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Atmospheric System Research Marine Low Clouds Workshop Report, January 27-29,2016 科技报告
来源:US Department of Energy (DOE). 出版年: 2016
作者:  Jensen, M.;  Wang, J.;  Wood, R.
收藏  |  浏览/下载:4/0  |  提交时间:2019/04/05
GoAmazon 2014/15. SRI-PTR-ToFMS Field Campaign Report 科技报告
来源:US Department of Energy (DOE). 出版年: 2016
作者:  Guenther, A.
收藏  |  浏览/下载:6/0  |  提交时间:2019/04/05
Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) Final Campaign Report 科技报告
来源:US Department of Energy (DOE). 出版年: 2016
作者:  Wood, R.
收藏  |  浏览/下载:3/0  |  提交时间:2019/04/05
MAGIC Cloud Properties from Zenith Radiance Data Final Campaign Summary 科技报告
来源:US Department of Energy (DOE). 出版年: 2016
作者:  Chiu, J. -Y.C.;  Gregory, L.;  Wagener, R.
收藏  |  浏览/下载:0/0  |  提交时间:2019/04/05
Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions 科技报告
来源:US Department of Energy (DOE). 出版年: 2015
作者:  McFarquhar, Greg
收藏  |  浏览/下载:0/0  |  提交时间:2019/04/05
Vertical microphysical profiles of convective clouds as a tool for obtaining aerosol cloud-mediated climate forcings 科技报告
来源:US Department of Energy (DOE). 出版年: 2015
作者:  Rosenfeld, Daniel
收藏  |  浏览/下载:5/0  |  提交时间:2019/04/05
Cloud aerosol interactions  
Laboratory Experiments and Instrument Intercomparison Studies of Carbonaceous Aerosol Particles 科技报告
来源:US Department of Energy (DOE). 出版年: 2015
作者:  Davidovits, Paul
收藏  |  浏览/下载:4/0  |  提交时间:2019/04/05
Assesment of the Indirect and Semi-Direct Aerosol-Effect During ISDAC Through Integrated Observational and Modeling Studies 科技报告
来源:US Department of Energy (DOE). 出版年: 2014
作者:  Boybeyi, Zafer
收藏  |  浏览/下载:5/0  |  提交时间:2019/04/05
Use of the ARM Measurements of Spectral Zenith Radiance for Better Understanding of 3D Cloud-Radiation Processes & Aerosol-Cloud Interaction 科技报告
来源:US Department of Energy (DOE). 出版年: 2014
作者:  Chiu, Jui-Yuan Christine
收藏  |  浏览/下载:7/0  |  提交时间:2019/04/05
Cloud  aerosol-cloud interaction  remote sensing  radiative transfer  cloud retrieval  
Collaborative Research: Using ARM Observations to Evaluate GCM Cloud Statistics for Development of Stochastic Cloud-Radiation Parameterizations 科技报告
来源:US Department of Energy (DOE). 出版年: 2013
作者:  Shen, Samuel S. P. [San Diego State Univ., CA (United States)]
收藏  |  浏览/下载:5/0  |  提交时间:2019/04/05
cloud statistics  stochastic cloud-radiation parameterizations  ARM data  Bayesian method