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Man-Li C. Wu, Oreste Reale, Siegfried D. Schubert, Max J. Suarez, and Chris D. Thorncroft

1. Introduction This article investigates some large-scale properties of the atmospheric circulation over western Africa and the northern tropical Atlantic across seasonal and subseasonal time scales. In particular, relationships between instability of the atmospheric flow computed on a seasonal time scale, African easterly wave (AEW) activity, and the spatial distribution of tropical genesis points are investigated. The problem of tropical cyclogenesis can be studied from a variety of

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Man-Li C. Wu, Oreste Reale, and Siegfried D. Schubert

.g., Burpee 1972 ). They began receiving special attention after the Global Atmospheric Research Program (GARP) Atlantic Tropical Experiment (GATE) field campaigns ( Burpee 1975 ; Reed et al. 1977 ; Thompson et al. 1979 ). In the following decades, evidence was provided that the range of time scales for African wave–like disturbances may be wider, and various authors started investigating a 2–10-day time window to properly encompass all time scales associated with AEWs (e.g., Dickinson and Molinari

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Siegfried Schubert, Hailan Wang, and Max Suarez

to diagnose the maintenance of both climatological and anomalous atmospheric circulation by evaluating the relative roles of stationary wave forcing over specific regions (e.g., Ting et al. 2001 ; Held et al. 2002 ; Lau et al. 2004 ). More details of the SWM can be found in Ting and Yu (1998) . In the experiments performed here, the background state for the SWM consists of the full three-dimensional climatological JJA flow computed from MERRA for the period 1979–2010. The stationary wave

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Tiffany A. Shaw, Judith Perlwitz, Nili Harnik, Paul A. Newman, and Steven Pawson

ozone changes in order to properly capture the impact of stratospheric ozone changes on tropospheric climate. The evaluation of the GEOS CCM showed that cross-spectral correlation and wave geometry diagnostics are appropriate tools for diagnosing downward wave coupling in atmospheric general circulation models. Acknowledgments We thank NASA’s Global Modeling and Assimilation Office for providing the MERRA dataset. This work was supported by the NASA Modeling and Analysis Program and used high

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Nili Harnik, Judith Perlwitz, and Tiffany A. Shaw

wave 1 cross correlations for the period 1979–98 were very close to those from ERA-40. Furthermore, the MERRA decadal cross-correlation changes during the period 1979–2009 agree well with similar estimates based on the National Centers for Environmental Prediction (NCEP)/Department of Energy (DOE) Atmospheric Model Intercomparison Project, phase 2 (AMIP-II) Reanalysis (R-2) ( Kanamitsu et al. 2002 ). Overall, the wave 1 decadal cross correlations are more reliable because they are directly based on

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Michael A. Brunke, Zhuo Wang, Xubin Zeng, Michael Bosilovich, and Chung-Lin Shie

1. Introduction The atmosphere and ocean interact at their interface through surface turbulent fluxes of temperature [sensible heat (SH)], moisture [latent heat (LH)], and momentum (wind stress τ ). Knowledge of these fluxes is important to understand the ocean heat and freshwater budget and the partitioning of the global pole-to-equator heat transport between the atmosphere and the ocean. The fluxes are also needed to provide a boundary condition for both atmospheric and ocean models and are

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Brian E. Mapes and Julio T. Bacmeister

on the right-hand side of each budget called the analysis tendency (AT) guarantees it. Construction of the ATs occurs during a predictor–corrector or forward–backward time integration that drives the model through a sequence of analyzed atmospheric states (as described in section 2 ). In a well-developed, comprehensive, full-physics GCM like GEOS-5, model shortcomings are mostly second-order weaknesses within adequate schemes, not wildly inaccurate or missing processes. This helps us interpret

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Michele M. Rienecker, Max J. Suarez, Ronald Gelaro, Ricardo Todling, Julio Bacmeister, Emily Liu, Michael G. Bosilovich, Siegfried D. Schubert, Lawrence Takacs, Gi-Kong Kim, Stephen Bloom, Junye Chen, Douglas Collins, Austin Conaty, Arlindo da Silva, Wei Gu, Joanna Joiner, Randal D. Koster, Robert Lucchesi, Andrea Molod, Tommy Owens, Steven Pawson, Philip Pegion, Christopher R. Redder, Rolf Reichle, Franklin R. Robertson, Albert G. Ruddick, Meta Sienkiewicz, and Jack Woollen

. , 1987 : The effect of orographically excited gravity wave drag on the general circulation of the lower stratosphere and troposphere . J. Atmos. Sci. , 44 , 1775 – 1800 . McMillin , L. M. , X. Xiong , Y. Han , T. J. Kleespies , and P. Van Delst , 2006 : Atmospheric transmittance of an absorbing gas. 7. Further improvements to the OPTRAN 6 approach . Appl. Opt. , 45 , 2028 – 2034 , doi:10.1364/AO.45.002028 . Moorthi , S. , and M. J. Suarez , 1992 : Relaxed Arakawa

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Franklin R. Robertson and Jason B. Roberts

1. Introduction Intraseasonal variability (ISV) of tropical convection (e.g., Madden and Julian 1972 , 1994 ; Lau and Chan 1986 ; Stephens et al. 2004 ) remains a compelling and enigmatic science target for several reasons. First, the role of various physical processes that govern organization of tropical convection remains unclear. Among the key mechanisms that have been invoked as crucial to the existence, organization, and pacing of ISV are variants of wave-conditional instability of the

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Aaron D. Kennedy, Xiquan Dong, Baike Xi, Shaocheng Xie, Yunyan Zhang, and Junye Chen

has been done to derive forcing using constrained variational analysis from observations during intensive observation periods (IOPs) at the Department of Energy (DOE) Atmospheric Radiation Measurement Program (ARM) sites ( Zhang and Lin 1997 ; Zhang et al. 2001 ). More recently, Xie et al. (2003) evaluated the forcing datasets derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) during three IOPs at the ARM Southern Great Plains (SGP) site. They found that although the

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