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Suzana J. Camargo, Claudia F. Giulivi, Adam H. Sobel, Allison A. Wing, Daehyun Kim, Yumin Moon, Jeffrey D. O. Strong, Anthony D. Del Genio, Maxwell Kelley, Hiroyuki Murakami, Kevin A. Reed, Enrico Scoccimarro, Gabriel A. Vecchi, Michael F. Wehner, Colin Zarzycki, and Ming Zhao

/or seasons the tropics are typically stable. Then, Gray (1979) developed an empirical relationship between genesis and climatological conditions of the environment, identifying six environmental conditions necessary for genesis: ocean thermal energy, low-level relative vorticity, vertical wind shear, Coriolis parameter, relative humidity of the troposphere, and a measure of instability of the atmosphere. Since then, many other empirical genesis indices have been developed ( DeMaria et al. 2001

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Fiaz Ahmed and J. David Neelin

studies. For instance, recent works ( Hannah et al. 2016 ; Allen and Mapes 2017 ) have suggested that the Lagrangian tracking of the CWV field can aid in interpreting salient synoptic variations in the tropics. Another avenue of research, directly relevant to this study, is the question of entrainment, which can be found in the earliest treatises on the subject ( Austin 1948 ; Houghton and Cramer 1951 ; Morton et al. 1956 ; Asai and Kasahara 1967 ). A satisfactory understanding and modeling of

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Samson M. Hagos, L. Ruby Leung, Oluwayemi A. Garuba, Charlotte Demott, Bryce Harrop, Jian Lu, and Min-Seop Ahn

precipitation and atmospheric moisture content is related to the constraint imposed by the atmospheric radiative cooling due to the increased temperature and humidity, which limits the precipitation change through the global energy and water balances ( Allen and Ingram 2002 ; Pendergrass and Hartmann 2014 ). Regional differences of the precipitation response are much less clear, particularly over the tropics, where spatial and temporal shifts related to dynamic and thermodynamic responses to warming can

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

.1029/2018MS001350 Xie , S. , and Coauthors , 2019 : Improved diurnal cycle of precipitation in E3SM with a revised convective triggering function . J. Adv. Model. Earth Syst. , 11 , 2290 – 2310 , https://doi.org/10.1029/2019MS001702 . 10.1029/2019MS001702 Yang , G. Y. , and J. Slingo , 2001 : The diurnal cycle in the tropics . Mon. Wea. Rev. , 129 , 784 – 801 , https://doi.org/10.1175/1520-0493(2001)129<0784:TDCITT>2.0.CO;2 . 10.1175/1520-0493(2001)129<0784:TDCITT>2.0.CO;2 Yang , Q

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Alexis Berg and Justin Sheffield

in the tropics, in many parts of the midlatitudes, and in Southeast Asia. This primarily corresponds to the distribution of vegetation around the globe ( Fig. 2a ): more vegetation leads to more of total ET to occur as transpiration. However, as vegetation gets denser (higher LAI), the fraction of transpiration tends to saturate in the models ( Fig. 2b ). For instance, in the tropics, where vegetation is the densest, the share of transpiration is not much greater than in the midlatitudes. This is

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Yi-Hung Kuo, Kathleen A. Schiro, and J. David Neelin

; Bernstein and Neelin 2016 ; Langenbrunner and Neelin 2017 ), the contribution of certain processes can be difficult to isolate, making constraining model performance challenging. As such, there is an emerging need for diagnostics targeting processes and focusing on the most relevant time scales. This study presents an example of such process-oriented diagnostics—the convective transition statistics—that focus on the fast-time-scale deep convection in the tropics. The sensitivity of moist convection to

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Alexis Berg and Justin Sheffield

. Figure 1a shows that a significant share of ET variance is explained by soil moisture variability (positive correlation values) in the subtropics and midlatitudes. These are drier regions, where ET is soil moisture limited; consequently, ET variations reflect variations in soil moisture availability. Conversely, more negative values indicate regions where ET variations drive soil moisture variations. These are wetter regions, at high latitudes and in the tropics, where soil moisture availability is

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Douglas E. Miller and Zhuo Wang

). The present study will focus on ENSO, the NAO, and midlatitude weather regimes and will evaluate their representations and impacts on the seasonal prediction skill in the Climate Forecast System, version 2 (CFSv2). ENSO is a prominent coupled mode involving the tropical atmosphere and ocean. Although the associated SST anomalies largely occur in the tropics, ENSO induces climate anomalies in many parts of the planet and plays an important role in seasonal prediction ( Power et al. 1999 ; Yuan

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Eric D. Maloney, Andrew Gettelman, Yi Ming, J. David Neelin, Daniel Barrie, Annarita Mariotti, C.-C. Chen, Danielle R. B. Coleman, Yi-Hung Kuo, Bohar Singh, H. Annamalai, Alexis Berg, James F. Booth, Suzana J. Camargo, Aiguo Dai, Alex Gonzalez, Jan Hafner, Xianan Jiang, Xianwen Jing, Daehyun Kim, Arun Kumar, Yumin Moon, Catherine M. Naud, Adam H. Sobel, Kentaroh Suzuki, Fuchang Wang, Junhong Wang, Allison A. Wing, Xiaobiao Xu, and Ming Zhao

are designed to inform parameterization improvements to address these long-standing model biases (e.g., Eyring et al. 2019 ). A POD characterizes a specific physical process or emergent behavior that is hypothesized to be related to the ability to simulate an observed phenomenon. An example of an observed phenomenon is the intraseasonal variability of tropical convection, as could be measured by an index or a power spectra of precipitation variance in the tropics. PODs representing the

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Stephanie A. Henderson, Eric D. Maloney, and Seok-Woo Son

represented by the time mean vertical gradient of dry static energy . On characteristic time scales of the MJO, the dominant thermodynamic energy balance in the tropics that results from conditions of weak temperature gradients is the following ( Wolding et al. 2016 ): where ω ′ is the vertical velocity perturbation associated with the MJO convection. The DJF mean 200–500-hPa vertically averaged static stability is calculated for each good MJO GCM over the MJO region (60°E–180°, 20°S–20°N). The areal

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