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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

What can we learn from relaxation measurements of a laser-perturbed atmosphere? A modeling study

The chemical kinetic aspects of a transient increase in OH and HO2 by several orders of magnitude are explored in three model tropospheres. This chemical kinetic modeling effort was undertaken to support the operation of a pump-and-probe LIDAR instrument. A powerful excimer laser pulse perturbs the troposphere after which its relaxation back to steady state is examined by remote sensing, for example by DIAL or LIF. Instead of probing ambient levels of key free radicals, a study of the relaxation kinetics in real time enables chemical mechanistic studies in situ.

Clericetti, Agostino↗
NASA NTRS1994

In situ measurements of the NO2/NO ratio for testing atmospheric photochemical models

Simultaneous in situ measurements of NO2, NO, O3, ClO, pressure and temperature have been made for the first time, presenting a unique opportunity to test our current understanding of the photochemistry of the lower stratospere. Data were collected from several flights of the ER-2 aircraft at mid-latitudes in May 1993 during NASA's Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE). The daytime ratio of NO2/NO remains fairly constant at 19 km with a typical value of 0.68 and standard deviation of +/- 17. The ratio observations are compared with simple steady-state calculations based on laboratory-measured reaction rates and modeled NO2 photolysis rates. At each measurement point the daytime NO2/NO with its measurements uncertainty overlap the results of steady-state caculations and associated uncertainty. Possible sources of error are examined in both model and measurements. It is shown that more accurate laboratory determinations of the NO + 03 reaction rate and of the NO2 cross-sections in the 200-220 K temperature range characteristic of the lower stratosphere would allow for a more robust test of our knowledge of NO(X) phtochemistry by reducing significant sources if uncertainties in the interpretation of statospheric measurements.

Jaegle, L.↗
NASA NTRS1994

In Situ Measurements of the NO2/NO Ratio for Testing Atmospheric Photochemical Models

Simultaneous in situ measurements of NO2, NO, O3, ClO, pressure and temperature have been made for the first time, presenting a unique opportunity to test our current understanding of the photochemistry of the lower stratosphere. Data were collected from several flights of the ER-2 aircraft at mid-latitudes in May 1993 during NASA's Stratospheric Photochemistry, Aerosols and Dynamics Expedition (SPADE). The daytime ratio of NO2/NO remains fairly constant at 19 km with a typical value of 0.68 and standard deviation of +/- 0.17. The ratio observations are compared with simple steady-state calculations based on laboratory-measured reaction rates and modeled NO2 photolysis rates. At each measurement point the daytime NO2/NO with its measurement uncertainty overlap the results of steady-state calculations and associated uncertainty. However, over all the ER-2 flights examined, the model systematically overestimates the ratio by 40% on average. Possible sources of error are examined in both model and measurements. It is shown that more accurate laboratory determinations of the NO + O3 reaction rate and of the NO2 cross-sections in the 200-220 K temperature range characteristic of the lower stratosphere would allow for a more robust test of our knowledge of NO(x) photochemistry by reducing significant sources of uncertainties in the interpretation of stratospheric measurements. The present measurements are compared with earlier observations of the ratio at higher altitudes.

Jaegle, L.↗
NASA NTRS2000

Use of Geostationary Satellite Data to Force Land Surface Schemes within Atmospheric Mesoscale Models

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the GHCC within the PSU/NCAR MM5. Assimilation has been performed on a grid centered over the Southeastern US since November 1998. Results from the past year show that assimilation of the satellite data reduces both the bias and RMSE for simulations of surface air temperature and relative humidity. These findings are based on comparison of assimilation runs with a control using the simple 5-layer soil model available in MM5. A significant development in the past several months was the inclusion of the detailed Oregon State University land surface model (OSU/LSM) as an option within MM5. One of our working hypotheses has been that the assimilation technique, although simple, may provide better short-term forecasts than a detailed LSM that requires significant number initialized parameters. Preliminary results indicate that the assimilation out performs the OSU/LSM as it is incorporated in MM5. Details will be presented at the symposium.

Lapenta, William M.↗
NASA NTRS2004

Topography Modeling in Atmospheric Flows Using the Immersed Boundary Method

Numerical simulation of flow over complex geometry needs accurate and efficient computational methods. Different techniques are available to handle complex geometry. The unstructured grid and multi-block body-fitted grid techniques have been widely adopted for complex geometry in engineering applications. In atmospheric applications, terrain fitted single grid techniques have found common use. Although these are very effective techniques, their implementation, coupling with the flow algorithm, and efficient parallelization of the complete method are more involved than a Cartesian grid method. The grid generation can be tedious and one needs to pay special attention in numerics to handle skewed cells for conservation purposes. Researchers have long sought for alternative methods to ease the effort involved in simulating flow over complex geometry.

Ackerman, A. S.↗
NASA NTRS2007

Evaluation of a Potential for Enhancing the Decision Support System of the Interagency Modeling and Atmospheric Assessment Center with NASA Earth Science Research Results

NASA's objective for the Applied Sciences Program of the Science Mission Directorate is to expand and accelerate the realization of economic and societal benefits from Earth science, information, and technology. This objective is accomplished by using a systems approach to facilitate the incorporation of Earth observations and predictions into the decision-support tools used by partner organizations to provide essential services to society. The services include management of forest fires, coastal zones, agriculture, weather prediction, hazard mitigation, aviation safety, and homeland security. In this way, NASA's long-term research programs yield near-term, practical benefits to society. The Applied Sciences Program relies heavily on forging partnerships with other Federal agencies to accomplish its objectives. NASA chooses to partner with agencies that have existing connections with end-users, information infrastructure already in place, and decision support systems that can be enhanced by the Earth science information that NASA is uniquely poised to provide (NASA, 2004).

Blonski, Slawomir↗
NASA NTRS2012

Modeling of Atmosphere Revitalization

NASA's AES is pioneering new approaches for future human missions beyond Earth orbit. All spacecraft systems must be minimized with respect to mass, power, and volume. Here, we show work related to improving system efficiency and reliability for water separation systems on crewed vehicles and the initial development of COMSOL simulations in support of the Atmosphere Revitalization Recovery and Environmental Monitoring (ARREM) project

Coker, Robert↗
NASA NTRS2020

Untangling causality in midlatitude aerosol–cloud adjustments

Aerosol–cloud interactions represent the leading uncertainty in our ability to infer climate sensitivity from the observational record. The forcing from changes in cloud albedo driven by increases in cloud droplet number (Nd) (the first indirect effect) is confidently negative and has narrowed its probable range in the last decade, but the sign and strength of forcing associated with changes in cloud macrophysics in response to aerosol (aerosol–cloud adjustments) remain uncertain. This uncertainty reflects our inability to accurately quantify variability not associated with a causal link flowing from the cloud microphysical state to the cloud macrophysical state. Once variability associated with meteorology has been removed, covariance between the liquid water path (LWP) averaged across cloudy and clear regions (here characterizing the macrophysical state) and Nd (characterizing the microphysical) is the sum of two causal pathways linking Nd to LWP: Nd altering LWP (adjustments) and precipitation scavenging aerosol and thus depleting Nd. Only the former term is relevant to constraining adjustments, but disentangling these terms in observations is challenging. We hypothesize that the diversity of constraints on aerosol–cloud adjustments in the literature may be partly due to not explicitly characterizing covariance flowing from cloud to aerosol and aerosol to cloud. Here, we restrict our analysis to the regime of extratropical clouds outside of low-pressure centers associated with cyclonic activity. Observations from MAC-LWP (Multisensor Advanced Climatology of Liquid Water Path) and MODIS are compared to simulations in the Met Office Unified Model (UM) GA7.1 (the atmosphere model of HadGEM3-GC3.1 and UKESM1). The meteorological predictors of LWP are found to be similar between the model and observations. There is also agreement with previous literature on cloud-controlling factors finding that increasing stability, moisture, and sensible heat flux enhance LWP, while increasing subsidence and sea surface temperature decrease it. A simulation where cloud microphysics are insensitive to changes in Nd is used to characterize covariance between Nd and LWP that is induced by factors other than aerosol–cloud adjustments. By removing variability associated with meteorology and scavenging, we infer the sensitivity of LWP to changes in Nd. Application of this technique to UM GA7.1 simulations reproduces the true model adjustment strength. Observational constraints developed using simulated covariability not induced by adjustments and observed covariability between Nd and LWP predict a 25 %–30 % overestimate by the UM GA7.1 in LWP change and a 30 %–35 % overestimate in associated radiative forcing.

Daniel T. McCoy↗
NASA NTRSDate not supplied

Application of Artificial Intelligence for Surface PM2.5 Estimations from Geostationary Satellite and Atmospheric Numerical Model Data

PM2.5, particulate matter (PM) with a diameter less than or equal to 2.5 μm, is emitted from anthropogenic fuel combustion and forest fires. Due to their small size, PM2.5 can penetrate into respiratory systems and cause or exacerbate serious illness. The US Environmental Protection Agency (EPA) regulates the levels of surface PM2.5 but surface monitoring has spatial and temporal limitations. The Aerosol Optical Depth (AOD) retrievals from the Geostationary Operational Environmental Satellite (GOES) missions and meteorological factors can be utilized as an alternative technique to estimate surface PM2.5 levels at a higher spatial and temporal resolution compared to surface monitors. Traditional estimation approaches rely on linear regression techniques and have limitations modeling the nonlinear relationship between the meteorological factors, AOD retrievals, and surface PM2.5. We compare different machine learning techniques and identify the best-suited model that can represent the nonlinearity between the factors affecting PM2.5 levels

Manisha Khatri↗