红外亮温(BT)、亮温差(BTD)以及近地面雨强为参数的二维和三维雨强查算表。通过反演试验, 找到能够较好地识别不同等级降雨强度的查算表, 其中三维查算表(BT10.4, BTD12.4-10.4, BTD6.2-7.3)对降雨事件表现出较高的检测概率(POD=0.8817)和较低的错判率(FAR=0.4042), 可以较好地判识降雨区域。

关键词: 卫星遥感, 亮温, 亮温差, 雨强, 反演