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The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA’s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA’s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given. By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses. Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC).

A benchmark calculation is proposed for evaluating the dynamical cores of atmospheric general circulation models independently of the physical parameterizations. The test focuses on the long-term statistical properties of a fully developed general circulation; thus, it is particularly appropriate for intercomparing the dynamics used in climate models. To illustrate the use of this benchmark, two very different atmospheric dynamical cores-one spectral, one finite difference-are compared. It is found that the long-term statistics produced by the two models are very similar. Selected results from these calculations are presented to initiate the intercomparison.

Abstract. The Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) version of the Goddard Earth Observing System-5 (GEOS-5) atmospheric general circulation model (AGCM) is currently in use in the NASA Global Modeling and Assimilation Office (GMAO) at a wide range of resolutions for a variety of applications. Details of the changes in parameterizations subsequent to the version in the original MERRA reanalysis are presented here. Results of a series of atmosphere-only sensitivity studies are shown to demonstrate changes in simulated climate associated with specific changes in physical parameterizations, and the impact of the newly implemented resolution-aware behavior on simulations at different resolutions is demonstrated. The GEOS-5 AGCM presented here is the model used as part of the GMAO MERRA2 reanalysis, global mesoscale simulations at 10 km resolution through 1.5 km resolution, the real-time numerical weather prediction system, and for atmosphere-only, coupled ocean-atmosphere and coupled atmosphere-chemistry simulations.The seasonal mean climate of the MERRA2 version of the GEOS-5 AGCM represents a substantial improvement over the simulated climate of the MERRA version at all resolutions and for all applications. Fundamental improvements in simulated climate are associated with the increased reevaporation of frozen precipitation and cloud condensate, resulting in a wetter atmosphere. Improvements in simulated climate are also shown to be attributable to changes in the background gravity wave drag, and to upgrades in the relationship between the ocean surface stress and the ocean roughness. The series of resolution-aware parameters related to the moist physics was shown to result in improvements at higher resolutions and result in AGCM simulations that exhibit seamless behavior across different resolutions and applications.

The North American Multimodel Ensemble prediction experiment is described, and forecast quality and methods for accessing digital and graphical data from the model are discussed.

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Abstract. A new strategy for modeling the land surface component of the climate system is described. The strategy is motivated by an arguable deficiency in most state-of-the-art land surface models, namely, the disproportionately higher emphasis given to the formulation of one-dimensional, vertical physics relative to the treatment of horizontal heterogeneity in surface properties, particularly subgrid soil moisture variability and its effects on runoff generation. The new strategy calls for the partitioning of the continental surface into a mosaic of hydrologic catchments, delineated through analysis of high-resolution surface elevation data. The effective "grid" used for the land surface is therefore not specified by the overlying atmospheric grid. Within each catchment, the variability of soil moisture is related to characteristics of the topography and to three bulk soil moisture variables through a well-established model of catchment processes. This modeled variability allows the partitioning of the catchment into several areas representing distinct hydrological regimes, wherein distinct (regime specific) evaporation and runoff parameterizations are applied. Care is taken to ensure that the deficiencies of the catchment model in regions of little to moderate topography are minimized.