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Shanshan Deng, Suxia Liu, and Xingguo Mo

correspond to the significance levels of 0.1, 0.05, and 0.01. Second, the mean values of the estimates and the GRACE data are used to show the level of imbalance between the input and output of the water budget. Since the mean value of the TWSC monthly series in each grid is the mass change rate on a monthly scale, it reflects the regional water balance. The imbalance in the GRACE data can be regarded as the real changes in the water cycle caused by climate change or anthropogenic influences because of

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Michael G. Bosilovich, Franklin R. Robertson, and Junye Chen

the formulation of the budgets is discussed by Rienecker et al. (2007) and Suarez et al. (2011) . 3. Water and energy budgets a. Global mean climatology TFK09 collect the global energy budget data from various sources, observational and reanalyses, and close it with consistency arguments from dataset intercomparisons, to determine estimates for principal energy flux components and balance. However, each term exhibits large variations among the different observing systems and reanalyses, so any

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Peter Kalmus, Matthew Lebsock, and João Teixeira

al. (2007 , 2009) and Stephens et al. (2012) have demonstrated the usefulness of the holistic budget approach on the global scale. Regional budgets are perhaps more difficult to close than global budgets because they include advective terms which vanish in the global mean ( Wong et al. 2011 ), but they may be useful in isolating and evaluating key atmospheric processes such as the SCT. In this paper we report on the climatological mean energy and water budgets in the subtropical marine BL

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Sanaa Hobeichi, Gab Abramowitz, and Jason Evans

the adjustments made to one budget affect the nature of adjustments made to the components of the other budget. For example, over the Amazon, there are large water and energy imbalances in June and July, caused by an excess of Q + ET + Δ S and R n , respectively. The energy balance enforcement is achieved after a decline in R n accompanied by an increase in H and G . On the other hand, the water balance is achieved after a significant increase in P accompanied by a decrease in Q and Δ

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J. E. Jack Reeves Eyre and Xubin Zeng

^ variability. Fig . 3. Correlation coefficients at (left) monthly, (center) seasonal, and (right) annual time scales between discharge observed at Óbidos (multiplied by 1.25 for the Amazon, although this does not affect the correlation) and discharge estimated from water balance: R ^ . Each point represents one combination of water budget terms: some are highlighted, as shown in the legend. Note that, within each plot and basin, points have been randomly displaced left and right to aid legibility. The

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Spencer K. Clark, Yi Ming, Isaac M. Held, and Peter J. Phillipps

examples above demonstrate the importance of the treatment of physical processes in setting the sensitivity of the ITCZ position to hemispherically asymmetric perturbations. In the context of radiation and the energy budget of the atmosphere, clouds and water vapor are the two most important spatially heterogeneous factors to consider ( Hartmann 2016 ). In terms of physical processes, previous studies have either included both cloud and water vapor radiative feedbacks, by using comprehensive aquaplanet

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Damien Irving, Will Hobbs, John Church, and Jan Zika

initialization of the coupled ocean–atmosphere system ( Sen Gupta et al. 2013 ). In addition to incomplete model spinup, drift is also caused by spurious mass or energy “leakage” into or out of the simulated climate system. This nonclosure of the global mass and energy budgets arises due to small inconsistencies in the model treatment of energy ( Lucarini and Ragone 2011 ; Hobbs et al. 2016 ) and/or water ( Liepert and Previdi 2012 ; Liepert and Lo 2013 ). In relation to the global energy budget, an

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Sarah G. Purkey and Gregory C. Johnson

potential isotherms (heave). Heave reflects changes in AABW volume, related to changes in the formation rate, circulation, or perhaps even formation properties of AABW. A shift in the θ– S curve indicates a change in water-mass properties. Decomposing the observed deep changes into these components allows for evaluation of the relative contributions of these changes to local sea level rise (SLR), freshwater, and heat budgets. AABW is a combination of very cold and relatively fresh water formed on

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Kirsten L. Findell, Patrick W. Keys, Ruud J. van der Ent, Benjamin R. Lintner, Alexis Berg, and John P. Krasting

meridional wind speeds and specific humidity. These data are used to solve the water balance of tagged moisture (subscript g ) in an upper and lower layer, S g ,upper and S g ,lower , where S is moisture in the atmospheric column. These calculations do not influence the total water balance. In forward tracking mode the water balance of tagged moisture in the lower layer is given by ∂ S g , lower ∂ t = − ∂ ( S g , lower u ) ∂ x − ∂ ( S g , lower υ ) ∂ y + E g − P g ± F υ , g , where F υ is

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Kyle S. Mattingly, Thomas L. Mote, Xavier Fettweis, Dirk van As, Kristof Van Tricht, Stef Lhermitte, Claire Pettersen, and Robert S. Fausto

discharge and through a reduced surface mass balance (SMB), when increases in surface ablation exceed those in snow accumulation and meltwater refreezing. SMB-related losses were responsible for a greater proportion of total mass loss than ice dynamical processes during the recent GrIS mass loss acceleration ( van den Broeke et al. 2017 ; Mouginot et al. 2019 ), and model projections indicate that SMB will play the dominant role in future GrIS mass losses ( Calov et al. 2018 ; Rückamp et al. 2018

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