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Constraining snowfall remote sensing using novel high-resolution three-dimensional imaging and mass measurements of hydrometeors in freefall

使用新型高分辨率三维成像和自由落体水凝物质量测量来约束降雪遥感

基本信息

批准号：
254901881
负责人：
Dr. Mathias Gergely
金额：
--
依托单位：
Department of Atmospheric Sciences
依托单位国家：
德国
项目类别：
Research Fellowships
财政年份：
2014
资助国家：
德国
起止时间：
2013-12-31 至 2015-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/254901881?language=en
关键词：
Constraining snowfall remote sensing using

项目摘要

Accurate snowfall retrieval from microwave remote sensing is essential for understanding cloud-precipitation interactions, for weather forecasting and for climate research. However, development of reliable snowfall retrieval algorithms remains severely limited by an absence of detailed snowflake measurements that characterize the natural variability of snowflake mass and three-dimensional (3D) shape. The proposed project aims to (i) obtain these data using novel high-resolution measurement methods and (ii) exploit the measurements to provide look-up tables for the scattering properties of realistic snowflakes.To accomplish these goals, we will acquire the necessary data at an existing mountain laboratory in Utah using a newly developed hotplate device and a recently available automated multi-angle snowflake camera that allows for collecting photographs from multiple directions simultaneously. It is anticipated that each instrument will sample of order one million snowflakes over a single winter season to capture the natural snowflake variability at an unprecedented degree of detail. The modeled scattering properties for these snowflake measurements will be compared to (i) existing microwave scattering calculations for simple idealized snowflake shapes that have been used thus far to approximate real snowflakes and retrieve snowfall from remote-sensing data, and (ii) collocated radar measurements of snowfall. Based on the calculations and experimental validation, we will compile new look-up tables that quantify how the natural variability of snowflake mass and 3D shape relates to microwave remote sensing of clouds and precipitation.

从微波遥感中精确获取降雪量对于理解云-降水相互作用、天气预报和气候研究至关重要。然而，由于缺乏描述雪花质量和三维形状自然变化特征的详细雪花测量，可靠的降雪检索算法的发展仍然受到严重限制。拟议的项目旨在(i)使用新颖的高分辨率测量方法获得这些数据，（ii）利用测量结果提供真实雪花散射特性的查找表。为了实现这些目标，我们将在犹他州现有的山区实验室使用新开发的热板设备和最近可用的自动多角度雪花相机获取必要的数据，该相机可以同时从多个方向收集照片。预计每台仪器将在一个冬季采集100万朵雪花的样本，以前所未有的细节捕捉自然雪花的变化。这些雪花测量的模型散射特性将与(i)现有的简单理想化雪花形状的微波散射计算进行比较，这些计算迄今已用于近似真实雪花并从遥感数据中检索降雪，以及（ii）与雷达测量的降雪。在计算和实验验证的基础上，我们将编制新的查找表，量化雪花质量和三维形状的自然变化与微波遥感云和降水的关系。