SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
We examine the sensitivity of ERS-1 C-band synthetic aperture radar (SAR) backscatter to springtime snow and vegetation thaw dynamics for boreal forest stands within the BOREAS Southern Study Area (SSA) in Canada during the 1994 winter-spring thaw transition.
Preliminary analyses of the POLSCAT data acquired from the CLPX-II in winter 2006-2007 are described in this paper. The data showed the response of the Ku-band radarechoes to snowpack changes for various types of background vegetation. We observed about 0.2 to 0.4 dB increases in backscatter for every 1 cm SWE accumulation for sage brush and agricultural fields. The co-polarized VV and HH radar resposnes are similar, while the corss-polarized (VH or HV) echoes showedgreater resposne to the change of SWE. The data also showed the impact of surface hoar growth and freeze/thaw cycles, whichcreated large snow grain sizes and ice lenses, respectively, and consequently increased the radar signals by a few dBs.
A support vector machine (SVM), a machine learning technique developed from statistical learning theory, is employed for the purpose of estimating passive microwave (PMW) brightness temperatures over snow-covered land in North America as observed by the Advanced Microwave Scanning Radiometer (AMSR-E) satellite sensor. The capability of the trained SVM is compared relative to the artificial neural network (ANN) estimates originally presented in [14]. The results suggest the SVM outperforms the ANN at 10.65 GHz, 18.7 GHz, and 36.5 GHz for both vertically and horizontally-polarized PMW radiation. When compared against daily AMSR-E measurements not used during the training procedure and subsequently averaged across the North American domain over the 9-year study period, the root mean squared error in the SVM output is 8 K or less while the anomaly correlation coefficient is 0.7 or greater. When compared relative to the results from the ANN at any of the six frequency and polarization combinations tested, the root mean squared error was reduced by more than 18 percent while the anomaly correlation coefficient was increased by more than 52 percent. Further, the temporal and spatial variability in the modeled brightness temperatures via the SVM more closely agrees with that found in the original AMSR-E measurements. These findings suggest the SVM is a superior alternative to the ANN for eventual use as a measurement operator within a data assimilation framework.
Theme is the comparison of in-situ snow depth measurements with airborne data.
Experimental characterization of the antenna for the Wideband Instrument for Snow Measurements (WISM) under development for the NASA Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP), is discussed. A current sheet antenna, consisting of a small, 6x6 element, dual-linear polarized array with integrated beamformer, feeds an offset parabolic reflector, enabling WISM operation over an 8 to 40 GHz frequency band. An overview of the test program implemented for both the feed and the reflector antenna is given along with select results for specific frequencies utilized by the radar and radiometric sensors of the WISM.
Experimental characterization of the antenna for the Wideband Instrument for Snow Measurement (WISM) under development for the NASA Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP), is discussed. A current sheet antenna, consisting of a small, 6x6 element, dual-linear polarized array with integrated beamformer, feeds an offset parabolic reflector, enabling WISM operation over an 8 to 40 GHz frequency band. An overview of the test program implemented for both the feed and the reflector antenna is given along with select results for specific frequencies utilized by the radar and radiometric sensors of the WISM.
The stable isotopic composition of water in ice cores is an important source of information on past climate variability. At its simplest level, the underlying assumption is that there is an empirical relationship between the normalized difference in the concentration for these stable isotopes and a specified local temperature at the ice core site. There are, however, nonlocal processes, such as a change in source region or a change in the atmospheric pathway, which can impact the stable isotope signal, thereby complicating its use as a proxy for temperature. In this paper, the importance of these nonlocal processes are investigated through the analysis of the synoptic-scale circulation during a snowfall event at the summit of Mount Wrangell (62 deg N, 144 deg W; 4300 m MSL) in south-central Alaska. During this event there was, over a 1-day period in which the local temperature was approximately constant, a change in delta18 O that exceeded half that normally seen to occur in the region between summer and winter. As shall be shown, this arose from a change in the source region, from the subtropical eastern Pacific to northeastern Asia, for the snow that fell on Mount Wrangell during the event.
Presented are the prior accomplishments, current status and path forward for GSFC's Wideband Instrument for Snow Measurement (WISM). This work is a high level overview of the project, presented via Webinar to the IEEE young professionals.
The spatial and temporal distributions of rain-on-snow (ROS) events across the Canadian Arctic Archipelago (CAA) remain poorly understood owing to their sporadic nature in time and space. This situation motivated the development of remote sensing detection algorithms. This paper uses a large meteorological dataset across the CAA to adapt an existing ROS-detection algorithm developed in a previous study by our group. Results highlight the spatial distribution and evolution of ROS occurrences reported since 1985 at 14 weather stations across the CAA. Results show that >600 ROS events were inventoried since 1985, for which >70% were classified as pure rain (liquid form) and 30% as mixed precipitation (solid/liquid). Of the pure rain events, 75% occurred during spring, 14% during fall, 8% during summer and <1% during winter. Such events can have significant impacts on ungulate grazing conditions through the creation of ice layers, causing serious problems for caribou calf survival, especially during the migration period. This paper introduces an adaptation for larger scale Arctic application of a detection algorithm (sensitivity analysis on the detection threshold) with an error of ~5%. The validation, however, remains limited due to a short study period and limited number of sites.
We present technical advances and methods to measure effective broadband physical albedo in snowy mountain headwaters using a prototype dual-sensor pyranometer mounted on an Autonomous Aerial Vehicle (an AAV). Our test flights over snowy meadows and forested areas performed well during both clear sky and snowy/windy conditions at an elevation of ~2650 m above mean sea level (MSL). Our AAV-pyranometer platform provided high spatial (m) and temporal resolution (sec) measurements of effective broadband (310–2700 nm) surface albedo. The AAV-based measurements reveal spatially explicit changes in landscape albedo that are not present in concurrent satellite measurements from Landsat and MODIS due to a higher spatial resolution. This AAV capability is needed for validation of satellite snow albedo products, especially over variable montane landscapes at spatial scales of critical importance to hydrological applications. Effectively measuring albedo is important, as annually the seasonal accumulation and melt of mountain snowpack represent a dramatic transformation of Earth’s albedo, which directly affects headwaters’ water and energy cycles.
Clouds and blowing snow (BLSN) occur frequently over Antarctica, where it is critical to understand their feedbacks to surface and atmospheric boundary layer processes. Dome C, an elevated East Antarctic station, dominated by lengthy periods of surface longwave (LW) radiative cooling, is selected to reveal cloud and BLSN impacts within a largely stable environment. The sky condition is classified as clear, cloudy, or BLSN, using 3 years of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite data. Co-located and contemporaneous in situ observations are used to investigate the relationship of sky condition with surface and atmospheric boundary layer thermal structure, focusing on seasonal variability. Results show that increased downwelling LW radiation from clouds abate surface radiative cooling losses, contributing to warming during all seasons. An increase of 3°C in the mean surface air temperature is observed during spring, whereas, a more dramatic rise (around 10°C), due to accompanying large-scale subsidence, is observed during fall and winter in association with clouds. For all seasons, the wind speed and wind speed shear are strongest during BLSN events, and the surface-based inversion is weakened by cooling which peaks in a shallow above-surface turbulent layer. The stronger background stability during fall and winter seasons, restricts turbulence and BLSN depths generally to the lowest tens of meters. The Earth's cryosphere is among the most rapidly evolving yet least well-observed regions, and knowledge of clouds and BLSN interactions with the typical stable atmospheric boundary layer can help further understand energy and moisture exchanges.
This poster provides an overview of ventilator improvements for reducing radiometer frost, snow, and ice accumulation.
The purpose of this paper is to provide clarification for applying winter precipitation requirements and guidance as provided in Department of Energy Standard (DOE-STD)-1020-2016 and Nuclear Regulatory Commission (NRC) NUREG-0800. Two snow load methodologies are presented, with selection of the preferred approach for use at Idaho National Laboratory (INL).
This paper presents a reconfigurable, low-cost ultra-wideband microwave radar front-end and radar demonstrator designed for nadir-looking measurements of layered media (e.g. snow or vegetation) from either a fast-moving ground-based platform or a C-3 class unmanned aerial system (UAS). The radar demonstrator uses a frequency modulated continuous-wave (FMCW) architecture and can be configured to operate in either the 2-8 GHz or in the 12-18 GHz range, providing fine vertical resolution while offering a significantly reduced weight, size, and power consumption with respect to prior implementations. We have demonstrated the operation of the system in the 2-8 GHz and 12-18 GHz bands in the laboratory; in the 2-8 GHz band using a surface-based setup in Antarctica; and in the 2.6-7 GHz band on local flight tests onboard an Aurelia X6 Pro UAS equipped with 3-D printed antennas. This paper provides an overview of the radar front-end and demonstrator design and implementation and a summary of the different tests completed to document their performance.
Cover crops, grown between cash crops when soil is fallow, are a management strategy that may help mitigate climate change. The biogeochemical effects of cover crops are well documented, as they provide numerous localized benefits to farmers. We test potential biogeophysical climate impacts of idealized cover crop scenarios by assuming that cover crops are planted offseason in all crop regions throughout North America. Our results suggest that planting cover crops increases wintertime temperature up to 3 °C in central North America by decreasing albedo in regions with variable snowpack. Cover crops with higher leaf area indices increase temperature more by decreasing broadband albedo, while decreasing cover crop height helped to mitigate the temperature increase as the shorter height was more frequently buried by snow. Thus, climate mitigation potential must consider the biogeophysical impacts of planting cover crops, and varietal selection can minimize winter warming.
This study aimed to understand the impacts of latent energy as well as snow fall speeds on precipitation properties and synoptic-scale storm characteristics of a wintertime midlatitude cyclone. Simulations of a potent winter storm that impacted the Rocky Mountains and northern Great Plains of the United States in February 2017 were performed using the Weather Research and Forecasting model with latent heating or cooling from individual microphysical processes systematically turned off and fall speeds adjusted by ±50%. Results indicated substantial impacts on the microphysical characteristics of the simulated storm to fall speed, cooling from sublimation, and warming from deposition. The impacts of cooling and warming were manifested as differences in accumulated snowfall. Increased (decreased) fall speeds led to smaller (larger) ice crystals and total mass, resulting in offsetting effects on the precipitation flux, and thus minimal impacts on snowfall and large-scale characteristics of the storm. Warming and cooling associated with deposition and sublimation, respectively, impacted the synoptic-scale dynamics, whereby removing warming from deposition resulted in an increased meridional temperature gradient near the jet stream, thus increasing the jet strength and causing it to be more westerly with less curvature aloft. This in turn limited upper-level divergence, creating a weaker surface low and shifting the precipitation shield southward. The opposite occurred with the removal of latent cooling due to sublimation. This study highlights the potential importance of latent energy associated with ice sublimation and deposition and fall speeds in the larger-scale characteristics of winter storms.
Here, this paper presents a closure to “Observation-Based Evaluation of Flood Estimation Techniques for a Small Snow-Dominated Basin in the Washington Cascade Mountains” by Hongxiang Yan, Zhuoran Duan, Mark S. Wigmosta, Ning Sun, Ethan D. Gutmann, Bert Kruyt, and Jeffrey R. Arnold. https://doi.org/10.1061/JHYEFF .HEENG-6147.
Abstract Ice fragments are generated by sublimation of ice particles in subsaturated conditions in natural clouds. Conceivably, such sublimational breakup would be expected to cause ice multiplication in natural clouds. Any fragment that survives will grow to become ice precipitation that may sublimate and fragment further. As a first step toward assessing this overlooked process, a formulation is proposed for the number of ice fragments from sublimation of ice particles for an atmospheric model. This is done by amalgamating laboratory observations from previously published studies. The concept of a “sublimated mass activity spectrum” for the breakup is applied to the dataset. The number of ice fragments is determined by the relative humidity over ice and the initial size of the parent ice particles. The new formulation applies to dendritic crystals and heavily rimed particles only. Finally, a thought experiment is performed for an idealized scenario of subsaturation with in-cloud descent. Scaling analysis yields an estimate of an ice enhancement ratio of about 5 (10) within a weak deep convective downdraft of about 2 m s −1 , for an initial monodisperse population of dendritic snow (graupel) particles of 3 L −1 and 2 mm. During descent, there is a dynamic equilibrium between continual emission of fragments and their depletion by sublimation. A simplified bin microphysics parcel model exhibits this dynamical quasi equilibrium, consistent with the thought experiment. The fragments have average lifetimes of around 90 and 70 s for dendrites and graupel, respectively. Sublimational breakup is predicted to cause significant secondary ice production.