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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Illinois Disasters: Utilizing NASA Earth Observations to Enhance Drought Monitoring in Illinois

Drought and flooding in Illinois have severe impacts on the communities and ecosystems of the state. Soil moisture is a valuable indicator of drought and flood vulnerability but can be difficult to measure since in situ monitoring is limited to discrete stations throughout the state. The team created a framework to compare in situ, modeled, and NASA satellite soil moisture measurements to increase the spatial coverage of soil moisture monitoring. The team partnered with the Illinois State Weather Survey, USDA Midwest Climate Hub, NOAA Regional Climate Services of the Central Region, NOAA National Integrated Drought Information System’s Midwest Drought Early Warning System, and the NOAA North Central River ForecastCenter. The team standardized and compared soil moisture data from NASA’s Soil Moisture Active Passive (SMAP) mission, modeled soil moisture outputs from NASA’s SPoRT Land Information System (SPoRT-LIS), and in situ measurements from the Illinois State Weather Survey’s Water and Atmospheric Resources Monitoring (WARM) program. Compared to the WARM data, the satellite and modeled data showed seasonally variable differences and bias. The difference was highest in the winter months and lowest in the late summer and early fall months for the SMAP and SPoRT-LIS data products. SPoRT-LIS produced lower seasonal variability and SMAP demonstrated higher correlation values and lower differences. These analyses suggest that both SMAP and SPoRT-LIS products offer unique strengths and limitations when used for soil moisture monitoring

Joshua Green↗
NASA NTRS2010

The Vertical Structure of Relative Humidity and Ozone in the Tropical Upper Troposphere: Intercomparisons Among In Situ Observations, A-Train Measurements and Large-Scale Models

In situ measurements in the tropics have shown that in regions of active convection, relative humidity with respect to ice in the upper troposphere is typically close to saturation on average, and supersaturations greater than 20% are not uncommon. Balloon soundings with the cryogenic frost point hygrometer (CFH) at Costa Rica during northern summer, for example, show this tendency to be strongest between 11 and 15.5 km (345-360 K potential temperature, or approximately 250-120 hPa). this is the altitude range of deep convective detrainment. Additionally, simultaneous ozonesonde measurements show that stratospheric air (O3 greater than 150 ppbv) can be found as low as approximately 14 km (350 K/150 hPa). In contrast, results from northern winter show a much drier upper troposphere and little penetration of stratospheric air below the tropopause at 17.5 km (approximately 383 K). We show that these results are consistent with in situ measurements from the Measurement of Ozone and water vapor by Airbus In-service airCraft (MOZAIC) program which samples a wider, though still limited, range of tropical locations. To generalize to the tropics as a whole, we compare our insitu results to data from two A-Train satellite instruments, the Atmospheric Infrared Sounder (AIRS) and the Microwave Limb Sounder (MLS) on the Aqua and Aura satellites respectively. Finally, we examine the vertical structure of water vapor, relative humidity and ozone in the NASA Goddard MERRA analysis, an assimilation dataset, and a new version of the GEOS CCM, a free-running chemistry-climate model. We demonstrate that conditional probability distributions of relative humidity and ozone are a sensitive diagnostic for assessing the representation of deep convection and upper troposphere/lower stratosphere mixing processes in large-scale analyses and climate models.

Selkirk, Henry B.↗
NASA NTRS2018

The Ability of NASA's Meteoroid Engineering Model to Replicate in Situ Impact Data

Meteoroid environment models must describe the mass, directionality, velocity, and density distributions of meteoroids in order to correctly predict the rate at which meteoroids impact spacecraft. We present an updated version of NASA's Meteoroid Engineering Model (MEM) that better captures the correlation between directionality and velocity and incorporates a bulk density distribution. We compare the resulting model with the rate of large particle impacts seen on the Long Duration Exposure Facility (LDEF) and the Pegasus I and II satellites. The updated model shows closer agreement with these in situ data than previous versions of MEM.

Moorhead, Althea V.↗
NASA NTRS1991

Sensor-model in-situ control of the RTM composite process

The paper reports on the use of in situ frequency dependent electromagnetic sensors (FDEMS) and the Loos resin transfer model to select and control the processing properties of an epoxy resin during RTM impregnation and cure. Once correlated with viscosity and degree of cure, FDEMS monitors the advancement of the resin, viscosity, and the impregnation of the fabric, allowing a direct means of monitoring in situ in the mold throughout the fabrication process the effects of time, temperature, vacuum, and pressure.

Kranbuehl, D. E.↗
NASA NTRS2017

Using the Coronal Evolution to Successfully Forward Model CMEs' In Situ Magnetic Profiles

Predicting the effects of a coronal mass ejection (CME) impact requires knowing if impact will occur, which part of the CME impacts, and its magnetic properties. We explore the relation between CME deflections and rotations, which change the position and orientation of a CME, and the resulting magnetic profiles at 1 AU. For 45 STEREO-era, Earth-impacting CMEs, we determine the solar source of each CME, reconstruct its coronal position and orientation, and perform a ForeCAT (Forecasting a CME's Altered Trajectory) simulation of the coronal deflection and rotation. From the reconstructed and modeled CME deflections and rotations, we determine the solar cycle variation and correlations with CME properties. We assume no evolution between the outer corona and 1 AU and use the ForeCAT results to drive the ForeCAT In situ Data Observer (FIDO) in situ magnetic field model, allowing for comparisons with ACE and Wind observations. We do not attempt to reproduce the arrival time. On average FIDO reproduces the in situ magnetic field for each vector component with an error equivalent to 35 percent of the average total magnetic field strength when the total modeled magnetic field is scaled to match the average observed value. Random walk best fits distinguish between ForeCAT's ability to determine FIDO's input parameters and the limitations of the simple flux rope model. These best fits reduce the average error to 30 percent.The FIDO results are sensitive to changes of order a degree in the CME latitude, longitude, and tilt, suggesting that accurate space weather predictions require accurate measurements of a CME's position and orientation.

Kay, C.↗
NASA NTRS2004

Interpretation of TOMS Observations of Tropical Tropospheric Ozone with a Global Model and In Situ Observations

We interpret the distribution of tropical tropospheric ozone columns (TTOCs) from the Total Ozone Mapping Spectrometer (TOMS) by using a global three-dimensional model of tropospheric chemistry (GEOS-CHEM) and additional information from in situ observations. The GEOS-CHEM TTOCs capture 44% of the variance of monthly mean TOMS TTOCs from the convective cloud differential method (CCD) with no global bias. Major discrepancies are found over northern Africa and south Asia where the TOMS TTOCs do not capture the seasonal enhancements from biomass burning found in the model and in aircraft observations. A characteristic feature of these northern topical enhancements, in contrast to southern tropical enhancements, is that they are driven by the lower troposphere where the sensitivity of TOMS is poor due to Rayleigh scattering. We develop an efficiency correction to the TOMS retrieval algorithm that accounts for the variability of ozone in the lower troposphere. This efficiency correction increases TTOC's over biomass burning regions by 3-5 Dobson units (DU) and decreases them by 2-5 DU over oceanic regions, improving the agreement between CCD TTOCs and in situ observations. Applying the correction to CCD TTOCs reduces by approximately DU the magnitude of the "tropical Atlantic paradox" [Thompson et al, 2000], i.e. the presence of a TTOC enhancement over the southern tropical Atlantic during the northern African biomass burning season in December-February. We reproduce the remainder of the paradox in the model and explain it by the combination of upper tropospheric ozone production from lightning NOx, peristent subsidence over the southern tropical Atlantic as part of the Walker circulation, and cross-equatorial transport of upper tropospheric ozone from northern midlatitudes in the African "westerly duct." These processes in the model can also account for the observed 13-17 DU persistent wave-1 pattern in TTOCs with a maximum above the tropical Atlantic and a minimum over the tropical Pacific during all seasons. The photochemical effects of mineral dust have only a minor role on the modeled distribution of TTOCs, including over northern Africa, due to multiple competing effects. The photochemical effects of mineral dust globally decease annual mean OH concentrations by 9%. A global lightning NOx source of 6 Tg N yr(sup -1) in the model produces a simulation that is most consistent with TOMS and in situ observations.

Martin, Randall V.↗
NASA NTRS2011

SO2 Emissions and Lifetimes: Estimates from Inverse Modeling Using In Situ and Global, Space-Based (SCIAMACHY and OMI) Observations

Top-down constraints on global sulfur dioxide (SO2) emissions are inferred through inverse modeling using SO2 column observations from two satellite instruments (SCIAMACHY and OMI). We first evaluated the S02 column observations with surface SO2 measurements by applying local scaling factors from a global chemical transport model (GEOS-Chem) to SO2 columns retrieved from the satellite instruments. The resulting annual mean surface SO2 mixing ratios for 2006 exhibit a significant spatial correlation (r=0.86, slope=0.91 for SCIAMACHY and r=0.80, slope = 0.79 for OMI) with coincident in situ measurements from monitoring networks throughout the United States and Canada. We evaluate the GEOS-Chem simulation of the SO2 lifetime with that inferred from in situ measurements to verity the applicability of GEOS-Chem for inversion of SO2 columns to emissions. The seasonal mean SO2 lifetime calculated with the GEOS-Chem model over the eastern United States is 13 h in summer and 48 h in winter, compared to lifetimes inferred from in situ measurements of 19 +/- 7 h in summer and 58 +/- 20 h in winter. We apply SO2 columns from SCIAMACHY and OMI to derive a top-down anthropogenic SO2 emission inventory over land by using the local GEOS-Chem relationship between SO2 columns and emissions. There is little seasonal variation in the top-down emissions (<15%) over most major industrial regions providing some confidence in the method. Our global estimate for annual land surface anthropogenic SO2 emissions (52.4 Tg S/yr from SCIAMACHY and 49.9 Tg S / yr from OMI) closely agrees with the bottom-up emissions (54.6 Tg S/yr) in the GEOS-Chem model and exhibits consistency in global distributions with the bottom-up emissions (r = 0.78 for SCIAMACHY, and r = 0.77 for OMI). However, there are significant regional differences.

Lee, Chulkyu↗
NASA NTRSDate not supplied

FORWARD AND INVERSE L-BAND RADIATIVE TRANSFER MODELING OVER THE DRY CHACO, USING SMOS OBSERVATIONS, LAND SURFACE MODELING AND IN SITU DATA

Passive microwave L-band remote sensing is well known for its sensitivity to surface soil moisture over land.The signal is also affected by other dynamic variables such as vegetation and soil salinity. In this research, L-band microwave observations of the Soil Moisture Ocean Salinity (SMOS) mission are used to explore soil surface salinity, moisture and vegetation, in the Argentinean Dry Chaco, an area with possible emerging dryland salinity. A Radiative Transfer Model (RTM) with inclusion of a correction to the soil’s dielectric constant for salinity was used in forward and inverse mode, using either in situ data or Catchment Land Surface Model (CLSM) simulations as RTM input. The forward analysis pointed out shortcomings in the modeled soil moisture and soil surface temperature estimates. The impact of salinity on forward simulations over the Dry Chaco was limited.The RTM inversion using 10 years of SMOS brightness temperature observations resulted in realistic estimates of vegetation and roughness, both with and withouto ptimizing a correction term for the dielectric constant in terms of salinity equivalents. However,the retrieval of the correction term to the dielectric constant was very uncertain and not representative of soil surface salinity, but rather of open water, texture uncertainty or soil moisture bias.

L-band↗