GMAO RESEARCH HIGHLIGHTS
Research in the GMAO emphasizes the use of satellite observations in global modeling systems, comprised of atmosphere, ocean, land-surface, and biogeochemistry model components. These components are integrated for assimilation and forecast systems to address questions about climate variability, water and energy budgets, composition, and weather and climate prediction; to form an integrated Earth system analysis; and to contribute to the design of future satellite missions.
Details about refereed scientific papers published by the GMAO staff are compiled on our GMAO Publications page.
This page lists titles and links to GMAO Research Highlights. These writeups are summaries of selected GMAO scientific research activities.
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The GEOS-5 atmospheric model and assimilation analyses are used every day to generate 5-day weather forecasts. One view of GEOS-5 performance is provided from the forecasts of two of the most destructive storms of the 2012 hurricane season: Hurricanes Isaac and Sandy.
The GMAO used GEOS-5 and MERRA to investigate the driving forces behind a major heat wave that occurred in western Russia in the summer of 2010 and to assess the predictability of such events.
The GMAO engages in research to understand drought and its predictability. GEOS-5 and MERRA have been used to examine drought in the U.S. in 2011 and 2012. In investigating the processes that control drought, the GMAO strives to improve the forecasting of drought on seasonal time scales.
Observation impacts on weather forecasts: Atmospheric motion vector winds (AMVs) have a high impact on Navy weather forecasts, but only a modest impact on GEOS-5 forecasts. Recent investigation has focused on determining why this is the case.
The paper, by Draper and colleagues, shows that assimilating satellite observations from active or passive microwave sensors into models can improve soil moisture estimates. The authors assimilated soil moisture derived from the active ASCAT and passive AMSR-E satellite sensors into a land surface model and assessed the resulting soil moisture estimates against in situ observations from 85 sites in the United States and Australia. They found that the active and passive microwave data both improved the model's soil moisture estimates in similar ways. Following the recent failure of AMSR-E, the new study shows that systems designed to assimilate AMSR-E soil moisture can switch to ASCAT data without loss of accuracy.
In a recent study, gravimetric measurements from the Gravity Recovery and Climate Experiment (GRACE) mission are used in a land surface model data assimilation framework to better characterize snow conditions in the Mackenzie River basin located in northern Canada. The assimilation of GRACE terrestrial water storage information into the Catchment land surface model improves snow mass estimates.
Simulations of trace gases in GEOS-5 have been used to interpret atmospheric bromine measurements from NASA's OMI instrument and from aircraft in the ARCTAS field campaign. The work was led by Professor Ross Salawitch at the University of Maryland, and is featured in a Geophysics Research Letters Editor's highlight and on the cover of the November 16, 2010, issue of GRL.
A new study uses the Goddard Earth Observing System, Version 5 (GEOS-5) atmospheric general circulation model to study the impact of aerosols produced by the 2006 Indonesian fires on atmospheric temperature, moisture, and circulation in the region.
A new study utilizes global analyses of the atmosphere obtained from the new GEOS-5 Data Assimilation System (DAS) developed for GMAO's Modern-Era Retrospective analysis for Research and Applications (MERRA) to examine the relationships between cloud parameters observed by the CloudSat satellite and predictors of convective cloud structure derived from MERRA reanalyses.
Modeled transport of CO and CO2 is used to evaluate parameterizations in GEOS-5 and to identify which parameters have the greatest impact on trace gas transport in three different storms.
Simulations from eleven coupled chemistry-climate models (CCMs) employing nearly identical forcings have been used to project the evolution of stratospheric ozone throughout the 21st century.
Daily, global surface chlorophyll values for 1998 to 2004 have been estimated by assimilation of SeaWiFS data into the NASA Ocean Biogeochemical Model.
To study global warming trends and the pan-decadal variability (PDV) in the Pacific, the dominating ENSO signal is removed first. After we do this, our investigations of observations and reanalysis datasets show that the warming in the Pacific basin is weaker than surrounding basins and that one of several PDV regime shifts occurred during the 1990s.
A new application of OSSEs shows great promise for helping to answer fundamental questions about atmospheric analysis techniques, observation instruments, and forecast skill measures.
GMAO scientists have developed a new formulation of the GEOS-5 atmospheric data assimilation system to understand and improve the way observations are used in weather and climate forecasts.
GMAO scientists use GEOS-5 to examine the leading modes of weather instability in the stratosphere to help provide insight into observed stratospheric dynamical phenomena.
AGCM studies show that interactive deep soil temperatures significantly increase surface air temperature variability but reduce the variability of the hydrological cycle.