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Seiji Kato, Kuan-Man Xu, Takmeng Wong, Norman G. Loeb, Fred G. Rose, Kevin E. Trenberth, and Tyler J. Thorsen

measurements. As a result, in order to balance the surface energy budget Trenberth et al. (2009) chose to adjust the surface downward longwave irradiance, which increased the irradiance by about 12 W m −2 from the value estimated more recently from satellite observations. The uncertainty (1 σ ) in the global annual mean surface downward longwave irradiance estimated by Kato et al. (2012) in the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) surface product is 7

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Seiji Kato and Fred G. Rose

. Notations used in KR2020 We admit that notations used in KR2020 might be confusing to those who are familiar with notations used for entropy studies, but notations used in KR2020 for entropy balance are consistent with notations used for energy balance. We briefly clarify our notations used in KR2020 here. Equation (5) of KR2020 expresses entropy balance at TOA. The net entropy flux is defined as positive inward. We denote J TOA net for entropy export to space, where the symbol J is used to

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Wenhui Cui and Ting Fong May Chui

hypothesized that neglecting lateral heat fluxes in the subsurface could contribute to the energy imbalance over the heterogeneous surface and that the level of energy balance closure could be improved if the lateral heat fluxes were considered. 2. Method Field measurements were performed using an eddy covariance system and an array of temperature and water-level sensors. The eddy covariance system was used to obtain the energy budget of a vegetated area, and the sensors were used to capture the

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

al. 2011 ). In reviewing the observed global energy budget, TFK09 also compared the reanalysis energy budgets (specifically ERA-40, NCEP–DOE R2, and JRA-25), and some similar biases are evident. First, the net TOA energy did not balance well, with too much upward flux. However, JRA-25 bias is related to too much outgoing longwave radiation (OLR), while NCEP–DOE R2 is due to too much reflected shortwave radiation, but both imbalances were on the order of 10 W m −2 . Also, all reanalyses had

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Lei Zhou, Adam H. Sobel, and Raghu Murtugudde

in the momentum equations [Eq. (1) ], the balance between these two terms indicates that the kinetic energy associated with MJO events is mainly controlled by linear processes, at least in the coarse view offered by the vertically and meridionally integrated kinetic energy budget. The horizontal structures of the most important terms (averaged between 1000 and 100 hPa in the vertical and over all MJO days) in the kinetic energy budget are shown in Figs. 6a and 6b . Positive [KE′ × PE′] and

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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

the surface and within the atmosphere, can exceed estimated perturbations driven by climate change by an order of magnitude. This is evident, for example, when satellite-derived products are used to close the surface energy budget, as there is a significant discrepancy in the annual global energy balance of 10 to 15 W m −2 ( Kato et al. 2011 ; L’Ecuyer et al. 2015 ). While the cause of the residual is unknown, Loeb et al. (2014) and Kato et al. (2016) used satellite-derived radiation

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Colin Plank and Bryan Shuman

wetlands on boreal climate. J. Geophys. Res. , 108 , 4520 . doi:10.1029/2002JD002597 . Kutzbach , J. E. , 1980 : Estimates of past climate at paleolake Chad, North Africa, based on a hydrological and energy balance model. Quat. Res. , 14 , 210 – 223 . Nagarajan , B. , M. K. Yau , and P. H. Schuepp , 2004 : The effects of small water bodies on the atmospheric heat and water budgets over the MacKenzie river basin. Hydrol. Processes , 18 , 913 – 938 . NCDC , 1994 : Time bias

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Osamu Miyawaki, Tiffany A. Shaw, and Malte F. Jansen

balance regimes in the modern climate provide a useful guide for interpreting the vertical structure of the warming response? To answer these questions, we develop a nondimensional number based on the MSE budget to quantify energy balance regimes ( section 2a ). We use this nondimensional number to quantify where and when energy balance regimes occur latitudinally and seasonally in Earth’s modern climate using reanalysis and Coupled Model Intercomparison Project phase 5 (CMIP5) data. We quantify the

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Andrea Ucker Timm, Débora R. Roberti, Nereu Augusto Streck, Luis Gustavo G. de Gonçalves, Otávio Costa Acevedo, Osvaldo L. L. Moraes, Virnei S. Moreira, Gervásio Annes Degrazia, Mitja Ferlan, and David L. Toll

data processing, gap filling, and energy balance Before computing the turbulent fluxes, the raw data undergo a quality-control stage ( Baldocchi et al. 1988 ; Wyngaard 1990 ; Aubinet et al. 2000 ), which comprises inadequate sensor frequency response correction, despiking, coordinate rotation, and air density adjustments. The turbulent fluxes were calculated over 1-h windows, allowing low-frequency processes, which in turn represent a relevant contribution to the energy budget closure ( Sakai et

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Yang Yang, Robert H. Weisberg, Yonggang Liu, and X. San Liang

assimilated to interrupt the forward run, the model outputs are kinematically and dynamically consistent, and hence are suitable for energy budget analyses. It should be mentioned that, due to the complexity of the LC system, it is almost impossible for a non-data-assimilative model to capture every observed shedding event in a single multiyear run. However, several key features of the LC are found to be well reproduced in the model. For instance, the spatial patterns of the modeled time-mean surface

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