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J.-L. F. Li, D. E. Waliser, G. Stephens, and Seungwon Lee

developing and evaluating clouds and radiation in GCM simulations were typically derived from cloud cover observations from the International Satellite Cloud Climatology Project (ISCCP) and related products (e.g., Han et al. 1999 ; Rossow and Zhang 1995 ; Rossow and Schiffer 1999 ) and from radiation budget observations from the Earth Radiation Budget Experiment/Clouds and the Earth’s Radiant Energy System (ERBE/CERES) ( Wielicki et al. 1996 ). In the last decade, the first satellite simulator was

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Steven K. Esbensen, Jan-Hwa Chu, Wen-wen Tung, and Robert G. Fovell

). Other investigations included the relationship between Indian monsoon rainfall and tropospheric temperature over the Eurasian continent ( Liu and Yanai 2001 ), and between Eurasian spring snow cover and Asian summer rainfall ( Liu and Yanai 2002 ). Professor Yanai, graduate student Chih-Wen Hung ( Fig. 15 ), and their Chinese colleague Xiaodong Liu identified factors contributing to the Australian summer monsoon and examined its symmetries and asymmetries with the Asian summer monsoon ( Hung and

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S. A. Ackerman, S. Platnick, P. K. Bhartia, B. Duncan, T. L’Ecuyer, A. Heidinger, G. Skofronick-Jackson, N. Loeb, T. Schmit, and N. Smith

the same approximate locations continuously. Great strides were made as routine imaging from the geostationary perspective quickly moved from the concept to the experimental and then operational stages; the experimental phase began in the mid-1960s, while the operational phase began in the mid-1970s and continues to this day. Satellites in geostationary orbit routinely monitor phenomena such as clouds, convection, hurricanes, fires, smoke, surface temperatures, atmospheric motions, snow cover, fog

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Larry K. Berg and Peter J. Lamb

. (1997) . Gao et al. (1998) identified biases in the MODIS data products and suggested that it is possible to parameterize the albedo only as a function of the solar zenith angle, while ignoring the land cover (assuming that the surface is snow free). The contrasting results found when using short-duration versus long-duration data records prove the value of long-term deployments like those associated with the ARM Program. Fig . 23-12. Surface shortwave albedo as a function of solar zenith angle at

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V. Ramaswamy, W. Collins, J. Haywood, J. Lean, N. Mahowald, G. Myhre, V. Naik, K. P. Shine, B. Soden, G. Stenchikov, and T. Storelvmo

−2 K −1 (e.g., Cess 1976 ). In current climate models, radiative feedbacks from water vapor, clouds, and snow/sea ice cover act to reduce α to a range ≈1–2 W m −2 K −1 ; this amplifies the change in temperature in response to a given radiative forcing. Most of the intermodel spread in α is due to differences in predicting the response of clouds to an external forcing ( Cess et al. 1990 ). Feedbacks from water vapor, clouds, snow, and sea ice cover have been well documented in both models

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Sue Ellen Haupt, Steven Hanna, Mark Askelson, Marshall Shepherd, Mariana A. Fragomeni, Neil Debbage, and Bradford Johnson

areas are a major source of anthropogenic carbon dioxide emissions that are a primary driver of climate change. Some estimates suggest that cities are responsible for more than 90% of anthropogenic carbon emissions ( Svirejeva-Hopkins et al. 2004 ). The land use/land cover change associated with urbanization also negatively impacts carbon sinks ( Hutyra et al. 2014 ). While being a major driver of global climate change, urban environments are simultaneously vulnerable to many of the ramifications

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atmosphere. Theoretical models predict a net surface warming of the globe from the direct radiative forcing of these gases and, more importantly, the resulting series of feedbacks. These feedbacks directly affect many processes important to climate such as snow cover and sea ice melting, cloud formation, air–ocean interaction, and global circulation patterns. Consequently, a lack of understanding of the complex response of the atmosphere–ocean system to anthropogenic inputs allows much room for

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M. A. Miller, K. Nitschke, T. P. Ackerman, W. R. Ferrell, N. Hickmon, and M. Ivey

resort city of Nainital, India, was selected as the AMF1 deployment site for the Ganges Valley Aerosol Experiment (GVAX; #6 in Fig. 9-1 ). The AMF1 was positioned at a location and height that enabled measurements of aerosols spilling through the foothills into the snow-covered peaks of the Himalayas. In February 2010, the AMF1 advance team traveled to India to organize the three components of the GVAX deployment: the AMF1 itself, a satellite measurement site near the city of Pantnagar, and a Mobile

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Guoxiong Wu and Yimin Liu

models—boundary processes, cloud, radiation, convection, etc.,—over the plateau. Work will focus on identifying and explaining potentially significant teleconnections, such as the influence of Tibetan snow cover on the Asian monsoon and Northern Hemispheric conditions. Employing existing theories in physics, chemistry, and mathematics to reveal the complex and relevant multisphere interaction and to get new insights into the impacts of the TP on climate will be significant for enhancing our

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Ismail Gultepe, Andrew J. Heymsfield, Martin Gallagher, Luisa Ickes, and Darrel Baumgardner

by modulating the heat and moisture fluxes in the surface layer and lower troposphere ( Curry et al. 1996 ; Beesley and Moritz 1999 ). During Arctic winters when temperatures fall well below −30°C and relative humidity with respect to liquid water (RHw) exceeds 80%, even a shallow layer of ice fog will significantly affect the surface energy budget ( Blanchet and Girard 1995 ; Curry et al. 1990 , 1996 ). Sea ice thickness and snow cover also are impacted because of ice fog’s interaction with

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