Global Energy and Water Budgets in MERRA

Bosilovich, Michael G.; Robertson, Franklin R.; Chen, Junye

doi:10.1175/2011jcli4175.1

Cited by 250 publications

(195 citation statements)

References 41 publications

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“…This comparison indicates that MERRA has comparable prescribed SIE to satellite observations and has the appropriate surface boundary forcing. Because of the general consistency of MERRA analysis with satellite observations on SIE as shown here and other key variables demonstrated by previous studies (Rienecker et al 2011;Bosilovich et al 2011), we use MERRA reanalyzed atmospheric parameters as an integrated part of our analysis in this study. Anomalies of the most relevant atmospheric parameters, such as meridional wind (V), SAT, PWV, CF, LWnet, andtotal surface energy budget, have the maximum positive and negative anomalies, respectively, during the summers (6/15-9/15) of these 2 years compared to other years.…”

Section: Results and Discussion: Inter-annual And Seasonal Variationsmentioning

confidence: 85%

Critical mechanisms for the formation of extreme arctic sea-ice extent in the summers of 2007 and 1996

Dong

Zib

et al. 2013

Clim Dyn

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Along with significant changes in the Arctic climate system, the largest year-to-year variation in sea-ice extent (SIE) has occurred in the Laptev, East Siberian, and Chukchi seas (defined here as the area of focus, AOF), among which the two highly contrasting extreme events were observed in the summers of 2007 and 1996 during the period 1979-2012. Although most efforts have been devoted to understanding the 2007 low, a contrasting high September SIE in 1996 might share some related but opposing forcing mechanisms. In this study, we investigate the mechanisms for the formation of these two extremes and quantitatively estimate the cloud-radiation-water vapor feedback to the sea-ice-concentration (SIC) variation utilizing satellite-observed sea-ice products and the NASA MERRA reanalysis. The low SIE in 2007 was associated with a persistent anticyclone over the Beaufort Sea coupled with low pressure over Eurasia, which induced anomalous southerly winds. Ample warm and moist air from the North Pacific was transported to the AOF and resulted in positive anomalies of cloud fraction (CF), precipitable water vapor (PWV), surface LWnet (down-up), total surface energy and temperature. In contrast, the high SIE event in 1996 was associated with a persistent low pressure over the central Arctic coupled with high pressure along the Eastern Arctic coasts, which generated anomalous northerly winds and resulted in negative anomalies of above mentioned atmospheric parameters. In addition to their immediate impacts on sea ice reduction, CF, PWV and radiation can interplay to lead to a positive feedback loop among them, which plays a critical role in reinforcing sea ice to a great low value in 2007. During the summer of 2007, the minimum SIC is 31 % below the climatic mean, while the maximum CF, LWnet and PWV can be up to 15 %, 20 Wm -2 , and 4 kg m -3 above. The high anti-correlations (-0.79, -0.61, -0.61) between the SIC and CF, PWV, and LWnet indicate that CF, PWV and LW radiation are indeed having significant impacts on the SIC variation. A new record low occurred in the summer of 2012 was mainly triggered by a super storm over the central Arctic Ocean in early August that caused substantial mechanical ice deformation on top of the long-term thinning of an Arctic ice pack that had become more dominated by seasonal ice.Keywords Trigger and cause of Arctic sea ice retreat Á Cloud-radiation-water vapor feedback to the sea-ice-concentration variation Á Extreme Arctic seaice extent formation mechanisms Á Triggered by atmospheric forcings Á Enhanced clouds-radiation-PWV feedback

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Section: Results and Discussion: Inter-annual And Seasonal Variationsmentioning

confidence: 85%

Critical mechanisms for the formation of extreme arctic sea-ice extent in the summers of 2007 and 1996

Dong

Zib

et al. 2013

Clim Dyn

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“…2b shows the corresponding observations-based estimates from GPCP (section 2b). MERRA and GPCP both have a global mean over land of around 2.3 mm day 21 for 1981-2008 (see Bosilovich et al 2011 for a discussion of the global water budget and trends of MERRA and other reanalysis products). To first order, the precipitation fields look similar, with MERRA locating deserts and rainy areas in the proper places and assigning, in most regions, approximately the correct magnitudes to the mean annual precipitation rates.…”

Section: ) Long-term Precipitation Totalsmentioning

confidence: 99%

Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

et al. 2011

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The Modern-Era Retrospective Analysis for Research and Applications (MERRA) is a state-of-the-art reanalysis that provides, in addition to atmospheric fields, global estimates of soil moisture, latent heat flux, snow, and runoff for 1979-present. This study introduces a supplemental and improved set of land surface hydrological fields (''MERRA-Land'') generated by rerunning a revised version of the land component of the MERRA system. Specifically, the MERRA-Land estimates benefit from corrections to the precipitation forcing with the Global Precipitation Climatology Project pentad product (version 2.1) and from revised parameter values in the rainfall interception model, changes that effectively correct for known limitations in the MERRA surface meteorological forcings. The skill (defined as the correlation coefficient of the anomaly time series) in land surface hydrological fields from MERRA and MERRA-Land is assessed here against observations and compared to the skill of the state-of-the-art ECMWF Re-Analysis-Interim (ERA-I). MERRA-Land and ERA-I root zone soil moisture skills (against in situ observations at 85 U.S. stations) are comparable and significantly greater than that of MERRA. Throughout the Northern Hemisphere, MERRA and MERRA-Land agree reasonably well with in situ snow depth measurements (from 583 stations) and with snow water equivalent from an independent analysis. Runoff skill (against naturalized stream flow observations from 18 U.S. basins) of MERRA and MERRA-Land is typically higher than that of ERA-I. With a few exceptions, the MERRA-Land data appear more accurate than the original MERRA estimates and are thus recommended for those interested in using MERRA output for land surface hydrological studies.

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“…MERRA is a reanalysis of the satellite era (1979-present) using the GEOS-5 data assimilation system. The objectives of MERRA are to provide a climate context for the NASA satellite-observing system and to improve the representation of the water cycle in reanalysis [Bosilovich et al, 2011]. Unlike NCEP-R1, NCEP-R2, or MERRA, ERA-I and JRA-55 used the most advanced four-dimensional variational data assimilation (4DVAR).…”

Section: Introductionmentioning

confidence: 99%

Evaporation variability under climate warming in five reanalyses and its association with pan evaporation over China

Feng

2015

JGR Atmospheres

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With the motivation to identify actual evapotranspiration (AE) variability under climate warming over China, an assessment is made from five sets of reanalysis data sets [National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR), NCEP-Department of Energy (NCEP-DOE), Modern-Era Retrospective Analysis for Research and Applications (MERRA), Interim Reanalysis, and Japanese 55-year Reanalysis (JRA-55)]. Based on comparison with AE estimates calculated using the Budyko equation, all five reanalysis data sets reasonably reproduce the spatial patterns of AE over China, with a clearly southeast-northwest gradient. Overall, JRA-55 (NCEP-DOE) gives the lowest (highest) reanalysis evaporation (RE) values. From 1979 to 2013, dominant modes of RE among five reanalyses are extracted using multivariate empirical orthogonal function analysis. Accordingly, the interdecadal variation of RE is likely driven by the change of temperature, and the interannual variation is constrained by the water supply conditions. Under climate warming, RE increase in the Northwest China, Yangtze-Huaihe river basin, and South China, while they decrease in Qinghai-Tibet Plateau, and northern and Northeast China. Moreover, the relationship between RE and pan evaporation (PE) are comprehensively evaluated in space-time. Negative correlations are generally confirmed in nonhumid environments, while positive correlations exist in the humid regions. Our analysis supports the interpretation that the relationship between PE and AE was complementary with water control and proportional with energy control. In view of data availability, important differences in spatial variability and the amount of RE can be found in Northwest China, the Qinghai-Tibet Plateau, and the Yangtze River Basin. Generally speaking, NCEP-NCAR and MERRA have substantial problems on describing the long-term change of RE; however, there are some inaccuracies in the JRA-55 estimates when focusing on the year-to-year variation.

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Global Energy and Water Budgets in MERRA

Cited by 250 publications

References 41 publications

Critical mechanisms for the formation of extreme arctic sea-ice extent in the summers of 2007 and 1996

Critical mechanisms for the formation of extreme arctic sea-ice extent in the summers of 2007 and 1996

Assessment and Enhancement of MERRA Land Surface Hydrology Estimates

Evaporation variability under climate warming in five reanalyses and its association with pan evaporation over China

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