Land Surface Precipitation in MERRA-2

Abstract

The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), features several major advances from the original MERRA reanalysis, including the use, outside of high latitudes, of observations-based precipitation data products to correct the precipitation falling on the land surface in the MERRA-2 system. The method for merging the observed precipitation into MERRA-2 has been refined from that of the (land-only) MERRA-Land reanalysis. This paper describes the method and evaluates the MERRA-2 land surface precipitation. 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 and MERRA systems. M2CORR is also better than MERRA-Land precipitation over Africa because in MERRA-2 a merged satellite–gauge precipitation product is used instead of the gauge-only data used for MERRA-Land. 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 MERRA-Land, which is important for applications such as land-only modeling studies. Where precipitation observations of sufficient quality are available for use in the reanalysis, the corrections facilitate the seamless spinup of the land surface initial conditions across the MERRA-2 production streams. At high latitudes, however, the lack of reliable precipitation observations results in undesirable land spinup effects that impact mostly the first published year of each MERRA-2 stream (1980, 1992, 2001, and 2011).

Upper Blue Nile basin water budget from a multi-model perspective

“…While M2 appears to follow a similar annual trend in the time series as ML, M2 is 33% higher than ML during the years 2006-2010. It implies that when compared to ML, a merged satellite-gauge precipitation product M2 was improved by its precipitation correction algorithm (Reichle et al, 2017). The other three datasets CH, TM, and TR agree well with annual rates within the range of the two MERRA precipitation products.…”

“…Previous studies Huffman et al, 2007;Reichle et al, 2017) have already demonstrated that by incorporating in situ observation, precipitation datasets CHIRPS, MERRA-2, TMPA3B42 are better than CHIRP, MERRA-Land, TMPA3B42RT, respectively. Besides, ground observations are generally point data whereas these satellite-and/or model-based precipitation datasets represents averages in large scale.…”

“…MERRA-Land is a supplemental land surface data product of MERRA. MERRA-2 is the second version of MERRA with several major upgrades, including observation-based precipitation corrections over Africa (Reichle et al, 2017). Both products are available globally at the hourly time step and horizontal resolution of 2/3°longitude by 1/2°latitude.…”

On the suitability of current atmospheric reanalyses for regional warming studies over China

“…The 2 m T a in NCEP-1, NCEP-2, MERRA, MERRA-2, ERA-20C, ERA-20CM, CERA-20C, NOAA 20CRv2c, NOAA 20CRv2 and CFSR are model-derived fields that are functions of the surface skin temperature, the temperature at the lowest model level, the vertical stability and the surface roughness, which are constrained primarily by observations of upper-air variables and the surface pressure (Kanamitsu et al, 2002;Rienecker et al, 2011;Reichle et al, 2017;Poli et al, 2016;Hersbach et al, 2015;Laloyaux et al, 2016;Compo et al, 2011;Saha et al, 2010). However, the T a in ERA-Interim and JRA-55 are post-processing products by a relatively simple analysis scheme between the lowest model level and the surface and are analysed using ground-based observations of T a , with the help of Monin-Obukhov similarity profiles consistent with the model's parameterization of the surface layer (Dee et al, 2011b;Kobayashi et al, 2015).…”

“…These reanalyses include the first two generations of global reanalyses produced by the National Centers for Environmental Prediction, NCEP-R1 (Kalnay et al, 1996) and NCEP-R2 (Kanamitsu et al, 2002); the reanalyses produced by the European Centre for MediumRange Weather Forecasts (ECMWF), ERA-15 (Gibson et al, 1997), ERA-40 (Uppala et al, 2005) and ERA-Interim (Dee et al, 2011b); the Japanese Meteorological Agency, JRA-25 (Onogi et al, 2007) and JRA-55 (Kobayashi et al, 2015); and the National Aeronautics and Space Administration, the Modern-Era Retrospective Analysis for Research and Applications (MERRA) (Rienecker et al, 2011) and its updated version, MERRA-2 (Reichle et al, 2017).…”