DOI: | 10.2172/1121094
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报告号: | Final Report
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报告题名: | Final Report fir DE-SC0005507 (A1618): The Development of an Improved Cloud Microphysical Product for Model and Remote Sensing Evaluation using RACORO Observations |
作者: | McFarquhar, Greg M.
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出版年: | 2012
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发表日期: | 2012-09-21
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国家: | 美国
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语种: | 英语
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中文主题词: | 散射
; 云
; 雷达
; 雷达反射率
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主题词: | SCATTERING
; CLOUDS
; RADAR
; RADAR REFLECTIVITY
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英文摘要: | We proposed to analyze data collected during the Routine Aerial Facilities (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) in order to develop an integrated product of cloud microphysical properties (number concentration of drops in different size bins, total liquid drop concentration integrated over all bin sizes, liquid water content LWC, extinction of liquid clouds, effective radius of water drops, and radar reflectivity factor) that could be used to evaluate large-eddy simulations (LES), general circulation models (GCMs) and ground-based remote sensing retrievals, and to develop cloud parameterizations with the end goal of improving the modeling of cloud processes and properties and their impact on atmospheric radiation. We have completed the development of this microphysical database. we investigated the differences in the size distributions measured by the Cloud and Aerosol Spectrometer (CAS) and the Forward Scattering Probe (FSSP), between the one dimensional cloud imaging probe (1DC) and the two-dimensional cloud imaging probe (2DC), and between the bulk LWCs measured by the Gerber probe against those derived from the size resolved probes. |
URL: | http://www.osti.gov/scitech/servlets/purl/1121094
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Citation statistics: |
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资源类型: | 研究报告
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标识符: | http://119.78.100.158/handle/2HF3EXSE/40813
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Appears in Collections: | 过去全球变化的重建 影响、适应和脆弱性 科学计划与规划 气候变化与战略 全球变化的国际研究计划 气候减缓与适应 气候变化事实与影响
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1121094.pdf(39KB) | 研究报告 | -- | 开放获取 | | View
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Recommended Citation: |
McFarquhar, Greg M.. Final Report fir DE-SC0005507 (A1618): The Development of an Improved Cloud Microphysical Product for Model and Remote Sensing Evaluation using RACORO Observations. 2012-01-01.
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