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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Airborne Spectral Measurements of Surface-Atmosphere Anisotropy for Arctic Sea Ice and Tundra

Angular distributions of spectral reflectance for four common arctic surfaces: snow-covered sea ice, melt-season sea ice, snow-covered tundra, and tundra shortly after snowmelt were measured using an aircraft based, high angular resolution (1-degree) multispectral radiometer. Results indicate bidirectional reflectance is higher for snow-covered sea ice than melt-season sea ice at all wavelengths between 0.47 and 2.3 pm, with the difference increasing with wavelength. Bidirectional reflectance of snow-covered tundra is higher than for snow-free tundra for measurements less than 1.64 pm, with the difference decreasing with wavelength. Bidirectional reflectance patterns of all measured surfaces show maximum reflectance in the forward scattering direction of the principal plane, with identifiable specular reflection for the melt-season sea ice and snow-free tundra cases. The snow-free tundra had the most significant backscatter, and the melt-season sea ice the least. For sea ice, bidirectional reflectance changes due to snowmelt were more significant than differences among the different types of melt-season sea ice. Also the spectral-hemispherical (plane) albedo of each measured arctic surface was computed. Comparing measured nadir reflectance to albedo for sea ice and snow-covered tundra shows albedo underestimated 5-40%, with the largest bias at wavelengths beyond 1 pm. For snow-free tundra, nadir reflectance underestimates plane albedo by about 30-50%.

Arnold, G. Thomas↗
NASA NTRS2012

Observational Evidence of EHP Effects on the Melting of Snowpack over the Tibetan Plateau

Observational evidences are presented showing that the Indo-Gangetic Plain (IGP) regions, bounded by the high altitude Himalayan mountains, are subject to heavy loading of absorbing aerosols, i.e., black carbon and dust, which can lead to widespread enhancement warming over the Tibetan Plateau and accelerated snowmelt in the western Tibetan Plateau (WTP) and Himalayas. The two pre-monsoon seasons of 2004 and 2005 were strikingly contrasting in terms of the aerosol loading over IGP. The warming of the TP in 2004 relative to 2005 was widespread, covering most of the WTP and Himalayas. This warming is closely linked to patterns of the snow melt. Consistent with the Elevated Heat Pump hypothesis, we find that increased loading of absorbing aerosols over IGP in the pre-monsoon season is associated with increased heating of the upper troposphere by dynamical feedback induced by aerosol heating, and enhances the rate of snowmelt over Himalayas and the WTP in April-May. Composite analysis with more contrasting years also shows that the heating of the troposphere by elevated dust and black carbon aerosols in the boreal spring can lead to widespread enhanced land-atmosphere warming, and accelerated snow melt in the Himalayas and Tibetan Plateau.

Kim, Maeng-Ki↗
NASA NTRS2012

Distributed Assimilation of Satellite-based Snow Extent for Improving Simulated Streamflow in Mountainous, Dense Forests: An Example Over the DMIP2 Western Basins

Snow cover area affects snowmelt, soil moisture, evapotranspiration, and ultimately streamflow. For the Distributed Model Intercomparison Project - Phase 2 Western basins, we assimilate satellite-based fractional snow cover area (fSCA) from the Moderate Resolution Imaging Spectroradiometer, or MODIS, into the National Weather Service (NWS) SNOW-17 model. This model is coupled with the NWS Sacramento Heat Transfer (SAC-HT) model inside the National Aeronautics and Space Administration's (NASA) Land Information System. SNOW-17 computes fSCA from snow water equivalent (SWE) values using an areal depletion curve. Using a direct insertion, we assimilate fSCAs in two fully distributed ways: 1) we update the curve by attempting SWE preservation, and 2) we reconstruct SWEs using the curve. The preceding are refinements of an existing simple, conceptually-guided NWS algorithm. Satellite fSCA over dense forests inadequately accounts for below-canopy snow, degrading simulated streamflow upon assimilation during snowmelt. Accordingly, we implement a below-canopy allowance during assimilation. This simplistic allowance and direct insertion are found to be inadequate for improving calibrated results, still degrading them as mentioned above. However, for streamflow volume for the uncalibrated runs, we obtain: (1) substantial to major improvements (64-81 %) as a percentage of the control run residuals (or distance from observations), and (2) minor improvements (16-22 %) as a percentage of observed values. We highlight the need for detailed representations of canopy-snow optical radiative transfer processes in mountainous, dense forest regions if assimilation-based improvements are to be seen in calibrated runs over these areas.

Yatheendradas, Soni↗
NASA NTRS1996

Subpixel Snow-Covered-Area and Snow Grain Size from Mixture Analysis with Aviris Data

Snow-covered-area (SCA) and snow grain size are crucial inputs to hydrologic and climatologic modeling of alpine and other seasonally snow-covered regions. SCA is necessary to parameterize energy budget calculations in climate models, to determine in which regions point snowmelt models are to be run for distributed snowmelt modeling efforts and to provide a basis from which estimates of snow water equivalent (SWE) may be made.

hydrologic↗
NASA NTRS2019

Possible Impacts of Snow Darkening Effects on the Hydrological Cycle over Western Eurasia and East Asia

In this paper, we investigated the possible impact of snow darkening effect (SDE) by light-absorbing aerosols on the regional changes of the hydrological cycle over Eurasia using the NASA GEOS-5 Model with aerosol tracers and a state-of-the-art snow darkening module, the Goddard SnoW Impurity Module (GOSWIM) for the land surface. Two sets of ten-member ensemble experiments for 10 years were carried out forced by prescribed sea surface temperature (2002–2011) with different atmospheric initial conditions, with and without SDE, respectively. Results show that SDE can exert a significant regional influence in partitioning the contributions of evaporative and advective processes on the hydrological cycle, during spring and summer season. Over western Eurasia, SDE-induced rainfall increase during early spring can be largely explained by the increased evaporation from snowmelt. Rainfall, however, decreases in early summer due to the reduced evaporation as well as moisture divergence and atmospheric subsidence associated with the development of an anomalous mid- to upper-tropospheric anticyclonic circulation. On the other hand, in the East Asian monsoon region, moisture advection from the adjacent ocean is a main contributor to rainfall increase in the melting season. A warmer land-surface caused by earlier snowmelt and subsequent drying further increases moisture transport and convergence significantly enhancing rainfall over the region. Our findings suggest that the SDE may play an important role in leading to hotter and drier summers over western Eurasia, through coupled land-atmosphere interaction, while enhancing East Asian summer monsoonal precipitation via enhanced land-ocean thermal contrast and moisture transport due to the SDE-induced warmer Eurasian continent.

snow darkening effect↗
NASA NTRS2020

Evaluating impacts of snow, surface water, soil and vegetation on empirical vegetation and snow indices for the Utqiaġvik tundra ecosystem in Alaska with the LVS3 model

Satellite observations for the Arctic and boreal region may contain information of vegetation, soil, snow, snowmelt, and/or other surface water bodies. We investigated the impacts of vegetation, soil, snow and surface water on empirical vegetation/snow indices on a tundra ecosystem area located around Utqiaġvik (formerly Barrow) of Alaska with the Moderate Resolution Imaging Spectrometer (MODIS) images in 2001–2014. Empirical vegetation indices, such as normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), the index of near infrared of vegetation (NIRv), and modified EVI (EVI2), have been used to monitor vegetation. Normalized difference snow index (NDSI) has been widely applied to monitor snow. The vegetation cover fraction (VGCF), the soil cover fraction (SOILCF), the snow cover fraction (SNOWCF), the surface water body cover fraction (WaterBodyCF), the fractional absorption of photosynthetically active radiation (PAR) by vegetation chlorophyll (fAPARchl), the fractional absorption of PAR by non-chlorophyll components of the vegetation (fAPARnon-chl), and the fractional absorption of PAR by the entire canopy (fAPARcanopy) are retrieved with the MODIS images and a coupled Leaf-Vegetation-Soil-Snow-Surface water body radiative transfer model, LVS3. The vegetation indices (NDVI, EVI, EVI2 and NIRv) differ from VGCF, fAPARchl, fAPARnon-chl, and fAPARcanopy. In addition to vegetation, we find that soil, snow and surface water also have impacts on vegetation indices NDVI, EVI (EVI2), and NIRv. Presence of snow makes lower the observed values of NDVI, EVI2 and NIRv. After snowmelt is gone, the vegetation indices (NDVI, EVI, EVI2 and NIRv) linearly decrease with SOILCF and WaterBodyCF, and WaterBodyCF has stronger impacts on these vegetation indices than SOILCF. The relationship between EVI and snow is complicated. NDSI non-linearly increases with SNOWCF, but linearly increases with sum of SNOWCF and WaterBodyCF (sum = 0.5893 × NDSI +0.4342, R2 = 0.976). NDSI linearly decreases with VGCF, and the relationship between NDSI and SOILCF is complex. Retrievals of VGCF, fAPARchl, fAPARnon-chl and fAPARcanopy with the LVS3 model provide alternatives for vegetation monitoring and ecological modeling.

Qingyuan Zhang↗
NASA NTRS2021

A Dusty Atmospheric River Brings Floods to the Middle East

Torrential rainfall and rapid snowmelt in April 2017 caused deadly floods in northwestern Iran. An atmospheric river (AR), propagating across the Middle East and North Africa, was found responsible for this extreme event. The snowmelt was triggered by precipitation and warm advection associated with the AR. Total satellite-based rainfall for April 2017 was moderately below normal, suggesting that a heavy flood can happen during dry years. The AR was fed by moisture from the Mediterranean and Red Seas. Despite its adverse societal consequences, this event was beneficial to the recovery of the desiccating Lake Urmia. The impacts of this AR were not limited to flooding; it also facilitated dust transport to the region. This distinct characteristic of the ARs in the Middle East is attributed to major mineral dust sources located along their pathways. This event was reasonably predicted at 7-day lead time, crucially important for successful early warning systems.

Atmospheric river↗
NASA NTRS2021

Groundwater Recharge Estimated by Land Surface Models: An Evaluation in the Conterminous U.S.

Estimating diffuse recharge of precipitation is fundamental to assessing groundwater sustainability. Diffuse recharge is also the process through which climate and climate change directly affect groundwater. In this study, we evaluated diffuse recharge over the conterminous U.S. simulated by a suite of land surface models (LSMs) that were forced using a common set of meteorological input data. Simulated annual recharge exhibited spatial patterns that were similar among the LSMs, with the highest values in the eastern U.S. and Pacific Northwest. However, the magnitudes of annual recharge varied significantly among the models and were associated with differences in simulated ET, runoff and snow. Evaluation against two independent datasets did not answer the question of whether the ensemble mean performs the best, due to inconsistency between those datasets. The amplitude and timing of seasonal maximum recharge differed among the models, influenced strongly by model physics governing deep soil moisture drainage rates and, in cold regions, snowmelt. Evaluation using in situ soil moisture observations suggested that true recharge peaks 1-3 months later than simulated recharge, indicating systematic biases in simulating deep soil moisture. However, recharge from lateral flows and through preferential flows cannot be inferred from soil moisture data, and the seasonal cycle of simulated groundwater storage actually compared well with in situ groundwater observations. Long-term trends in recharge were not consistently correlated with either precipitation trends or temperature trends. This study highlights the need to employ dynamic flow models in LSMs, among other improvements, to enable more accurate simulation of recharge.

snowmelt↗
NASA NTRS2021

The sensitivity of runoff generation to spatial snowpack uniformity in an alpine watershed: Green Lakes Valley, Niwot Ridge Long-Term Ecological Research station

Seasonal water storage in high-elevation alpine catchments are critical sources of water for mountainous regions like the western U.S. The spatial distribution of snow in these topographically complex catchments is primarily governed by orography, solar radiation, and wind redistribution. While the effect of solar shading is relatively consistent from year-to-year, the redistribution of snow due to wind is more variable–capable of producing snowpacks that have varying degrees of uniformity across these hydrologically-important catchments. A reasonable hypothesis is that a warmer climate will cause snowfall to become more dense (i.e. wetter and heavier), possibly leading to less wind redistribution and thus produce a more uniformly distributed snowpack across the landscape. In this study, we investigate the role of increasingly uniform spatial snowpack distributions on streamflow generation in the Green Lakes Valley Niwot Ridge Long Term Ecological Research station, within the headwaters of the Boulder Creek watershed in Colorado. A set of idealized hydrologic simulation experiments driven by reconstructed snowpacks spanning 2001–2014 show that more a more uniform spatial snowpack distribution leads to an earlier melt-out of31 days on average and tends to produce less total streamflow, with maximum decreases as large as 7.5%. Isolating the role of snowpack heterogeneity from melt-season precipitation, we find that snowpack uniformity reduces total streamflow by as much as 13.2%. Reductions in streamflow are largely explained by greater expo-sure to solar radiation in the uniformly distributed case relative to a more heterogeneous snowpack, with this exposure driving shifts towards earlier snowmelt and changes in soil water storage. Overall, we find that the runoff efficiency from shallower snowpacks is more sensitive to the effects of uniformity than deeper snowpacks, which has potential implications for a warming climate where shallower snowpacks and enhanced sensitivities may be present.

Alpine catchment↗
NASA NTRS1972

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers

The author has identified the following significant results. Preliminary results on the feasibility of mapping snow cover extent have been obtained from a limited number of ERTS-1 images of mountains in Alaska, British Columbia, and Washington. The snowline on land can be readily distinguished, except in heavy forest where such distinction appears to be virtually impossible. The snowline on very large glaciers can also be distinguished remarkably easily, leading to a convenient way to measure glacier accumulation area ratios or equilibrium line altitude. Monitoring of large surging glaciers appears to be possible, but only through observation of a change in area and/or medial moraine extent. Under certain conditions, ERTS-1 imagery appears to have high potential for mapping snow cover in mountainous areas. Distinction between snow and clouds appears to require use of the human eye, but in a cloud-free scene the snow cover is sufficiently distinct to allow use of automated techniques. This technique may prove very useful as an aid in the monitoring of the snowpack water resource and the prediction of summer snowmelt runoff volume.

Meier, M. F.↗
NASA NTRS1972

Applications of remote sensing to stream discharge predictions

A feasibility study has been initiated on the use of remote earth observations for augmenting stream discharge prediction for the design and/or operation of major reservoir systems, pumping systems and irrigation systems. The near-term objectives are the interpolation of sparsely instrumented precipitation surveillance networks and the direct measurement of water loss by evaporation. The first steps of the study covered a survey of existing reservoir systems, stream discharge prediction methods, gage networks and the development of a self-adaptive variation of the Kentucky Watershed model, SNOPSET, that includes snowmelt. As a result of these studies, a special three channel scanner is being built for a small aircraft, which should provide snow, temperature and water vapor maps for the spatial and temporal interpolation of stream gages.

Krause, F. R.↗
NASA NTRS1973

Break-up characteristics of Chena River Basin

The author has identified the following significant results. Results from snowmelt model were obtained showing the decreasing changes in snow depth for four elevational ranges in the Chena River Basin. This model is based on the energy balance of the snowpack and the results are shown on attached figures. Also, the measured hydrographs for two stations on the Chena River are shown. The next phase of the study will be to analyze the model using both ERTS-1 imagery and measured field values.

Carlson, R. F.↗
NASA NTRS1973

Satellite geological and geophysical remote sensing of Iceland

The author has identified the following significant results. Under a binational, multidisciplinary experiment ERTS-1 imagery is being used to measure and map dynamic natural phenomena in Iceland. A few of the initial results from the project are: (1) a large variety of geological and volcanic features can be studied, particularly on imagery acquired at low sun angle ( 10 deg), which have not been previously recognized; (2) under optimum snow cover conditions, geothermal areas can be discerned by their snowmelt pattern or by warm spring discharge into frozen lakes; (3) a variety of map types at scale of 1:1,000,000 and 1:500,000, can be compiled, made more accurate, or updated (changes in coastline, glaciers, lakes, etc.); (4) the persistence of snow in the highland areas, during the summer months, has important ramifications to rangeland management; (5) false color composites (MSS) permitted the mapping of four types of vegetation; forested, reclaimed, cultivated areas and grasslands, and the mapping of the seasonal change of the vegetation, all of high value to rangeland management when complete, repetitive coverage of Iceland becomes a reality with an operational satellite; and (6) the volcanic eruption on Heimaey was recorded.

Williams, R. S., Jr.↗
NASA NTRS1973

Evaluation of ERTS data for certain hydrological uses

The author has identified the following significant results. A snow-extent map of the American River basin was prepared for 27 May 1973 from MSS band 4 imagery. The basin was 14% snow covered. NOAA-2 visible band imagery was used to determine date of disappearance of snow in the basin: 15 July 1973. A snowmelt curve comparing ERTS-1 and NOAA-2 snow-extent maps is provided. ERTS-1 data were superior in quality and outstanding in cartographic fidelity and were found to be an excellent control or calibration for the distorted and coarse (1 km) imagery from NOAA-2's VHRR which, however, is available on a daily basis.

Wiesnet, D. R.↗
NASA NTRS1974

Satellite geological and geophysical remote sensing of Iceland

The author has identified the following significant results. ERTS-1 imagery provides sufficient resolution to discern two effects of geothermal activity at the Namafjall geothermal area: snowmelt anomalies and delineation of altered ground. The fallout pattern of tephra from Hekla's 1970 volcanic eruption can be mapped where sufficient depth of deposition destroyed the vegetation. Lava flows from the volcanic eruptions at Askja and Hekla can be delineated. Low sun-angle imagery of snow-covered terrain has permitted the mapping of new structural and volcanic features beneath the icecaps. Coastline changes on the islands of Surtsey and Heimaey can be mapped. Variations of sediment plumes from glacial rivers on the south coast give a qualitative indication of seasonal changes in melting rates of glaciers. ERTS-1 imagery has been shown to be especially amenable to portrayal of changing glaciological phenomena: surging glaciers, collapse features in icecaps caused by subglacial volcanic (?) and geothermal activity and resulting jokulhlaups, and variations in size of glacier-margin lakes. A fifth vegetation class has now been added: lichen-covered bedrock. The high latitude permits more precise analysis of landforms, vegetation distribution, occurrence of snow cover, glaciers, and geologic structure.

Williams, R. S., Jr.↗
NASA NTRS1974

Snow-extent mapping and lake ice studies using ERTS-1 MSS together with NOAA-2 VHRR

Five snow extent maps of the 5,601 sq km American River Basin were prepared using a Zoom Transfer Scope from ERTS-1 MSS band 4 imagery. The maps were generally completed within one hour. A snowmelt curve based on ERTS-1 imagery was used as a calibration standard or comparison for maps prepared from NOAA-2 VHRR imagery in the same manner. Cost comparisons with U-2 derived imagery indicate that ERTS-1 snow mapping of the basins is six times faster. Conservative estimates of comparable aircraft snow survey flights yields a cost figure 200 times that of the ERTS-1 snow map. Snow mapping attempts in the Lake Ontario Basin demonstrated that ERTS-1 is not well suited to large basins. Optimum size of basins for ERTS studies is believed to range from about 250 sq km to 30,000 sq km. The value of the ERTS-1 MSS for Great Lake ice evaluation was proved during the past winter on Lake Erie. Not only were ice features and types of ice identified, but melting ice was detected through the combined use of band 5 and band 7. Ice movement (direction and speed) was mapped by examining imagery from two successive days.

Wiesnet, D. R.↗
NASA NTRS1974

A study of remote sensing as applied to regional and small watersheds. Volume 2: Supporting technical details

The Stanford Watershed Model, the Kentucky Watershed Model and OPSET program, and the NASA-IBM system for simulation and analysis of watersheds are described in terms of their applications to the study of remote sensing of water resources. Specific calibration processes and input and output parameters that are instrumental in the simulations are explained for the following kinds of data: (1) hourly precipitation data; (2) daily discharge data; (3) flood hydrographs; (4) temperature and evaporation data; and (5) snowmelt data arrays. The Sensitivity Analysis Task, which provides a method for evaluation of any of the separate simulation runs in the form of performance indices, is also reported. The method is defined and a summary of results is given which indicates the values obtained in the simulation runs performed for Town Creek, Alabama; Alamosa Creek, Colorado; and Pearl River, Louisiana. The results are shown in tabular and plot graph form. For Vol. 1, see N74-27813.

Source record↗
NASA NTRS1973

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers

The author has identified the following significant results. A new procedure to determine snowcovered areas has been devised. Aside from problems in heavily forested areas this method shows promise in predicting snowmelt runoff from mountain areas and will also assist in energy balance modeling of large snowfields. Snowcover results compare favorably with measurements made by high altitude aircraft photography. Changes in snowcover in areas as small as 3 x 5 km can be determined from ERTS-1 images by both optical and electronic methods. Snowcover changes determined by these two methods in the experimental South Cascade Glacier Basin were verified by field mapping. Image enahancement techniques on ERTS-1 images of large Alaskan glaciers (the Hubbard, Yentna, and Kahiltna) have given new insights into the large-scale structures and flow dynamics of these potentially hazardous glaciers. The Hubbard Glacier, in particular, is one which poses a threat to man and should be monitored for future changes.

Meier, M. F.↗