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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Investigation of remote sensing techniques of measuring soil moisture

Major activities described include development and evaluation of theoretical models that describe both active and passive microwave sensing of soil moisture, the evaluation of these models for their applicability, the execution of a controlled field experiment during which passive microwave measurements were acquired to validate these models, and evaluation of previously acquired aircraft microwave measurements. The development of a root zone soil water and soil temperature profile model and the calibration and evaluation of gamma ray attenuation probes for measuring soil moisture profiles are considered. The analysis of spatial variability of soil information as related to remote sensing is discussed as well as the implementation of an instrumented field site for acquisition of soil moisture and meteorologic information for use in validating the soil water profile and soil temperature profile models.

Newton, R. W.↗
NASA NTRS2004

Bias Reduction in Short Records of Satellite Soil Moisture

Although surface soil moisture data from different sources (satellite retrievals, ground measurements, and land model integrations of observed meteorological forcing data) have been shown to contain consistent and useful information in their seasonal cycle and anomaly signals, they typically exhibit very different mean values and variability. These biases pose a severe obstacle to exploiting the useful information contained in satellite retrievals through data assimilation. A simple method of bias removal is to match the cumulative distribution functions (cdf) of the satellite and model data. However, accurate cdf estimation typically requires a long record of satellite data. We demonstrate here that by wing spatial sampling with a 2 degree moving window we can obtain local statistics based on a one-year satellite record that are a good approximation to those that would be derived from a much longer time series. This result should increase the usefulness of relatively short satellite data records.

Reichle, Rolf H.↗
NASA NTRS1999

The Vertical Structure of Major Meteorological Features on Jupiter: The Great Red Spot and White Ovals BC and DE

Multi-spectral imagery of Jupiter's Great Red Spot (GRS) and two White ovals acquired by the Galileo/NIMS are used to constrain the spatial variability of the vertical aerosol structure and the distribution of ammonia in and around these most-prominent anti-cyclonic features. All three features exhibit a high-altitude core spanning about 3/4 of their visual size when viewed with moderate absorption wavelengths, indicating a bulk elliptical, "wedding cake" shape in their overall three-dimensional cloud structure. A distinctive spiral pattern within the GRS core is seen in moderate methane and hydrogen absorption bandpasses. This pattern - which has been modelled to show a 2 km variation in cloudtop pressure within the GRS - is inconsistent with a different spiral-shaped pattern observed in ammonia-sensitive wavelengths, thus indicating spatial variability not only in the column abundance of ammonia within the GRS, but in its mixing ratio as well. White Ovals BC and DE were observed in February 1997, just a year before their unusual merger into a single feature. At the time of these observations, the centers of the two anti-cyclones were about 16 degrees apart, separated by a complex cyclonic feature which exhibited unusual spatial variability in its appearance in images acquired at ammonia-sensitive wavelengths. In particular, the northern half of this feature has the largest ammonia column abundance seen within the environs around the white ovals, indicating unusual variability in either cloud structure/altitude and/or ammonia humidity within the cyclone.

Baines, Kevin H.↗
NASA NTRS2004

Characterization of Transport Errors in Chemical Forecasts from a Global Tropospheric Chemical Transport Model

We propose a new methodology to characterize errors in the representation of transport processes in chemical transport models. We constrain the evaluation of a global three-dimensional chemical transport model (GEOS-CHEM) with an extended dataset of carbon monoxide (CO) concentrations obtained during the Transport and Chemical Evolution over the Pacific (TRACE-P) aircraft campaign. The TRACEP mission took place over the western Pacific, a region frequently impacted by continental outflow associated with different synoptic-scale weather systems (such as cold fronts) and deep convection, and thus provides a valuable dataset. for our analysis. Model simulations using both forecast and assimilated meteorology are examined. Background CO concentrations are computed as a function of latitude and altitude and subsequently subtracted from both the observed and the model datasets to focus on the ability of the model to simulate variability on a synoptic scale. Different sampling strategies (i.e., spatial displacement and smoothing) are applied along the flight tracks to search for systematic model biases. Statistical quantities such as correlation coefficient and centered root-mean-square difference are computed between the simulated and the observed fields and are further inter-compared using Taylor diagrams. We find no systematic bias in the model for the TRACE-P region when we consider the entire dataset (i.e., from the surface to 12 km ). This result indicates that the transport error in our model is globally unbiased, which has important implications for using the model to conduct inverse modeling studies. Using the First-Look assimilated meteorology only provides little improvement of the correlation, in comparison with the forecast meteorology. These general statements can be refined when the entire dataset is divided into different vertical domains, i.e., the lower troposphere (less than 2 km), the middle troposphere (2-6 km), and the upper troposphere (greater than 6 km). The best agreement between the observations and the model is found in the lower and middle troposphere. Downward displacements in the lower troposphere provide a better fit with the observed value, which could indicate a problem in the representation of boundary layer height in the model. Significant improvement is also found for downward and southward displacements in the upper troposphere. There are several potential sources of errors in our simulation of the continental outflow in the upper troposphere which could lead to such biases, including the location and/or the strength of deep convective cells as well as that of wildfires in Southeast Asia.

Bey, I.↗
NASA NTRS1985

Density and temperature structure over northern Europe

During the Energy Budget Campaign, a number of profiles of the density and temperature were obtained to study the structure and variability of the atmosphere. The measurements were made using rocketborne instrumentation launched from Esrange, Sweden, and Andoya Rocket Range, Norway, during November and December 1980. The techniques included meteorological temperature sondes, passive falling sphere, accelerometer instrumented falling spheres, density gauges, mass spectrometers and infrared emission experiments. The instruments provided data covering the altitude range from 20 to 150 km. The measurements were made during periods which have been grouped into three categories by level of geomagnetic activity. Analysis has been made to compare the results and to examine the wave features and variations in the vertical profiles for scales ranging between hundreds of meters and tens of kilometers. Most of the features observed fit qualitatively within the range expected for internal gravity waves. However, the features in the profiles during one of the measurement periods are unusual and may be due to aurorally generated shock waves. The geomagnetic storm conditions caused temperature increases in the lower thermosphere which maximized in the 120-140 km region.

Philbrick, C. R.↗
NASA NTRS1991

The phytoplankton bloom in the northwestern Arabian Sea during the southwest monsoon of 1979

The present study investigates the biological variability of the northwestern Arabian Sea during the 1979 southwest monsoon by the synthesis of satellite ocean color remote sensing with an analysis of in situ hydrographic and meteorological data sets and the results of wind-driven modeling of upper-ocean circulation. The phytoplankton bloom peaked during August-September, extended from the Oman coast to about 65 deg E, and lagged behind the development of open-sea upwelling by at least 1 mo. The pigment distributions, hydrographic data, and model results all suggest that the boom was driven by spatially distinct upward nutrient fluxes to the euphotic zone forced by the physical processes of coastal upwelling and offshore Ekman pumping. Coastal upwelling was evident from May through September, yielded the most extreme concentrations of phytoplankton biomass, and, along the Arabian coast, was limited to the continental shelf in the promotion of high concentrations of phytoplankton.

Brock, John C.↗
NASA NTRS2010

Modeling Fire Severity in Black Spruce Stands in the Alaskan Boreal Forest Using Spectral and Non-Spectral Geospatial Data

Biomass burning in the Alaskan interior is already a major disturbance and source of carbon emissions, and is likely to increase in response to the warming and drying predicted for the future climate. In addition to quantifying changes to the spatial and temporal patterns of burned areas, observing variations in severity is the key to studying the impact of changes to the fire regime on carbon cycling, energy budgets, and post-fire succession. Remote sensing indices of fire severity have not consistently been well-correlated with in situ observations of important severity characteristics in Alaskan black spruce stands, including depth of burning of the surface organic layer. The incorporation of ancillary data such as in situ observations and GIS layers with spectral data from Landsat TM/ETM+ greatly improved efforts to map the reduction of the organic layer in burned black spruce stands. Using a regression tree approach, the R2 of the organic layer depth reduction models was 0.60 and 0.55 (pb0.01) for relative and absolute depth reduction, respectively. All of the independent variables used by the regression tree to estimate burn depth can be obtained independently of field observations. Implementation of a gradient boosting algorithm improved the R2 to 0.80 and 0.79 (pb0.01) for absolute and relative organic layer depth reduction, respectively. Independent variables used in the regression tree model of burn depth included topographic position, remote sensing indices related to soil and vegetation characteristics, timing of the fire event, and meteorological data. Post-fire organic layer depth characteristics are determined for a large (N200,000 ha) fire to identify areas that are potentially vulnerable to a shift in post-fire succession. This application showed that 12% of this fire event experienced fire severe enough to support a change in post-fire succession. We conclude that non-parametric models and ancillary data are useful in the modeling of the surface organic layer fire depth. Because quantitative differences in post-fire surface characteristics do not directly influence spectral properties, these modeling techniques provide better information than the use of remote sensing data alone.

Barrett, K.↗
NASA NTRS2011

Using Satellite Aerosol Retrievals to Monitor Surface Particulate Air Quality

The MODIS and MISR aerosol products were designed nearly two decades ago for the purpose of climate applications. Since launch of Terra in 1999, these two sensors have provided global, quantitative information about column-integrated aerosol properties, including aerosol optical depth (AOD) and relative aerosol type parameters (such as Angstrom exponent). Although primarily designed for climate, the air quality (AQ) community quickly recognized that passive satellite products could be used for particulate air quality monitoring and forecasting. However, AOD and particulate matter (PM) concentrations have different units, and represent aerosol conditions in different layers of the atmosphere. Also, due to low visible contrast over brighter surface conditions, satellite-derived aerosol retrievals tend to have larger uncertainty in urban or populated regions. Nonetheless, the AQ community has made significant progress in relating column-integrated AOD at ambient relative humidity (RH) to surface PM concentrations at dried RH. Knowledge of aerosol optical and microphysical properties, ambient meteorological conditions, and especially vertical profile, are critical for physically relating AOD and PM. To make urban-scale maps of PM, we also must account for spatial variability. Since surface PM may vary on a finer spatial scale than the resolution of standard MODIS (10 km) and MISR (17km) products, we test higher-resolution versions of MODIS (3km) and MISR (1km research mode) retrievals. The recent (July 2011) DISCOVER-AQ campaign in the mid-Atlantic offers a comprehensive network of sun photometers (DRAGON) and other data that we use for validating the higher resolution satellite data. In the future, we expect that the wealth of aircraft and ground-based measurements, collected during DISCOVER-AQ, will help us quantitatively link remote sensed and ground-based measurements in the urban region.

Levy, Robert C.↗
NASA NTRS2012

The Cabauw Intercomparison Campaign for Nitrogen Dioxide Measuring Instruments (CINDI): Design, Execution, and Early Results

From June to July 2009 more than thirty different in-situ and remote sensing instruments from all over the world participated in the Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI). The campaign took place at KNMI's Cabauw Experimental Site for Atmospheric Research (CESAR) in the Netherlands. Its main objectives were to determine the accuracy of state-ofthe- art ground-based measurement techniques for the detection of atmospheric nitrogen dioxide (both in-situ and remote sensing), and to investigate their usability in satellite data validation. The expected outcomes are recommendations regarding the operation and calibration of such instruments, retrieval settings, and observation strategies for the use in ground-based networks for air quality monitoring and satellite data validation. Twenty-four optical spectrometers participated in the campaign, of which twenty-one had the capability to scan different elevation angles consecutively, the so-called Multi-axis DOAS systems, thereby collecting vertical profile information, in particular for nitrogen dioxide and aerosol. Various in-situ samplers and lidar instruments simultaneously characterized the variability of atmospheric trace gases and the physical properties of aerosol particles. A large data set of continuous measurements of these atmospheric constituents has been collected under various meteorological conditions and air pollution levels. Together with the permanent measurement capability at the CESAR site characterizing the meteorological state of the atmosphere, the CINDI campaign provided a comprehensive observational data set of atmospheric constituents in a highly polluted region of the world during summertime. First detailed comparisons performed with the CINDI data show that slant column measurements of NO2, O4 and HCHO with MAX-DOAS agree within 5 to 15%, vertical profiles of NO2 derived from several independent instruments agree within 25% of one another, and MAX-DOAS aerosol optical thickness agrees within 20-30% with AERONET data. For the in-situ NO2 instrument using a molybdenum converter, a bias was found as large as 5 ppbv during day time, when compared to the other in-situ instruments using photolytic converters.

Atmospheric composition↗
NASA NTRS2014

Water Balance in the Amazon Basin from a Land Surface Model Ensemble

Despite recent advances in land surfacemodeling and remote sensing, estimates of the global water budget are still fairly uncertain. This study aims to evaluate the water budget of the Amazon basin based on several state-ofthe- art land surface model (LSM) outputs. Water budget variables (terrestrial water storage TWS, evapotranspiration ET, surface runoff R, and base flow B) are evaluated at the basin scale using both remote sensing and in situ data. Meteorological forcings at a 3-hourly time step and 18 spatial resolution were used to run 14 LSMs. Precipitation datasets that have been rescaled to matchmonthly Global Precipitation Climatology Project (GPCP) andGlobal Precipitation Climatology Centre (GPCC) datasets and the daily Hydrologie du Bassin de l'Amazone (HYBAM) dataset were used to perform three experiments. The Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme was forced with R and B and simulated discharges are compared against observations at 165 gauges. Simulated ET and TWS are compared against FLUXNET and MOD16A2 evapotranspiration datasets andGravity Recovery and ClimateExperiment (GRACE)TWSestimates in two subcatchments of main tributaries (Madeira and Negro Rivers).At the basin scale, simulated ET ranges from 2.39 to 3.26 mm day(exp -1) and a low spatial correlation between ET and precipitation indicates that evapotranspiration does not depend on water availability over most of the basin. Results also show that other simulated water budget components vary significantly as a function of both the LSM and precipitation dataset, but simulated TWS generally agrees with GRACE estimates at the basin scale. The best water budget simulations resulted from experiments using HYBAM, mostly explained by a denser rainfall gauge network and the rescaling at a finer temporal scale.

GPCP↗
NASA NTRS2016

The Quality Control Algorithms Used in the Creation of NASA Kennedy Space Center Lightning Protection System Towers Meteorological Database

An accurate database of meteorological data is essential for designing any aerospace vehicle and for preparing launch commit criteria. Meteorological instrumentation were recently placed on the three Lightning Protection System (LPS) towers at Kennedy Space Center (KSC) launch complex 39B (LC-39B), which provide a unique meteorological dataset existing at the launch complex over an extensive altitude range. Data records of temperature, dew point, relative humidity, wind speed, and wind direction are produced at 40, 78, 116, and 139 m at each tower. The Marshall Space Flight Center Natural Environments Branch (EV44) received an archive that consists of one-minute averaged measurements for the period of record of January 2011 - April 2015. However, before the received database could be used EV44 needed to remove any erroneous data from within the database through a comprehensive quality control (QC) process. The QC process applied to the LPS towers' meteorological data is similar to other QC processes developed by EV44, which were used in the creation of meteorological databases for other towers at KSC. The QC process utilized in this study has been modified specifically for use with the LPS tower database. The QC process first includes a check of each individual sensor. This check includes removing any unrealistic data and checking the temporal consistency of each variable. Next, data from all three sensors at each height are checked against each other, checked against climatology, and checked for sensors that erroneously report a constant value. Then, a vertical consistency check of each variable at each tower is completed. Last, the upwind sensor at each level is selected to minimize the influence of the towers and other structures at LC-39B on the measurements. The selection process for the upwind sensor implemented a study of tower-induced turbulence. This paper describes in detail the QC process, QC results, and the attributes of the LPS towers meteorological database.

Orcutt, John M.↗
NASA NTRS2012

Quantifying Interannual Variability of the UTLS Ozone Using Assimilation of Satellite Data

An accurate representation of spatial and temporal variability of the Upper Troposphere Lower Stratosphere (UTLS) ozone is essential for understanding both the tropospheric ozone budget and ozone s contribution to radiative forcing. The complex, dynamically driven structure of trace gas fields in the UTLS presents a challenge to data-based and modelling studies. Small features are not fully resolved in data from limb-sounding instruments such as the Microwave Limb Sounder on EOS-Aura (the EOS-MLS), but are captured in assimilation of those data as vertical structure is added from the assimilated meteorology. This will be demonstrated using a multi-year assimilation of EOS-MLS observations in the Goddard Earth Observing System, Version 5 (GEOS-5) data assimilation system. The results demonstrate the realism of the seasonal and year to year variability of laminar structures in the mid-latitudinal ozone field between years 2005-2007, for which independent validation data are available from the HIRDLS instrument. The analysis is done in the context of the underlying large scale dynamics. The lifetimes of most research instruments are too short for them to be used throughout the duration of long-term (at least 3 decades) reanalyses. For example, the EOS-MLS instrument has operated since mid-2004 until present. By contrast, Solar Backscatter Ultra Violet (SBUV) measurements provide continuous data since late 1978, but their vertical resolution is insufficient to represent the profile shape in the UTLS. Assimilation of these SBUV/2 observations in the GEOS-5 data assimilation system has hitherto not captured a realistic ozone structure in the UTLS, even though transport studies using GEOS-5 wind fields do show such structures. We show that careful construction of the background error covariance structure in GEOS-5 can lead to more realistic UTLS ozone fields when assimilating SBUV/2 observations. The reasoning behind this will be discussed, emphasizing the need to retain the sharp gradient of ozone concentrations across the tropopause. We analyze the UTLS ozone distributions in multi-year SBUV/2 assimilation experiments, comparing the results against the independent HIRDLSdataset and, for a longer period, with the MLS assimilation and discuss the consequences for tropospheric ozone and radiative forcing.

Wargan, K.↗
NASA NTRS2017

Estimating Evaporative Fraction From Readily Obtainable Variables in Mangrove Forests of the Everglades, U.S.A.

A remote-sensing-based model to estimate evaporative fraction (EF) the ratio of latent heat (LE; energy equivalent of evapotranspiration -ET-) to total available energy from easily obtainable remotely-sensed and meteorological parameters is presented. This research specifically addresses the shortcomings of existing ET retrieval methods such as calibration requirements of extensive accurate in situ micro-meteorological and flux tower observations, or of a large set of coarse-resolution or model-derived input datasets. The trapezoid model is capable of generating spatially varying EF maps from standard products such as land surface temperature [T(sub s)] normalized difference vegetation index (NDVI)and daily maximum air temperature [T(sub a)]. The 2009 model results were validated at an eddy-covariance tower (Fluxnet ID: US-Skr) in the Everglades using T(sub s) and NDVI products from Landsat as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. Results indicate that the model accuracy is within the range of instrument uncertainty, and is dependent on the spatial resolution and selection of end-members (i.e. wet/dry edge). The most accurate results were achieved with the T(sub s) from Landsat relative to the T(sub s) from the MODIS flown on the Terra and Aqua platforms due to the fine spatial resolution of Landsat (30 m). The bias, mean absolute percentage error and root mean square percentage error were as low as 2.9% (3.0%), 9.8% (13.3%), and 12.1% (16.1%) for Landsat-based (MODIS-based) EF estimates, respectively. Overall, this methodology shows promise for bridging the gap between temporally limited ET estimates at Landsat scales and more complex and difficult to constrain global ET remote-sensing models.

trapezoid↗
NASA NTRS1981

Plant cover, soil temperature, freeze, water stress, and evapotranspiration conditions

Emissive and reflective data for 10 days, and IR data for 6 nights in south Texas scenes were analyzed after procedures were developed for removing cloud-affected data. HCMM radiometric temperatures were: within 2 C of dewpoint temperatures on nights when air temperature approached dewpoint temperatures; significantly correlated with variables important in evapotranspiration; and, related to freeze severity and planting depth soil temperatures. Vegetation greenness indexes calculated from visible and reflective IR bands of NOAA-6 to -9 meteorological satellites will be useful in the AgRISTARS program for seasonal crop development, crop condition, and drought applications.

Wiegand, C. L.↗
NASA NTRS1981

Medium-range, objective predictions of thunderstorm location and severity for aviation

This paper presents a computerized technique for medium-range (12-48h) prediction of both the location and severity of thunderstorms utilizing atmospheric predictions from the National Meteorological Center's limited-area fine-mesh model (LFM). A regional-scale analysis scheme is first used to examine the spatial and temporal distributions of forecasted variables associated with the structure and dynamics of mesoscale systems over an area of approximately 10 to the 6th sq km. The final prediction of thunderstorm location and severity is based upon an objective combination of these regionally analyzed variables. Medium-range thunderstorm predictions are presented for the late afternoon period of April 10, 1979, the day of the Wichita Falls, Texas tornado. Conventional medium-range thunderstorm forecasts, made from observed data, are presented with the case study to demonstrate the possible application of this objective technique in improving 12-48 h thunderstorm forecasts for aviation.

Wilson, G. S.↗
NASA NTRS1983

Description and overview of an instrument designed to measure line-of-sight delay due to water vapor

Eight dual channel microwave radiometers were constructed as a research and development effort for the Crustal Dynamics Project and the Deep Space Network. These instruments, known as water vapor radiometers, are primarily intended to demonstrate that the variable path delay imposed by atmospheric water vapor can be calibrated in microwave tracking and distance measuring systems but could also be used in other applications involving moist air meteorology and propagation studies. They are being deployed to various stations and observatories that participate in Very Long Baseline Interferometry experiments. The development history of these instruments are reviewed, the theory of operation and overall design considerations are outlined, and the instrumental parameters and performance characteristics are described.

Resch, G. M.↗
NASA NTRS1985

Participation in the Mars Data Analysis Program: Analysis of cloud forms in Viking and Mariner 9 images

The first systematic account of the climate of Mars, based upon observations was produced. Cloud data were used to determine spatially and temporally varying near-surface wind direction, relative wind speed, static stability, and humidity conditions on a global scale. Existing models of meteorological processes were critically reexamined in light of the data, and more stringent constraints were set on global processes. Several discoveries were made, including the large extent and seasonal variability of the Mars equatorial Hadley cell, the failure of high latitude winds to reverse direction in early northern spring, the change in meridional wind component in southern midautum, and the almost constant cloud cover in the northern hemisphere, during spring and summer primarily by condensate clouds and in fall and winter by condensates and dust. The implications of these observations are discussed.

Gierasch, P.↗
NASA NTRS1991

High resolution atmospheric and surface variability from combined MAMS and VAS radiances

Measuring of the variation of atmospheric and surface quantities such as moisture and stability at small scales is an important step to monitoring, understanding and forecasting mesoscale processes. For instance, moisture and stability products from the geostationary platform VISSR Atmospheric Sounder (VAS) exhibit interesting detail at the meso B (20-200 km) level (Chesters et al., 1986; Smith et al., 1985). However, variations at the meso C scale (2-20 km) and at the lower end of the meso B scale (20-100 km) suffer from the effects of noise. Noise can be greatly reduced by using a high resolution data collection system. The Multispectral Atmospheric Mapping Sensor (MAMS), with its 100-m resolution over a 36km swath, is well suited to provide high resolution mesoscale information about the atmosphere and surface of the earth. A more complete depiction of the atmospheric state at the smaller scales is possible through the combination of the high horizontal resolution MAMS data with the vertical sounding data of the VAS. This paper demonstrates a procedure for combining MAMS and VAS data in a physical retrieval to produce high resolution derived products of precipitable water (PW), lifted index (LI), and skin temperature (TS). The variability of these products is evaluated in a structure function analysis similar to that of Hillger and Vonder Haar (1979). Results for 19 June 1986 from the Cooperative Hunstville Meteorological Experiment (COHMEX) are presented.

Moeller, Christopher C.↗