Search Results

You are looking at 1 - 10 of 15 items for :

  • Model performance/evaluation x
  • Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) x
  • All content x
Clear All
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

aerosol products while highlighting both the model’s skill and deficiencies. In section 2 , we provide details about the GEOS-5/GOCART model and aerosol emissions. Section 3 discusses the aerosol assimilation system and the AOD observing system. We then evaluate the performance of the analyzed AOD fields with respect to the observing system and demonstrate the stability of the assimilation system ( section 4a ). The impact of the AOD assimilation is shown by comparisons to a control simulation

Full access
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

background forecast (i.e., aerosol speciation, size, and vertical structure, plus the assumed optical properties that are used to convert aerosol mass to AOD). Furthermore, like the AOD, these diagnostics also depend on the parameterization of error covariances in the aerosol data assimilation algorithm. This paper is the second of a pair that summarize our effort to evaluate MERRA-2 aerosol fields. Part I focused on describing the aerosol data assimilation system as well as the performance of MERRA-2

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

moisture ( section 3b ), snow ( section 3c ), streamflow ( section 3d ), and interception loss fraction ( section 3e ) are evaluated against independent data. Finally, section 4 provides a summary of the findings and conclusions. 2. Data a. The MERRA-2 data product and system 1) Overview The MERRA-2 reanalysis is produced by the National Aeronautics and Space Administration (NASA) Global Modeling and Assimilation Office (GMAO) using the GEOS-5.12.4 system ( Bosilovich et al. 2015 , 2016 ; Gelaro et

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

and SH can be evaluated. Several recent efforts have compared global LH estimates from different combinations of reanalyses, offline land surface models, and diagnostic methods. Most estimates generally agree on the regional patterns and local seasonal cycle of LH, although there is considerable disagreement in the absolute values and temporal behavior across different flux estimates ( Jiménez et al. 2011 ; Mueller et al. 2011 ; Miralles et al. 2011 ). Additionally, uncertainty in the basic

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

difference (1980–2015; mm day −1 ) between the (corrected) MERRA-2 precipitation seen by the land surface and the model-generated precipitation within the MERRA-2 system. Results are derived from the data collections described in GMAO (2015h , j ). Based on the evaluation of several metrics, Reichle et al. (2017a) found the observation-corrected precipitation to be more realistic overall than that generated by the model within the cycling MERRA-2 system, or that of the MERRA and MERRA-Land data

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

) describe the fundamental changes to the reanalysis system for MERRA-2 that differentiate it from MERRA ( Rienecker et al. 2011 ) and provide more information about the system components, data, and evaluation. The prescribed SST data are described in Bosilovich et al. (2015b) . For total solar irradiance, the 11-yr cycle of Lean (2000) plus the background adjustment from Wang et al. (2005) , as recommended for phase 5 of the Coupled Model Intercomparison Project (CMIP5), has been implemented in

Full access
Laura M. Hinkelman

-2 radiative terms. A thorough evaluation of the radiative energy budget in MERRA-2 is thus absent from the literature, and it is the gap that we address here. This evaluation covers variability in both time and space and is made relative to the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Edition 2.8 satellite radiative flux product, which is designed specifically for climate model assessment and estimation of the global mean radiative energy budget

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

as well as the model formulations are still important error sources ( Jiménez et al. 2011 ; Mueller et al. 2013 ). Thus, we examine differences among the P − ET estimates and evaluate their utility as a means of reanalysis validation. 3) We then show that using rotated empirical orthogonal function (REOF) analysis, along with some prefiltering, artificial steps, and trends induced by changing satellite data streams can be largely isolated and removed. 2. Data Our investigation depends

Full access
Gloria L. Manney and Michaela I. Hegglin

[standard pressure level grids with >2 km level spacing in the upper troposphere–lower stratosphere (UTLS)] resolutions, use outdated models and assimilation methods, and have been shown to be inadequate for studies of the UT and stratosphere [see Fujiwara et al. (2017) for a review of reanalysis system characteristics and evaluations]. Peña-Ortiz et al. (2013) also used the NCEP 20CR reanalysis, which assimilates only surface observations and also has coarse horizontal and vertical resolution and

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

-surface meteorological data from reanalysis products to force land surface models ( Nijssen et al. 2001 ; Dirmeyer et al. 2006 ; Qian et al. 2006 ; Sheffield et al. 2006 ; Koster et al. 2011 ; to name a few). Since precipitation is the dominant driver of the land surface water cycle, the objectives of this paper are as follows: to document the land surface precipitation correction approach used in MERRA-2, to provide an initial evaluation of the resulting MERRA-2 precipitation estimates, and to demonstrate the

Full access