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Zhe Feng, Fengfei Song, Koichi Sakaguchi, and L. Ruby Leung

released can invigorate storms and enhance precipitation intensity ( Trenberth et al. 2003 ), increasing the risk of flooding. Large disagreements in phase 5 of the Coupled Model Intercomparison Project (CMIP5; Taylor et al. 2012 ) projections of future precipitation show that the current generation of global climate models (GCMs) have large uncertainties in simulating one of the key components of the water cycle. In contrast, high-resolution GCMs have been shown to provide improved, globally

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Motoki Nagura, J. P. McCreary, and H. Annamalai

erroneously fresh near-equatorial water generated by the large precipitation bias there ( Fig. 5b ; see also Figs. 10e–h below): Our interpretation is that during the summer, this erroneously freshwater is advected first northward along the western boundary by the Somali and Omani Currents and then eastward into the interior of Arabian Sea ( Fig. 6e ). Farther north, the fresh anomaly weakens in response to wintertime entrainment of the subsurface salt bias and to advection of less-freshwater into the

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James F. Booth, Young-Oh Kwon, Stanley Ko, R. Justin Small, and Rym Msadek

a reasonable proxy for climatological activity of extratropical cyclones ( Hoskins and Hodges 2002 ), and their maxima occur over the oceans, in the vicinity of ocean western boundary currents (WBCs) and their extensions (e.g., Fig. 1b ). WBCs are unique regions of air–sea coupling: ocean currents in these regions generate strong ocean heat flux convergence, which can dictate spatial and temporal variability in air–sea fluxes [see reviews by Kwon et al. (2010) and Kelly et al. (2010) ]. The

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Fiaz Ahmed and J. David Neelin

-scale turbulence. The convective transition statistics thus have potential to contribute constraints for reworking some of the basic assumptions about entrainment as currently implemented in cumulus parameterization schemes. The convective transition statistics over the tropical oceans have received much attention in the preceding decade, with only a few recent investigations of these statistics over tropical land. Ahmed and Schumacher (2017) , using satellite and reanalysis data, showed that for land regions

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Catherine M. Naud, James F. Booth, Jeyavinoth Jeyaratnam, Leo J. Donner, Charles J. Seman, Ming Zhao, Huan Guo, and Yi Ming

cyclones. Coincidently Naud et al. (2014) showed that recent versions of reanalyses do not have enough clouds in extratropical cyclone cold sectors. This underestimate in cloud cover over southern oceans was diagnosed in models from both phase 3 and phase 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5) and until recently was found to affect most current models ( Bodas-Salcedo et al. 2014 ). That GCMs do not produce enough cloud in the southern oceans is problematic: it causes errors

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Maik Renner, Axel Kleidon, Martyn Clark, Bart Nijssen, Marvin Heidkamp, Martin Best, and Gab Abramowitz

redistribution into the lower atmosphere is achieved by turbulent heat transfer driving the atmospheric boundary layer development ( Oke 1987 ), while subsurface heat redistribution includes the conduction and storage of heat in the soil and canopy. These processes are linked through the surface energy balance [in simplified form following Ohmura (2014) ] (1) R sd − R su + R ld − H − λ E − d U s / d t = ϵ s σ T 4 , where R sd is the incoming and R su the reflected solar radiation at the surface, R ld

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Jiabao Wang, Hyemi Kim, Daehyun Kim, Stephanie A. Henderson, Cristiana Stan, and Eric D. Maloney

position of the Pacific westerly jet cause errors in simulating MJO teleconnections, in addition to the effects of poor MJO performance. By comparing multimodel hindcasts, Vitart (2017) found that the amplitude of predicted MJO teleconnections is often too strong over the western North Pacific compared to reanalysis. Our understanding of the current model performance in terms of MJO teleconnection simulation is still limited. One reason that makes rigorous model evaluation and comparison difficult is

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Grey S. Nearing, Benjamin L. Ruddell, Martyn P. Clark, Bart Nijssen, and Christa Peters-Lidard

similar conclusions after benchmarking CLM and ORCHIDEE against linear and nonlinear regressions (again with no state memory), and Nearing et al. (2016) used benchmarking to show that Noah, SAC-SMA, Mosaic, and VIC each use generally less than half of the information available to them from parameters and boundary conditions. Results like this indicate that there is substantial potential to improve even our most sophisticated land models. One result lacking in these benchmarking studies was any

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Alexis Berg and Justin Sheffield

interactions encompass a broad range of processes and spatiotemporal scales, from local diurnal surface-boundary layer interactions to longer-term continental-scale ecosystem–climate feedbacks. On time scales from intraseasonal to interannual, soil moisture is the dominant land surface state variable affecting the global atmosphere ( Dirmeyer 2011a ). By regulating surface water and energy fluxes, soil moisture variations feedback onto near-surface surface climate (e.g., temperature and humidity); these

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Daehyun Kim, Yumin Moon, Suzana J. Camargo, Allison A. Wing, Adam H. Sobel, Hiroyuki Murakami, Gabriel A. Vecchi, Ming Zhao, and Eric Page

vertical levels. The observed SST is prescribed as the boundary condition for AM2.5 and HiRAM, while the FLOR SSTs are calculated interactively by its oceanic component model and restored toward the observed SSTs with a 5-day nudging time scale to keep the model mean state close to observed. In this sense, in FLOR, the atmosphere and ocean are semicoupled. From a long-term (over 20 years) simulation made using each model, a period of 2 years (1984–85) is chosen for the current study. Note that the TC

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