Reichle, R. H., R. D. Koster, C. S. Draper, Q. Liu, M. Girotto, S. P. P. Mahanama, G. J. M. De Lannoy, and G. S. Partyka:
"Land surface precipitation and hydrology in MERRA-2"
Presentation at the 5th International Conference on Reanalysis, Rome, Italy, 2017.

Abstract:
The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), provides global, 1-hourly estimates of land surface conditions for 1980-present at ~50-km resolution. Outside of the high latitudes, MERRA-2 uses observations-based precipitation data products to correct the precipitation falling on the land surface.

This paper describes the precipitation correction method and evaluates the MERRA-2 land surface precipitation and hydrology. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is better than the precipitation generated by the atmospheric models within the cycling MERRA-2 system and the earlier MERRA reanalysis. Compared to 3-hourly TRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation.

Because correcting the precipitation within the coupled atmosphere-land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from the earlier, offline MERRA-Land reanalysis. Overall, MERRA-2 land hydrology estimates are better than those of MERRA-Land and MERRA.

A comparison against GRACE satellite observations of terrestrial water storage demonstrates clear improvements in MERRA-2 over MERRA in South America and Africa but also reflects known errors in the observations used to correct the MERRA-2 precipitation. The MERRA-2 and MERRA-Land surface and root zone soil moisture skill vs. in situ measurements is slightly higher than that of ERA-Interim/ Land and higher than that of MERRA (significantly for surface soil moisture).

Snow amounts from MERRA-2 have lower bias and correlate better against reference data than do those of MERRALand and MERRA, with MERRA-2 skill roughly matching that of ERA-Interim/ Land. Seasonal anomaly R values against naturalized streamflow measurements in the United States are, on balance, highest for MERRA-2 and ERA-Interim/ Land, somewhat lower for MERRA-Land, and lower still for MERRA.


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NASA-GSFC / GMAO / Rolf Reichle