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Bin Guan, Duane E. Waliser, and F. Martin Ralph

1. Introduction Characterized by enhanced water vapor transport in long and narrow corridors in the lower troposphere, atmospheric rivers (ARs) play important roles in the global water cycle ( Zhu and Newell 1998 ) and deliver precious freshwater to many arid/semiarid regions ( Guan et al. 2010 ; Dettinger et al. 2011 ; Rutz and Steenburgh 2012 ), but they can also represent a significant hazard around the globe due to the associated extreme wind and precipitation (e.g., Waliser and Guan

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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

( Gershunov et al. 2009 ) and the Pacific Northwest ( Bumbaco et al. 2013 ) on Tmin heat-wave days. Fig . 9. Composites of daily anomalies in (a),(b) total precipitable water vapor (kg m −2 ); (c),(d) 2-m specific humidity (g kg −1 ); and (e),(f) surface downward longwave flux (W m −2 ) for (left) daytime hours on daytime heat-wave days and (right) nighttime hours on nighttime heat-wave days. Regions where the composite mean is not statistically significantly at the 95% confidence level are masked out. c

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

, this leads to an imbalance in the long term average of the physical and dynamical terms, and reflects systematic model biases. For example, high tropical warm pool precipitation ( Bosilovich et al. 2008 ) and trends in water vapor transport ( Robertson et al. 2014 ) have been noted. The atmospheric water budget may also require large increments locally to preserve a closed atmospheric budget in the assimilation data ( Bosilovich et al. 2015a ). The analysis increment is a crucial component of the

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Allison B. Marquardt Collow and Mark A. Miller

with a resolution of 15 min demonstrated the impact of clouds on the downwelling shortwave (SW) radiation, and variability in the SW RFD resulting from changing cloud cover was easily detected through analyzing the SW radiation budget in combination with cloud radar data. Slingo et al. (2009) later expanded this study using the same dataset to provide a seasonal view over the West African Sahel and demonstrated that water vapor in the wet season prevented a portion of longwave (LW) radiation at

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

. Significant increases in precipitation in the Northeast have been documented in the fall and on an annual time scale ( Kunkel et al. 2013 ), and a statistically significant increase in extreme precipitation events has been documented during the Northeast warm season ( Frei et al. 2015 ). Many studies have shown that warmer air can hold more water vapor, thereby increasing extreme rainfall; however, the increase in extreme precipitation in the Northeast has been shown to exceed that dictated by the

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

satellite observations especially, have a time-dependent ability to correct the model first-guess fields. Therefore discrete biases develop in water and energy fluxes and transports. For reanalyses the vertically integrated atmospheric moisture budget over land grid points is that is, vapor plus condensate W a increases as the result of vertically integrated atmospheric moisture flux convergence (VMFC) and ET and is depleted by precipitation P . In reanalyses, the analysis increment (ANA) represents

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Laura M. Hinkelman

contributes to the TOA ASWUP. Large surface albedos occur over the Saharan Desert and eastern Saudi Arabia, Greenland, and Antarctica. Somewhat higher-than-average albedos also occur over the Arctic, Antarctic marginal ice zone, and Mongolia. Summing these fluxes with the cloud reflection accounts for most of the observed TOA ASWUP pattern. The effects of aerosol and water vapor absorption and reflection can be deduced from the surface clear-sky downward SW flux. In the EBAF CSWDN map of Fig. 4d , areas

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

structure is physically linked to diabatic temperature tendency and water vapor tendency as shown in Fig. 14 . It is clear that diabatic heating (shaded) is more pronounced slightly north of the equator in the 2015/16 El Niño, while the maximum heating is farther to the south in the other two EP events, especially the 1997/98 event as the 2015/16 event has characteristics of both CP and EP warming (e.g., Figs. 8 and 9 ) ( Xie and Yang 2014 ). This difference in the heating latitudes seems to imply

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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

variable for moisture used in recent versions of GSI and MERRA-2 differs from the one used in MERRA. Whereas MERRA used the so-called pseudorelative humidity ( Dee and da Silva 2003 ) defined by the water vapor mixing ratio scaled by its saturation value, MERRA-2 uses the normalized pseudorelative humidity ( Holm 2003 ) defined by the pseudorelative humidity scaled by its background error standard deviation. The latter has a near Gaussian error distribution, making it more suitable for the minimization

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Clara S. Draper, Rolf H. Reichle, and Randal D. Koster

tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities . Bull. Amer. Meteor. Soc. , 82 , 2415 – 2434 , https://doi.org/10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2 . 10.1175/1520-0477(2001)082<2415:FANTTS>2.3.CO;2 Beck , H. , A. van Dijk , V. Levizzani , J. Schellekens , D. Miralles , B. Martens , and A. de Roo , 2017 : MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge

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