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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

( Meehl and Tebaldi 2004 ; Wang et al. 2020 ). Over the United States, trends in heat-wave frequency have been generally positive in recent decades ( Oswald and Rood 2014 ; Schoof et al. 2017 ; Oswald 2018 ; Shafiei Shiva et al. 2019 ), although regional trends vary based on the index used ( Smith et al. 2013 ). Several studies have noted the greater increase in nighttime (Tmin) versus daytime (Tmax) heat waves over the United States ( Lyon and Barnston 2017 ; Rennie et al. 2019 ), specifically

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Allison B. Marquardt Collow and Mark A. Miller

1. Introduction The Amazon rain forest is an important component of the global carbon and hydrologic cycles and is a region within the tropics with potential climate change sensitivities, especially with the recent trend of deforestation. Climate change is driven by alterations to regional and global radiation budgets, and uncertainties remain in the relationships between the biosphere, radiation, clouds, and aerosols. It is therefore important to assemble a collection of observations from

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Michael G. Bosilovich, Franklin R. Robertson, Lawrence Takacs, Andrea Molod, and David Mocko

effect of AIRS itself is best seen here as an additional jump in the PC value in 2002 indicating an increased drying. From Table 2 , which contains the percent variance explained by the first five modes at each level, it is clear that one mode at 975 hPa and at most three modes at the other levels clearly delineate the impact of the sensors. Mode-2 and mode-3 PCs and EOFs at the upper levels (not shown) serve largely to modify the seasonal cycle effects and regional details of the patterns. Table 2

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Franklin R. Robertson, Michael G. Bosilovich, and Jason B. Roberts

; Ting et al. 2011 ] also modulate moisture transport. Anthropogenic radiative forcing changes and the consequent hydrologic cycle effects are expected to produce regional variations, encapsulated in the “wet get wetter and dry get drier” paradigm ( Chou and Neelin 2004 ) wherein hydrologic extremes are expected to increase. As yet, evidence for this behavior in observational datasets is weak at best ( Greve et al. 2014 ). There is also substantial uncertainty as to trends in soil moisture dryness

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Gloria L. Manney and Michaela I. Hegglin

westerly winds in the subtropical upper troposphere (e.g., Held and Hou 1980 ). Eddy-driven jets are maintained by disturbances in the atmospheric zonal mean flow ( Held and Hoskins 1985 ; Lorenz and Hartmann 2003 ; Robinson 2006 ; Baldwin et al. 2007 ; Garfinkel et al. 2013 , and references therein). However, observations show a complex seasonally and regionally varying picture in which distinct radiatively driven or eddy-driven jets cannot be identified (e.g., Manney et al. 2014 ), consistent

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C. A. Randles, A. M. da Silva, V. Buchard, P. R. Colarco, A. Darmenov, R. Govindaraju, A. Smirnov, B. Holben, R. Ferrare, J. Hair, Y. Shinozuka, and C. J. Flynn

observations to produce four-dimensional, gridded output that optimally combines the continuity of a model with real-world observations that may be sparse and/or irregularly spaced both spatially and temporally ( Rienecker et al. 2011 ; Schutgens et al. 2010 ). The analyzed aerosol fields from reanalyses such as MERRA-2 have numerous applications [see Bocquet et al. (2015) and citations therein]. Briefly, these fields can serve as initial conditions for regional modeling and air quality forecasting

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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

statistics. Section 5 examines global and regional aspects of the representation of precipitation in MERRA-2, focusing on areas of difficulty in MERRA. Stratospheric processes and the representation of ozone are discussed in section 6 . Section 7 addresses the representation of the cryosphere in MERRA-2, with focus on glaciated land surface processes. Section 8 provides information about MERRA-2 products and how they can be accessed. It is noted here that each MERRA-2 data collection has its own

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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

1. Introduction The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), is NASA’s latest reanalysis for the satellite era (1980 onward) using the Goddard Earth Observing System, version 5 (GEOS-5), Earth system model. MERRA-2 provides several improvements over its predecessor MERRA-1 ( Rienecker et al. 2011 ), including online aerosol fields that interact with model radiation fields (i.e., aerosol direct and semidirect effects) for the entire period ( Randles

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Laura M. Hinkelman

-sky surface fluxes have improved going from MERRA to MERRA-2, the disagreement from EBAF in ATOTNET is much worse in MERRA-2. This is because the large biases in MERRA ASWDN and ALWDN are of opposite sign and thus offsetting, while the smaller biases in MERRA-2 reinforce each other. Overall, the MERRA and MERRA-2 clear-sky surface radiative fluxes agree better with EBAF. The chief exception is CSWDN term in MERRA-2, for which the difference has increased from −0.9 to 5.0 W m −2 . Apparently, cloud effects

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Allison B. Marquardt Collow, Michael G. Bosilovich, and Randal D. Koster

global precipitation and surface evaporation ( Reichle and Liu 2014 ; Takacs et al. 2016 ). MERRA-2 also features numerous developments in the underlying model ( Molod et al. 2015 ), such as in the surface layer and boundary layer parameterizations and in the cumulus convection scheme. The data assimilation has been updated to the latest Gridpoint Statistical Interpolation analysis scheme version and includes global dry mass constraints that help minimize spurious temporal variability effects

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