Introduction to MERRA

Retrospective-analyses (or reanalyses) integrate a variety of observing systems with numerical models to produce a temporally and spatially consistent synthesis of observations and analyses of variables not easily observed. The breadth of variables, as well as observational influence, make reanalyses ideal for investigating climate variability. The Modern Era-Retrospective Analysis for Research and Applications supports NASA's Earth science objectives, by applying the state-of-the-art GEOS-5 data assimilation system that includes many modern observing systems (such as EOS) in a climate framework.

The MERRA project supports NASA's Earth science interests by:
  1. utilizing the NASA global data assimilation system to produce a long-term (1979-present) synthesis that places the current suite of research satellite observations in a climate data context.
  2. providing the science and applications communities with state-of-the-art global analyses, with emphasis on improved estimates of the hydrological cycle on a broad range of weather and climate time scales.

The MERRA time period covers the modern era of remotely sensed data, from 1979 through the present, and the special focus of the atmospheric assimilation is the hydrological cycle. Previous long-term reanalyses of the Earth's climate had high levels of uncertainty in precipitation and inter-annual variability. The GEOS-5 data assimilation system used for MERRA implements Incremental Analysis Updates (IAU) to slowly adjust the model states toward the observed state. The water cycle benefits as unrealistic spin down is minimized. In addition, the model physical parameterizations have been tested and evaluated in a data assimilation context, which also reduces the shock of adjusting the model system. Land surface processes are modeled with the state-of-the-art GEOS-5 Catchment hydrology land surface model. MERRA thus makes significant advances in the representation of the water cycle in reanalyses.

An improved set of land surface hydrological fields is provided in the supplemental MERRA-Land data product. In addition to the above-mentioned improvements, this product benefits from observation-based corrections to the precipitation forcing and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings.

The 72 vertical levels in GEOS-5 extend through the stratosphere. A special data product, developed in conjunction with the chemistry community supports chemistry transport modeling. The disseminated data products provide much improved initial conditions for predicting weather and other subseasonal variability that is strongly linked to tropical moisture. Studies of climate variability rely on reanalysis data sets. Limited domain models use reanalyses to provide the boundary forcing and initial conditions for mesoscale and regional climate simulations.

MERRA output data resemble other global reanalyses, with several key advances, including output at frequencies higher than the 6-hourly analyses. Two-dimensional diagnostics (surface fluxes, single level meteorology, vertical integrals and land states) are produced at 1-hour intervals. These data products and the 6-hourly three-dimensional atmospheric analyses are also available at the full spatial resolution (1/2 degrees latitude × 2/3 degrees longitude). Extensive three-dimensional 3-hourly atmospheric diagnostics on 42 pressure levels are also available, but at coarser (1.25 degree) resolution. The Goddard Earth Sciences Data Information Services Center (GES DISC) provides utilities for users to access and subset the MERRA data products.

MERRA is funded by the NASA Modeling Analysis and Prediction (MAP) program. Initial funding was also provided by a NASA Cooperative Agreement Notice (CAN): Earth Science REASoN - Research, Education, and Applications Solutions Network.