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David M. Bjerklie, Thomas J. Trombley, and Roland J. Viger

forecasts and limitations of the downscaling technique to interpolate these forecasts to a finer resolution serve as an important constraint on the fineness of the spatial and temporal scales at which the hydrologic modeling can be carried out. As a result, many of the regional hydrologic studies of climate change impacts cited above and in general use lumped or semidistributed models and do not have an explicit routing scheme. Gosling et al. ( Gosling et al. 2010 ) point out that uncertainty of climate

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Ansar Khan, Samiran Khorat, Rupali Khatun, Quang-Van Doan, U. S. Nair, and Dev Niyogi

2000 ): (13) Q = ∑ j = 1 n ∑ i = 1 n ⁡ ( A i j h i ) 4 − ∑ j = 1 n ⁡ ( ∑ i = 1 n A i j 2 h i 2 ) 2 , (14) h i 2 = ∑ j = 1 n A i j 2 ,   and (15) Z i k = ∑ i = 1 n A i j R j k , where n denotes the number of cities, A ij represents the loading of the i th city on the j th VR–principal component (PC), h i is the commonality of the i th city, and R jk denotes the score of the k th pollutant for the j th rotated PC. The procedure of the VR technique aims to maximize the variances of the

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Paolina Bongioannini Cerlini, Lorenzo Silvestri, Silvia Meniconi, and Bruno Brunone

resource availability in India is based on the use of satellite-derived remote sensing data and the obtained results are compared with data from wells. In Bjerklie et al. (2011) , future trends of groundwater recharge in Long Island Sound have been evaluated from GCM forecasts by assuming different scenarios in terms of carbon emissions. Within the water table fluctuation (WTF) method, valid for unconfined aquifers, the recharge is assumed as proportional to the measured rise of the water table, with

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Mark R. Jury

provided by monthly Simple Ocean Data Assimilation version 2.4 (SODA2.4; Carton and Giese 2008 ) comprising European Centre for Medium-Range Weather Forecasts (ECMWF) wind stress, sea surface height, temperature, salinity, currents, and vertical motion at 50-km horizontal resolution and ~30-m vertical resolution. Both reanalysis products are based on a four-dimensional numerical model assimilation of all available in situ and remotely sensed data, and they include atmospheric profilers, scatterometer

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Jay Golden, W. C. Chuang, and W. L. Stefanov

historically weighted as a sum of the individual surface materials and incorporated in mesoscale modeling applications, such as the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), Weather Research and Forecasting (WRF) Model and the Objective Hysteresis Model (OHM) by Grimmond et al. ( Grimmond et al. 1991 ) and the more user-friendly zero-dimensional model for urban climate ( Silva et al. 2009 ). A grid-type approach to evaluate the storage

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Weile Wang, Bruce T. Anderson, Dara Entekhabi, Dong Huang, Robert K. Kaufmann, Christopher Potter, and Ranga B. Myneni

1. Introduction In the first part of this study ( Wang et al. 2006 , hereafter W1 ), statistical techniques are used to detect and analyze the influence of vegetation on climate variability over the North American Grasslands. Results indicate significant Granger causal relationships ( Granger 1969 ; Granger 1980 ) from lagged anomalies of vegetation activity to variations of summertime precipitation and surface temperature, particularly when time lags are longer than 2 months ( W1 ). That is

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Brandon J. Vogt

coordinate boundaries of the study area. Comparing the sums of actual strikes (actual distribution) to randomly generated points (expected distribution) collected in the buffers served as the basis to confirm or reject the notion that CG strikes favor highpoints. These actual-to-random comparisons by buffer size and by kiloamp class served as the basis to evaluate the notion that a positive relationship exists between striking distance and peak current. 3.3. Data analysis techniques Two

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Mark R. Jury

. 2007 ). The paper outlines the data and methods utilized, followed by results on the mean state and sensitivity of South African rainfall anomalies to the Agulhas SST. Air–sea interactions emerge in composite analysis, and a concluding discussion highlights the key features. 2. Data and methods This section describes the data and analysis techniques used to determine the climatic influence of the Agulhas Current. The domain considered is 25°–41°S, 16°–36°E ( Figure 1a ). This contains the whole of

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Hongshou Li

atmospheric pressure ( Buckingham 1904 ), so the ground surface can be thought of as undergoing “passive respiration” ( Elberling et al. 1998 ; He 2009 ). In ancient China, an EP-monitoring technique named “hou-qi (候气)” was used as the foundation of an ancient calendar and used to forecast weather. Indeed, the expression “earth–air (地气)” is one that is still familiar to Chinese people. The ancient Chinese believed in the existence of air pressure changes within Earth, and hou-qi theory is a foundation of

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Pennan Chinnasamy and Jason A. Hubbart

Biogeochemistry: Synthesis of Past Research and Future Directions, D. F. Levia et al., Eds., Springer, 729–733 . Luo , Y. , and M. Sophocleous , 2010 : Seasonal groundwater contribution to crop-water use assessed with lysimeter observations and model simulations . J. Hydrol. , 389 , 325 – 335 , doi: 10.1016/j.jhydrol.2010.06.011 . Marzolf , E. R. , P. J. Mulholland , and A. D. Steinman , 1994 : Improvements to the diurnal upstream–downstream dissolved oxygen change technique for determining

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