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Ming Pan, Alok K. Sahoo, Tara J. Troy, Raghuveer K. Vinukollu, Justin Sheffield, and Eric F. Wood

combined estimate of a variable is to be made from many competing sources, how do we determine the accuracy and consistency of each source and assign uncertainties to the final estimate? Another challenge is that, in many cases, estimates of budget components from different sources do not close the water budget ( Pan and Wood 2006 ; Sheffield et al. 2009 ; Gao et al. 2010 ; McCabe et al. 2008 ; Sahoo et al. 2011 ); that is, the basic physical constraint of mass balance of water is not satisfied

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Elizabeth Carter, Christopher Hain, Martha Anderson, and Scott Steinschneider

, annual ET WB was calculated using Eq. (1.2) , as was the 13-yr mean ( ). Basins with any ET WB values less than zero were eliminated from the analysis. 2) Energy balance–based ET products In addition to the water budget approach, ET can be characterized using a surface energy budget as follows: where Rn (net radiation, generally expressed as W m −2 ) is partitioned to sensible heat flux H (W m −2 ), latent heat flux (LE; W m −2 ), and ground heat flux G (W m −2 ), with the partitioning between

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K. K. Szeto, H. Tran, M. D. MacKay, R. Crawford, and R. E. Stewart

other to within 10% of the corresponding ensemble mean values. An accurate and complete quantitative characterization of the water and energy cycle for a region requires both accurate evaluations of the budget components and adequate closure of the budget balance. The degree to which the budgets are closed in the various datasets is given conveniently by the residuals in balancing their corresponding budgets. Theoretically, there should be perfect balance in purely modeled water and energy budgets

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Rebecca A. Smith and Christian D. Kummerow

closure. This paper is organized as follows. Section 2 introduces details about the datasets. Section 3 analyzes the consistency among the datasets and the variability of each water budget component. In the discussion, section 4 , a balance of the surface and atmospheric budgets is performed. Conclusions are presented in section 5 . 2. Data and methodology The UCRB, with an areal size of about 2.6 × 10 5 km 2 , is located in the western United States ( Fig. 1 ). Table 1 details the

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Yanhong Wu, Hongxing Zheng, Bing Zhang, Dongmei Chen, and Liping Lei

the central TP. A dynamic monthly water balance model is developed for this purpose and is calibrated using lake level data derived from the ICESat altimetry dataset. Based on the dynamic simulation, long-term changes of lake water budget are investigated with respect to climate changes in the TP. 2. Study area and data a. Study area Nam Co is a closed, semi-brackish lake ( Wang et al. 2009 ) located in the central part of the TP (30°30′–30°55′N, 90°16′–91°03′E) with a catchment area of 10 610 km

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Alan K. Betts and Pedro Viterbo

continent into the Arctic Ocean. The Mackenzie basin is large (drainage area of 1.8 × 10 6 km 2 ), and surface and upper-air observations are relatively sparse, so models are essential to estimate the surface energy and water balance over the annual cycle. This paper summarizes the liquid and frozen surface water and energy budgets from the European Centre for Medium-Range Forecasts (ECMWF) operational model for two years from 1 September 1996 to 31 August 1998 for seven subbasins of the ECMWF model

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P. Irannejad and A. Henderson-Sellers

information with a climate-driven water balance model. We have compared the 17-yr mean monthly runoff simulation with observed climatologies, assuming that the seasonal cycle and spatial distribution averaged over 17 yr resembles the climatologies of the simulated runoff. 3. Analysis of AMIP II AGCM simulations Analysis of AMIP II land surface water budget simulations is presented in the three following sections. In section 3a , simulations of land surface water budget components by the AGCMs are

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Chester F. Ropelewski and Evgeney S. Yarosh

cycle and their individual components. In this paper we document the mean water balance for the central United States based on an analysis of monthly radiosonde, precipitation, and river discharge data for a 20-yr period. A major emphasis here is on obtaining the best estimates of precipitation minus evapotranspiration ( P − E ) from the radiosonde-based atmospheric budget and, in addition, in obtaining the best estimates of evaporation and surface–subsurface water storage as the residuals from

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Seiji Kato, Norman G. Loeb, John T. Fasullo, Kevin E. Trenberth, Peter H. Lauritzen, Fred G. Rose, David A. Rutan, and Masaki Satoh

all water variables are separated from dry air. We then use improved energy equations to assess the effect of horizontal transport of hydrometeors and enthalpy transport associated with precipitation on the atmospheric energy budget. Energy and water budget equations are formulated in section 2 . Water mass balance and the effect of water mass balance residual and horizontal transport of hydrometeors are assessed in section 3 . Enthalpy fluxes at the surface due to water mass fluxes are

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C. P. Kim and J. N. M. Stricker

MAY 1996 KIM AND STRICKER 749Consistency of Modeling the Water Budget over Long Time Series: Comparison of Simple Parameterizations and a Physically Based Model C. P. KhM AND J. N. M. STRICKERDepartment of Water Resources, Wageningen Agricultural University, Wageningen, the Netherlands(Manuscript received 27 July 1994, in final form 27 November 1995)ABSTRACT This

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