Search NASA⌕ Search

SEARCH · Search NASA

Results for “Soil heating”

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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

Environmental microbiology as related to planetary quarantine

The mechanistic basis of the synergetic effect of combined heat and radiation on microbial destruction was analyzed and results show that radiation intensity, temperature, and relative humidity are the determining factors. Dry heat resistance evaluation for selected bacterial spore crops indicates that different strains of Bacillus stearothermophilus demonstrate marked differences in resistance. Preliminary work to determine the effects of storage time, suspending medium, storage temperature and spore crop cleaning procedures on dry heat survival characteristics of Bacillus subtilis var. Niger, and dry heat resistance of natural microflora in soil particles is also reported.

Pflug, I. J.↗
NASA NTRS1974

Automated microbial metabolism laboratory

The labeled release concept was advanced to accommodate a post- Viking mission designed to extend the search, to confirm the presence of, and to characterize any Martian life found, and to obtain preliminary information on control of the life detected. The advanced labeled release concept utilizes four test chambers, each of which contains either an active or heat sterilized sample of the Martian soil. A variety of C-14 labeled organic substrates can be added sequentially to each soil sample and the resulting evolved radioactive gas monitored. The concept can also test effects of various inhibitors and environmental parameters on the experimental response. The current Viking '75 labeled release hardware is readily adaptable to the advanced labeled release concept.

Source record↗
NASA NTRS1984

Land-surface influences on weather and climate

Land-surface influences on weather and climate are reviewed. The interrelationship of vegetation, evapotranspiration, atmospheric circulation, and climate is discussed. Global precipitation, soil moisture, the seasonal water cycle, heat transfer, and atmospheric temperature are among the parameters considered in the context of a general biosphere model.

Baer, F.↗
NASA NTRS1985

The evolution of CO2 on Mars

At the surface, the atmosphere of Mars contains approximately 95.3 percent CO2 by volume. At the Viking Lander 1 (VL1) site, the total surface pressure varied with the season between about 6.89 and 8.94 mbar. Questions related to the observed CO2 pressure on Mars are explored. Several published estimates of the total amount of CO2 outgassed over the history of Mars, varying between 140 and 3000 mbar, are shown in a table. It is pointed out that the study of likely reservoirs for outgassed CO2 has focused mainly on the polar caps and regolith. Constraints on the formation of transitory pockets of moist soil are discussed, taking into account heat requirements, supply of water, and constraints related to pressure. Attention is also given to chemical considerations, implications for the current status of CO2 reservoirs, and scenarios for the evolution of CO2 pressure.

Kahn, R.↗
NASA NTRS1986

Release of noble gases and nitrogen from grain-surface sites in lunar ilmenite by closed-system oxidation

Noble gases and nitrogen were extracted from a 100 to 150 microns ilmenite separate from lunar soil 71501 by closed system stepped heating in approx. 10 torr O2 at 300 C, 400 C, 500 C, 600 C and 630 C, followed by stepped pyrolysis at ten temperatures between 680 C and approx. 1500 C. The five oxidation steps together liberated approx. 65% of the total He-4, 45% of the Ne-20, 23% of the N-14 and Ar-36, 12% of the Kr-84 and 8% of the Xe-132 in the sample; Ne-20/Ar-36 and Ne-20/Ne-22 ratios agree with the solar wind composition experiment, and Kr-84/Ar-36 and Xe-132/Ar-36 are within approx. 10% of Cameron's estimates for the sun and solar wind. The remaining gases, released above 630 C by pyrolysis, are strongly fractionated with respect to the SWC-Cameron solar wind elemental composition. Large concentrations of fractionated noble gases in grain interiors, their virtual absence in the relatively unfractionated surface gas reservoir, and the high N/noble gas ratio all imply that most of the solar wind noble gases initially implanted in grain surfaces are eventually lost by diffusion. Loss limits can be estimated by considering two given scenarios. It is concluded tat approx. 70 to 97% or more of the Ar implanted in 71501 ilmenite grains has diffusively escaped.

Frick, U.↗
NASA NTRS1992

A model of the CO2 exchanges between biosphere and atmosphere in the tundra

A physical model of the soil thermal regime in a permafrost terrain has been developed and validated with soil temperature measurements at Barrow, Alaska. The model calculates daily soil temperatures as a function of depth and average moisture contents of the organic and mineral layers using a set of five climatic variables, i.e., air temperature, precipitation, cloudiness, wind speed, and relative humidity. The model is not only designed to study the impact of climate change on the soil temperature and moisture regime, but also to provide the input to a decomposition and net primary production model. In this context, it is well known that CO2 exchanges between the terrestrial biosphere and the atmosphere are driven by soil temperature through decomposition of soil organic matter and root respiration. However, in tundra ecosystems, net CO2 exchange is extremely sensitive to soil moisture content; therefore it is necessary to predict variations in soil moisture in order to assess the impact of climate change on carbon fluxes. To this end, the present model includes the representation of the soil moisture response to changes in climatic conditions. The results presented in the foregoing demonstrate that large errors in soil temperature and permafrost depth estimates arise from neglecting the dependence of the soil thermal regime on soil moisture contents. Permafrost terrain is an example of a situation where soil moisture and temperature are particularly interrelated: drainage conditions improve when the depth of the permafrost increases; a decrease in soil moisture content leads to a decrease in the latent heat required for the phase transition so that the heat penetrates faster and deeper, and the maximum depth of thaw increases; and as excepted, soil thermal coefficients increase with moisture.

Labgaa, Rachid R.↗
NASA NTRS1998

Surface Emissivity Derived From Multispectral Satellite Data

Surface emissivity is critical for remote sensing of surface skin temperature and infrared cloud properties when the observed radiance is influenced by the surface radiation. It is also necessary to correctly compute the longwave flux from a surface at a given skin temperature. Surface emissivity is difficult to determine because skin temperature is an ill-defined parameter. The surface-emitted radiation may arise from a range of surface depths depending on many factors including soil moisture, vegetation, surface porosity, and heat capacity. Emissivity can be measured in the laboratory for pure surfaces. Transfer of laboratory measurements to actual Earth surfaces, however, is fraught with uncertainties because of their complex nature. This paper describes a new empirical approach for estimating surface skin temperature from a combination of brightness temperatures measured at different infrared wavelengths with satellite imagers. The method uses data from the new Geostationary Operational Environmental Satellite (GOES) imager to determine multispectral emissivities from the skin temperatures derived over the ARM Southern Great Plains domain.

Minnis, P.↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗
NASA NTRS2005

A comparison of soil moisture sensors for space flight applications

Plants will be an important part of future long-term space missions. Automated plant growth systems require accurate and reliable methods of monitoring soil moisture levels. There are a number of different methods to accomplish this task. This study evaluated sensors using the capacitance method (ECH2O), the heat-pulse method (TMAS), and tensiometers, compared to soil water loss measured gravimetrically in a side-by-side test. The experiment monitored evaporative losses from substrate compartments filled with 1- to 2-mm baked calcinated clay media. The ECH2O data correlated well with the gravimetric measurements, but over a limited range of soil moisture. The averaged TMAS sensor data overstated soil moisture content levels. The tensiometer data appeared to track evaporative losses in the 0.5- to 2.5-kPa range of matric potential that corresponds to the water content needed to grow plants. This small range is characteristic of large particle media, and thus high-resolution tensiometers are required to distinguish changing moisture contents in this range.

NASA Center KSC↗
DOE OSTI2021

Quantifying the Impacts of Land Surface Modeling on Hub-Height Wind Speed under Different Soil Conditions

We investigate the impact of three land surface models (LSMs) on hub-height wind speed under three different soil regimes (dry, wet, and frozen) to understand and improve the physics of wind energy forecasts using the Weather Research and Forecasting (WRF) model. A six-day representative period is selected for each soil condition. The simulated wind speed, surface energy budget and soil properties are compared with the observations collected from the second Wind Forecast Improvement Project (WFIP2). For the selected cases, our simulation results suggest that, the impact of LSMs on hub-height wind speed are sensitive to the soil states but not so much to the choice of LSM. The simulated hub-height wind speed is in much better agreement with the observations for the dry soil case than the wet and frozen soil cases. Over the dry soil, there is a strong physical connection between the land surface and hub-height wind speed through near-surface turbulent mixing. Over the wet soil, the simulated hub-height wind speed is less impacted by land surface due to weaker surface fluxes and more dominated by large-scale synoptic disturbances. Over the frozen soil, the land surface model seems to have limited impact on hub-height wind speed variability due to the decoupling of the land surface with the overlying atmosphere. Two main sources of modeling uncertainties are proposed. The first are the insufficient model physics representing the surface energy budget, especially the ground heat flux, and the second are the inaccurate initial soil states such as soil temperature and soil moisture.

Xia, Geng↗
NASA NTRS1984

Soil temperature extrema recovery rates after precipitation cooling

From a one dimensional view of temperature alone variations at the Earth's surface manifest themselves in two cyclic patterns of diurnal and annual periods, due principally to the effects of diurnal and seasonal changes in solar heating as well as gains and losses of available moisture. Beside these two well known cyclic patterns, a third cycle has been identified which occurs in values of diurnal maxima and minima soil temperature extrema at 10 cm depth usually over a mesoscale period of roughly 3 to 14 days. This mesoscale period cycle starts with precipitation cooling of soil and is followed by a power curve temperature recovery. The temperature recovery clearly depends on solar heating of the soil with an increased soil moisture content from precipitation combined with evaporation cooling at soil temperatures lowered by precipitation cooling, but is quite regular and universal for vastly different geographical locations, and soil types and structures. The regularity of the power curve recovery allows a predictive model approach over the recovery period. Multivariable linear regression models alloy predictions of both the power of the temperature recovery curve as well as the total temperature recovery amplitude of the mesoscale temperature recovery, from data available one day after the temperature recovery begins.

Welker, J. E.↗
DOE OSTI2023

Robust inference of ecosystem soil water stress from eddy covariance data

Eddy covariance data are invaluable for determining ecosystem water use strategies under soil water stress. However, existing stress inference methods require numerous subjective data processing and model specification assumptions whose effect on the inferred soil water stress signal is rarely quantified. These uncertainties may confound the stress inference and the generalization of ecosystem water use strategies across multiple sites and studies. In this research, we quantify the sensitivity of soil water stress signals inferred from eddy covariance data to the prevailing data and modeling assumptions (i.e., their robustness) to compile a comprehensive list of sites with robust soil water stress signals and assess the performance of current stress inference methods. To accomplish this, we identify the most prevalent assumptions from the literature and perform a digital factorial experiment to extract probability distributions of plausible soil water stress signals and model performance at 151 FLUXNET2015 and AmeriFlux-FLUXNET sites. Here, we develop a new framework that summarizes these probability distributions to classify and rank the robustness of each site’s soil water stress signal, which we display with a user-friendly heat map. We estimate that only 5%–36% of sites exhibit a robust soil water stress signal due to deficient model performance and poorly constrained ecosystem water use parameters. We also find that the lack of robustness is site-specific, which undermines grouping stress signals by broad ecosystem categories or comparing results across studies with differing assumptions. Lastly, existing stress inference methods appear better suited for eddy covariance sites with grass/annual vegetation. Our findings call for more careful and consistent inference of ecosystem water stress from eddy covariance data.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Reconciling the MOLA, TES, and Neutron Observations of the North Polar CO2 Mass Budget on Mars

There are now three independent observations of the CO2 polar cap mass budget of Mars' north polar cap. The first is based elevation changes detected by the Mars Orbiter Laser Altimeter (MOLA) on the Mars Global Surveyor (MGS). The second is based on MGS Thermal Emission Spectrometer (TES) broadband observations of the solar and infrared radiation fields at the top of the atmosphere. The third is based on neutron counts measured by the neutron spectrometer (NS) on Odyssey. The TES data are based on an energy balance. The net radiative loss (gain) in a column is balanced by latent heating due condensation (sublimation) of CO2. In calculating the mass budget, the other main energy sources, atmospheric heat transport and subsurface conduction, were neglected. At the pole, atmospheric heat transport is indeed a small term. However, subsurface heat conduction can be significant because at the North Pole water ice, which has a high thermal conductivity compared to bare soil, is a dominant component of the subsurface. Thus, heat conducted down into the ice during summer will slowly bleed back out during fall and winter reducing the amount of CO2 that condenses on the pole. We have taken a first cut at quantifying this effect by fitting a curve to Paige's estimates of the conducted energy flux in his analysis of Viking IRTM data.

Haberle, R. M.↗
NASA NTRS1993

Comparison between the land surface response of the ECMWF model and the FIFE-1987 data

An averaged time series for the surface data for the 15 x 15 km FIFE site was prepared for the summer of 1987. Comparisons with 48-hr forecasts from the ECMWF model for extended periods in July, August, and October 1987 identified model errors in the incoming SW radiation in clear skies, the ground heat flux, the formulation of surface evaporation, the soil-moisture model, and the entrainment at boundary-layer top. The model clear-sky SW flux is too high at the surface by 5-10 percent. The ground heat flux is too large by a factor of 2 to 3 because of the large thermal capacity of the first soil layer (which is 7 cm thick), and a time truncation error. The surface evaporation was near zero in October 1987, rather than of order 70 W/sq m at noon. The surface evaporation falls too rapidly after rainfall, with a time-scale of a few days rather than the 7-10 d (or more) of the observations. On time-scales of more than a few days the specified 'climate layer' soil moisture, rather than the storage of precipitation, has a large control on the evapotranspiration. The boundary-layer-top entrainment is too low. This results in a moist bias in the boundary-layer mixing ratio of order 2 g/Kg in forecasts from an experimental analysis with nearly realistic surface fluxes; this because there is insufficient downward mixing of dry air.

Betts, Alan K.↗
NASA NTRS2011

Simulated Seasonal Spatio-Temporal Patterns of Soil Moisture, Temperature, and Net Radiation in a Deciduous Forest

The temperature and moisture regimes in a forest are key components in the forest ecosystem dynamics. Observations and studies indicate that the internal temperature distribution and moisture content of the tree influence not only growth and development, but onset and cessation of cambial activity [1], resistance to insect predation[2], and even affect the population dynamics of the insects [3]. Moreover, temperature directly affects the uptake and metabolism of population from the soil into the tree tissue [4]. Additional studies show that soil and atmospheric temperatures are significant parameters that limit the growth of trees and impose treeline elevation limitation [5]. Directional thermal infrared radiance effects have long been observed in natural backgrounds [6]. In earlier work, we illustrated the use of physically-based models to simulate directional effects in thermal imaging [7-8]. In this paper, we illustrated the use of physically-based models to simulate directional effects in thermal, and net radiation in a adeciduous forest using our recently developed three-dimensional, macro-scale computational tool that simulates the heat and mass transfer interaction in a soil-root-stem systems (SRSS). The SRSS model includes the coupling of existing heat and mass transport tools to stimulate the diurnal internal and external temperatures, internal fluid flow and moisture distribution, and heat flow in the system.

Ballard, Jerrell R., Jr.↗
NASA NTRS2016

A Review of Recent Advances in Research on Extreme Heat Events

Reviewing recent literature, we report that changes in extreme heat event characteristics such as magnitude, frequency, and duration are highly sensitive to changes in mean global-scale warming. Numerous studies have detected significant changes in the observed occurrence of extreme heat events, irrespective of how such events are defined. Further, a number of these studies have attributed present-day changes in the risk of individual heat events and the documented global-scale increase in such events to anthropogenic-driven warming. Advances in process-based studies of heat events have focused on the proximate land-atmosphere interactions through soil moisture anomalies, and changes in occurrence of the underlying atmospheric circulation associated with heat events in the mid-latitudes. While evidence for a number of hypotheses remains limited, climate change nevertheless points to tail risks of possible changes in heat extremes that could exceed estimates generated from model outputs of mean temperature. We also explore risks associated with compound extreme events and nonlinear impacts associated with extreme heat.

Heat events↗
NASA NTRS1991

Nonlinear dynamics of global atmospheric and Earth-system processes

General Circulation Model (GCM) studies of the atmospheric response to change boundary conditions are discussed. Results are reported on an extensive series of numerical studies based on the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM) general circulation model. In these studies the authors determined the response to systematic changes in atmospheric CO2 ranging from 100 to 1000 ppm; to changes in the prescribed sea surface temperature (SST) in the Gulf of Mexico, such as occurred during the deglaciation phase of the last ice age; to changes in soil moisture over North America; and to changes in sea ice extent in the Southern Hemisphere. Study results show that the response of surface temperature and other variables is nearly logarithmic, with lower levels of CO2 implying greater sensitivity of the atmospheric state to changes in CO2. It was found that the surface temperature of the Gulf of Mexico exerts considerable control over the storm track and behavior of storm systems over the North Atlantic through its influence on evaporation and the source of latent heat. It was found that reductions in soil moisture can play a significant role in amplifying and maintaining North American drought, particularly when a negative soil moisture anomaly prevails late in the spring.

Saltzman, Barry↗