SEARCH · Search NASA

Results for “heterogeneous energy transfer”

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.

SourceResearch connectionFrom yearThrough year

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

At least 19 records

All sources NASA NTRS DOE OSTI

NASA NTRS1994

Simulating fluxes from heterogeneous land surfaces: Explicit subgrid method employing the biosphere-atmosphere transfer scheme (BATS)

A vectorized version of the biosphere-atmosphere transfer scheme (VBATS) is used to study moisture, energy, and momentum fluxes from heterogeneous land surfaces st the scale of an atmospheric model (AM) grid cells. To incorporate subgrid scale inhomogeneity, VBATS includes two important features: (1) characterization of the land surface (vegetation and soil parameters) at N subgrid points within an AM grid cell and (2) explicit distribution of climate forcing (precipitation, clouds, etc.) over the subgrid. In this study, VBATS is used in stand-alone mode to simulate a single AM grid cell and to evaluate the effects of subgrid scale vegetation and climate specification on the surface fluxes and hydrology. It is found that the partitioning of energy can be affected by up to 30%, runoff by 50%, and surface stress in excess of 60%. Distributing climate forcing over the AM grid cell increases the Bowen ratio, as a result of enhanced sensible heat flux and reduced latent heat flux. The combined effect of heterogeneous vegetation and distribution of climate is found to be dependent on the dominat vegetation class in the AM grid cell. Development of this method is part of a larger program to explore the importance of subgrid scale processes in regional and global climate simulations.

Seth, Anji↗

NASA NTRS1997

The Aggregate Description of Semi-Arid Vegetation with Precipitation-Generated Soil Moisture Heterogeneity

Meteorological measurements in the Walnut Gulch catchment in Arizona were used to synthesize a distributed, hourly-average time series of data across a 26.9 by 12.5 km area with a grid resolution of 480 m for a continuous 18-month period which included two seasons of monsoonal rainfall. Coupled surface-atmosphere model runs established the acceptability (for modelling purposes) of assuming uniformity in all meteorological variables other than rainfall. Rainfall was interpolated onto the grid from an array of 82 recording rain gauges. These meteorological data were used as forcing variables for an equivalent array of stand-alone Biosphere-Atmosphere Transfer Scheme (BATS) models to describe the evolution of soil moisture and surface energy fluxes in response to the prevalent, heterogeneous pattern of convective precipitation. The calculated area-average behaviour was compared with that given by a single aggregate BATS simulation forced with area-average meteorological data. Heterogeneous rainfall gives rise to significant but partly compensating differences in the transpiration and the intercepted rainfall components of total evaporation during rain storms. However, the calculated area-average surface energy fluxes given by the two simulations in rain-free conditions with strong heterogeneity in soil moisture were always close to identical, a result which is independent of whether default or site-specific vegetation and soil parameters were used. Because the spatial variability in soil moisture throughout the catchment has the same order of magnitude as the amount of rain failing in a typical convective storm (commonly 10% of the vegetation's root zone saturation) in a semi-arid environment, non-linearitv in the relationship between transpiration and the soil moisture available to the vegetation has limited influence on area-average surface fluxes.

White, Cary B.↗

NASA NTRS1993

Lifetimes of bacteriochlorophyll fluorescence in Rhodopseudomonas viridis and Heliobacterium chlorum at low temperatures

Fluorescence lifetimes of isolated membranes of Rhodopseudomonas viridis were measured in the temperature range of 77 K to 25 K. At room temperature, the main component of the fluorescence decay of bacteriochlorophyll (BChl) b had a time constant of 50 ps. In contrast to other purple bacteria, the emission at low temperature was spectrally homogeneous and showed essentially single lifetimes of 140 ps at 77 K and 180 ps at 25 K, with the primary electron donor in the oxidized state. Taking into account the relative fluorescence yields with open and closed reaction centers, we arrive at numbers of 125 ps and 215 ps, respectively, for open reaction centers. These numbers are significantly smaller than expected on the basis of measurements of the efficiency of charge separation, perhaps suggesting that the excitation decay in the absence of reaction centers is considerably faster at low temperature than at room temperature. At least four different spectral components with different lifetimes were observed at 25 K in the emission of Heliobacterium chlorum, a short-wavelength component of about 30 ps and three longer-wavelength components of about 100 ps, 300 ps, and 900 ps. This indicates a strong heterogeneity in the emitting pigment, BChl g-808. The component with the shortest lifetime does not appear to be affected by the redox state of the reaction center and might reflect energy transfer to BChl g species which are connected to the reaction center.

NASA Discipline Number 52-30↗

NASA NTRS1973

Effect of surface catalytic activity on stagnation heat-transfer rates.

An experiment was made to determine the effect heterogeneous catalytic surface reactions have on heat-transfer rates in highly frozen low-density stagnation-point boundary layers. Data were obtained in arc-heated facilities that were capable of producing large percentages of chemical energy frozen in a supersonic freestream. The heat-transfer rate to a silicon-dioxide surface was reduced to a minimum value of only one-third of the value obtained on relatively active nickel and platinum surfaces. This is the result of its low catalytic efficiency. Ionization energy was recovered on both the active and the inactive surfaces, indicating that this energy either was released many times faster than the recombination energy or was not controlled by the surface composition.

Anderson, L. A.↗

NASA NTRSDate not supplied

Illuminating Albedo: Using MOSAiC Data to Assess the CERES Cloud Radiative Swath (CRS) Albedo Quantification Process

Increasing surface and lower tropospheric air temperatures as a result of rising greenhouse gases are expected to be most pronounced over the Arctic. Such rapid changes alter the surface climate of the region, and impacts can be observed atmospherically, oceanographically, and biogeophysically. Accurately quantifying the impact of decreasing surface albedo on the surface energy budget with satellite observations alone is complicated by a lack of shortwave radiation during winter and seasonal/spatial heterogeneity of surface type and associated spectral albedo. NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project features the Cloud Radiative Swath (CRS) product, which builds upon the Single Scanner Footprint (SSF) product by using the NASA Langley Fu-Liou radiative transfer model to calculate a robust and high-quality array of surface and atmospheric radiative fluxes on an instantaneous, footprint-level scale. This study aims to use MOSAiC and CRS data to illuminate potential uncertainties in the CERES albedo production process, with goals of determining 1) spectral albedo under clear sky conditions when stratified by ice concentration, 2) the uncertainty associated with CERES surface albedo “history maps” when compared against observations captured during MOSAiC, and 3) the magnitude of variation between meteorological inputs compared to those from MOSAiC.

Emily Monroe↗

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 NTRS1999

Modeling of Sub-Grid Heterogeneity and its Impact on GCM Global Radiation Balance

The spatial and temporal variability of high, low, and mid-level clouds is obtained from ISCCP D1 data. Monthly mean global maps of the observed cloud variability are used to re-scale GCM prognostic cloud optical depths and radiative parameters via the Monte Carlo cloud heterogeneity parameterization that utilizes the existing plane-parallel GCM radiative transfer model to compute radiative fluxes for inhomogeneous cloud distributions. The GCM radiative fluxes at TOA and the ground surface are then compared to ERBE and GEBA results. These comparisons show that including sub-grid cloud variability in the GCM radiative model improves agreement between the GCM radiative energy budget components and observations,

Lacis, Andrew↗

NASA NTRS2010

Using Leaf Chlorophyll to Parameterize Light-Use-Efficiency Within a Thermal-Based Carbon, Water and Energy Exchange Model

Chlorophylls absorb photosynthetically active radiation and thus function as vital pigments for photosynthesis, which makes leaf chlorophyll content (C(sub ab) useful for monitoring vegetation productivity and an important indicator of the overall plant physiological condition. This study investigates the utility of integrating remotely sensed estimates of C(sub ab) into a thermal-based Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes and incorporates LUE modifications from a nominal (species-dependent) value (LUE(sub n)) in response to short term variations in environmental conditions, However LUE(sub n) may need adjustment on a daily timescale to accommodate changes in plant phenology, physiological condition and nutrient status. Day to day variations in LUE(sub n) were assessed for a heterogeneous corn crop field in Maryland, U,S.A. through model calibration with eddy covariance CO2 flux tower observations. The optimized daily LUE(sub n) values were then compared to estimates of C(sub ab) integrated from gridded maps of chlorophyll content weighted over the tower flux source area. The time continuous maps of daily C(sub ab) over the study field were generated by focusing in-situ measurements with retrievals generated with an integrated radiative transfer modeling tool (accurate to within +/-10%) using at-sensor radiances in green, red and near-infrared wavelengths acquired with an aircraft imaging system. The resultant daily changes in C(sub ab) within the tower flux source area generally correlated well with corresponding changes in daily calibrated LUE(sub n) derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C(sub ab) for delineating spatio-temporal variations in LUE(sub n). The results demonstrate the synergy between thermal infrared and shortwave reflective wavebands in producing valuable remote sensing data for operational monitoring of carbon and water fluxes.

Houlborg, Rasmus↗

NASA NTRS1999

Real-Time Assimilation of Goes-Derived Products into A Mesoscale Model and It's Impact on Short-Term (06-36hr) Forecasts from 17 October 1998 through the Present

As the parameterizations of surface energy budgets in regional models have become more complete physically, models have the potential to be much more realistic in simulations of coupling between surface radiation, hydrology, and surface energy transfer. Realizing the importance of properly specifying the surface energy budget, many institutions are using land-surface models to represent the lower boundary forcing associated with biophysical processes and soil hydrology. However, the added degrees of freedom due to inclusion of such land-surface schemes require the specification of additional parameters within the model system such as vegetative resistances, green vegetation fraction, leaf area index, soil physical and hydraulic characteristics, stream flow, runoff, and the vertical distribution of soil moisture. Spatial heterogeneity of these parameters makes correct specification problematic since measurements are not routinely available. A technique has been developed for assimilating GOES-IR skin temperature tendencies, solar insolation, and surface albedo into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. The technique has been successfully employed in a number of mesoscale models in case-study mode. We have taken the next step and developed a study to determine if assimilating these types of data into mesoscale models in real-time can improve short-term (648h) forecasts of temperature, relative humidity, and QPF on a daily basis over relatively large regions. Therefore, an operational modeling/assimilation system has been developed at the GHCC during the past summer that allows us to produce simulations out to 48 hours in a timely manor. The PSU/NCAR MM5 is used in a nested configuration with a 25 km grid covering the southeastern third of the US. The model has been on-line since 1 July 1998 and forecast products are posted on our web site. The satellite algorithms that generate data to be assimilated came on-line 17 October 1998. Quantitative assessment of the forecast quality is performed via traditional verification statistics. In addition, invaluable qualitative information is obtained through close collaboration with several NWSFO's who are using the MM5 products in real-time on a daily basis. The assimilation technique has been applied in an off-line mode since 17 October. Results based on bulk statistical verification of surface meteorology over the entire Southeastern US show that assimilating the GOES-derived land surface tendencies and solar radiation results in a significant reduction of the shelter air temperature and RH bias on a daily basis. In fact, the assimilation technique has produced improved temperature and RH forecasts for 97% of the 100 simulations performed to date. Work is currently underway to determine the sensitivity of the assimilation procedure to the availability of satellite data, length of assimilation period, model initialization, and synoptic-scale meteorological conditions. In addition, results from a detailed energy budget analysis using the Early Eta, our operational MM5, and the assimilation runs will help us to better understand the satellite assimilation the land-surface energy budge. Research during the spring-summer of 1999 will focus on the impact of the assimilation technique during the warm season where it is hypothesized that it can have a positive impact on QPF during conditions of weak synoptic-scale forcing.

Lapenta, William M.↗

NASA NTRS1993

Simulated retrieval of land surface parameters using multichannel satellite microwave radiometry

The current global change research emphasis on understanding water and energy fluxes at the land-atmosphere interface provided renewed interest in using passive microwave satellite data for land studies. Radiative transfer models of microwave emission and scattering in the soil-vegetation-atmosphere column, though still in the process of development, can be used to estimate the accuracies with which land surface parameters can be derived from satellite data. These parameters include surface soil moisture, surface temperature, vegetation water content, and atmospheric water content. A microwave radiative transfer model is used to develop linear and nonlinear versions of a multichannel retrieval algorithm to simulate retrievals of the surface and atmospheric parameters. These simulations include the effect of additive noise, and examine the effects of nonlinearities in the radiative transfer models. However, effects of spatial heterogeneity are not considered. Satellite data to which the retrieval algorithms may be applied include the SSMR and SSM/I, and in future will include the Multifrequency Imaging Microwave Radiometer (MIMR) to be launched as part of the Earth Observing System (EOS). The Scanning Multichannel Microwave Radiometer (SMMR) on the Nimbus-7 satellite provided data from 1978 to 1987 at five microwave frequencies between 6.6 and 37 GHz. The series of Special Sensor Microwave/Imager (SSM/I) instruments launched on the DMSP satellites provide data from 1987 to the present at four frequencies between 19.35 and 8.5 GHz. Spatial resolutions of the data range from approximately 12 to 120 km depending on the frequency. Examples using data from these sensors are shown to indicate the results of applying retrieval algorithms based on model simulations to real data.

Njoku, Eni G.↗

NASA NTRS1994

The influence of dose, dose-rate and particle fragmentation on cataract induction by energetic iron ions

Because activities in space necessarily involve chronic exposure to a heterogeneous charged particle radiation field it is important to assess the influence of dose-rate and the possible modulating role of heavy particle fragmentation on biological systems. Using the well-studied cataract model, mice were exposed to plateau 600 MeV/amu Fe-56 ions either as acute or fractionated exposures at total doses of 5-504 cGy. Additional groups of mice received 20, 360 and 504 cGy behind 50 mm of polyethylene, which simulates body shielding. The reference radiation consisted of Co-60 gamma radiation. The animals were examined by slit lamp biomicroscopy over their three year life spans. In accordance with our previous observations with heavy particles, the cataractogenic potential of the 600 MeV/amu Fe-56 ions was greater than for low-Linear Energy Transfer (LET) radiation and increased with decreasing dose relative to gamma rays. Fractionation of a given dose of Fe-56 ions did not reduce the cataractogenicity of the radiation compared to the acute regimen. Fragmentation of the beam in the polyethylene did not alter the cataractotoxicity of the ions, either when administered singly or in fractions.

Medvedovsky, C.↗

NASA NTRS1985

Bidirectional Reflectance Modeling of Non-homogeneous Plant Canopies

The objective of this research is to develop a 3-dimensional radiative transfer model for predicting the bidirectional reflectance distribution function (BRDF) for heterogeneous vegetation canopies. The model (named BIGAR) considers the angular distribution of leaves, leaf area index, the location and size of individual subcanopies such as widely spaced rows or trees, spectral and directional properties of leaves, multiple scattering, solar position and sky condition, and characteristics of the soil. The model relates canopy biophysical attributes to down-looking radiation measurements for nadir and off-nadir viewing angles. Therefore, inversion of this model, which is difficult but practical should provide surface biophysical pattern; a fundamental goal of remote sensing. Such a model also will help to evaluate atmospheric limitations to satellite remote sensing by providing a good surface boundary condition for many different kinds of canopies. Furthermore, this model can relate estimates of nadir reflectance, which is approximated by most satellites, to hemispherical reflectance, which is necessary in the energy budget of vegetated surfaces.

Norman, J. M.↗

NASA NTRS2022

An Evaluation of the Liquid Cloud Droplet Effective Radius Derived from MODIS, Airborne Remote Sensing, and in Situ Measurements from CAMP2Ex

The cloud drop effective radius (Re) of the drop size distribution derived from passive satellite sensors is a key variable used in climate research. Validation of these satellite products has often taken place under stratiform cloud conditions that favor the assumption of cloud horizontal homogeneity used by the retrieval techniques. However, many studies have noted concerns with respect to significant biases in retrieved Re arising from cloud heterogeneity, for example, in cumulus cloud fields. Here, we examine data collected during the 2019 “Cloud, Aerosol and Monsoon Processes Philippines Experiment” (CAMP2Ex), which, in part, targeted the objective of providing the first detailed evaluation of Re retrieved across multiple platforms and techniques in a cumulus and congestus cloud region. Our evaluation consists of cross-comparisons of Re between the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, the Research Scanning Polarimeter (RSP) onboard the NASA P-3 aircraft, and in situ measurements from both the NASA P-3 and Learjet aircraft that are all taken in close spatiotemporal proximity to the same cloud fields. A particular advantage of our approach lies in the capability of the RSP to retrieve Re using a bi-spectral MODIS approach and a polarimetric approach, which allows for the evaluation of bi-spectral and polarimetric Re retrievals from an airborne perspective using the same samples. Averaged over all P-3 flight segments examined here for warm clouds, the RSP polarimetric method, the in situ method, and the bias-adjusted MODIS method of Fu et al. (2019) show a comparable median (mean ± standard deviation) for the Re samples of 9.6 (10.2 ± 4.0) µm, 11.0 (13.6 ± 11.3) µm, and 10.4 (10.8 ± 3.8) µm, respectively. These values are far lower than the values of 15.1 (16.2 ± 5.5) µm and 17.2 (17.7 ± 5.7) µm from the bi-spectral retrievals of RSP and MODIS, respectively. Similar results are observed when Re is segregated by cloud-top height and in detailed case studies. The clouds sampled during CAMP2Ex consist of mostly small (mean transect length ∼ 1.4 km) and low clouds (mean cloud-top height ∼ 1 km), which had more numerous small clouds than the trade wind cumuli sampled in past field campaigns such as Rain in Shallow Cumulus over the Ocean (RICO) and the Indian Ocean Experiment (INDOEX). The overestimates of Re from the RSP bi-spectral technique compared with the polarimetric technique increased as cloud size and cloud optical depth decreased. Drizzle, cloud-top bumpiness, and solar zenith angle, however, are not closely correlated with the overestimate of bi-spectral Re. For shallow clouds that dominated the liquid cloud cover for the CAMP2Ex region and period, we show that 3-D radiative transfer and cloud heterogeneity, particularly for the optically thin and small clouds, appear to be the leading cause of the large positive biases in bi-spectral retrievals. Because this bias varies with the underlying structure of the cloud field, caution continues to be warranted in studies that use bi-spectral Re retrievals in cumulus cloud fields.

Cloud microphysics↗

NASA NTRS1998

Real Time Land-Surface Hydrologic Modeling Over Continental US

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

Houser, Paul R.↗

NASA NTRS1998

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model: Overview - Part 1

Knowledge of the amount of water in the soil is of great importance to many earth science disciplines. Soil moisture is a key variable in controlling the exchange of water and energy between the land surface and the atmosphere. Thus, soil moisture information is valuable in a wide range of applications including weather and climate, runoff potential and flood control, early warning of droughts, irrigation, crop yield forecasting, soil erosion, reservoir management, geotechnical engineering, and water quality. Despite the importance of soil moisture information, widespread and continuous measurements of soil moisture are not possible today. Although many earth surface conditions can be measured from satellites, we still cannot adequately measure soil moisture from space. Research in soil moisture remote sensing began in the mid 1970s shortly after the surge in satellite development. Recent advances in remote sensing have shown that soil moisture can be measured, at least qualitatively, by several methods. Quantitative measurements of moisture in the soil surface layer have been most successful using both passive and active microwave remote sensing, although complications arise from surface roughness and vegetation type and density. Early attempts to measure soil moisture from space-borne microwave instruments were hindered by what is now considered sub-optimal wavelengths (shorter than 5 cm) and the coarse spatial resolution of the measurements. L-band frequencies between 1 and 3 GHz (10-30 cm) have been deemed optimal for detection of soil moisture in the upper few centimeters of soil. The Electronically Steered Thinned Array Radiometer (ESTAR), an aircraft-based instrument operating a 1,4 GHz, has shown great promise for soil moisture determination. Initiatives are underway to develop a similar instrument for space. Existing space-borne synthetic aperture radars (SARS) operating at C- and L-band have also shown some potential to detect surface wetness. The advantage of radar is its much higher resolution than passive microwave systems, but it is currently hampered by surface roughness effects and the lack of a good algorithm based on a single frequency and single polarization. In addition, its repeat frequency is generally low (about 40 days). In the meantime, two new radiometers offer some hope for remote sensing of soil moisture from space. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in November 1997, possesses a 10.65 GHz channel and the Advanced Microwave Scanning Radiometer (AMSR) on both the ADEOS-11 and Earth Observing System AM-1 platforms to be launched in 1999 possesses a 6.9 GHz channel. Aside from issues about interference from vegetation, the coarse resolution of these data will provide considerable challenges pertaining to their application. The resolution of TMI is about 45 km and that of AMSR is about 70 km. These resolutions are grossly inconsistent with the scale of soil moisture processes and the spatial variability of factors that control soil moisture. Scale disparities such as these are forcing us to rethink how we assimilate data of various scales in hydrologic models. Of particular interest is how to assimilate soil moisture data by reconciling the scale disparity between what we can expect from present and future remote sensing measurements of soil moisture and modeling soil moisture processes. It is because of this disparity between the resolution of space-based sensors and the scale of data needed for capturing the spatial variability of soil moisture and related properties that remote sensing of soil moisture has not met with more widespread success. Within a single footprint of current sensors at the wavelengths optimal for this application, in most cases there is enormous heterogeneity in soil moisture created by differences in landcover, soils and topography, as well as variability in antecedent precipitation. It is difficult to interpret the meaning of 'mean' soil moisture under such conditions and even more difficult to apply such a value. Because of the non-linear relationships between near-surface soil moisture and other variables of interest, such as surface energy fluxes and runoff, mean soil moisture has little applicability at such large scales. It is for these reasons that the use of remote sensing in conjunction with a hydrologic model appears to be of benefit in capturing the complete spatial and temporal structure of soil moisture. This paper is Part I of a four-part series describing a method for intermittently assimilating remotely-sensed soil moisture information to improve performance of a distributed land surface hydrology model. The method, summarized in section II, involves the following components, each of which is detailed in the indicated section of the paper or subsequent papers in this series: Forward radiative transfer model methods (section II and Part IV); Use of a Kalman filter to assimilate remotely-sensed soil moisture estimates with the model profile (section II and Part IV); Application of a soil hydrology model to capture the continuous evolution of the soil moisture profile within and below the root zone (section III); Statistical aggregation techniques (section IV and Part II); Disaggregation techniques using a neural network approach (section IV and Part III); and Maximum likelihood and Bayesian algorithms for inversely solving for the soil moisture profile in the upper few cm (Part IV).

Crosson, William L.↗

NASA NTRS1995

The origin of the solar wind

The high speed solar wind, which is associated with coronal holes and unipolar interplanetary magnetic field, has now been observed in situ beyond 0.3 a.u. and at latitudes up to 80 degrees. Its important characteristics are that it is remarkably steady in terms of flow properties and composition and that the ions, especially minor species, are favored in terms of heating and acceleration. We have proposed that the high speed wind, with its associated coronal holes, forms the basic mode of solar wind flow. In contrast, the low speed wind is inherently non-stationary, filamentary and not in equilibrium with conditions at the coronal base. It is presumably the result of continual reconfigurations of the force-free magnetic field in the low-latitude closed corona which allow trapped plasma to drain away along transiently open flux tubes. Observations of high speed solar wind close to its source are hampered by the essential heterogeneity of the corona, even at sunspot minimum. In particular it is difficult to determine more than limits to the density, temperature and wave amplitude near the coronal base as a result of contamination from fore- and back-ground plasma. We interpret the observations as indicating that the high speed solar wind originates in the chromospheric network, covering only about 1% of the surface of the sun, where the magnetic field is complex and not unipolar. As a result of small-scale reconnection events in this 'furnace', Alfven waves are generated with a flat spectrum covering the approximate range 10 kHz to 10 Hz. The plasma is likely to be produced as a result of downwards thermal conduction and possibly photoionization at the top of the low density chromospheric interface to the furnace, thus controlling the mass flux in the wind. The immediate source of free (magnetic) energy is in the form of granule-sized loops which are continually carried into the network from the sides. The resulting wave spectrum is such that energy can be efficiently transferred to the ions within a few solar radii of the base of the corona, favoring heavy species and creating stable, fast solar wind.

Axford, W. I.↗

NASA NTRS2011

Dynamic Simulation of Human Thermoregulation and Heat Transfer for Spaceflight Applications

Models of human thermoregulation and heat transfer date from the early 1970s and have been developed for applications ranging from evaluating thermal comfort in spacecraft and aircraft cabin environments to predicting heat stress during EVAs. Most lumped or compartment models represent the body as an assemblage cylindrical and spherical elements which may be subdivided into layers to describe tissue heterogeneity. Many existing models are of limited usefulness in asymmetric thermal environments, such as may be encountered during an EVA. Conventional whole-body clothing models also limit the ability to describe local surface thermal and evaporation effects in sufficient detail. A further limitation is that models based on a standard man model are not readily scalable to represent large or small subjects. This work describes development of a new human thermal model derived from the 41-node man model. Each segment is divided into four concentric, constant thickness cylinders made up of a central core surrounded by muscle, fat, and skin, respectively. These cylinders are connected by the flow of blood from a central blood pool to each part. The central blood pool is updated at each time step, based on a whole-body energy balance. Results show the model simulates core and surface temperature histories, sweat evaporation and metabolic rates which generally are consistent with controlled exposures of human subjects. Scaling rules are developed to enable simulation of small and large subjects (5th percentile and 95th percentile). Future refinements will include a clothing model that addresses local surface insulation and permeation effects and developing control equations to describe thermoregulatory effects such as may occur with prolonged weightlessness or with aging.

Miller, Thomas R.↗

NASA NTRS2011

Long-Term Evolution of the Aerosol Debris Cloud Produced by the 2009 Impact on Jupiter

We present a study of the long-term evolution of the cloud of aerosols produced in the atmosphere of Jupiter by the impact of an object on 19 July 2009. The work is based on images obtained during 5 months from the impact to 31 December 2009 taken in visible continuum wavelengths and from 20 July 2009 to 28 May 2010 taken in near-infrared deep hydrogen-methane absorption bands at 2.1-2.3 micron. The impact cloud expanded zonally from approximately 5000 km (July 19) to 225,000 km (29 October, about 180 deg in longitude), remaining meridionally localized within a latitude band from 53.5 deg S to 61.5 deg S planetographic latitude. During the first two months after its formation the site showed heterogeneous structure with 500-1000 km sized embedded spots. Later the reflectivity of the debris field became more homogeneous due to clump mergers. The cloud was mainly dispersed in longitude by the dominant zonal winds and their meridional shear, during the initial stages, localized motions may have been induced by thermal perturbation caused by the impact's energy deposition. The tracking of individual spots within the impact cloud shows that the westward jet at 56.5 deg S latitude increases its eastward velocity with altitude above the tropopause by 5- 10 m/s. The corresponding vertical wind shear is low, about 1 m/s per scale height in agreement with previous thermal wind estimations. We found evidence for discrete localized meridional motions with speeds of 1-2 m/s. Two numerical models are used to simulate the observed cloud dispersion. One is a pure advection of the aerosols by the winds and their shears. The other uses the EPIC code, a nonlinear calculation of the evolution of the potential vorticity field generated by a heat pulse that simulates the impact. Both models reproduce the observed global structure of the cloud and the dominant zonal dispersion of the aerosols, but not the details of the cloud morphology. The reflectivity of the impact cloud decreased exponentially with a characteristic timescale of 15 days; we can explain this behavior with a radiative transfer model of the cloud optical depth coupled to an advection model of the cloud dispersion by the wind shears. The expected sedimentation time in the stratosphere (altitude levels 5-100 mbar) for the small aerosol particles forming the cloud is 45-200 days, thus aerosols were removed vertically over the long term following their zonal dispersion. No evidence of the cloud was detected 10 months after the impact.

Sanchez-Lavega, A.↗