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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

The first International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment - FIFE

The International Satellite Land Surface Climatology Project (ISLSCP) will verify the use of satellite data for the estimation of land-surface properties through field experiments using point measurements on the ground and areal measurements from aircraft overflights. It will study approaches for obtaining areal averages of the radiation, moisture, and heat fluxes made using remotely sensed data, by combining the surface point measurements of the fluxes with the aircraft areal observations using a surface energy balance model. Surface parameters to be estimated from aircraft observations include: surface radiation temperature, albedo, land cover or vegetation index, and surface soil moisture. The latter will be obtained using passive and active microwave approaches. The area-averages of the surface properties will be compared with satellite data. The First ISLSCP Field Experiment is planned for a site having relatively uniform vegetation cover in the central great plains of the U.S.A.

Schmugge, T. J.↗
NASA NTRS2017

Data Assimilation to Extract Soil Moisture Information From SMAP Observations

Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, they can be used to reduce the need for localized bias correction techniques typically implemented in data assimilation (DA) systems that tend to remove some of the independent information provided by satellite observations. Here, we use a statistical neural network (NN) algorithm to retrieve SMAP (Soil Moisture Active Passive) surface soil moisture estimates in the climatology of the NASA Catchment land surface model. Assimilating these estimates without additional bias correction is found to significantly reduce the model error and increase the temporal correlation against SMAP CalVal in situ observations over the contiguous United States. A comparison with assimilation experiments using traditional bias correction techniques shows that the NN approach better retains the independent information provided by the SMAP observations and thus leads to larger model skill improvements during the assimilation. A comparison with the SMAP Level 4 product shows that the NN approach is able to provide comparable skill improvements and thus represents a viable assimilation approach.

D↗
NASA NTRS1988

An attempt to remotely sense from space the surface heat budget over the Indian Ocean during the 1979 monsoon

Satellite data are used to estimate the net surface heat flux (Q) over the Indian Ocean during June 1979. Ten-day and monthly average fields of Q and its components are produced and analyzed in relation to monsoon dynamics. When compared to ship-based estimates, the satellite-derived fluxes exhibit correct orders of magnitude and their temporal evolution is consistent with the present monsoon knowledge. This study, which represents a first attempt to remotely sense from space the earth surface net heat flux, demonstrates that current satellite sensor data can be combined to accurately describe net heat flux changes in areas such as the Arabian Sea, where they are large, rapid, and spatially extended, and therefore not fully observed by ships.

Gautier, Catherine↗
NASA NTRS2024

Influence of SMAP Soil Moisture Retrieval Assimilation on Runoff Estimation Across South Asia

This study was designed to characterize and quantify the influence of surface soil moisture assimilation on estimated runoff (surface flow and baseflow) and hydraulically-routed streamflow across three large river basins in South Asia that are at risk of impending water stress. Soil Moisture Active Passive (SMAP) surface soil moisture retrievals were assimilated into the Noah-MP land surface model. The gridded runoff was hydraulically routed to obtain volumetric streamflow values for a river network using a runoff routing module (Hydrological Modeling and Analysis Platform, HyMAP). The open loop (OL, model-only) and data assimilated (DA, includes soil moisture retrieval assimilation) Noah-MP runoff estimates highlighted the improvements in estimated total runoff across irrigated areas. Soil moisture assimilation impacted baseflow more relative to surface runoff. The HyMAP-based OL and DA streamflow generally underestimated the streamflow at upstream stations and overestimated the streamflow at downstream stations within the Indus basin due to missing physics related to reservoir operations. For stations located in the Ganges–Brahmaputra basins, the OL and DA estimation performance varied. The OL and DA results showed that the assimilation of soil moisture retrievals improves gridded runoff and volumetric streamflow across irrigated areas. Considerable relative change in streamflow (>70% increase in magnitude relative to OL) is noted after assimilation across the highly irrigated lower Indus basin and high precipitation regions in Bangladesh. Improving the modeling system’s representativeness of ground conditions via inclusion of water management information could improve large-scale streamflow modeling across South Asia.

soil moisture↗
NASA NTRS1978

Estimating tropical cyclone central pressure and outer winds from satellite microwave data

A new technique is presented for estimating central pressure and surface winds outside of the radius of maximum winds from brightness temperatures measured by the SCAMS on Nimbus 6. The problem of estimating maximum surface winds is not treated because the spatial resolution of the radiometer is not high enough for this purpose. The technique is developed on the basis of measurements over eight typhoons and five hurricanes during 1975. It is shown that the warm 55.45-GHz brightness temperature anomaly previously observed over Typhoon June can be found over other tropical cyclones. Maximum brightness temperature anomaly correlates with central pressure with a correlation coefficient of -0.859. Outer surface wind speeds are calculated by assuming gradient balance and using the regression between brightness temperature anomaly and central pressure to estimate pressure gradients.

Kidder, S. Q.↗
NASA NTRS2012

Application of Artificial Neural Networks to the Development of Improved Multi-Sensor Retrievals of Near-Surface Air Temperature and Humidity Over Ocean

Improved estimates of near-surface air temperature and air humidity are critical to the development of more accurate turbulent surface heat fluxes over the ocean. Recent progress in retrieving these parameters has been made through the application of artificial neural networks (ANN) and the use of multi-sensor passive microwave observations. Details are provided on the development of an improved retrieval algorithm that applies the nonlinear statistical ANN methodology to a set of observations from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A) that are currently available from the NASA AQUA satellite platform. Statistical inversion techniques require an adequate training dataset to properly capture embedded physical relationships. The development of multiple training datasets containing only in-situ observations, only synthetic observations produced using the Community Radiative Transfer Model (CRTM), or a mixture of each is discussed. An intercomparison of results using each training dataset is provided to highlight the relative advantages and disadvantages of each methodology. Particular emphasis will be placed on the development of retrievals in cloudy versus clear-sky conditions. Near-surface air temperature and humidity retrievals using the multi-sensor ANN algorithms are compared to previous linear and non-linear retrieval schemes.

Roberts, J. Brent↗
NASA NTRS2011

Land Data Assimilation of Satellite-Based Soil Moisture Products Using the Land Information System Over the NLDAS Domain

This presentation will include results from data assimilation simulations using the NASA-developed Land Information System (LIS). Using the ensemble Kalman filter in LIS, two satellite-based soil moisture products from the AMSR-E instrument were assimilated, one a NASA-based product and the other from the Land Parameter Retrieval Model (LPRM). The domain and land-surface forcing data from these simulations were from the North American Land Data Assimilation System Phase-2, over the period 2002-2008. The Noah land-surface model, version 3.2, was used during the simulations. Changes to estimates of land surface states, such as soil moisture, as well as changes to simulated runoff/streamflow will be presented. Comparisons over the NLDAS domain will also be made to two global reference evapotranspiration (ET) products, one an interpolated product based on FLUXNET tower data and the other a satellite- based algorithm from the MODIS instrument. Results of an improvement metric show that assimilating the LPRM product improved simulated ET estimates while the NASA-based soil moisture product did not.

Mocko, David M.↗
NASA NTRS2012

Characterization of Turbulent Latent and Sensible Heat Flux Exchange Between the Atmosphere and Ocean in MERRA

Turbulent fluxes of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth's energy and water balance. Characterizing both the spatiotemporal variability and the fidelity of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. This study examines the veracity of the recently completed NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) product with respect to its representation of the surface turbulent heat fluxes. A validation of MERRA turbulent heat fluxes and near-surface bulk variables at local, high-resolution space and time scales is achieved by making comparisons to a large suite of direct observations. Both in situ and satellite-observed gridded surface heat flux estimates are employed to investigate the spatial and temporal variability of the surface fluxes with respect to their annual mean climatologies, their seasonal covariability of near-surface bulk parameters, and their representation of extremes. The impact of data assimilation on the near-surface parameters is assessed through evaluation of incremental analysis update tendencies produced by the assimilation procedure. It is found that MERRA turbulent surface heat fluxes are relatively accurate for typical conditions but have systematically weak vertical gradients in moisture and temperature and have a weaker covariability between the near-surface gradients and wind speed than found in observations. This results in an underestimate of the surface latent and sensible heat fluxes over the western boundary current and storm track regions. The assimilation of observations mostly acts to bring MERRA closer to observational products by increasing moisture and temperature near the surface and decreasing the near-surface wind speeds. The major patterns of spatial and temporal variability of the turbulent heat fluxes produced by MERRA compare favorably to observationally based estimates. However, MERRA is distinct in terms of amplitude. These results suggest that MERRA is likely to be a valuable resource for a number of research applications though, as with all turbulent flux estimates, systematic issues should be taken into account

Robert, J. Brent↗
NASA NTRS2012

Characterization of Turbulent Latent and Sensible Heat Flux Exchange Between the Atmosphere and Ocean in MERRA

Turbulent fluxes of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth s energy and water balance. Characterizing both the spatiotemporal variability and the fidelity of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. This study examines the veracity of the recently completed NASA Modern-Era Retrospective analysis for Research and Applications (MERRA) product with respect to its representation of the surface turbulent heat fluxes. A validation of MERRA turbulent heat fluxes and near-surface bulk variables at local, high-resolution space and time scales is achieved by making comparisons to a large suite of direct observations. Both in situ and satellite-observed gridded surface heat flux estimates are employed to investigate the spatial and temporal variability of the surface fluxes with respect to their annual mean climatologies, their seasonal covariability of near-surface bulk parameters, and their representation of extremes. The impact of data assimilation on the near-surface parameters is assessed through evaluation of incremental analysis update tendencies produced by the assimilation procedure. It is found that MERRA turbulent surface heat fluxes are relatively accurate for typical conditions but have systematically weak vertical gradients in moisture and temperature and have a weaker covariability between the near-surface gradients and wind speed than found in observations. This results in an underestimate of the surface latent and sensible heat fluxes over the western boundary current and storm track regions. The assimilation of observations mostly acts to bring MERRA closer to observational products by increasing moisture and temperature near the surface and decreasing the near-surface wind speeds. The major patterns of spatial and temporal variability of the turbulent heat fluxes produced by MERRA compare favorably to observationally based estimates. However, MERRA is distinct in terms of amplitude. These results suggest that MERRA is likely to be a valuable resource for a number of research applications though, as with all turbulent flux estimates, systematic issues should be taken into account.

Roberts, J. Brent↗
NASA NTRS1990

A preliminary estimate of geoid-induced variations in repeat orbit satellite altimeter observations

Altimeter satellites are often maintained in a repeating orbit to facilitate the separation of sea-height variations from the geoid. However, atmospheric drag and solar radiation pressure cause a satellite orbit to drift. For Geosat this drift causes the ground track to vary by + or - 1 km about the nominal repeat path. This misalignment leads to an error in the estimates of sea surface height variations because of the local slope in the geoid. This error has been estimated globally for the Geosat Exact Repeat Mission using a mean sea surface constructed from Geos 3 and Seasat altimeter data. Over most of the ocean the geoid gradient is small, and the repeat-track misalignment leads to errors of only 1 to 2 cm. However, in the vicinity of trenches, continental shelves, islands, and seamounts, errors can exceed 20 cm. The estimated error is compared with direct estimates from Geosat altimetry, and a strong correlation is found in the vicinity of the Tonga and Aleutian trenches. This correlation increases as the orbit error is reduced because of the increased signal-to-noise ratio.

Brenner, Anita C.↗
NASA NTRS2012

Quantitative Infrared Image Analysis Of Thermally-Thin Cellulose Surface Temperatures During Upstream and Downstream Microgravity Flame Spread from A Central Ignition Line

Surface view calibrated infrared images of ignition and flame spread over a thin cellulose fuel were obtained at 30 Hz during microgravity flame spread tests in the 10 second Japan Microgravity Center (JAMIC). The tests also used a color video of the surface view and color images of the edge view using 35 millimeter 1600 Kodak Ektapress film at 2 Hz. The cellulose fuel samples (50% long fibers from lumi pine and 50% short fibers from birch) were made with an area density of 60 grams per square meters. The samples were mounted in the center of a 12 centimeter wide by 16 centimeter tall flow duct that uses a downstream fan to draw the air through the flow duct. Samples were ignited after the experiment package was released using a straight hot wire across the center of the 7.5 centimeter wide by 14 centimeter long samples. One case, at 1 atmosphere 35%O2 in N2, at a forced flow of 10 centimeters per second, is presented here. In this case, as the test progresses, the single flame begins to separate into simultaneous upstream and downstream flames. Surface temperature profiles are evaluated as a function of time, and temperature gradients for upstream and downstream flame spread are measured. Flame spread rates from IR image data are compared to visible image spread rate data. IR blackbody temperatures are compared to surface thermocouple readings to evaluate the effective emissivity of the pyrolyzing surface. Preheat lengths are evaluated both upstream and downstream of the central ignition point. A surface energy balance estimates the net heat flux from the flame to the fuel surface along the length of the fuel.

Olson, Sandra L.↗
NASA NTRS2013

Quantitative Infrared Image Analysis Of Simultaneous Upstream and Downstream Microgravity Flame Spread over Thermally-Thin Cellulose in Low Speed Forced Flow

The effect of low velocity forced flow on microgravity flame spread is examined using quantitative analysis of infrared video imaging. The objective of the quantitative analysis is to provide insight into the mechanisms of flame spread in microgravity where the flame is able to spread from a central location on the fuel surface, rather than from an edge. Surface view calibrated infrared images of ignition and flame spread over a thin cellulose fuel were obtained along with a color video of the surface view and color images of the edge view using 35 mm color film at 2 Hz. The cellulose fuel samples were mounted in the center of a 12 cm wide by 16 cm tall flow duct and were ignited in microgravity using a straight hot wire across the center of the 7.5 cm wide by 14 cm long samples. Four cases, at 1 atm. 35%O2 in N2, at forced flows from 2 cm/s to 20 cm/s are presented here. This flow range captures flame spread from strictly upstream spread at low flows, to predominantly downstream spread at high flow. Surface temperature profiles are evaluated as a function of time, and temperature gradients for upstream and downstream flame spread are measured. Flame spread rates from IR image data are compared to visible image spread rate data. IR blackbody temperatures are compared to surface thermocouple readings to evaluate the effective emissivity of the pyrolyzing surface. Preheat lengths and pyrolysis lengths are evaluated both upstream and downstream of the central ignition point. A surface energy balance estimates the net heat flux from the flame to the fuel surface along the length of the fuel. Surface radiative loss and gas-phase radiation from soot are measured relative to the net heat feedback from the flame. At high surface heat loss relative to heat feedback, the downstream flame spread does not occur.

Olson, S. L.↗
NASA NTRS1982

A statistical examination of Nimbus 7 SMMR data and remote sensing of sea surface temperature, liquid water content in the atmosphere and surfaces wind speed

Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperature measurements over the global oceans have been examined with the help of statistical and empirical techniques. Such analyses show that zonal averages of brightness temperature measured by SMMR, over the oceans, on a large scale are primarily influenced by the water vapor in the atmosphere. Liquid water in the clouds and rain, which has a much smaller spatial and temporal scale, contributes substantially to the variability of the SMMR measurements within the latitudinal zones. The surface wind not only increases the surface emissivity but through its interactions with the atmosphere produces correlations, in the SMMR brightness temperature data, that have significant meteorological implications. It is found that a simple meteorological model can explain the general characteristics of the SMMR data. With the help of this model methods to infer over the global oceans, the surface temperature, liquid water content in the atmosphere, and surface wind speed are developed. Monthly mean estimates of the sea surface temperature and surface winds are compared with the ship measurements. Estimates of liquid water content in the atmosphere are consistent with earlier satellite measurements.

Prabhakara, C.↗
NASA NTRS1983

A statistical examination of Nimbus-7 SMMR data and remote sensing of sea surface temperature, liquid water content in the atmosphere and surface wind speed

Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperature measurements over the global oceans have been examined with the help of statistical and empirical techniques. Such analyses show that zonal averages of brightness temperature measured by SMMR over the oceans on a large scale are primarily influenced by the water vapor in the atmosphere. Liquid water in the clouds and rain, which has a much smaller spatial and temporal scale, contributes substantially to the variability of the SMMR measurements within the latitudinal zones. The surface wind not only increases the surface emissivity, but through its interactions with the atmosphere produces correlations in the SMMR brightness temperature data that have significant meteorological implications. It is found that a simple meteorological model can explain the general characteristics of the SMMR data. With the help of this model, methods to infer over the global oceans, the surface temperature, liquid water content in the atmosphere, and surface wind speed are developed. Monthly mean estimates of the sea surface temperature and surface winds are compared with the ship measurements. Estimates of liquid water content in the atmosphere are consistent with earlier satellite measurements. Previously announced in STAR as N83-19187

Prabhakara, C.↗
NASA NTRS1988

The estimation of precipitation intensity in the presence of surface backscatter and the converse using a spaceborne radar

The 'rain-modified' surface backscattering coefficient and the rain intensity can be estimated simultaneously by analyzing the return echo waveforms obtained by a nonnadir pointing spaceborne radar. Preliminary simulation results, using system parameters for the TRMM rain mapping radar, indicate that path-averaged rain attenuation coefficient can be estimated to 20 percent by such technique.

Im, K. Eastwood↗