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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Precipitation Measurements from Space: The Global Precipitation Measurement Mission

Water is fundamental to the life on Earth and its phase transition between the gaseous, liquid, and solid states dominates the behavior of the weather/climate/ecological system. Precipitation, which converts atmospheric water vapor into rain and snow, is central to the global water cycle. It regulates the global energy balance through interactions with clouds and water vapor (the primary greenhouse gas), and also shapes global winds and dynamic transport through latent heat release. Surface precipitation affects soil moisture, ocean salinity, and land hydrology, thus linking fast atmospheric processes to the slower components of the climate system. Precipitation is also the primary source of freshwater in the world, which is facing an emerging freshwater crisis in many regions. Accurate and timely knowledge of global precipitation is essential for understanding the behavior of the global water cycle, improving freshwater management, and advancing predictive capabilities of high-impact weather events such as hurricanes, floods, droughts, and landslides. With limited rainfall networks on land and the impracticality of making extensive rainfall measurements over oceans, a comprehensive description of the space and time variability of global precipitation can only be achieved from the vantage point of space. This presentation will examine current capabilities in space-borne rainfall measurements, highlight scientific and practical benefits derived from these observations to date, and provide an overview of the multi-national Global Precipitation Measurement (GPM) Mission scheduled to bc launched in the early next decade.

Hou, Arthur Y.↗
NASA NTRS1974

Environmental microbiology as related to planetary quarantine

Continued experimental work related to dry heat resistance of microorganisms. One phase of this research has been concerned with the viability and dry heat resistance of indigenous microflora associated with small soil particles. The second part of this report is an analysis of the present status of dry heat sterilization. An attempt is made to integrate results for both laboratory grown spores and spores in soil.

Pflug, I. J.↗
NASA NTRS1991

Analysis of normalized difference and surface temperature observations over southeastern Australia

Relations between radiative surface temperature (TR) and visible and near-IR reflectances expressed as the normalized difference (ND) from a Landsat Thematic Mapper scene are analyzed to examine the heat balance of agriculture and native evergreen forests in southeastern Australia. Factors determining the residual scatter about, and slope of, the TR/ND relationships were analyzed using a coupled two-layer soil-vegetation model of the surface heat balance. Inverse linear relationships were observed between TR and ND for agriculture, but not for forests. This was due to a wide range of ND and TR values in agricultural regions caused by wide variations in fractional vegetation cover.

Smith, R. C. G.↗
DOE OSTI2021

Changes in precipitation and air temperature contribute comparably to permafrost degradation in a warmer climate

Abstract Surface energy budgets of high-latitude permafrost systems are poorly represented in Earth system models (ESMs), yet permafrost is rapidly degrading and these dynamics are critical to future carbon-climate feedback predictions. A potentially important factor in permafrost degradation neglected so far by ESMs is heat transfer from precipitation, although increases in soil temperature and thaw depth have been observed following increases in precipitation. Using observations and a mechanistic ecosystem model, we show here that increases in precipitation hasten active layer development beyond that caused by surface air warming across the North Slope of Alaska (NSA) under recent and 21st century climate (RCP8.5). Modeled active layer depth (ALD) in simulations that allow precipitation heat transfer agreed very well with observations from 28 Circumpolar Active Layer Monitoring sites (R 2 = 0.63; RMSE = 10 cm). Simulations that ignored precipitation heat transfer resulted in lower spatially-averaged soil temperatures and a 39 cm shallower ALD by 2100 across the NSA. The results from our sensitivity analysis show that projected increases in 21st century precipitation deepen the active layer by enhancing precipitation heat transfer and ground thermal conductivity, suggesting that precipitation is as important an environmental control on permafrost degradation as surface air temperature. We conclude that ESMs that do not account for precipitation heat transfer likely underestimate ALD rates of change, and thus likely predict biased ecosystem responses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Kinetic and temperature sensitivity properties of soil exoenzymes through the soil profile down to one-meter depth at a temperate coniferous forest (Blodgett, CA)

This dataset contains data on kinetic and temperature sensitivity parameters of the exoenzymes β-glucosidase (BG), leucine/leucyl aminopeptidase (LAP) and acid phosphatase (AP) across a soil profile down to 90 cm depth at Blodgett forest, CA, USA. These data were generated to determine if kinetic and thermal properties of microbial exoenzymes involved in organic matter decomposition varied with soil depth, following variation in soil properties and microbial communities, as part of the study: Alves et al. (2021). Kinetic Properties of Microbial Exoenzymes Vary with Soil Depth but Have Similar Temperature Sensitivities Through the Soil Profile. Frontiers in Microbiology 12:3618. https://doi.org/10.3389/fmicb.2021.735282. This research was performed within the framework of the TES Belowground Biogeochemistry SFA project, in particular association with a long-term field warming experiment of the whole soil profile at Blodgett forest. Samples for this work were collected from locations representative of the field experimental plots. Potential enzyme activity rates were measured using laboratory fluorometric assays with soils collected at 0-10, 10-20, 30-40, 50-60, 60-70 and 80-90 cm deep in biological triplicates (i.e., three soil cores collected at different representative locations). Assays with each soil were conducted over a gradient of eight substrate concentrations per enzyme, and incubated at 4, 10, 16, 25, 35 or 50°C. Enzyme Michaelis-Menten kinetics were modeled over the eight substrate concentrations at each temperature, and the temperature sensitivity of the kinetic parameters was modeled over the six temperatures using linear Arrhenius/Q10 and non-linear Macromolecular Rate Theory (MMRT) models. The dataset includes the fully processed enzyme activity rate data used to model Michaelis-Menten kinetics, calculated kinetic and temperature sensitivity parameters, and basic soil and microbial biomass chemistry for each sample. All data is provided for each individual biological replicate, and kinetic and temperature sensitivity parameters are also provided as means of the biological replicates. The dataset also includes all raw measurement data and code used to parse, combine and perform the analyses described by Alves et al. (2021). For file descriptions, see the file-level metadata files: “enzymes_dataProcessed_flmd.xlsx” (processed data); “enzymes_dataRaw_flmd.xlsx” (compressed raw data and metadata); and “enzymes_code_flmd.xlsx” (compressed code). The experimental design, list of parameters measured, soil and microbial biomass chemistry data, and means of biological replicates for kinetic and temperature sensitivity parameters are also provided as human-readable tables in file “enzymeTraits_design_results_tables.xlsx”.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Numerical experiments related to the summer 1980 U.S. heat wave

The NASA Goddard Laboratory for Atmospheres fourth-order GCM was used in a series of medium-range numerical forecast experiments in order to improve understanding of the severe summer 1980 heat wave over the U.S. The results show that the derived soil moisture anomalies in the summer of 1980 contributed positively to the model's simulation of the heat wave maintenance, and suggest that once a region of reduced soil moisture is established, it tends to persist and maintain warmer and drier conditions. The lower soil moisture values resulted in reduced evaporation, higher ground temperatures, increased sensible heat flux from ground to air, higher surface air temperature, lower sea-level pressure, and higher 500-mb height. The effects of North Pacific sea-surface-temperature anomalies were mostly opposite to those of the soil-moisture anomalies: enhanced northerly flow of cooler drier air, increased evaporation, lower ground and air temperature, higher sea level pressure, and lower 500 mb heights over the Great Plains.

Wolfson, N.↗
NASA NTRS2007

Estimating the Soil Temperature Profile from a Single Depth Observation: A Simple Empirical Heatflow Solution

Two data sets of experimental field observations with a range of meteorological conditions are used to investigate the possibility of modeling near-surface soil temperature profiles in a bare soil. It is shown that commonly used heat flow methods that assume a constant ground heat flux can not be used to model the extreme variations in temperature that occur near the surface. This paper proposes a simple approach for modeling the surface soil temperature profiles from a single depth observation. This approach consists of two parts: 1) modeling an instantaneous ground flux profile based on net radiation and the ground heat flux at 5cm depth; 2) using this ground heat flux profile to extrapolate a single temperature observation to a continuous near surface temperature profile. The new model is validated with an independent data set from a different soil and under a range of meteorological conditions.

Holmes, Thomas↗
DOE OSTI2025

CO2 Profiling System for CO2 Storage (a1-level)

The Southern Great Plains (SGP) carbon dioxide flux (CO2FLUX) measurement systems provide half-hour average fluxes of CO2, H2O (latent heat), sensible heat, and momentum. The systems use the eddy covariance technique, which computes the fluxes from the vertical wind speed in combination with the concentrations of CO2 and H2O, temperature, and horizontal wind speed, respectively. A 3D sonic anemometer obtains the wind components and the temperature, while an infrared gas analyzer measures CO2 and H2O. A sub-system also measures half-hour averages of radiation, meteorological, and soil measurements.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Evaluation Analysis of NASA SMAP L3 and L4 and SPoRT-LIS Soil Moisture Data in the United States

Soil moisture has a critical role in the development, frequency and persistence of climatic and hydrologic extremes such as drought, heat wave and flooding events. In situ soil moisture data are uneven and sparse in time and space. This highlights the need to utilize other soil moisture sources to fill this spatiotemporal gap. The goal of this study is to validate one satellite-based and two model-based soil moisture datasets with in situ data across the United States. Soil moisture information from the Soil Moisture Active Passive (SMAP) enhanced level 3 (L3) (SMAP L3) and modeled level 4 (L4) (SMAP L4) data at 9-km resolution and Short-term Prediction Research and Transition-Land Information System (SPoRT-LIS) modeled at 3-km resolution were selected for evaluation. SPoRT-LIS is a near real-time, high resolution operational land analysis data. Ground-based data were obtained from the North American Soil Moisture Database (NASMD) for 362 stations. Seven statistical indicators including anomaly, Spearman, and Pearson correlation coefficients, the systematic error (Bias), root mean square error (RMSE), unbiased root mean square error (ubRMSE), and normalized standard deviation (SDV) were used to evaluate the satellite- and model-derived soil moisture data. In addition, the triple collocation (TC) error model was used to measure the error among SMAP L4, SPoRT-LIS and ground-based data. This study assesses which satellite or modeled dataset is most appropriate for specific times and locations to use as a surrogate for in situ observations. Temporal and spatial analysis demonstrated that, overall, SMAP L4 performed better than SMAP L3 and SPoRT-LIS. Strong agreement was observed between SMAP L4 and in situ observations (ρ = 0.53, Bias = −0.006) in all seasons and most regions with various land covers, especially in winter and in the central regions of the United States. For croplands, SMAP L4 presented the best agreement with in situ data, analyzing all period (ρ = 0.60) and non-winter period (ρ = 0.61) separately.

Tavakol, Ameneh↗
DOE OSTI2023

Optimization of the number and locations of the calibration stations needed to monitor soil moisture using distributed temperature sensing systems: A proof-of-concept study

The single-probe heat-pulse (SPHP) technique combined with the Fiber-optic Distributed Temperature Sensing (DTS) technology can offer novel high-resolution measurements of soil moisture (θ) over spatial scales ranging from several centimeters to several kilometers. However, the key limitation of this method is in obtaining the calibration relationship between θ and soil thermal conductivity (λ) across a specific field. In a previous study, a new methodology using a Gaussian processes model was presented to account for the spatial variability in the λ-θ relationship. The model aggregated θ measurements from soil moisture sensors scattered over the SPHP transect with the corresponding DTS λ measurements at their locations. In this study, a novel methodology is tested to optimize the number and locations of soil moisture sensors required to account for the spatial variability of the λ - θ relationship to achieve higher accuracy from the SPHP technique. The proposed methodology utilizes hierarchical clustering to analyze the information contained in the spatial structure of the SPHP measurements as the soil dries from a nearly-saturated condition. The proposed methodology was tested using data from a field in Oklahoma. Monte-Carlo simulation was performed to validate the performance of the proposed methodology. The predictions obtained from the proposed methodology resulted in θ measurements accuracy comparable to those obtained from the 10% best Monte-Carlo iterations of randomly assigned soil moisture locations. Further, this study demonstrates that the proposed methodology is more efficient than the traditional practice of randomly spreading calibration soil moisture sensors along the SPHP transect.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Heating effects on jack pine pyrogenic organic matter properties from a pyrocosm study in 2022

This dataset contains data associated with the preprint “Fire removes preexisting pyrogenic organic matter from the ecosystem through the mechanisms of both direct combustion and increasing mineralizability” (Luo et al., 2025b), which is the complementary study to the published paper “Reburning pyrogenic organic matter: a laboratory method for dosing dynamic heat fluxes from above” (Luo et al., 2025a). We designed a full-factorial experiment with different burial depths of jack pine (Pinus banksiana Lamb) pyrogenic organic matter (PyOM) (Surface, 1 cm, and 5 cm) and different heat-flux profiles (High, Low, and Control) to examine how subsequent fires affect the properties of preexisting PyOM. We measured total carbon (C), pH, dissolved organic carbon (DOC), dissolved inorganic carbon (DIC), and mineralized C (as CO₂-C, from a 12-week incubation).We found that high heat flux and/or surface placement resulted in substantial direct C losses through combustion. Intermediate heat exposure produced both combustion losses and increases in DOC and mineralizability, which may have complex long-term implications: an increased dissolved fraction of PyOM may promote downward transport into mineral soils and potentially contribute to deeper, longer-term C storage, but it may also make PyOM more susceptible to microbial decomposition. Under the lowest heat flux and deepest burial, most PyOM was retained, and changes in DOC and C mineralization were minimal. Finally, PyOM pH, an important chemical property, decreased under low-temperature heating but increased under higher temperatures.We uploaded pH data for all samples (“pH_of_all_samples.csv”); pH and temperature-related data (peak temperature and degree hours) for samples in High and Low heat-flux treatments (“pH_vs_peakT_and_degree_hours_only_for_heated_samples.csv”); total C data (“CN_pct_C_stock_C_loss_in_samples.csv”); DOC and DIC data (“doc_dic.csv”); and mineralized C (CO₂-C) data (“CO2-C_all_original.csv”). Additional details can be found in the Methods & Sampling section.All datasets uploaded to ESS-DIVE are clearly labeled, cleaned, and include both raw and derived data, ready for reuse in other analyses. All analysis code and raw datasets are also available on GitHub: https://github.com/MengmengLuo/Fire-removes-preexisting-pyrogenic-organic-matter-from-the-ecosystem.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

A scheme for computing surface fluxes from mean flow observations

A computational method for estimating turbulent surface stress, sensible heat flux, and humidity flux from mean velocity, temperature, and humidity at a single height in the atmospheric surface layer is presented. The method is based on coupling a Monin-Obukhov similarity profile to a 'force-restore' formulation for the evolution of surface soil temperature to yield the local values of shear stress, heat flux, and surface temperature. In addition to reference-level mean flow properties, the parameters required to implement this method are the thermal heat capacity of the soil, the surface aerodynamic roughness, latitude, solar declination, surface albedo, surface emissivity, and atmospheric transmissivity. Sample calculations are presented for (1) constant atmospheric forcing at the reference level, and (2) variable atmospheric forcing corresponding to Kahle's (1977) measurements of windspeed, air temperature, and radiometer soil surface temperature under dry vegetatively sparse conditions in the Mohave Desert, Calif.

Hoffert, M. I.↗
NASA NTRS1988

Use of LANDSAT images of vegetation cover to estimate effective hydraulic properties of soils

The estimation of the spatially variable surface moisture and heat fluxes of natural, semivegetated landscapes is difficult due to the highly random nature of the vegetation (e.g., plant species, density, and stress) and the soil (e.g., moisture content, and soil hydraulic conductivity). The solution to that problem lies, in part, in the use of satellite remotely sensed data, and in the preparation of those data in terms of the physical properties of the plant and soil. The work was focused on the development and testing of a stochastic geometric canopy-soil reflectance model, which can be applied to the physically-based interpretation of LANDSAT images. The model conceptualizes the landscape as a stochastic surface with bulk plant and soil reflective properties. The model is particularly suited for regional scale investigations where the quantification of the bulk landscape properties, such as fractional vegetation cover, is important on a pixel by pixel basis. A summary of the theoretical analysis and the preliminary testing of the model with actual aerial radiometric data is provided.

Eagleson, Peter S.↗
NASA NTRS1992

An annual model of SSM/I radiobrightness for dry soil

An annual model is presented of the temperature structure within a homogeneous, dry soil halfspace that is subject to both diurnal and annual insolation, radiant heating from the atmosphere, sensible heat exchange with the atmosphere, and radiant cooling. The thermal constitutive properties of the soil are assumed to be constant so that the heat flow equation can be solved analytically. For computational economy, a variable time interval Laplace transform method is developed to predict the temperature.

Liou, Yuei-An↗
NASA NTRS1981

HCMM detection of high soil moisture areas

It is noted that one objective of NASA's Heat Capacity Mapping Mission (HCMM) is to evaluate the feasibility of using HCMM data to assess soil moisture effects by observing temperatures near the maximum and minimum of the diurnal temperature cycle. The satellite, which carries a two-channel radiometer (0.5-1.1 and 10.5-12.5 microns) gathers data at 1:30 P.M. and 2:30 A.M. local time at midlatitudes, with a repeat cycle of 5 or 16 days depending on latitude. The spatial resolutions are 0.5 x 0.5 km at nadir for the visible channel and 0.6 x 0.6 km at nadir for the thermal infrared channel. An example is presented here of HCMM detection of a region of high soil moisture.

Heilman, J. L.↗
NASA NTRS2013

Northern Eurasian Heat Waves and Droughts

This article reviews our understanding of the characteristics and causes of northern Eurasian summertime heat waves and droughts. Additional insights into the nature of temperature and precipitation variability in Eurasia on monthly to decadal time scales and into the causes and predictability of the most extreme events are gained from the latest generation of reanalyses and from supplemental simulations with the NASA GEOS-5 AGCM. Key new results are: 1) the identification of the important role of summertime stationary Rossby waves in the development of the leading patterns of monthly Eurasian surface temperature and precipitation variability (including the development of extreme events such as the 2010 Russian heat wave), 2) an assessment of the mean temperature and precipitation changes that have occurred over northern Eurasia in the last three decades and their connections to decadal variability and global trends in SST, and 3) the quantification (via a case study) of the predictability of the most extreme simulated heat wave/drought events, with some focus on the role of soil moisture in the development and maintenance of such events. A literature survey indicates a general consensus that the future holds an enhanced probability of heat waves across northern Eurasia, while there is less agreement regarding future drought, reflecting a greater uncertainty in soil moisture and precipitation projections. Substantial uncertainties remain in our understanding of heat waves and drought, including the nature of the interactions between the short-term atmospheric variability associated with such extremes and the longer-term variability and trends associated with soil moisture feedbacks, SST anomalies, and an overall warming world.

SST↗
NASA NTRS2009

Impact of Land Surface Heterogeneity on Mesoscale Atmospheric Dispersion

Prior numerical modelling studies show that atmospheric dispersion is sensitive to surface heterogeneities, but past studies do not consider the impact of a realistic distribution of surface heterogeneities on mesoscale atmospheric dispersion. While these focussed on dispersion in the convective boundary layer, the present work also considers dispersion in the nocturnal boundary layer and above. Using a Lagrangian particle dispersion model (LPDM) coupled to the Eulerian Regional Atmospheric Modeling System (RAMS), the impact of topographic, vegetation, and soil moisture heterogeneities on daytime and nighttime atmospheric dispersion is examined. In addition, the sensitivity to the use of Moderate Resolution Imaging Spectroradiometer (MODIS)-derived spatial distributions of vegetation characteristics on atmospheric dispersion is also studied. The impact of vegetation and terrain heterogeneities on atmospheric dispersion is strongly modulated by soil moisture, with the nature of dispersion switching from non-Gaussian to near- Gaussian behaviour for wetter soils (fraction of saturation soil moisture content exceeding 40%). For drier soil moisture conditions, vegetation heterogeneity produces differential heating and the formation of mesoscale circulation patterns that are primarily responsible for non-Gaussian dispersion patterns. Nighttime dispersion is very sensitive to topographic, vegetation, soil moisture, and soil type heterogeneity and is distinctly non-Gaussian for heterogeneous land-surface conditions. Sensitivity studies show that soil type and vegetation heterogeneities have the most dramatic impact on atmospheric dispersion. To provide more skillful dispersion calculations, we recommend the utilisation of satellite-derived vegetation characteristics coupled with data assimilation techniques that constrain soil-vegetation-atmosphere transfer (SVAT) models to generate realistic spatial distributions of surface energy fluxes.

Wu, Yuling↗
NASA NTRS2012

Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the SPoRT-MODIS GVF dataset on a land surface model (LSM) apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. In the West, higher latent heat fluxes prevailed, which enhanced the rates of evapotranspiration and soil moisture depletion in the LSM. By late Summer and Autumn, both the average sensible and latent heat fluxes increased in the West as a result of the more rapid soil drying and higher coverage of GVF. The impacts of the SPoRT GVF dataset on NWP was also examined for a single severe weather case study using the Weather Research and Forecasting (WRF) model. Two separate coupled LIS/WRF model simulations were made for the 17 July 2010 severe weather event in the Upper Midwest using the NCEP and SPoRT GVFs, with all other model parameters remaining the same. Based on the sensitivity results, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). Portions of the Northern Plains states experienced substantial increases in convective available potential energy as a result of the higher SPoRT/MODIS GVFs. These differences produced subtle yet quantifiable differences in the simulated convective precipitation systems for this event.

Bell, Jordan R.↗