Latent heating profiles from GOES-16 and its comparison to heating from NEXRAD and GPM

Yoonjin Lee, C. Kummerow, M. Zupanski
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引用次数: 1

Abstract

Abstract. Latent heating (LH) is an important quantity in both weather forecasting and climate analysis, being the essential factor driving convective systems. Yet, inferring LH rates from our current observing systems is challenging at best. For climate studies, LH has been retrieved from the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) using model simulations in the look-up table (LUT) that relates instantaneous radar profiles to corresponding heating profiles. These radars, first on TRMM and then Global Precipitation Measurement (GPM), provide a continuous record of LH. However, with observations approximately 3 days apart, its temporal resolution is too coarse to be used to initiate convection in forecast models. In operational forecast models such as High-Resolution Rapid Refresh (HRRR), convection is initiated from LH derived from ground based radar. Despite the high spatial and temporal resolution of ground-based radars, one disadvantage of using it is that its data are only available over well observed land areas. This study suggests a method to derive LH from the Geostationary Operational-Environmental Satellite-16 (GOES-16) in near-real time. Even though the visible and infrared channels on the Advanced Baseline Imager (ABI) provide mostly cloud top information, rapid changes in cloud top visible and infrared properties, when coupled to a LUT similar to those used by the TRMM and GPM radars, can equally be used to derive LH profiles for convective regions using model simulations coupled to a convective classification scheme and channel 14 (11.2 μm) brightness temperature. Convective regions detected by GOES-16 are assigned LH from the LUT, and they are compared with LH from NEXRAD and one of Dual-frequency Precipitation Radar (DPR) products, Goddard Convective-Stratiform Heating (CSH). LH obtained from GOES-16 show similar magnitude with NEXRAD and CSH, and vertical distribution of LH is also very similar with CSH. Overall, GOES LH appear to have the ability to mimic LH from radars, although the area identified as convective is roughly 25 % smaller than the current HRRR model, while the heating is correspondingly higher.
GOES-16的潜热分布及其与NEXRAD和GPM的比较
摘要潜热是天气预报和气候分析中的一个重要量,是对流系统的重要驱动因素。然而,从我们目前的观测系统中推断LH率充其量是具有挑战性的。对于气候研究,利用查找表(LUT)中的模式模拟,从热带降雨测量任务(TRMM)的降水雷达(PR)中检索了LH,该查找表将瞬时雷达廓线与相应的加热廓线联系起来。这些雷达首先在TRMM上,然后在全球降水测量(GPM)上,提供LH的连续记录。然而,由于观测间隔约为3天,其时间分辨率太粗,无法用于预报模式中启动对流。在高分辨率快速刷新(HRRR)等业务预报模式中,对流是由地面雷达的LH引发的。尽管地面雷达具有很高的时空分辨率,但使用它的一个缺点是,它的数据只能在观测良好的陆地地区使用。本研究提出了一种从地球同步运行环境卫星-16 (GOES-16)近实时获取LH的方法。尽管高级基线成像仪(ABI)上的可见光和红外通道提供的主要是云顶信息,但当与TRMM和GPM雷达使用的LUT相结合时,云顶可见光和红外特性的快速变化也可以同样用于导出对流区域的LH剖面,使用模型模拟耦合对流分类方案和通道14 (11.2 μm)亮度温度。GOES-16探测到的对流区域由LUT分配LH值,并与NEXRAD和双频降水雷达(DPR)产品之一Goddard对流-层状加热(CSH)的LH值进行比较。GOES-16获得的LH与NEXRAD和CSH的量级相似,LH的垂直分布也与CSH非常相似。总的来说,GOES LH似乎有能力从雷达上模拟LH,尽管被确定为对流的区域比目前的HRRR模型小大约25%,而加热相应更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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