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Mohar Chattopadhyay, Will McCarty, and Isaac Moradi

(FOV) ( Mo 1999 ; Mo and Liu 2008 ). These observations are not intercalibrated among instruments. In other words, no attempt is made to correct for cross-instrument differences as seen in observation space. AMSU-A data play an important role in globally constraining atmospheric temperature. In the absence of a realistic GWD parameterization in a model, the intercalibrated AMSU-A data can significantly improve the temperature of the middle atmosphere ( Polavarapu et al. 2005 ). There have been

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Natalie P. Thomas, Michael G. Bosilovich, Allison B. Marquardt Collow, Randal D. Koster, Siegfried D. Schubert, Amin Dezfuli, and Sarith P. Mahanama

. 2011 ). Presumably, this is due to the fact that warm nights eliminate the anticipated recovery period during extreme heat events. Both daytime and nighttime heat waves can be harmful to society, so it is important to understand the unique mechanisms leading to the onset of each. Atmospheric conditions characteristic of daytime heat waves are well-studied. Typically, heat waves are associated with anticyclonic circulation and subsidence in the middle and upper troposphere ( Namias 1982 ; Chang and

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Young-Kwon Lim, Robin M. Kovach, Steven Pawson, and Guillaume Vernieres

not foreseen until the middle of 2015. Model forecasts in January 2015 predicted that weak warm conditions over the tropical Pacific would decay in Northern Hemisphere spring ( McPhaden 2015 ). The problem raised here suggests that the growth of ENSO and its strength strongly depend on subseasonal atmosphere and ocean variability. Additionally, this study identified that SST and 2mT anomalies in 2015/16 are positive and generally greater than 1982/83 and 1997/98 over the majority of the WMI and

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Laura M. Hinkelman

1. Introduction Reanalysis products are now accepted by the majority of atmospheric scientists as the best available long-term representations of the large-scale dynamical and thermodynamical states of the atmosphere. By incorporating observations such as pressure, wind, temperature, and humidity profiles from radiosondes as well as radiances and other quantities retrieved by satellites into an atmospheric model via data assimilation, model processes are closely constrained to the true

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Krzysztof Wargan, Gordon Labow, Stacey Frith, Steven Pawson, Nathaniel Livesey, and Gary Partyka

1. Introduction Atmospheric reanalyses produce global high spatial and temporal resolution long-term records of meteorological fields and composition of Earth’s atmosphere by utilizing the data assimilation methodology ( Cohn 1997 ; Kalnay 2003 ), whereby satellite and ground-based observations are combined with general circulation model (GCM) simulations in a statistically optimal way. The Modern-Era Retrospective Analysis for Research and Applications (MERRA: Rienecker et al. 2011 ) was the

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Rolf H. Reichle, Q. Liu, Randal D. Koster, Clara S. Draper, Sarith P. P. Mahanama, and Gary S. Partyka

corrected using a global, gauge-based precipitation product, and because important changes were made to the rainfall interception parameterization in the land surface model ( Reichle et al. 2011 ). The land surface model and parameters in MERRA-2 closely resemble those of MERRA-Land, thus carrying the land model improvements into the coupled atmosphere–land MERRA-2 reanalysis. The precipitation corrections in MERRA-2 are refined from those used in MERRA-Land, with three main differences. First, and

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Ronald Gelaro, Will McCarty, Max J. Suárez, Ricardo Todling, Andrea Molod, Lawrence Takacs, Cynthia A. Randles, Anton Darmenov, Michael G. Bosilovich, Rolf Reichle, Krzysztof Wargan, Lawrence Coy, Richard Cullather, Clara Draper, Santha Akella, Virginie Buchard, Austin Conaty, Arlindo M. da Silva, Wei Gu, Gi-Kong Kim, Randal Koster, Robert Lucchesi, Dagmar Merkova, Jon Eric Nielsen, Gary Partyka, Steven Pawson, William Putman, Michele Rienecker, Siegfried D. Schubert, Meta Sienkiewicz, and Bin Zhao

with different bias characteristics ( Kobayashi et al. 2009 ). The CRTM has been enhanced for SSU data assimilation since MERRA and now accounts for these biasing factors. The main additional observations relevant to the stratosphere for MERRA-2 are GPSRO bending angle observations from the suite of platforms beginning in July 2004 and temperature and ozone measurements of the middle atmosphere from MLS and OMI on the EOS Aura satellite beginning later the same year ( Froidevaux et al. 2006

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Krzysztof Wargan and Lawrence Coy

improve the manuscript significantly. REFERENCES Andrews , D. G. , J. R. Holton , and C. B. Leovy , 1987 : Middle Atmosphere Dynamics . International Geophysics Series, Vol. 40, Academic Press, 489 pp . Birner , T. , 2006 : Fine-scale structure of the extratropical tropopause region . J. Geophys. Res. , 111 , D04104 , doi: 10.1029/2005JD006301 . Birner , T. , 2010 : Residual circulation and tropopause structure . J. Atmos. Sci. , 67 , 2582 – 2600 , doi: 10.1175/2010JAS3287

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V. Buchard, C. A. Randles, A. M. da Silva, A. Darmenov, P. R. Colarco, R. Govindaraju, R. Ferrare, J. Hair, A. J. Beyersdorf, L. D. Ziemba, and H. Yu

geographical and temporal coverage due to cloud contamination, uncertainties in aerosol retrievals, and sensor-specific data gaps. Although they provide continuity, aerosol models experience uncertainties due to emissions and physical parameterizations. One approach to provide a better representation of aerosols in the atmosphere is to take advantage of both models and sparse observations using data assimilation techniques. By combining the high temporal and spatial coverage of a global model with

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Rolf H. Reichle, Clara S. Draper, Q. Liu, Manuela Girotto, Sarith P. P. Mahanama, Randal D. Koster, and Gabrielle J. M. De Lannoy

both the MERRA-Land precipitation and the (uncorrected) AGCM-generated precipitation from MERRA-2 and MERRA. Moreover, in MERRA-2 the precipitation is corrected within the coupled atmosphere–land modeling system, allowing the near-surface air temperature and humidity to respond to the improved precipitation forcing. MERRA-2 thus provides more self-consistent surface meteorological data than were used for MERRA-Land ( Reichle et al. 2017 ). This enhanced self-consistency in the forcing data also

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