The Global Radiative Energy Budget in MERRA and MERRA-2: Evaluation with Respect to CERES EBAF Data

The representation of the long-term radiative energy budgets in NASA’s MERRA and MERRA-2 reanalyses has been evaluated, emphasizing changes associated with the reanalysis system update. Data from the CERES EBAF Edition 2.8 satellite product over 2001–15 were used as a reference. For both MERRA and MERRA-2, the climatological global means of most TOA radiative flux terms agree to within ~3 W m−2 of EBAF. However, MERRA-2’s all-sky reflected shortwave flux is ~7 W m−2 higher than either MERRA or EBAF’s, resulting in a net TOA flux imbalance of −4 W m−2. At the surface, all-sky downward longwave fluxes are problematic for both reanalyses, while high clear-sky downward shortwave fluxes indicate that their atmospheres are too transmissive. Although MERRA-2’s individual all-sky flux terms agree better with EBAF, its net flux agreement is worse (−8.3 vs −3.3 W m−2 for MERRA) because MERRA benefits from cancellation of errors. Analysis by region and surface type gives mixed outcomes. The results consistently indicate that clouds are overrepresented over the tropical oceans in both reanalyses, particularly MERRA-2, and somewhat underrepresented in marine stratocumulus areas. MERRA-2 also exhibits signs of excess cloudiness in the Southern Ocean. Notable discrepancies occur in the polar regions, where the effects of snow and ice cover are important. In most cases, MERRA-2 better represents variability and trends in the global mean radiative fluxes over the period of analysis. Overall, the performance of MERRA-2 relative to MERRA is mixed; there is still room for improvement in the radiative fluxes in this family of reanalysis products.

[1]  David R. Doelling,et al.  Surface Irradiances of Edition 4.0 Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Data Product , 2018 .

[2]  E. Fetzer,et al.  The Observed State of the Energy Budget in the Early Twenty-First Century , 2015 .

[3]  Benjamin Scarino,et al.  A Dynamic Approach to Addressing Observation-Minus-Forecast Bias in a Land Surface Skin Temperature Data Assimilation System , 2015 .

[4]  Thomas M. Smith,et al.  An Improved In Situ and Satellite SST Analysis for Climate , 2002 .

[5]  J. Key,et al.  The influence of winter cloud on summer sea ice in the Arctic, 1983–2013 , 2016 .

[6]  Max J. Suarez,et al.  A Solar Radiation Parameterization for Atmospheric Studies , 2013 .

[7]  G. Kopp,et al.  A new, lower value of total solar irradiance: Evidence and climate significance , 2011 .

[8]  N. Loeb,et al.  Surface Irradiances Consistent With CERES-Derived Top-of-Atmosphere Shortwave and Longwave Irradiances , 2013 .

[9]  Takashi Nakajima,et al.  Impact of different definitions of clear-sky flux on the determination of longwave cloud radiative forcing: NICAM simulation results , 2010 .

[10]  Xiquan Dong,et al.  Evaluation and intercomparison of clouds, precipitation, and radiation budgets in recent reanalyses using satellite-surface observations , 2016, Climate Dynamics.

[11]  Timothy Shippert,et al.  The Continual Intercomparison of Radiation Codes: Results from Phase I , 2012 .

[12]  Greg Kopp,et al.  The Total Irradiance Monitor (TIM): Instrument Design , 2005 .

[13]  B. Barkstrom,et al.  Clouds and the Earth's Radiant Energy System (CERES): An Earth Observing System Experiment , 1996 .

[14]  G. Potter,et al.  Object-Based Evaluation of MERRA Cloud Physical Properties and Radiative Fluxes during the 1998 El Niño–La Niña Transition , 2012 .

[15]  R. Dickinson,et al.  Global atmospheric downward longwave radiation at the surface from ground‐based observations, satellite retrievals, and reanalyses , 2013 .

[16]  Xin-Zhong Liang,et al.  A Thermal Infrared Radiation Parameterization for Atmospheric Studies , 2001 .

[17]  David R. Doelling,et al.  Toward Optimal Closure of the Earth's Top-of-Atmosphere Radiation Budget , 2009 .

[18]  H. La,et al.  The Evident Role of Clouds on Phytoplankton Abundance in Antarctic Coastal Polynyas , 2016 .

[19]  Xiquan Dong,et al.  Evaluation and Intercomparison of Cloud Fraction and Radiative Fluxes in Recent Reanalyses over the Arctic Using BSRN Surface Observations , 2012 .

[20]  Thomas M. Smith,et al.  Daily High-Resolution-Blended Analyses for Sea Surface Temperature , 2007 .

[21]  Michael G. Bosilovich,et al.  The Energy Budget of the Polar Atmosphere in MERRA , 2012 .

[22]  S. Moorthi,et al.  Relaxed Arakawa-Schubert - A parameterization of moist convection for general circulation models , 1992 .

[23]  Sunny Sun-Mack,et al.  Uncertainty Estimate of Surface Irradiances Computed with MODIS-, CALIPSO-, and CloudSat-Derived Cloud and Aerosol Properties , 2012, Surveys in Geophysics.

[24]  S. Nowicki,et al.  Greenland Ice Sheet Surface Melt and Its Relation to Daily Atmospheric Conditions , 2017 .

[25]  Michael G. Bosilovich,et al.  Global Energy and Water Budgets in MERRA , 2011 .

[26]  Kevin E. Trenberth,et al.  Climate variability and relationships between top‐of‐atmosphere radiation and temperatures on Earth , 2015 .

[27]  S. Schubert,et al.  Climatology of the Simulated Great Plains Low-Level Jet and Its Contribution to the Continental Moisture Budget of the United States , 1995 .

[28]  N. Loeb,et al.  CERES Synoptic Product: Methodology and Validation of Surface Radiant Flux , 2015 .

[29]  D. F. Young,et al.  Geostationary Enhanced Temporal Interpolation for CERES Flux Products , 2013 .

[30]  M. Miller,et al.  The Seasonal Cycle of the Radiation Budget and Cloud Radiative Effect in the Amazon Rain Forest of Brazil , 2015 .

[31]  Bin Zhao,et al.  The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). , 2017, Journal of climate.

[32]  Xubin Zeng,et al.  Evaluation of multireanalysis products with in situ observations over the Tibetan Plateau , 2012 .

[33]  P. Colarco,et al.  The MERRA-2 Aerosol Reanalysis, 1980 Onward. Part II: Evaluation and Case Studies. , 2017, Journal of climate.

[34]  Robert Pincus,et al.  Reconciling Simulated and Observed Views of Clouds: MODIS, ISCCP, and the Limits of Instrument Simulators in Climate Models , 2011 .

[35]  W. Paul Menzel,et al.  State of the Climate in 2016 , 2017 .

[36]  Loeb,et al.  Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product , 2018 .

[37]  C. Donlon,et al.  The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system , 2012 .

[38]  R. Shekhar,et al.  Weakening and Shifting of the Saharan Shallow Meridional Circulation During Wet Years of the West African Monsoon , 2016, 1609.08515.

[39]  C. Frantzidis,et al.  Response to Reviewers Reviewer #1 , 2010 .

[40]  J. Louis A parametric model of vertical eddy fluxes in the atmosphere , 1979 .

[41]  Bryan A. Baum,et al.  Clouds and the Earth's Radiant Energy System (CERES) , 1995 .

[42]  C. Flynn,et al.  The MERRA-2 Aerosol Reanalysis, 1980 - onward, Part I: System Description and Data Assimilation Evaluation. , 2017, Journal of climate.

[43]  Ricardo Todling,et al.  The GEOS-5 Data Assimilation System-Documentation of Versions 5.0.1, 5.1.0, and 5.2.0 , 2008 .

[44]  B. Goswami,et al.  Aerosol and cloud feedbacks on surface energy balance over selected regions of the Indian subcontinent , 2012 .

[45]  Andrea Molod,et al.  The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna , 2012 .

[46]  Konstantin V. Khlopenkov,et al.  A Supplementary Clear-Sky Snow and Ice Recognition Technique for CERES Level 2 Products , 2013 .

[47]  Julio T. Bacmeister,et al.  Rain Reevaporation, Boundary Layer Convection Interactions, and Pacific Rainfall Patterns in an AGCM , 2006 .

[48]  M. Chin,et al.  Online simulations of global aerosol distributions in the NASA GEOS‐4 model and comparisons to satellite and ground‐based aerosol optical depth , 2010 .

[49]  S. Schubert,et al.  MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications , 2011 .

[50]  Randal D. Koster,et al.  Assessment of MERRA-2 Land Surface Energy Flux Estimates , 2018 .