Search NASA⌕ Search

SEARCH · Search NASA

Results for “surface water temperature”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

Land surface temperature measurements from EOS MODIS data

A generalized split-window method for retrieving land-surface temperature (LST) from AVHRR and MODIS data has been developed. Accurate radiative transfer simulations show that the coefficients in the split-window algorithm for LST must depend on the viewing angle, if we are to achieve a LST accuracy of about 1 K for the whole scan swath range (+/-55.4 deg and +/-55 deg from nadir for AVHRR and MODIS, respectively) and for the ranges of surface temperature and atmospheric conditions over land, which are much wider than those over oceans. We obtain these coefficients from regression analysis of radiative transfer simulations, and we analyze sensitivity and error by using results from systematic radiative transfer simulations over wide ranges of surface temperatures and emissivities, and atmospheric water vapor abundance and temperatures. Simulations indicated that as atmospheric column water vapor increases and viewing angle is larger than 45 deg it is necessary to optimize the split-window method by separating the ranges of the atmospheric column water vapor and lower boundary temperature, and the surface temperature into tractable sub-ranges. The atmospheric lower boundary temperature and (vertical) column water vapor values retrieved from HIRS/2 or MODIS atmospheric sounding channels can be used to determine the range where the optimum coefficients of the split-window method are given. This new LST algorithm not only retrieves LST more accurately but also is less sensitive than viewing-angle independent LST algorithms to the uncertainty in the band emissivities of the land-surface in the split-window and to the instrument noise.

Wan, Zhengming↗

International Satellite Cloud Climatology Project (ISCCP) TIROS Operational Vertical Sounder (TOVS) Product in Native (NAT) Format (ISCCP_TOVS_NAT)

Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=280 degree; Longitude_Resolution=280 degree; Temporal_Resolution=Daily - < Monthly].

PRECIPITABLE WATER PROFILES↗

Internship Tasks Associated With CIF Icy Regolith Excavation and Volatile Capture Under Vacuum Conditions

Understanding the surface and atmosphere of Mars is critical to current and future development of exploration systems. Dealing with the Martian regolith-the top layer of soil-remains a significant challenge, and much research is still needed. Addressing this need, the Cryogenics Test Lab and Granular Mechanics and Regolith Operations Lab at NASA's Kennedy Space Center are partnering to develop an apparatus that utilizes simulated Martian regolith in an analogous atmospheric environment to gather data about how the material behaves when exposed to water vapor. Martian surface temperatures range from 128 K (-145 C) to 308 K (35 C), and the average pressure is approximately 4.5 Torr; which presents an environment where water can potentially exist in vapor, solid or liquid form. And based on prior Mars missions such as the Phoenix Lander, it is known that water-ice exists just below the surface. This test apparatus will attempt to recreate the conditions that contributed to the Martian ice deposits by exposing a sample to water vapor at low pressure and temperature; thereby forming ice inside the simulant via diffusion. From this, we can better understand the properties and behavior of the regolith, and have more knowledge concerning its ability to store water-and subsequently, how to dig up and extract that water-which will be crucial to sample gathering when the first manned Mars mission takes place.

Thermal-Vacuum Testing↗

Spatial and temporal variability of soil temperature, moisture and surface soil properties

The overall objectives of this research were to: (l) Relate in-situ measured soil-water content and temperature profiles to remotely sensed surface soil-water and temperature conditions; to model simultaneous heat and water movement for spatially and temporally changing soil conditions; (2) Determine the spatial and temporal variability of surface soil properties affecting emissivity, reflectance, and material and energy flux across the soil surface. This will include physical, chemical, and mineralogical characteristics of primary soil components and aggregate systems; and (3) Develop surface soil classes of naturally occurring and distributed soil property assemblages and group classes to be tested with respect to water content, emissivity and reflectivity. This document is a report of studies conducted during the period funded by NASA grants. The project was designed to be conducted over a five year period. Since funding was discontinued after three years, some of the research started was not completed. Additional publications are planned whenever funding can be obtained to finalize data analysis for both the arid and humid locations.

Hajek, B. F.↗

Application of statistical inversion to ground-based microwave remote sensing of temperature and water vapor profiles

Surface-based observations of downwelling microwave thermal emission are related to temperature and humidity profiles via a standard integral equation of radiative transfer. Both in clear and in cloudy atmospheres, statistical inversion techniques are used to retrieve profiles from a data vector of brightness observations and surface meteorological constraints. For the clear case, accuracy predictions and profile retrievals are illustrated for: (1) single frequency angular scanned data; (2) multi-frequency angular scanned data; and (3) multi-frequency zenith data. For the last case predicted and achieved accuracies were compared in a recently conducted radiometric experiment. Retrievals of cloud contaminated radiometric data are elaborated.

Westwater, E. R.↗

Stream discharge and water quality data for East Fork Poplar Creek beginning 2012

This data note describes 15-min discharge and in situ water quality data at two locations along East Fork Poplar Creek in east Tennessee, USA. Data records include temperature, gauge height, water surface elevation above mean sea level, and volumetric discharge. Water quality measurements include temperature, specific conductance, pH, dissolved oxygen (percent saturation and concentration), turbidity, and less extensive fDOM data at one site. The data records begin in 2012 at one site and 2015 at the second site; monitoring at both sites is ongoing (as of 2021). The goal of this data collection is to improve understanding of watershed functions, hydrologic dynamics, and material flux. The data will contribute to site conceptual and numerical models, exposure and risk evaluation, remediation selection and design, and performance monitoring. The data are publicly available and can be accessed via unique url or DOI.

54 ENVIRONMENTAL SCIENCES↗

Scientific results of the Viking missions

The two Viking missions to Mars have been extraordinarily successful. Thirteen scientific investigations yielded information about the atmosphere and surface. Two orbiters and landers operating for several months photographed the surface extensively from 1500 kilometers and directly on the surface. Measurements were made of the atmospheric composition, the surface elemental abundance, the atmospheric water vapor, temperature of the surface, and meteorological conditions; direct tests were made for organic material and living organisms. The question of life on Mars remains unanswered. The Viking spacecraft are designed to continue the investigations for at least one Mars year.

Soffen, G. A.↗

NIMBUS-5 sounder data processing system. Part 2: Results

The Nimbus-5 spacecraft carries infrared and microwave radiometers for sensing the temperature distribution of the atmosphere. Methods developed for obtaining temperature profiles from the combined set of infrared and microwave radiation measurements are described. Algorithms used to determine (a) vertical temperature and water vapor profiles, (b) cloud height, fractional coverage, and liquid water content, (c) surface temperature, and (d) total outgoing longwave radiation flux are described. Various meteorological results obtained from the application of the Nimbus-5 sounding data processing system during 1973 and 1974 are presented.

Smith, W. L.↗

Assessing the capability of EOS sensors in measuring ocean-atmosphere moisture exchange

As part of the Science Synergism Studies to identify interdisciplinary Scientific studies, which could be addressed by the Environmental Observing System (EOS), the techniques being developed to measure ocean-atmosphere moisture exchanges using satellite sensors were evaluated. Studies required to use sensors proposed for EOS were examined. A method has been developed to compute the moisture flux using the wind speed, sea surface temperature, and preciptable water measured by satellite sensors. It relies on a statistical model which predicts surface-level humidity from precipitable water. The Scanning Multichannel Microwave Radiometer (SMMR) measures all 3 parameters and was found to be sensitive to the annual cycle and large interannual variations such as the 1982 to 1983 El Nino. There are systematic differences between geophysical parameters measured by Nimbus/SMMR and in situ measurements. After quadratic trends and crosstalks were removed from the parameters through multivariate regressions, the latent heat fluxes computed from SMMR agree with those computed from ship reports to within 30 W/sq m. The poor quality of ship reports may be the cause of a portion of this scatter. Similar results are found using SEASAT/SMMR data. When the scatterometer winds were used instead of the SMMR winds, the difference between the satellite fluxes and the ship fluxes was reduced.

Liu, W. T.↗

Implementation of the ASTER Science Standard Data Product Requirements in the EOSDIS System

The Advanced Spaceborne Thermal Emmission and Reflection Radiometer (ASTER) is designed to provide a high-resolution map of the Earth in both visible, near-infrared, and thermal spectral regions of the electromagnetic spectrum. The ASTER Science Team has developed standard data product algorithms to permit the estimation of surface radiances and reflectance values, to calculate surface temperatures both over water and land, to provide a color enhanced product with a high degree of surface discriminability, in addition to other functions. The ASTER Product Generation System (PGS) Team is implementing these requirements within the constraints of the EOSDIS system, using a rapid development methodology that emphasizes open lines of communication in a team approach using concurrent engineering techniques. This paper describes the critical elements in the development and integration of the ASTER PGS system.

ASTER↗

Application of LANDSAT satellite imagery and oceanographic data for verification of an upwelling mathematical model

The author has identified the following significant results. Data obtained during the cruise of the Cabo Frio and from LANDSAT imagery are used to discuss the characteristics of a linear model which simulates wind induced currents calculated from meteorological conditions at the time of the mission. There is a significant correspondance between the model of simulated horizontal water circulation, sea surface temperature, and surface currents observed on LANDSAT imagery. Close approximations were also observed between the simulation of vertical water movement (upwelling) and the oceanographic measurements taken along a series of points of the prevailing currents.

Dejesusparada, N.↗

Communicating Metrics of Land Surface Temperature Variability Using Multi-sensor Machine Learning

Land surface temperature (LST) is a key climate observable used to detect changes in the Earth’s surface energy budget that influence carbon and water cycles. Land surface temperature exhibits strong diurnal variability, which geostationary satellites can observe at scale thanks to their temporal resolution. Due to anthropogenic climate and land use changes, the surface energy balance has been considerably modified and may be described by changes in diurnal temperature range and extremes. Using high performance computing and datasets from the NASA Earth Exchange, we exploit co-located, co-temporal observations from low-earth orbit (LEO) and geostationary (GEO) sensors to develop a deep learning-based method for LEO-to-GEO algorithm emulation. Our model is trained to predict MODIS Terra LST from GOES-16 thermal bands and achieves validation error <2K. Application of the model to unseen times of day (observed by MODIS Aqua) and a new GEO sensor (Himawari-8) observing an unseen spatial domain, demonstrate the generalization of the deep learning model across space, time and spectra. Further, time series clustering approaches are examined with the objective of identifying key indicators of change in diurnal cycling and extremes on a continental scale. Communicating LST variability observed by geostationary satellites can have impacts in multiple disciplines, from understanding of snow, vegetation and soil dynamics, to recognizing trends in heat events relevant to human health.

Kate Duffy↗

LEO Sensor to GEO Sensor Algorithm Transfer Models for Land Surface Temperature

Land surface temperature (LST) is a key climate observable used to detect changes in the Earth’s surface energy budget that influence carbon and water cycles. Land surface temperature exhibits strong diurnal variability, which geostationary satellites can observe at scale thanks to their temporal resolution. Due to anthropogenic climate and land use changes, the surface energy balance has been considerably modified and may be described by changes in diurnal temperature range and extremes. Using high performance computing and datasets from the NASA Earth Exchange, we exploit co-located, co-temporal observations from low-earth orbit (LEO) and geostationary (GEO) sensors to develop a deep learning-based method for LEO-to-GEO algorithm emulation. Our model is trained to predict MODIS Terra LST from GOES-16 thermal bands and achieves validation error <2K. Application of the model to unseen times of day (observed by MODIS Aqua) and a new GEO sensor (Himawari-8) observing an unseen spatial domain, demonstrate the generalization of the deep learning model across space, time and spectra. Communicating diurnal LST variability observed by geostationary satellites can have impacts in multiple disciplines, from understanding of snow, vegetation and soil dynamics, to recognizing trends in heat events relevant to human health.

Kate Marie Duffy↗

An overview of the NSCAT/N-ROSS program

The NASA Scatterometer (NSCAT) to fly on the U.S. Navy Remote Ocean Sensing System (N-ROSS) mission is presented. The overall N-ROSS mission, the NSCAT flight instrument and groundbased data processing/distribution system, and NASA-supported science and verification activities are described. The N-ROSS system is designed to provide measurements of near-surface wind, ocean topography, wave height, sea-surface temperature, and atmospheric water content over the global oceans. The NSCAT is an improved version of the Seasat scatterometer. It will measure near surface vector winds.

Martin, B. D.↗

Science Data Processing for the Advanced Microwave Scanning Radiometer: Earth Observing System

The National Aeronautics and Space Administration established the framework for the Science Investigator-led Processing Systems (SIPS) to enable the Earth science data products to be produced by personnel directly associated with the instrument science team and knowledgeable of the science algorithms. One of the first instantiations implemented for NASA was the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) SIPS. The AMSR-E SIPS is a decentralized, geographically distributed ground data processing system composed of two primary components located in California and Alabama. Initial science data processing is conducted at Remote Sensing Systems (RSS) in Santa Rosa, California. RSS ingests antenna temperature orbit data sets from JAXA and converts them to calibrated, resampled, geolocated brightness temperatures. The brightness temperatures are sent to the Global Hydrology and Climate Center in Huntsville, Alabama, which generates the geophysical science data products (e.g., water vapor, sea surface temperature, sea ice extent, etc.) suitable for climate research and applications usage. These science products are subsequently sent to the National Snow and Ice Data Center Distributed Active Archive Center in Boulder, Colorado for archival and dissemination to the at-large science community. This paper describes the organization, coordination, and production techniques employed by the AMSR-E SIPS in implementing, automating and operating the distributed data processing system.

Goodman, H. Michael↗

The utility of surface temperature measurements for the remote sensing of surface soil water status

Experiments carried out on an Avondale loam soil indicated that the thermal inertia concept of soil water content detection is reasonably sound. The volumetric water contents of surface soil layers between 2 and 4 cm thick were found to be linear functions of the amplitude of the diurnal surface soil temperature wave for clear day-night periods. They were also found to be linear functions of the daily maximum value of the surface soil-air-temperature differential. Tests on three additional soils ranging from sandy loam to clay indicated that the relations determined for Avondale loam could not be accurately applied to these other soil types. When the moisture characteristic curves of each soil were used to transform water contents into pressure potentials, however, it was found that soil water pressure potential could be determined without prior knowledge of soil type, and thus its value as a potential soil water status survey tool was significantly enhanced.

Idso, S. B.↗

Surface Hydrology in Global River Basins in the Off-Line Land-Surface GEOS Assimilation (OLGA) System

Land surface hydrology for the Off-line Land-surface GEOS Analysis (OLGA) system and Goddard Earth Observing System (GEOS-1) Data Assimilation System (DAS) has been examined using a river routing model. The GEOS-1 DAS land-surface parameterization is very simple, using an energy balance prediction of surface temperature and prescribed soil water. OLGA uses near-surface atmospheric data from the GEOS-1 DAS to drive a more comprehensive parameterization of the land-surface physics. The two global systems are evaluated using a global river routing model. The river routing model uses climatologic surface runoff from each system to simulate the river discharge from global river basins, which can be compared to climatologic river discharge. Due to the soil hydrology, the OLGA system shows a general improvement in the simulation of river discharge compared to the GEOS-1 DAS. Snowmelt processes included in OLGA also have a positive effect on the annual cycle of river discharge and source runoff. Preliminary tests of a coupled land-atmosphere model indicate improvements to the hydrologic cycle compared to the uncoupled system. The river routing model has provided a useful tool in the evaluation of the GCM hydrologic cycle, and has helped quantify the influence of the more advanced land surface model.

Bosilovich, Michael G.↗