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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Applied Uses of MERRA Reanalyses: Current and Future Prospects

During the initial planning of the Modern Era Retrospective-analysis for Research and Applications (MERRA), the project was envisioned to become a tool for applied sciences and decision makers, as well as weather and climate research. MERRA was the first reanalysis to provide data at 1 hourly frequencies. After discussions with wind energy users, 50m above the surface winds were included in the data collection to begin to represent the environment at the turbine height. MERRA-2 was the first reanalysis to include interactive and assimilated aerosols. From these, PM 1, 2.5 and 10 records have been computed and contribute to the climate and health sector. The US Center for Disease Control is accessing MERRA-2 data for comparison along with their health data. MERRA-2 Extreme Indices have been computed from the high frequency data (e.g. precipitation maxima, heat waves and fire weather). These have been used to characterize the changing extremes in the United States and around the globe as well as the weather associated with the extremes. The next-generation, MERRA-21C, includes increased resolution (25km) and continues to provide innovative Earth system data. For example, a boundary layer collection will provide constant height level data starting at 100m, continuing up to 4000m. This will provide detailed information about the boundary layer processes that greatly affect the biosphere. Chemical tracers for constituents are included in the system. The ensemble data assimilation is run with 32 members, and the variance for critical variables are stored. We will explore the use of this variance as one measure of uncertainty relevant for applied uses, which has not been included in any MERRA reanalysis. We will discuss use case scenarios developed to engage with the energy and financial sectors, to better understand their needs for climate data. Prospects for further downscaling of reanalyses will also be explored.

Michael Bosilovich↗
NASA NTRS2003

Data Assimilation Office (DAO) Operational Analyses and Reanalyses for Coordinated Enhanced Observing Period (CEOP)

The DAO operational assimilation system has produced and archived gridded data since 1998, and will continue through the CEOP period. However, major system upgrades and new assimilation variables will significantly affect the surface energy balance and data product. These changes will be discussed and the prospects for a CEOP reanalysis will be presented. W e will also review the data currently available and describe how to access the data.

Bosilovich, M.↗
NASA NTRS2012

Closing the Seasonal Ocean Surface Temperature Balance in the Eastern Tropical Oceans from Remote Sensing and Model Reanalyses

The Eastern tropical ocean basins are regions of significant atmosphere-ocean interaction and are important to variability across subseasonal to decadal time scales. The numerous physical processes at play in these areas strain the abilities of coupled general circulation models to accurately reproduce observed upper ocean variability. Furthermore, limitations in the observing system of important terms in the surface temperature balance (e.g., turbulent and radiative heat fluxes, advection) introduce uncertainty into the analyses of processes controlling sea surface temperature variability. This study presents recent efforts to close the surface temperature balance through estimation of the terms in the mixed layer temperature budget using state-of-the-art remotely sensed and model-reanalysis derived products. A set of twelve net heat flux estimates constructed using combinations of radiative and turbulent heat flux products - including GEWEX-SRB, ISCCP-SRF, OAFlux, SeaFlux, among several others - are used with estimates of oceanic advection, entrainment, and mixed layer depth variability to investigate the seasonal variability of ocean surface temperatures. Particular emphasis is placed on how well the upper ocean temperature balance is, or is not, closed on these scales using the current generation of observational and model reanalysis products. That is, the magnitudes and spatial variability of residual imbalances are addressed. These residuals are placed into context within the current uncertainties of the surface net heat fluxes and the role of the mixed layer depth variability in scaling the impact of those uncertainties, particularly in the shallow mixed layers of the Eastern tropical ocean basins.

Roberts, J. Brent↗
NASA NTRS2012

Closing the Seasonal Ocean Surface Temperature Balance in the Eastern Tropical Oceans from Remote Sensing and Model Reanalyses

Residual forcing necessary to close the MLTB on seasonal time scales are largest in regions of strongest surface heat flux forcing. Identifying the dominant source of error - surface heat flux error, mixed layer depth estimation, ocean dynamical forcing - remains a challenge in the eastern tropical oceans where ocean processes are very active. Improved sub-surface observations are necessary to better constrain errors. 1. Mixed layer depth evolution is critical to the seasonal evolution of mixed layer temperatures. It determines the inertia of the mixed layer, and scales the sensitivity of the MLTB to errors in surface heat flux and ocean dynamical forcing. This role produces timing impacts for errors in SST prediction. 2. Errors in the MLTB are larger than the historical 10Wm-2 target accuracy. In some regions, a larger accuracy can be tolerated if the goal is to resolve the seasonal SST cycle.

Roberts, J. Brent↗
NASA NTRS2016

Evaluation of the Sensitivity of the Amazonian Diurnal Cycle to Convective Intensity in Reanalyses

Model parameterizations of tropical deep convection are unable to reproduce the observed diurnal and spatial variability of convection in the Amazon, which contributes to climatological biases in the water cycle and energy budget. Convective intensity regimes are defined using percentiles of daily minimum 3-hourly averaged outgoing longwave radiation (OLR) from Clouds and the Earth's Radiant Energy System (CERES). This study compares the observed spatial variability of convective diurnal cycle statistics for each regime to MERRA-2 and ERA-Interim (ERA) reanalysis data sets. Composite diurnal cycle statistics are computed for daytime hours (06:00-21:00 local time) in the wet season (December-January-February). MERRA-2 matches observations more closely than ERA for domain averaged composite diurnal statistics-specifically precipitation. However, ERA reproduces mesoscale features of OLR and precipitation phase associated with topography and the propagation of the coastal squall line. Both reanalysis models are shown to underestimate extreme convection.

Itterly, Kyle F.↗
NASA NTRS2019

A Terrestrial Validation of ICESat Elevation Measurements and Implications for Global Reanalyses

The primary goal of NASA's Ice, Cloud, and land Elevation Satellite (ICESat) mission was to detect centimeter-level changes in global ice sheet elevations at the spatial scale of individual ice streams. Confidence in detecting these small signals requires careful validation over time to characterize the uncertainty and stability of measured elevations. A common validation approach compares altimeter elevations to an independently characterized and stable reference surface. Using a digital elevation model (DEM) from geodetic surveys of one such surface, the salar de Uyuni in Bolivia, we show that ICESat elevations at this location have a 0.0-centimeter bias relative to the WGS84 ellipsoid, 4.0-centimeter (1-sigma) uncertainty overall, and 1.8-centimeter uncertainty under ideal conditions over short (50 kilometer) profiles. We observe no elevation bias between ascending and descending orbits, but we do find that elevations measured immediately after transitions from low to high surface albedo may be negatively biased. Previous studies have reported intercampaign biases (ICBs) between various ICESat observation campaigns, but we find no statistically significant ICBs or ICB trends in our data. We do find a previously unreported 3.1-centimeter bias between ICESat's Laser 2 and Laser 3, and we find even larger interlaser biases in reanalyzed data from other studies. For an altimeter with an exact repeat orbit like ICESat, we also demonstrate that validation results with respect to averaged elevation profiles along a single ground track are comparable to results obtained using reference elevations from an in situ survey.

Laser Ranging↗
NASA NTRS2019

Recent Antarctic Sea Ice Extent Variability and Its Relation to Atmospheric Circulation in Reanalyses and Seasonal Forecasts

Sea ice is considered an important indicator of climate change. Interest has focused on the trend towards reduced sea ice cover in the Arctic Ocean, particularly during summer months. In the Southern Hemisphere, sea ice has also received attention due to a trend towards increasing cover, in opposition to the Northern Hemisphere and to climate model projections. This all changed in the austral spring 2016, when the Southern Ocean sea ice cover dropped dramatically, and has remained consistently at below average values up to the present. Here I review some of the issues and perceived causes of the 2016 sea ice reduction. Several studies have suggested a change in surface winds, which would allow warmer waters to move upwards in the water column and towards the surface. Results from the GMAO (Global Modeling and Assimilation Office) ocean data assimilation system are consistent with this hypothesis, and indicate a significant warming of subsurface waters occurred in the winter of 2016, and has remained in place.

Polar↗