首页> 外文期刊>Journal of Applied Meteorology and Climatology >Dependence of the Ice Water Content and Snowfall Rate on Temperature, Globally: Comparison of in Situ Observations, Satellite Active Remote Sensing Retrievals, and Global Climate Model Simulations
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Dependence of the Ice Water Content and Snowfall Rate on Temperature, Globally: Comparison of in Situ Observations, Satellite Active Remote Sensing Retrievals, and Global Climate Model Simulations

机译:冰水含量和降雪率对温度的依赖性,全球范围内:原位观察,卫星活跃遥感检索和全球气候模型模拟的比较

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摘要

Cloud ice microphysical properties measured or estimated from in situ aircraft observations are compared with global climate models and satellite active remote sensor retrievals. Two large datasets, with direct measurements of the ice water content (IWC) and encompassing data from polar to tropical regions, are combined to yield a large database of in situ measurements. The intention of this study is to identify strengths and weaknesses of the various methods used to derive ice cloud microphysical properties. The in situ data are measured with total water hygrometers, condensed water probes, and particle spectrometers. Data from polar, midlatitude, and tropical locations are included. The satellite data are retrieved from CloudSat/CALIPSO [the CloudSat Ice Cloud Property Product (2C-ICE) and 2C-SNOW-PROFILE] and Global Precipitation Measurement (GPM) Level2A. Although the 2CICE retrieval is for IWC, a method to use the IWC to get snowfall rates S is developed. The GPM retrievals are for snowfall rate only. Model results are derived using the Community Atmosphere Model (CAM5) and the Met Office Unified Model [Global Atmosphere 7 (GA7)]. The retrievals and model results are related to the in situ observations using temperature and are partitioned by geographical region. Specific variables compared between the in situ observations, models, and retrievals are the IWCand S. Satellite-retrieved IWCs are reasonably close in value to the in situ observations, whereas the models' values are relatively low by comparison. Differences between the in situ IWCs and those from the other methods are compounded when S is considered, leading to model snowfall rates that are considerably lower than those derived from the in situ data. Anomalous trends with temperature are noted in some instances.
机译:从原位飞机观察测量或估计的云冰微神科性质与全球气候模型和卫星主动远程传感器检索进行比较。两种大型数据集,具有直接测量冰水含量(IWC)并包含来自极北极地地区的数据,以产生大量的原位测量数据库。本研究的目的是识别用于衍生冰云微神经性质的各种方法的优点和弱点。用总水湿镜,冷凝水探针和粒子光谱仪测量原位数据。包括来自极地,中间位置和热带地点的数据。从CloudSat / Calipso [CloudSat冰云属性产品(2C-ICE)和2C-Snople型]和全局降水测量(GPM)级别2A中检索卫星数据。虽然2CICE检索是用于IWC的,但开发了一种使用IWC来获得降雪率的方法。 GPM检索仅用于降雪率。模型结果使用社区氛围模型(CAM5)和MET Office Unified Model [全球大气7(GA7)]。检索和模型结果与使用温度的原位观察有关,并由地理区域划分。在原位观察,模型和检索之间比较的特定变量是IWCAND S.卫星检索的IWC在原位观察中合理地接近值,而模型的值相对较低。当考虑S时,原位IWC和来自其他方法的那些之间的差异化,导致模型降雪率比从原位数据衍生的降雪率。在某些情况下,注意到温度的异常趋势。

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