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Kirsten L. Findell and Thomas L. Delworth

and 80th percentile thresholds for precipitation deciles, which, by definition, produce 2.4 months yr −1 in drought or pluvial in the control run. One of the beneficial qualities of the SDDI is the easy-to-understand notion of supply versus demand. However, the demand side of the equation has many potential definitions, and it depends on atmospheric conditions, soil water availability, and vegetation type and growth stage. The concept of potential evaporation was first discussed in 1948

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Matías Méndez and Víctor Magaña

weather stations over Mexico. The number of stations increased to hundreds and even thousands after the 1930s and 1950s, respectively. For outside Mexico, monthly precipitation data was obtained from Global Historical Climatological Network (GHCN) version 2 ( Peterson et al. 1998 ). The precipitation reports have been subjected to quality control by including a duplicate station check and spatial consistency (or “buddy”) check. In addition, the coherence in monthly precipitation among neighboring

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Alfredo Ruiz-Barradas and Sumant Nigam

will be analyzed because the NCEP’s AMIP simulations are very short for the present study and NOAA/GFDL has not made public its AMIP simulations. The paper is organized beginning with section 2 , which provides some basic information on the models and their simulations as well as the observational data. Next, in section 3 the interannual variability of summer precipitation in North America in general, and in the Great Plains in particular, is analyzed. Then, section 4 elaborates on the SST

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Antonietta Capotondi and Michael A. Alexander

conclusions are provided in section 6 . 2. Models and data We examine the PICNTRL from six of the IPCC climate models, as listed in Table 1 . The preindustrial control simulations are multicentury simulations with the chemical composition of the atmosphere fixed at preindustrial conditions. The absence of any anthropogenic forcing in these simulations allows us to focus on natural variability only. The model outputs have been collected at the Program for Climate Model Diagnosis and Intercomparison. The

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

. Vanyarkho , 1999 : Monitoring the 1996 drought using the standardized precipitation index. Bull. Amer. Meteor. Soc. , 80 , 429 – 438 . Hidalgo , H. G. , and J. A. Dracup , 2003 : ENSO and PDO effects on hydroclimate variations of the upper Colorado River basin. J. Hydrometeor. , 4 , 5 – 23 . Higgins , R. W. , W. Shi , E. Yarosh , and R. Joyce , 2000 : Improved United States Precipitation Quality Control System and Analysis . NCEP/CPC Atlas No. 7, 40 pp . Hu , Q. , and S

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Caio A. S. Coelho and Lisa Goddard

others have looked at regional precipitation changes, but little has been done on how ENSO teleconnections—particularly El Niño–induced drought patterns—together with projected precipitation changes in the tropics can inform the changing risk of drought conditions. This study first evaluates the patterns, magnitude, and spatial extent of El Niño–induced tropical droughts during a control period in the twentieth century in climate simulations, which have realistic evolution of greenhouse gasses. Next

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Rachel R. McCrary and David A. Randall

1. Introduction The risk of future long-term drought (a dry period that exhibits below-average annual precipitation for 5 yr or longer) is one of the biggest concerns facing the Great Plains region of the United States (defined here as the region bounded by 30°–50°N, 95°–105°W). Droughts have serious social, economic, and environmental consequences and can negatively impact surface and groundwater supplies, water quality, agriculture and rangeland productivity, natural ecosystems, and

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Scott J. Weaver, Siegfried Schubert, and Hailan Wang

Intercomparison Project (AMIP)-style GCM simulations serve as a contextual reference for the idealized responses. Section 2 describes the observational data and AMIP and idealized SST model simulations. Section 3 discusses the structure of the seasonal cycle of the GPLLJ and interannual variability of precipitation. Section 4 shows connections of the GPLLJ to SST variability and the large-scale circulation. Section 5 highlights results from the idealized SST experiments, while section 6 is left for

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