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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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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Towards A More Realistic Representation of Nasa Ceres-Derived Surface Radiative Fluxes During Polar Night: A Comparison With the Mosaic Field Campaign

The Arctic remains one of the more difficult regions observe, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite surface radiative flux estimates is difficult because of the lack of in situ measurements. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. Continuing this work, we examine the effects of errors in cloud water path on surface radiative fluxes. When using all cloud conditions, errors in cloud water are also significantly correlated with surface radiative flux errors, though the size off the effect is only about half that of cloud amount. But when considering low cloud conditions only, the effects of cloud water and cloud amount are comparable.

J. Brant Dodson↗
NASA NTRSDate not supplied

Improving the Representation of Land Surface Processes Using the Data Assimilation Research Testbed (DART)

The land surface is a critical part of the earth system as processes related to water, carbon, energy and nitrogen cycling have important implications for climate forcing, air quality, water availability and seasonal atmospheric forecasting. Despite advances in land surface modeling, land surface model performance is often limited because of errors related to initial and boundary conditions, model structure, and parameters. Data assimilation (DA) techniques combined with an expanding network of earth system observations present an opportunity to reduce these errors and improve simulations. Here, we emphasize the implementation of tools and approaches to overcome challenges related to land DA to constrain carbon and water cycling. In particular, we discuss the implementation of adaptive inflation to modify ensemble spread in response to time-varying networks of gridded observations. We also discuss methods to generate ensemble spread through boundary condition (meteorology) forcing that can be applied to site-level applications. Next, we describe the application of vertical localization upon surface soil moisture observations, and forward operators specifically designed for the assimilation of snow and solar-induced fluorescence observations. Finally, we discuss the potential benefit of a quantile conserving filter used to update bounded quantities (state or parameter values).

Brett Raczka↗
NASA NTRSDate not supplied

Towards a More Realistic Representation of NASA CERES-derived Surface Radiative Fluxes during Polar Night: A Comparison with the MOSAiC Field Campaign

The Arctic remains one of the more difficult regions observe, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite surface radiative flux estimates is difficult because of the lack of in situ measurements. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. Continuing this work, we examine the effects of errors in cloud water path on surface radiative fluxes. When using all cloud conditions, errors in cloud water are also significantly correlated with surface radiative flux errors, though the size off the effect is only about half that of cloud amount. But when considering low cloud conditions only, the effects of cloud water and cloud amount are comparable. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. We further examine this source of error by examining selected case studies in which the disagreements in radiative fluxes and clouds are large.

J Brant Dodson↗
NASA NTRSDate not supplied

Quantifying the Influence of Mechanistic Representation of Particle Dry Deposition on Historical Changes in Aerosol-Climate Interactions

Dry deposition removes short-lived climate forcers and their precursors from the atmosphere. The aerosol dry deposition schemes in many global climate models have been untouched for decades. Previous work hints that aerosol dry deposition is an uncertainty with respect to aerosol impacts on climate change. Here we demonstrate the impact of a more mechanistic aerosol dry deposition parameterization on the historical aerosol direct and cloud albedo effects using the NASA GISS global chemistry-climate model. We investigate two aerosol configurations – a “bulk” mass-based scheme and a modal scheme that more explicitly represents internal mixing and microphysics – of the global model. Both configurations show ~20% larger historical increases in non-dust aerosols globally with more mechanistic dry deposition. Changes to particle dry deposition, which are strongly a function of particle diameter, have a greater influence on the cloud albedo effect (up to 0.1 W m-2) when aerosols are more explicitly resolved in the modal scheme. On the other hand, impacts on the direct aerosol effect are small for both model configurations. In both aerosol configurations, the global climate effects are relatively insensitive to uncertainty in the strength of the uptake to dry deposition as suggested by (limited) measurements. In general, the low number of aerosol flux measurements and strong variability across existing observations challenge confidence in our understanding of dry depositional processes and changes with environmental conditions. Nonetheless, our work suggests that changes in dry deposition may be important for accurately estimating increases in aerosol abundances over the historical period, which is key for correct inferences about how cooling from aerosols has offset warming from greenhouse gases.

Dry deposition↗
NASA NTRSDate not supplied

The Representation of Aerosols in GMAO’s Newest Reanalyses

Over the past few years, NASA’s Global Modelling and Assimilation Office has been working on the configuration and production of three new reanalysis products, GEOS-IT, GiOcean, and MERRA-21C. GEOS-IT, or the Goddard Earth Observing System for Instrument Teams, is a 3D variational data assimilation system that runs in a near real time framework however retrospectively provides data back through 1998 to deliver a consistent view of the Earth-atmosphere system for the production of observational NASA products. Retrospective production for GEOS-IT is complete and the meteorology has since been used to produce the one way weakly coupled GiOcean reanalysis. Due to differences in the atmospheric model, particularly related to scavenging, aerosols are not identical in GEOS-IT and GiOcean. MERRA-21C, or the Modern Era Restrospective analysis for Research and Applications in the 21st century, is a hybrid 4D ensemble variational system at a finer horizontal resolution of 0.25 degrees. Although different in their intended use, and therefore configuration, these systems prominently feature coupling between meteorology and aerosols. The differences and similarities in the aerosol configuration between the three systems will be discussed, covering biomass burning and anthropogenic emissions as well as observations used for the assimilation of aerosol optical depth. A large emphasis will be placed on the version of the underlying aerosol module, GOCART, which underwent a complete refactoring and the addition of radiatively active brown carbon between GEOS-IT and MERRA-21C. Independent observations will be used to evaluate the performance of aerosols in both reanalyses, focusing on aerosol optical depth, surface particulate matter, and vertical profiles of aerosol backscatter.

Allison Collow↗