Tao W-K, Iguchi T, Lang S
Mesoscale Atmospheric Processes Laboratory NASA/Goddard Space Flight Center Greenbelt, MD 20771.
Earth System Science Interdisciplinary Center University of Maryland College Park, MD.
J Appl Meteorol Climatol. 2019 May;58(5):921-946. doi: 10.1175/jamc-d-18-0215.1. Epub 2019 Apr 16.
The Goddard Convective-Stratiform Heating (CSH) algorithm has been used to retrieve latent heating (LH) associated with clouds and cloud systems in support of the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) mission. The CSH algorithm required the use of a cloud-resolving model (CRM) to simulate LH profiles to build look-up tables (LUTs). However, the current LUTs in the CSH algorithm are not suitable for retrieving LH profiles at high latitudes or winter conditions that are needed for GPM. The NASA Unified-Weather Research and Forecasting (NU-WRF) model is used to simulate three eastern continental US (CONUS) synoptic winter and three western coastal/offshore events. The relationship between LH structures (or profiles) and other precipitation properties (radar reflectivity, freezing level height, echo-top height, maximum radar reflectivity height and surface precipitation rate) is examined, and a new classification system is adopted with varying ranges for each of these precipitation properties to create LUTs representing high latitude/winter conditions. The performance of the new LUTs is examined using a self-consistency check for one CONUS and one West Coast offshore event by comparing LH profiles retrieved from the LUTs using model-simulated precipitation properties with those originally simulated by the model. The results of the self-consistency check validate the new classification and LUTs. High latitude retrievals from the new LUTs are merged with those from the CSH algorithm to retrieve LH profiles over the GPM domain using precipitation properties retrieved from the GPM combined algorithm.
戈达德对流层状加热（CSH）算法已被用于反演与云及云系统相关的潜热加热（LH），以支持热带降雨测量任务（TRMM）和全球降水测量（GPM）任务。CSH算法需要使用云分辨模型（CRM）来模拟潜热加热廓线以构建查找表（LUT）。然而，CSH算法中当前的查找表并不适用于反演GPM所需的高纬度或冬季条件下的潜热加热廓线。美国国家航空航天局统一天气研究与预报（NU-WRF）模型被用于模拟美国东部大陆（CONUS）的三次冬季天气尺度事件以及西部沿海/近海的三次事件。研究了潜热加热结构（或廓线）与其他降水特性（雷达反射率、冻结层高度、回波顶高度、最大雷达反射率高度和地面降水率）之间的关系，并采用了一种新的分类系统，为这些降水特性中的每一个设定不同的范围，以创建代表高纬度/冬季条件的查找表。通过将使用模型模拟降水特性从查找表中反演得到的潜热加热廓线与模型最初模拟的廓线进行比较，利用一个CONUS事件和一个西海岸近海事件的自一致性检验来检验新查找表的性能。自一致性检验的结果验证了新的分类和查找表。利用从GPM组合算法中反演得到的降水特性，将新查找表在高纬度地区的反演结果与CSH算法的反演结果合并，以反演GPM区域上的潜热加热廓线。
