The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)

Gelaro, Ronald; McCarty, Will; Suárez, Max J.; Todling, Ricardo; Molod, Andrea; Takacs, Lawrence L.; Randles, C. A.; Darmenov, Anton; Bosilovich, Michael G.; Reichle, Rolf H.; Wargan, Krzysztof; Coy, Lawrence; Cullather, Richard I.; Draper, C.; Akella, Santha; Buchard, Virginie; Conaty, Austin; Silva, Arlindo da; Gu, W; Kim, Gi-Kong; Koster, Randal D.; Lucchesi, Robert A.; Merkova, D.; Nielsen, J. E.; Partyka, Gary; Pawson, Steven; Putman, William M.; Rienecker, Michele M.; Schubert, Siegfried D.; Sienkiewicz, Meta; Zhao, Bin

doi:10.1175/jcli-d-16-0758.1

Cited by 5,304 publications

(3,950 citation statements)

References 97 publications

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“…Additional context is provided by ancillary meteorological information from the Modern Era Retrospective-Analysis for Research (MERRA-2) reanalysis product (Gelaro et al, 2017) and the Aura MLS Derived Meteorological Products (DMPs) 15 Manney et al, 2011a). A brief description of these datasets is provided below.…”

Section: Datasetsmentioning

confidence: 99%

Polar stratospheric cloud climatology based on CALIPSO spaceborne lidar measurements from 2006–2017

Pitts¹,

Poole²,

Gonzalez³

2018

Preprint

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Section: Datasetsmentioning

confidence: 99%

Polar stratospheric cloud climatology based on CALIPSO spaceborne lidar measurements from 2006–2017

Pitts¹,

Poole²,

Gonzalez³

2018

Preprint

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“…MERRA-2 (Gelaro et al, 2017) uses a similar model and assimilation system to MERRA, with updates also described by Bosilovich et al (2015), Molod et al (2015), and Takacs et al (2016). Some of the changes between MERRA and MERRA-2 that may affect UTLS dynamical fields are as follows:…”

Section: Merra and Merra-2mentioning

confidence: 99%

“…Details of these changes are given by Gelaro et al (2017) and references therein. The MERRA-2 data products are described by Bosilovich et al (2016).…”

Section: Merra and Merra-2mentioning

confidence: 99%

Reanalysis comparisons of upper tropospheric–lower stratospheric jets and multiple tropopauses

et al. 2017

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Abstract. The representation of upper tropospheric–lower stratospheric (UTLS) jet and tropopause characteristics is compared in five modern high-resolution reanalyses for 1980 through 2014. Climatologies of upper tropospheric jet, subvortex jet (the lowermost part of the stratospheric vortex), and multiple tropopause frequency distributions in MERRA (Modern-Era Retrospective analysis for Research and Applications), ERA-I (ERA-Interim; the European Centre for Medium-Range Weather Forecasts, ECMWF, interim reanalysis), JRA-55 (the Japanese 55-year Reanalysis), and CFSR (the Climate Forecast System Reanalysis) are compared with those in MERRA-2. Differences between alternate products from individual reanalysis systems are assessed; in particular, a comparison of CFSR data on model and pressure levels highlights the importance of vertical grid spacing. Most of the differences in distributions of UTLS jets and multiple tropopauses are consistent with the differences in assimilation model grids and resolution – for example, ERA-I (with coarsest native horizontal resolution) typically shows a significant low bias in upper tropospheric jets with respect to MERRA-2, and JRA-55 (the Japanese 55-year Reanalysis) a more modest one, while CFSR (with finest native horizontal resolution) shows a high bias with respect to MERRA-2 in both upper tropospheric jets and multiple tropopauses. Vertical temperature structure and grid spacing are especially important for multiple tropopause characterizations. Substantial differences between MERRA and MERRA-2 are seen in mid- to high-latitude Southern Hemisphere (SH) winter upper tropospheric jets and multiple tropopauses as well as in the upper tropospheric jets associated with tropical circulations during the solstice seasons; some of the largest differences from the other reanalyses are seen in the same times and places. Very good qualitative agreement among the reanalyses is seen between the large-scale climatological features in UTLS jet and multiple tropopause distributions. Quantitative differences may, however, have important consequences for transport and variability studies. Our results highlight the importance of considering reanalyses differences in UTLS studies, especially in relation to resolution and model grids; this is particularly critical when using high-resolution reanalyses as an observational reference for evaluating global chemistry–climate models.

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“…The first is the European Centre for Medium-range Weather Forecasts (ECMWF) Reanalysis 5, known as ERA5. The other is the Modern Era Retrospective Analysis for Research and Applications (MERRA) version 2 (Gelaro et al, 2017), a dataset produced by NASA's Global Modeling and Assimilation Office. Both reanalyses provide profiles of ice water content.…”

mentioning

confidence: 99%

“…Because all other 30 datasets queried treat all ice together, ERA5 values reported here are combined unless otherwise stated. In contrast, MERRA parametrizes frozen precipitation (Gelaro et al, 2017) and does not output atmospheric ice except for non-precipitating ice.…”

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confidence: 99%

An update on global atmospheric ice estimates from satellite observations and reanalyses

Duncan¹,

Eriksson²

2018

Preprint

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Abstract. This study assesses the global distribution of mean atmospheric ice mass from current state-of-the-art estimates and its variability on daily and seasonal timescales. Ice water path (IWP) retrievals from active and passive satellite platforms are compared and analysed against estimates from two reanalysis datasets, ERA5 (European Centre for Medium-range Weather homologous structures in some regions, but the degree and sign of the variability varies widely; the reanalyses exhibit noisier and higher amplitude diurnal variability than borne out by the satellite estimates. Spatial structures governed by the atmospheric general circulation are fairly consistent across the datasets, as principal component analysis shows that the patterns of 10 seasonal variability line up well between the datasets but disagree in severity. These results underscore the limitations of the current Earth observing system with respect to atmospheric ice, as the level of consensus between observations is mixed. The large-scale variability of IWP is relatively consistent, whereas disagreements on diurnal variability and global means point to varying microphysical assumptions in retrievals and models alike that seem to underlie the biggest differences.

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The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2)

Cited by 5,304 publications

References 97 publications

Polar stratospheric cloud climatology based on CALIPSO spaceborne lidar measurements from 2006–2017

Polar stratospheric cloud climatology based on CALIPSO spaceborne lidar measurements from 2006–2017

Reanalysis comparisons of upper tropospheric–lower stratospheric jets and multiple tropopauses

An update on global atmospheric ice estimates from satellite observations and reanalyses

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