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At least 109 records · Page 6

The Role of Declining Snow Cover in the Desiccation of the Great Salt Lake, Utah, using MODIS Data

The Great Salt Lake (GSL) in Utah has been shrinking since the middle of the 19th Century, leading to decreased area and volume, and increased salinity. We use satellite data products from the Terra and Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the Landsat-7 and -8 satellites, along with meteorological and streamflow data, and modeled data products to study the relationship between changing snow-cover conditions and the decline of the GSL since 2000 in the context of the historical record of lake levels. The GSL basin includes much of the snow-dominated Wasatch and Uinta mountain ranges to the east of the lake. Snowmelt feeds the Bear, Jordan, and Weber rivers which are the three main rivers that flow into the lake. Snowmelt-timing maps, derived from a new MODIS standard snow-cover product, MOD10A1F, show that snow melted ~9.5 days earlier in the GSL basin during the study period, extending from 2000 – 2018. Air temperatures derived from 26 meteorological stations and surface temperatures measured by the Aqua MODIS land-surface temperature (LST) products, MYD21A1D and MYD21A1N, show trends of increasing temperature of ~0.94°C (a=0.05), and ~2.18°C, respectively, with most of the LST trends in the GSL basin being statistically significant (a=0.05). Increasing air temperatures in the basin have led to less precipitation falling as snow, lower snow depth (by ~34.5 mm (=0.01)) and snow-water equivalent (0.02 mm (a=0.01)), and earlier snowmelt. Also during the study period, Global Land surface Evaporation Amsterdam Model data show evaporation increasing by ~3.2 mm/yr, with trends in much of the basin being statistically significant (a=0.05). Trends calculated from the various products are generally in agreement indicating higher temperatures, greater evaporation, less snowfall and snow-on-the ground, and earlier snowmelt. Earlier snowmelt contributes to increasing evaporative loss from water flowing toward the lake. Furthermore, a lower mountain snowpack and less precipitation falling as snow (versus rain) is associated with lower stream discharge even if overall precipitation stays the same. The surface-water temperature of the GSL also increased over the study period by ~ 0.69°C, according to the MODIS LST data products, and the surface-water elevation of the lake dropped by ~1.7 m between 2000 and 2018 based on United States Geological Survey measurements, and the areal extent of the lake decreased by ~901 km2 as measured using Landsat imagery. Desiccation of the lake is associated with deleterious effects on wildlife, recreational activities, and some local industries. And, importantly, an expanding lake bed can also fuel dust storms that promote dangerous air quality along the Wasatch Front. This work elucidates the key role that satellite remote sensing can play in documenting earlier snowmelt and other changes in the GSL basin that influence the ongoing decline of the Great Salt Lake.

Dorothy K Hall↗

The GPM Ground Validation Program

We present a detailed overview of the structure and activities associated with the NASA-led ground-validation component of the NASA-JAXA Global Pre­cipitation Measurement (GPM) mission. The overarching philosophy and approaches for NASA's GV program are presented with primary focus placed on aspects of direct validation and a summary of physical validation campaigns and results. We describe a spectrum of key instruments, methods, field campaigns and data products developed and used by NASA's GV team to verify GPM level-2 precipitation products in rain and snow. We describe the tools and analysis framework used to confirm that NASA's Level-I science requirements for GPM are met by the GPM Core Observatory. Examples of routine validation activities related to verification of Integrated Multi­satellitE Retrievals for GPM (IMERG) products for two different regions of the globe (Korea and the US) are provided, and a brief analysis related to IMERG performance in the extreme rainfall event associated with Hurricane Florence is discussed.

precipitation↗

The GF Convection Parameterization: Recent Developments, Extensions, and Applications

Recent developments and options in the GF (Grell and Freitas, 2014, Freitas et al.,2018) convection parameterization are presented. The parameterization has been expanded to atrimodal spectral size to simulate three convection modes: shallow, congestus and deep. Incontrast to usual entrainment/detrainment assumptions, we assume that Beta Functions (BFs),commonly applied to represent Probability Density Functions (PDF’s), can be used tocharacterize the vertical mass flux profiles for the three modes, and use the BFs to deriveentrainment and detrainment rates. We also added a new closure for non-equilibrium convectionthat improved the simulation of the diurnal cycle of convection, with a better representation ofthe transition from shallow to deep convection regimes over land. The transport of chemicalconstituents (including wet deposition) can be treated inside the GF scheme. The tracer transportis handled in flux form and is mass conserving. Finally, the cloud microphysics has beenextended to include the ice phase to simulate the conversion from liquid water to ice in updraftswith resulting additional heat release and the melting from snow to rain.

Saulo R De Freitas↗

Applications of MERRA-2 data for avian migration, biomass burning, and dusty atmospheric rivers

Three different applications of MERRA-2 data are presented. 1) Using radar data, we introduced a new concept for spatial patterns of bird migration across the contiguous U.S. This approach allowed us to use MERRA-2 data and learn that remote forcing in the tropical Pacific—through a chain of processes including atmospheric Rossby wave trains— controls the climatic conditions, associated with bird migration in North America. 2) We showed that emissions from biomass burning in the Congo Basin are partly controlled by the low-level winds, which are in turn associated with the intensity of the subtropical high in the Indian Ocean. Using back-trajectory analysis, we found that these emissions combined with their transport mechanism explain the interannual variability of black carbon in West Africa. 3) Our analysis showed that atmospheric rivers in the Middle East contribute to both heavy flood and dust transport within their corridor. We also found that warm advection and rain-on-snow effect of dusty atmospheric rivers further enhance the chance of flood through rapid snowmelt processes.

Amin Dezfuli↗

Simulating Microwave and Radar Signals in Severe Weather Conditions

The development of radiative transfer simulators for radar and microwave signals, spanning a range of frequencies from 10 to 800 GHz, is paramount for enhancing weather forecasting accuracy, particularly for severe weather events. These tools facilitate the assimilation of microwave and radar observations into numerical weather prediction models, thereby improving accuracy of weather forecasts. Additionally, they directly simulate radar signals crucial for autonomous vehicle operation, with frequencies commonly used in radar systems such as 24, 74, 77, and 79 GHz. However, these frequencies are susceptible to weather phenomena like severe rain and snow, which can significantly impact vehicle safety and performance. These simulation tools, including radiative transfer simulators, serve a dual purpose. Firstly, they enhance forecasts for severe weather events, contributing to autonomous vehicle safety by providing early warnings and risk assessments. Secondly, they enable the direct simulation of radar signals in autonomous vehicle driving systems, allowing researchers and engineers to evaluate radar system performance under various weather conditions. In addition to the radar signal simulator, this abstract discusses the incorporation of advanced scattering properties developed using the discrete dipole approximation (DDA). The DDA technique enhances scattering calculations for frozen hydrometeors at microwave frequencies, thereby improving the accuracy of radar signal simulations and enabling more accurate assessments of radar system performance in adverse weather conditions. In summary, this abstract explores the development and utilization of comprehensive simulation tools, emphasizing their significance in simulating microwave and radar signals and improving weather forecasts. Special attention is given to the simulation of radar signals at critical frequencies for autonomous vehicle sensing and navigation, addressing challenges posed by severe weather phenomena and their effects on signal propagation and detection

Isaac Moradi↗

Applications of MERRA-2 Data for Avian Migration, Biomass Burning, and Dusty Atmospheric Rivers

Three different applications of MERRA-2 data are presented. 1) Using radar data, we introduced a new concept for spatial patterns of bird migration across the contiguous U.S. This approach allowed us to use MERRA-2 data and learn that remote forcing in the tropical Pacific—through a chain of processes including atmospheric Rossby wave trains— controls the climatic conditions, associated with bird migration in North America. 2) We showed that emissions from biomass burning in the Congo Basin are partly controlled by the low-level winds, which are in turn associated with the intensity of the subtropical high in the Indian Ocean. Using back-trajectory analysis, we found that these emissions combined with their transport mechanism explain the interannual variability of black carbon in West Africa. 3) Our analysis showed that atmospheric rivers in the Middle East contribute to both heavy flood and dust transport within their corridor. We also found that warm advection and rain-on-snow effect of dusty atmospheric rivers further enhance the chance of flood through rapid snowmelt processes.

Amin Dezfuli↗

Parametric analysis of an imaging radar for use as an imaging radar for use as an independent landing monitor

The capabilities are analyzed of a real aperture, forward-looking imaging radar for use as an independent landing monitor, which will provide the pilot with an independent means of assessing the progress of an automatic landing during Category 3 operations. The analysis shows that adequate ground resolution and signal-to-noise ratio can be obtained to image a runway with grassy surroundings using a radar operating at 35 GHz in good weather and in most fog but that performance is severely degraded in moderate to heavy rain and wet snow. Weather effects on a 10 GHz imager are not serious, with the possible exception of very heavy rain, but the azimuthal resolution at 10 GHz is inadequate with antennas up to 2 m long.

Bundick, W. T.↗

New Developments for Physically-based Falling Snow Retrievals over Land in Preparation for GPM

The NASA Global Precipitation Measurement mission (GPM) concept centers on deploying a Core spacecraft carrying a dual-frequency precipitation radar and a microwave radiometric imager with channels from 10 to 183 GHz to serve as a precipitation physics observatory and a calibration reference to unify a constellation of dedicated and operational passive microwave sensors. Because of the extended orbit of the Core (plus or minus 65 deg) and the enhanced dual frequency radar and high frequency radiometer, GPM will be able to sense falling snow precipitation and light rain over land. Accordingly, GPM has partnered with the Canadian CloudSat/CALIPSO Validation Project (C3VP) to obtain observations to provide one of several important ground-based validation data sets around which the falling snow models and retrieval algorithms can be further developed and tested. In this work we compare and correlate the long time series (Nov.'06 - March '07) measurements of precipitation rate from parsivels to the passive (89, 150, 183 plus or minus 1, plus or minus 3, plus or minus 7 GHz) observations of NOAA's AMSU-B radiometer. We separate the comparisons into categories of no precipitation, liquid rain and falling snow precipitation. We found that there are similar TBs (especially at 89 and 150 GHz) for cases with falling snow and for non-precipitating cases. The comparisons indicate that surface emissivity contributions to the satellite observed TB over land can add uncertainty in detecting and estimating falling snow. The newest results show that by computing brightness temperatures based on CARE radiosonde data and a rough estimate of surface emissivity show that the cloud ice scattering signal in the AMSU-B data is detected. That is the differences in computed TB and AMSU-B TB for precipitating and non-precipitating cases are unique such that the precipitating and non-precipitating cases can be identified. These results require that the radiosonde releases are within an hour of the AMSU-B data. Forest fraction, snow cover, and measured emissivities were combined to calculate the surface emissivities.

Jackson, Gail S.↗

GPM Pre-Launch Algorithm Development for Physically-Based Falling Snow Retrievals

In this work we compare and correlate the long time series (Nov.-March) n~easurements of precipitation rate from the Parsivels and 2DVD to the passive (89, 150, 183+/-1, +/-3, +/-7 GHz) observations of NOAA's AMSU-B radiometer. There are approximately 5-8 AMSU-B overpass views of the CARE site a day. We separate the comparisons into categories of no precipitation, liquid rain and falling snow precipitation. Scatterplots between the Parsivel snowfall rates and AMSU-B brightness temperatures (TBs) did not show an exploitable relationship for retrievals. We further compared and contrasted brightness temperatures to other surface measurements such as temperature and relative humidity with equally unsatisfying results. We found that there are similar TBs (especially at 89 and 150 GHz) for cases with falling snow and for non-precipitating cases. The comparisons indicate that surface emissivity contributions to the satellite observed TB over land can add uncertainty in detecting and estimating falling snow. The newest results show that the cloud icc scattering signal in the AMSU-B data call be detected by computing clear air TBs based on CARE radiosonde data and a rough estimate of surface emissivity. That is the differences in computed TI3 and AMSU-B TB for precipitating and nonprecipitating cases are unique such that the precipitating versus ~lon-precipitating cases can be identified. These results require that the radiosonde releases are within an hour of the AMSU-B data and allow for three surface types: no snow on the ground, less than 5 cm snow on the ground, and greater than 5 cm on the ground (as given by ground station data). Forest fraction and measured emissivities were combined to calculate the surface emissivities. The above work and future work to incorporate knowledge about falling snow retrievals into the framework of the expected GPM Bayesian retrievals will be described during this presentation.

Gail Skofronick-Jackson↗

CloudSat Bias on Falling Snow Estimates Over the Daylight Only Operational Period (2012-2019)

Falling snow is a key component for the global atmospheric, hydrological and energy cycles, and its retrieval from space-based observations represents the best current capability to evaluate it globally. The Global Precipitation Measurement (GPM) Mission Core Observatory, launched in 2014, together with its constellation sensors, can provide quasi-global precipitation estimates every 30 minutes (for level 3 products). Evaluation and validation efforts for such products are crucial, and for global evaluations, one of the most suitable instruments is the Cloud Profiling Radar (CPR) on board CloudSat, which is sensitive to light rain and falling snow. However, due to a battery anomaly in 2011, during its period of overlapping observations with GPM the CPR has operated in a Daylight Only Operations mode (DO-Op) in which it makes measurements primarily during only the daylit portion of its orbit. The goal of this work is to estimate biases inherent in global snowfall amounts derived from CPR measurements due to this shift to DO-Op mode. We use CloudSat's snowfall measurements during its Full Operations (Full-Op) period from 2006 to 2010 to evaluate the impact DO-Op mode would have had during this period. Results indicate that omitting the nocturnal component of the diurnal cycle of snowfall has nonnegligible impact on snowfall amounts in some regions. The lack of nighttime data during DO-Op biases the latitudinally averaged mean snowfall rates as well as some regional values. Hemispheric differences in bias may be due to more pronounced diurnal variability in the northern hemisphere owing to more prevalent land surface versus the southern hemisphere. The results highlight the need to sample consistently with the CloudSat observations or to adjust snowfall estimates derived from CloudSat when using DO-Op data to evaluate other precipitation products.

Milani, Lisa↗

Advance particle and Doppler measurement methods

Particle environments, i.e., rain, ice, and snow particles are discussed. Two types of particles addressed are: (1) the natural environment in which airplanes fly and conduct test flights; and (2) simulation environments that are encountered in ground-test facilities such as wind tunnels, ranges, etc. There are characteristics of the natural environment that one wishes to measure. The liquid water content (LWC) is the one that seems to be of most importance; size distribution may be of importance in some applications. Like snow, the shape of the particle may be an important parameter to measure. As one goes on to environment in simulated tests, additional parameters may be required such as velocity distribution, the velocity lag of the particle relative to the aerodynamic flow, and the trajectory of the particle as it goes through the aerodynamic flow and impacts on the test object.

Busch, C.↗

Cabin fuselage structural design with engine installation and control system

Design requirements for the cabin, cabin system, flight controls, engine installation, and wing-fuselage interface that provide adequate interior volume for occupant seating, cabin ingress and egress, and safety are presented. The fuselage structure must be sufficient to meet the loadings specified in the appropriate sections of Federal Aviation Regulation Part 23. The critical structure must provide a safe life of 10(exp 6) load cycles and 10,000 operational mission cycles. The cabin seating and controls must provide adjustment to account for various pilot physiques and to aid in maintenance and operation of the aircraft. Seats and doors shall not bind or lockup under normal operation. Cabin systems such as heating and ventilation, electrical, lighting, intercom, and avionics must be included in the design. The control system will consist of ailerons, elevator, and rudders. The system must provide required deflections with a combination of push rods, bell cranks, pulleys, and linkages. The system will be free from slack and provide smooth operation without binding. Environmental considerations include variations in temperature and atmospheric pressure, protection against sand, dust, rain, humidity, ice, snow, salt/fog atmosphere, wind and gusts, and shock and vibration. The following design goals were set to meet the requirements of the statement of work: safety, performance, manufacturing and cost. To prevent the engine from penetrating the passenger area in the event of a crash was the primary safety concern. Weight and the fuselage aerodynamics were the primary performance concerns. Commonality and ease of manufacturing were major considerations to reduce cost.

Balakrishnan, Tanapaal↗

Seasonally Frozen Soil Monitoring Using Passive Microwave Satellite Data and Simulation Modeling

Satellite data and simulation modeling were used to assess seasonally frozen soils in the central US - Canada borders area (46-53 degrees N and 96-108 degrees). We used Scanning Multichannel Microwave Radiometer (SMMR) satellite data to delineate the top layer of frozen soils. SMMR is a passive microwave sensor having five channels (6.6, 10, 18, 21 and 37 GHz) with a horizontal and vertical polarization. SMRR data are available between 1978-1987 with noon and midnight overpass and footprint sizes between 25 km and 150 km. SMMR data were processed from resampled 1/4 degree grid cells during fall freeze-up and spring thaw (fall 1985 - spring 1987). The dielectric properties of a target may directly affect the satellite signal. The dielectric value is an order of magnitude smaller for frozen soil water. There are other significant changes to the emitted microwave signal from changes to the surface physical temperature, attenuation of the soil signal from plant water and soil moisture. We further characterized the temporal and spatial dynamic of frozen soils using the FroST (Frozen Soil Temperature) simulation model. The FroST model was used to further predict soil water and ice content, and soil temperature. SMMR results were compared versus 5-cm soil temperature data from available weather stations (14 in Canada and 11 for available months in the US). SMMR data were analyzed as a function of frequency, polarization, polarization difference, and "frequency gradient". In addition, vegetation density, physical temperature and snow depth were also considered. Preliminary analysis of SMMR derived frozen soil/thaw classification using a simple threshold classification indicates a mean overall classification accuracy by season of 85 percent. A sensitivity analysis for different soils with varying amounts of snow was conducted with FroST, which showed that the amount of snow, and the time of snow fall and melt affected the ice and water content, and depth of thaw. These results indicate a potential source of flooding and erosion under conditions when melting snow and spring rains provide a source of infiltrating water.

Toll, D. L.↗

Launch Pad 39 Hail Monitor Array System

Weather conditions at Kennedy Space Center are extremely dynamic, and they greatly affect the safety of the Space Shuttles sitting on the launch pads. For example, on May 13, 1999, the foam on the External Tank (ET) of STS-96 was significantly damaged by hail at the launch pad, requiring rollback to the Vehicle Assembly Building. The loss of ET foam on STS-114 in 2005 intensified interest in monitoring and measuring damage to ET foam, especially from hail. But hail can be difficult to detect and monitor because it is often localized and obscured by heavy rain. Furthermore, the hot Florida climate usually melts the hail even before the rainfall subsides. In response, the hail monitor array (HMA) system, a joint effort of the Applied Physics Laboratory operated by NASA and ASRC Aerospace at KSC, was deployed for operational testing in the fall of 2006. Volunteers from the Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network, in conjunction with Colorado State University, continue to test duplicate hail monitor systems deployed in the high plains of Colorado.

Source record↗

Ares I Scale Model Acoustic Test Instrumentation for Acoustic and Pressure Measurements

Ares I Scale Model Acoustic Test (ASMAT) is a 5% scale model test of the Ares I vehicle, launch pad and support structures conducted at MSFC to verify acoustic and ignition environments and evaluate water suppression systems Test design considerations 5% measurements must be scaled to full scale requiring high frequency measurements Users had different frequencies of interest Acoustics: 200 - 2,000 Hz full scale equals 4,000 - 40,000 Hz model scale Ignition Transient: 0 - 100 Hz full scale equals 0 - 2,000 Hz model scale Environment exposure Weather exposure: heat, humidity, thunderstorms, rain, cold and snow Test environments: Plume impingement heat and pressure, and water deluge impingement Several types of sensors were used to measure the environments Different instrument mounts were used according to the location and exposure to the environment This presentation addresses the observed effects of the selected sensors and mount design on the acoustic and pressure measurements

Vargas, Magda B.↗

Chemical and Mineralogical Characterization of Acid-Sulfate Alteration of Basaltic Material on Mauna Kea Volcano, Hawaii: Jarosite and Hydrated Halloysite

Sulfates have been identified on the martian surface during robotic surface exploration and by orbital remote sensing. Measurements at Meridiani Planum (MP) by the Alpha-Particle X-ray Spectrometer (APXS) and Mossbauer (MB) instruments on the Mars Exploration Rover Opportunity document the presence of a ubiquitous sulfate-rich outcrop (20-40% SO3) that has jarosite as an anhydrous Fe3+-sulfate [1- 3]. The presence of jarosite implies a highly acidic (pH <3) formation environment [4]. Jarosite and other sulfate minerals, including kieserite, gypsum, and alunite have also been identified in several locations in orbital remote sensing data from the MEx OMEGA and MRO CRISM instruments [e.g. 5-8]. Acid sulfate weathering of basaltic materials is an obvious pathway for formation of sulfate-bearing phases on Mars [e.g. 4, 9, 10]. In order to constrain acid-sulfate pathways on Mars, we are studying the mineralogical and chemical manifestations of acid-sulfate alteration of basaltic compositions in terrestrial environments. We have previously shown that acidsulfate alteration of tephra under hydrothermal conditions on the Puu Poliahu cone (summit region of Mauna Kea volcano, Hawaii) resulted in jarosite and alunite as sulfate-bearing alteration products [11-14]. Other, more soluble, sulfates may have formed, but were leached away by rain and melting snow. Acidsulfate processes on Puu Poliahu also formed hematite spherules similar (except in size) to the hematite spherules observed at MP as an alteration product [14]. Phyllosilicates, usually smectite }minor kaolinite are also present as alteration products [13]. We discuss here an occurrence of acid-sulfate alteration on Mauna Kea Volcano (Hawaii). We report VNIR spectra (0.35-2.5 microns ASD spectrometer), Mossbauer spectra (MER-like ESPI backscatter spectrometer), powder XRD (PANalytical), and major element chemical compositions (XRF with LOI and Fe redox) for comparison to similar data acquired or to be acquired by MRO-CRISM and MEx OMEGA, MERMB, MSL-CheMin, and MER and MSL APXS, respectively.

Graff, Trevor G.↗

Analysis of the March 30, 2011 Hail Event at Shuttle Launch Pad 39A

The Kennedy Space Center (KSC) Hail Monitor System, a joint effort of the NASA KSC Physics Lab and the KSC Engineering Services Contract (ESC) Applied Technology Lab, was first deployed for operational testing in the fall of 2006. Volunteers from the Community Collaborative Rain, Hail, and Snow Network (CoCoRaHS) in conjunction with Colorado State University have been instrumental in validation testing using duplicate hail monitor systems at sites in the hail prone high plains of Colorado. The KSC Hail Monitor System (HMS), consisting of three stations positioned approximately 500 ft from the launch pad and forming an approximate equilateral triangle, as shown in Figure 1, was first deployed to Pad 39B for support of STS-115. Two months later, the HMS was deployed to Pad 39A for support of STS-116. During support of STS-117 in late February 2007, an unusually intense (for Florida standards) hail event occurred in the immediate vicinity of the exposed space shuttle and launch pad. Hail data of this event was collected by the HMS and analyzed. Support of STS-118 revealed another important application of the hail monitor system. Ground Instrumentation personnel check the hail monitors daily when a vehicle is on the launch pad, with special attention after any storm suspected of containing hail. If no hail is recorded by the HMS, the vehicle and pad inspection team has no need to conduct a thorough inspection of the vehicle immediately following a storm. On the afternoon of July 13, 2007, hail on the ground was reported by observers at the Vertical Assembly Building (VAB) and Launch Control Center (LCC), about three miles west of Pad 39A, as well as at several other locations at KSC. The HMS showed no impact detections, indicating that the shuttle had not been damaged by any of the numerous hail events which occurred on that day.

Lane, John E.↗