Search Results

You are looking at 1 - 10 of 13 items for :

  • Water budget/balance x
  • Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) x
  • All content x
Clear All
Natalie P. Thomas, Michael G. Bosilovich, Allison B. Marquardt Collow, Randal D. Koster, Siegfried D. Schubert, Amin Dezfuli, and Sarith P. Mahanama

heat waves over the Pacific Northwest United States, Bumbaco et al. (2013) also noted a greater role of precipitable water in nighttime heat waves, compared with a stronger 500-hPa ridge and increased subsidence during daytime heat waves. Over the Korean Peninsula, nighttime heat events were found to be associated with a baroclinic atmospheric structure and increased cloud cover ( Hong et al. 2018 ). A comprehensive analysis of mechanisms driving nighttime heat waves for different regions of the

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

E − P ocor is consistent with the land surface water budget but not the atmospheric water budget. The performance of the MERRA-2 land system in the context of land surface hydrology and GRACE observations will be reported separately ( Reichle et al. 2016 , unpublished manuscript); here we focus primarily on the atmospheric water balance except where specifically noted by calling out the observation-corrected precipitation P ocor . In some comparisons, we will include a pure model experiment

Full access
Allison B. Marquardt Collow and Mark A. Miller

) handbook. ARM Climate Research Facility Rep. ARM TR-027, 13 pp . Takacs , L. L. , M. J. Suárez , and R. Todling , 2016 : Maintaining atmospheric mass and water balance in reanalyses . Quart. J. Roy. Meteor. Soc. , 142 , 1565 – 1573 , doi: 10.1002/qj.2763 . Trenberth , K. E. , J. T. Fasullo , and J. Kiehl , 2009 : Earth’s global energy budget . Bull. Amer. Meteor. Soc. , 90 , 311 – 323 , doi: 10.1175/2008BAMS2634.1 . Wang , Z. , and K. Sassen , 2001 : Cloud type and

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

from the literature. These literature estimates, from Trenberth et al. (2009) , Wild et al. (2015) , and the NASA Energy and Water Cycle Studies (NEWS) program ( NEWS Science Integration Team 2007 ; L’Ecuyer et al. 2015 ), were each produced by carefully combining multiple input datasets with global energy balance constraints. Taken together they represent our best understanding of the long-term annual mean energy budget over land. Next, we consider global maps of the performance of the land

Full access
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

Full access
Laura M. Hinkelman

data, even though these fluxes are crucial drivers of the water cycle. For this reason, radiative fluxes from reanalyses must be thoroughly evaluated before they are used in climate or atmospheric process studies. Certain aspects of the reanalyses’ radiative energy budgets have been evaluated previously. As the older of the two products, MERRA has received more attention in this regard. Bosilovich et al. (2011) examined MERRA’s TOA and surface radiative fluxes, looking not only at global values

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

original MERRA system. Additionally, MERRA-2 benefits from advances in the Goddard Earth Observing System, version 5 (GEOS-5) AGCM. MERRA-2 also uses observations-based precipitation data products to drive the land surface water budget. In most reanalysis systems, including the original MERRA, the precipitation seen by the land surface is generated by the system’s AGCM following the assimilation of atmospheric temperature, humidity, and wind observations, among others. The MERRA-2 model

Full access
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

description of the MERRA-2 aerosol analysis system and its validation are presented in Randles et al. (2017) and Buchard et al. (2017, manuscript submitted to J. Climate , hereinafter B17). Reichle et al. (2017a , b ) assess the land surface precipitation and land surface hydrology, while Draper et al. (2017, manuscript submitted to J. Climate ) examine the land surface energy budget. Bosilovich et al. (2017) evaluate the global water balance and water cycle variability in MERRA-2. Collow et al

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

Earth Observing System, version 5 (GEOS-5), AGCM. Another new element in MERRA-2 is its use of observations-based precipitation data products to drive the land surface water budget (and aerosol wet deposition). Precipitation is the dominant driver of land surface hydrologic conditions. In most reanalysis systems, including the original MERRA, the precipitation seen by the land surface is generated by the system’s AGCM following the assimilation of atmospheric observations. The model

Full access
Richard I. Cullather and Sophie M. J. Nowicki

). Observed, enhanced surface melt over the GrIS in the past decade has led to an increased focus on surface mass balance (SMB) and an identification of surface melt as having a dominant role in the contribution of the ice sheet to sea level rise ( Rignot et al. 2011 ; Velicogna et al. 2014 ; Enderlin et al. 2014 ; van den Broeke et al. 2016 ). Arguably, the most consistent and reliable source of surface melt data encompassing the full GrIS is passive microwave data. NASA’s Making Earth System Data

Full access