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TOSCA: Development of an optimal estimation technique to profile snowing and thick ice clouds by exploiting a suite of active and passive microwave (PHW) sensors in two configurations by coupling detailed microphysical and electromagnetic models of ice cl

TOSCA：通过耦合冰层的详细微物理和电磁模型，利用两种配置的一套主动和被动微波 (PHW) 传感器，开发一种最佳估计技术来描绘降雪和厚冰云。

基本信息

批准号：
35224719
负责人：
Dr. Martin Hagen
金额：
--
依托单位：
Meteorologisches Institut (MI)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2007
资助国家：
德国
起止时间：
2006-12-31 至 2011-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/35224719?language=en
关键词：
TOSCA Development optimal estimation technique

项目摘要

Given the enormous uncertainties in the prediction of frozen hydrometeors in NWP and climate models, reliable monitoring of ice water content (IWC) in the presence of thick ice and snowy conditions at mid and high latitudes is an important goal of the meteorological community. Remote sensing retrievals are the only means suited for this purpose because direct observations, e.g. by airplane, can only deliver snapshots of extremely limited spatial and temporal extent. Moreover, hazards in flying in such conditions are prohibitive for the retrieval of samples of useful quantities. We propose to build a prototype of an optimal-estimation based algorithm for the characterization of snowing and thick ice clouds based on a database of single scattering (SS) computations for non-spherical ice crystals and on studies based on active and PMW observations. The prototype algorithm will be applied to the satellite A-Train constellation2 and to a ground-based suite of instruments located at Umweltforschungsstation Schneefernerhaus (UFS) with the goal of retrieving IWC profiles, and, when possible, mean size and type (habit) for given environmental conditions. Our results will gather an unprecedented test-bed for evaluating cold cloud microphysical schemes and will significantly improve the understanding of the microphysical characteristics of mid-latitude winterly precipitation systems and of related MW signatures.

由于NWP和气候模式中冻结水凝物的预测存在巨大的不确定性，在中高纬度存在厚冰和积雪条件下对冰水含量进行可靠监测是气象界的一个重要目标。遥感检索是适合于这一目的的唯一手段，因为直接观测，例如通过飞机，只能提供极其有限的空间和时间范围的快照。此外，在这种条件下飞行的危险使回收有用数量的样品受到限制。我们建议建立一个原型的最佳估计为基础的算法的表征下雪和厚冰云的基础上的数据库的单散射（SS）计算的非球形冰晶和主动和PMW观测的基础上的研究。原型算法将应用于卫星A-Train星座2和位于Umweltforschungsstation Schneefernerhaus（UFS）的地面仪器套件，目的是检索IWC剖面，并在可能的情况下，给定环境条件下的平均大小和类型（习惯）。我们的研究结果将收集一个前所未有的测试平台，用于评估冷云微物理方案，并将显着提高中纬度冬季降水系统和相关MW签名的微物理特性的理解。