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Bradfield Lyon

waves that often, though certainly not always, accompany them. For example, during the 1991/92 summer drought in southern Africa it is estimated that as much as 3 million tons of grain production were lost in this predominately rain-fed agricultural region ( Dilley and Heyman 1995 ). The extreme high temperatures that accompanied the drought not only contributed to the crop losses but also to widespread livestock mortality ( Sivakumar 2006 ) and stresses on regional water supplies. The joint

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Siegfried Schubert, David Gutzler, Hailan Wang, Aiguo Dai, Tom Delworth, Clara Deser, Kirsten Findell, Rong Fu, Wayne Higgins, Martin Hoerling, Ben Kirtman, Randal Koster, Arun Kumar, David Legler, Dennis Lettenmaier, Bradfield Lyon, Victor Magana, Kingtse Mo, Sumant Nigam, Philip Pegion, Adam Phillips, Roger Pulwarty, David Rind, Alfredo Ruiz-Barradas, Jae Schemm, Richard Seager, Ronald Stewart, Max Suarez, Jozef Syktus, Mingfang Ting, Chunzai Wang, Scott Weaver, and Ning Zeng

experiments are described in the appendix . Another related and important set of experiments consist of Atmospheric Model Intercomparison Project (AMIP)-style simulations ( Gates et al. 1999 ). These are simulations (typically several decades long) in which the models are forced by the historical record of observed SSTs. While the focus of the runs described here is on understanding mechanisms and model sensitivity to idealized SST forcing, the AMIP runs are important in that they facilitate model

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Philip J. Pegion and Arun Kumar

. Six modeling groups joined in the effort and produced a wealth of model simulation. The primary goal of the focused effort was to quantify the role of sea surface temperature (SST) variability in changes of the atmospheric circulation and terrestrial climate. Various large-scale patterns of sea surface temperature (SST) variability have been known for many years. A dominant mode of SST variability is associated with the El Niño–Southern Oscillation (ENSO). Other well-known modes of SST variability

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Matías Méndez and Víctor Magaña

analysis of prolonged drought in Mexico should focus on Northern Hemisphere (NH) summer rains. During this season, trade winds and easterly waves produce moisture flux from the Americas warm pools into continental Mesoamerica (i.e., the geographical area that extends from central Mexico down through Central America) ( Mestas-Nuñez et al. 2002 ; Wu et al. 2009 ). In the northern part of Mexico subsidence persists most of the year. It is only when easterly waves (EW) or tropical cyclones (TC) force

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Kingtse C. Mo, Jae-Kyung E. Schemm, and Soo-Hyun Yoo

streamflow in winter. Different phases of the AMO also link to different summer precipitation modes of the North American monsoon ( Hu and Feng 2008 ). With the progress of climate modeling, current climate models in general are able to predict ENSO relatively well ( Saha et al. 2006 ). Responses to SSTAs in the Atlantic simulated by atmospheric GCMs (AGCMs) are more diverse. In the review paper by Kushnir et al. (2002) , the authors stated that the atmosphere indeed responds to the SSTAs in the

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Scott J. Weaver, Siegfried Schubert, and Hailan Wang

1. Introduction The central United States is a hydroclimatically and economically sensitive region given its agricultural prominence and significant warm season precipitation variability. The proximity of this region to the Rocky Mountains, Gulf of Mexico, and Atlantic and Pacific Oceans provide a unique combination of potential climate influences, including large-scale atmospheric circulation variations emanating over the adjoining ocean basins and local land–atmosphere interactions. As such

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Yochanan Kushnir, Richard Seager, Mingfang Ting, Naomi Naik, and Jennifer Nakamura

, b) and Seager et al. (2005b) . Seager et al. (2005b) , in particular, integrated two ensembles of the National Center for Atmospheric Research (NCAR) Community Climate Model 3 (CCM3), both of which were forced with a century and a half (1856–2006) of observed monthly mean SSTs. One ensemble was forced with observed global SST variability, and the other with SSTs prescribed only in the tropical Pacific. 3 The two ensembles yielded extremely similar results regarding the variability of

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Randal D. Koster, Hailan Wang, Siegfried D. Schubert, Max J. Suarez, and Sarith Mahanama

above-mentioned connection between seasonally averaged evaporation and surface temperature, used the curve in Fig. 1 to interpret interannual variations in June–August (JJA) temperature averages in terms of the two evaporation regimes. Using both atmospheric general circulation model (AGCM) data and multidecadal precipitation and temperature observations, they showed that drier-than-average JJA conditions in regions characterized by soil moisture–controlled evaporation do indeed lead to positive

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M. Biasutti, A. H. Sobel, and Suzana J. Camargo

1. Introduction As a global mean temperature increase in response to increasing atmospheric greenhouse gases becomes more certain ( Meehl et al. 2007b ), new challenges emerge: to reach similar certainty regarding the response of other climatic variables, first and foremost of precipitation, and to describe the climate response at the regional level. Important disagreements remain with regards to the regional precipitation response to global warming. Different numerical climate models give very

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