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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

A case study of gravity waves-convective storms interaction 9 May 1979

An analysis is presented of a series of severe storms which occurred in the north central United States on 9 May 1979 and whose spatial distribution and movement correlate well with observed gravity waves. Two gravity wave trains of 2.1-3 mb amplitude, 2.5-3.3 h period and 240-265 km horizontal wavelength were isolated through power spectra analysis and cross-correlation techniques applied to National Weather Service barograph traces. The wave trains propagated in the 200 deg direction, which coincided with the jet axis, with a phase velocity of 20-30 m/s and within a 300 km wide band. The storms were identified on enhanced infrared GOES satellite pictures with the help of radar summaries. These convective systems initially developed in Nebraska and propagated north-northeast at 25 m/s, revealing wave-like characteristics with a separation of 300-400 km. The convective systems were closely linked to the observed wave trains with cell intensity, height and associated rainfall maximized at the wave ridge. One of the two wave trains developed in regions of weak or no convection and appeared to initiate more intense convective clusters downstream from the point of origin. It is shown that the characteristics of the wave trains are consistent with those of gravity waves generated in a region of strong vertical shear associated with the jet. It is suggested that the wave trains continue to extract energy from the basic state all along their track through critical level interaction.

Stobie, J. G.↗
NASA NTRS2012

TRMM Precipitation Application Examples Using Data Services at NASA GES DISC

Data services to support precipitation applications are important for maximizing the NASA TRMM (Tropical Rainfall Measuring Mission) and the future GPM (Global Precipitation Mission) mission's societal benefits. TRMM Application examples using data services at the NASA GES DISC, including samples from users around the world will be presented in this poster. Precipitation applications often require near-real-time support. The GES DISC provides such support through: 1) Providing near-real-time precipitation products through TOVAS; 2) Maps of current conditions for monitoring precipitation and its anomaly around the world; 3) A user friendly tool (TOVAS) to analyze and visualize near-real-time and historical precipitation products; and 4) The GES DISC Hurricane Portal that provides near-real-time monitoring services for the Atlantic basin. Since the launch of TRMM, the GES DISC has developed data services to support precipitation applications around the world. In addition to the near-real-time services, other services include: 1) User friendly TRMM Online Visualization and Analysis System (TOVAS; URL: http://disc2.nascom.nasa.gov/Giovanni/tovas/); 2) Mirador (http://mirador.gsfc.nasa.gov/), a simplified interface for searching, browsing, and ordering Earth science data at GES DISC. Mirador is designed to be fast and easy to learn; 3) Data via OPeNDAP (http://disc.sci.gsfc.nasa.gov/services/opendap/). The OPeNDAP provides remote access to individual variables within datasets in a form usable by many tools, such as IDV, McIDAS-V, Panoply, Ferret and GrADS; and 4) The Open Geospatial Consortium (OGC) Web Map Service (WMS) (http://disc.sci.gsfc.nasa.gov/services/wxs_ogc.shtml). The WMS is an interface that allows the use of data and enables clients to build customized maps with data coming from a different network.

Liu, Zhong↗
NASA NTRS1989

Multispectral retrieval of rainfall rates using the Special Sensor Microwave/Imager (SSM/I)

Collocated SSM/I and radar measurements are compared to model simulated radiances upwelling from precipitating clouds. A methodology maximizing the correlation between the radar rain rate estimates and surface rainfall amounts is presented, along with data sources and samples. Geolocation of both the satellite and radar data is assessed, and statistical rainfall-rate retrieval algorithms are analyzed. Regression analysis of collocated SSM/I brightness-temperature measurements and radar-derived rainfall rates show the potential of the SSM/I to provide 25-km resolution rain-rate estimates over land and ocean surfaces.

Olson, William S.↗
NASA NTRS1974

The influence of polarization on millimeter wave propagation through rain

The influence of polarization on millimeter wave propagation through rain is investigated. The experimental equipment consisted of a 1.43 km line-of-sight path with 4-foot diameter dual-polarized parabolic reflector antennas at each end. Linearly polarized 17.65 GHz signals were transmitted with the electric field vectors at plus 45 degrees and minus 45 degrees from the vertical. These polarizations were initially chosen to maximize the measured depolarization at any given rainfall rate. Later it was discovered that the cross polarization levels measured with plus or minus 45 degree linearly polarized signals are theoretically the least sensitive to variations in drop canting angle and this choice of polarization reduces the scatter in the data.

Bostian, C. W.↗
NASA NTRS2019

An Update on GPM and TRMM Data Services at NASA GES DISC

The Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to data archives of the NASA-JAXA Global Precipitation Measurement (GPM), the Tropical Rainfall Measuring Mission (TRMM), and other NASA missions and projects. To maximize the use of NASA data products in scientific research and applications as well as for societal benefits, we provide data and information services that make datasets easy to find and use through simplification of data access for users at all levels around the world. Over the years, user-friendly data services have been developed at GES DISC, including data subsetting, format conversion, online visualization and analysis (i.e. Giovanni), user support system, etc. We routinely analyze questions, feedback, and use cases from users and algorithm developers around the world as well as best practices and new technology to improve existing services and formulate new data services. Interaction between users and algorithm developers is an important process for identifying issues in products, collecting user requirements, and improving product quality and usability. Staff members regularly communicate with algorithm developers with user questions and concerns through conferences and workshops. We publish peer-reviewed papers and articles in major Earth science journals and book chapters to describe NASA global and regional precipitation datasets and services with examples. News articles about GPM and TRMM datasets associated with significant events are regularly posted in the GES DISC Web portal and social media. We also actively participate in training activities. In this presentation, we present our latest activities about GPM and TRMM data services, data/service metrics, and future plans at GES DISC.

Liu, Z.↗
NASA NTRS2001

Interannual Variability of Tropical Precipitation: How Well Do Climate Models Agree With Current Satellite Estimates?

Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. Recent availability of the TRMM (Tropical Rainfall Measuring Mission) has further aided in narrowing uncertainties in rainfall over die tropics and subtropics. Although climate modeling efforts have long relied on space-based precipitation estimates for validation, we now are in a position to make more quantitative assessments of model performance, particularly in tropical regions. An integration of the CCM3 using observed SSTs as a lower boundary condition is used to examine how well this model responds to ENSO forcing in terms of anomalous precipitation. An integration of the NCEP spectral model used for the Reanalysis-H effort is also examined. This integration is run with specified SSTs, but with no data assimilation. Our analysis focuses on two aspects of inter-annual variability. First are the spatial anomalies that are indicative of dislocations in Hadley and Walker circulations. Second, we consider the ability of models to replicate observed increases in oceanic precipitation that are noted in satellite observations for large ENSO events. Finally, we consider a slab ocean version of the CCM3 model with prescribed ocean beat transports that mimic upwelling anomalies, but which still allows the surface energy balance to be predicted. This less restrictive experiment is used to understand why model experiments with specified SSTs seem to have noticeably less interannual variability in precipitation than do the satellite observations.

Robertson, Franklin R.↗
NASA NTRS2000

Interannual Variability of the Tropical Energy Balance: Reconciling Observations and Models

Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. Recent availability of the TRMM (Tropical Rainfall Measuring Mission) has further aided in narrowing uncertainties in rainfall over the tropics and subtropics. Although climate modeling efforts have long relied on space-based precipitation estimates for validation, we now are in a position to make more quantitative assessments of model performance, particularly in tropical regions. An integration of the CCM3 using observed SSTs as a lower boundary condition is used to examine how well this model responds to ENSO forcing in terms of anomalous precipitation. An integration of the NCEP spectral model used for the Reanalysis-11 effort is also examined. This integration is run with specified SSTs, but no data assimilation. Our analysis focuses on two aspects. First are the spatial anomalies that are indicative of dislocations in Hadley and Walker circulations. Second, we consider the ability of models to replicate observed increases in oceanic precipitation that are noted in satellite observations for large ENSO events. Finally, we consider a slab ocean version of the CCM3 model with prescribed ocean heat transports that mimic upwelling anomalies, but which still allows the surface energy balance to be predicted. This less restrictive experiment is used to understand why model experiments with specified SSTs seem to have noticeably less interannual variability than do the satellite precipitation observations.

Robertson, Franklin R.↗
NASA NTRS2004

A Reply to Diem et al.'s Commentary on a Recent Literature Contribution Focused on Urban-Induced Rainfall in Atlanta

A response is provided to Diem and colleagues discussion on the whether urbanization-enhanced precipitation should be maximized in the South-Southeast of Atlanta, Georgia as documented in Shepherd et al. (2003). Diem and colleagues have offered a critical response to Shepherd et al. (2002). The response herein offers both general and specific responses to issues raised by Diem and colleagues.

Shepherd, J. Marshall↗
NASA NTRS2013

Application and Evaluation of a Snowmelt Runoff Model in the Tamor River Basin, Eastern Himalaya Using a Markov Chain Monte Carlo (MCMC) Data Assimilation Approach

Previous studies have drawn attention to substantial hydrological changes taking place in mountainous watersheds where hydrology is dominated by cryospheric processes. Modelling is an important tool for understanding these changes but is particularly challenging in mountainous terrain owing to scarcity of ground observations and uncertainty of model parameters across space and time. This study utilizes a Markov Chain Monte Carlo data assimilation approach to examine and evaluate the performance of a conceptual, degree-day snowmelt runoff model applied in the Tamor River basin in the eastern Nepalese Himalaya. The snowmelt runoff model is calibrated using daily streamflow from 2002 to 2006 with fairly high accuracy (average Nash-Sutcliffe metric approx. 0.84, annual volume bias <3%). The Markov Chain Monte Carlo approach constrains the parameters to which the model is most sensitive (e.g. lapse rate and recession coefficient) and maximizes model fit and performance. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall compared with simulations using observed station precipitation. The average snowmelt contribution to total runoff in the Tamor River basin for the 2002-2006 period is estimated to be 29.7+/-2.9% (which includes 4.2+/-0.9% from snowfall that promptly melts), whereas 70.3+/-2.6% is attributed to contributions from rainfall. On average, the elevation zone in the 4000-5500m range contributes the most to basin runoff, averaging 56.9+/-3.6% of all snowmelt input and 28.9+/-1.1% of all rainfall input to runoff. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall versus snowmelt compared with simulations using observed station precipitation. Model experiments indicate that the hydrograph itself does not constrain estimates of snowmelt versus rainfall contributions to total outflow but that this derives from the degree-day melting model. Lastly, we demonstrate that the data assimilation approach is useful for quantifying and reducing uncertainty related to model parameters and thus provides uncertainty bounds on snowmelt and rainfall contributions in such mountainous watersheds.

runoff↗
NASA NTRS2021

Achieving Breakthroughs in Global Hydrologic Science by Unlocking the Power of Multisensor, Multidisciplinary Earth Observations

Over the last half century, remote sensing has transformed hydrologic science. Whereas early efforts were devoted to observation of discrete variables, we now consider spaceborne missions dedicated to interlinked global hydrologic processes.Furthermore, cloud computing and computational techniquesare accelerating analyses of these data. How will the hydrologic community use these new resources to better understand the world’s water and relatedchallenges facing society? In this Commentary, we suggest that optimizing the benefits of remote sensing for advancing hydrologic research will happen byintegratingmultidisciplinary and multisensor data, leveraging commercial satellite measurements, and employingdata assimilation, cloud computing, and machine learning.We provide several recommendations to these ends. Plain Language Summary Observations from satellites have transformed hydrologic science. Early efforts, five decades ago, mapped attributes like snow cover, rainfall, topography, and vegetation, but now we consider new missions specifically designed to study global hydrologic processes. We also take advantageof new technologies like cloud computing and artificial intelligence. We describe strategiesfor maximizing the benefits of remote sensing for hydrology, encouraging research across disciplines using multiple sensors, using new commercially available satellites, and combining remote sensing measurements with hydrologic models.

Michael Durand↗
NASA NTRS2004

Economic Impact of Water Allocation on Agriculture in the Lower Chattahoochee River Basin

The relative value of irrigation water was assessed for three important crops (corn, cotton, and peanuts) grown in the southeastern United States. A decision tool was developed with the objective of allocating limited available water among competing crops in a manner that would maximize the economic returns to the producers. The methodology was developed and tested for a hypothetical farm located in Henry County, Alabama in the Chattahoochee river basin. Crop yield - soil moisture response functions were developed using Monte Carlo simulated data for cotton, corn, and peanuts. A hydrologic model was employed to simulate runoff over the period of observed rainfall the county to provide inflows to storage facilities that could be used as constraints for the optimal allocation of the available water in the face of the uncertainty of future rainfall and runoff. Irrigation decisions were made on a weekly basis during the critical water deficit period in the region. An economic optimization model was employed with the crop responses, and soil moisture functions to determine the optimum amount of water place on each crop subject to the amount of irrigation water availability and climatic uncertainty. The results indicated even small amounts of irrigation could significantly benefit farmers in the region if applied judiciously. A weekly irrigation sequence was developed that maintained the available water on the crops that exhibited the most significant combination of water sensitivity and cash value.

Limaye, Ashutosh S.↗
NASA NTRS2016

Climate Change Adaptation Activities at the NASA John F. Kennedy Space Center, FL., USA

In 2010, the Office of Strategic Infrastructure and Earth Sciences established the Climate Adaptation Science Investigators (CASI) program to integrate climate change forecasts and knowledge into sustainable management of infrastructure and operations needed for the NASA mission. NASA operates 10 field centers valued at $32 billion dollars, occupies 191,000 acres and employs 58,000 people. CASI climate change and sea-level rise forecasts focus on the 2050 and 2080 time periods. At the 140,000 acre Kennedy Space Center (KSC) data are used to simulate impacts on infrastructure, operations, and unique natural resources. KSC launch and processing facilities represent a valued national asset located in an area with high biodiversity including 33 species of special management concern. Numerical and advanced Bayesian and Monte Carlo statistical modeling is being conducted using LiDAR digital elevation models coupled with relevant GIS layers to assess potential future conditions. Results are provided to the Environmental Management Branch, Master Planning, Construction of Facilities, Engineering Construction Innovation Committee and our regional partners to support Spaceport development, management, and adaptation planning and design. Potential impacts to natural resources include conversion of 50% of the Center to open water, elevation of the surficial aquifer, alterations of rainfall and evapotranspiration patterns, conversion of salt marsh to mangrove forest, reductions in distribution and extent of upland habitats, overwash of the barrier island dune system, increases in heat stress days, and releases of chemicals from legacy contamination sites. CASI has proven successful in bringing climate change planning to KSC including recognition of the need to increase resiliency and development of a green managed shoreline retreat approach to maintain coastal ecosystem services while maximizing life expectancy of Center launch and payload processing resources.

plant communities↗
NASA NTRS2002

Optimal Strategies for Validating TRMM Rainfall Estimates with Rain-Gauge Data

In spite of all their problems, rain gauges measure rainfall in such a direct way when compared with other methods of estimating rainfall that comparing their totals to satellite estimates remains an essential tool in the validation of satellite products. Some disagreement between averages of satellite data and rain-gauge data is expected because of the very different sampling patterns of the two systems--the satellite provides only occasional snapshots of large areas, whereas rain gauges provide continuous measurements over very small areas. A quantitative estimate of the expected level of disagreement due to the differences in sampling is needed in order for comparisons of the two kinds of averages to be informative. As part of an earlier effort to determine the sampling error of satellite averages, a space-time model for rainfall statistics was developed. Sets of parameter values for the model have been obtained for which the model statistics are found to agree quite well with those of radar data taken over the Atlantic during GATE and the western Pacific during TOGA COARE. Although the model was intended to represent the statistics of relatively large scale fluctuations of rain, it is surprisingly consistent with the very different scales on which rain gauges observe. Implications for maximizing the benefit in comparisons of rain gauge averages and TRMM estimates are derived using the model predictions.

Bell, Thomas L.↗
NASA NTRS2010

Quality Control and Calibration of the Dual-Polarization Radar at Kwajalein, RMI

Weather radars, recording information about precipitation around the globe, will soon be significantly upgraded. Most of today s weather radars transmit and receive microwave energy with horizontal orientation only, but upgraded systems have the capability to send and receive both horizontally and vertically oriented waves. These enhanced "dual-polarimetric" (DP) radars peer into precipitation and provide information on the size, shape, phase (liquid / frozen), and concentration of the falling particles (termed hydrometeors). This information is valuable for improved rain rate estimates, and for providing data on the release and absorption of heat in the atmosphere from condensation and evaporation (phase changes). The heating profiles in the atmosphere influence global circulation, and are a vital component in studies of Earth s changing climate. However, to provide the most accurate interpretation of radar data, the radar must be properly calibrated and data must be quality controlled (cleaned) to remove non-precipitation artifacts; both of which are challenging tasks for today s weather radar. The DP capability maximizes performance of these procedures using properties of the observed precipitation. In a notable paper published in 2005, scientists from the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) at the University of Oklahoma developed a method to calibrate radars using statistically averaged DP measurements within light rain. An additional publication by one of the same scientists at the National Severe Storms Laboratory (NSSL) in Norman, Oklahoma introduced several techniques to perform quality control of radar data using DP measurements. Following their lead, the Topical Rainfall Measuring Mission (TRMM) Satellite Validation Office at NASA s Goddard Space Flight Center has fine-tuned these methods for specific application to the weather radar at Kwajalein Island in the Republic of the Marshall Islands, approximately 2100 miles southwest of Hawaii and 1400 miles east of Guam in the tropical North Pacific Ocean. This tropical oceanic location is important because the majority of rain, and therefore the majority of atmospheric heating, occurs in the tropics where limited ground-based radar data are available.

Marks, David A.↗
NASA NTRSDate not supplied

Usage-Based Discovery of Earth Observations

Most providers of Earth Observation data enable search via dataset characteristics, (e.g., quantity being measured, instrument, location, and time). However, the Earth Science Information Partners Federation (ESIP) is attempting to improve dataset discovery by capturing information on how datasets are used. At a usage-based discovery hackfest at the July 2020 ESIP Summer Meeting, participants pooled their collective skills to implement a prototype based on the connections between datasets and data usage, which can reveal unanticipated patterns in dataset connectivity that are not apparent through traditional approaches. A survey of natural hazards websites, focusing on hydrology-related hazards such as floods and hydrology datasets such as rainfall, illustrated the difficulty of gleaning which dataset was actually used and how it was accessed. This difficulty highlights the need for greater transparency on dataset usage in website design. An application wireframe for a usage-based discovery database was conceptualized as a tool to help applications data specialists rapidly assemble a fit-for-purpose website as part of a disaster response, where customer feedback was integral to the manner in which the website would be developed and delivered. Capturing connections among datasets and instances of usage, either for research or applications, could help users identify datasets with a proven track record of utility or those that have been supplanted by more accurate and(or) precise representations. It may also help Earth Observation providers maximize returns on investments in data services. Social discovery, i.e, following discovery paths laid down by previous users of the data, could be a critical tool for improving the timeliness and applicability of dataset delivery at times and in circumstances where practitioners don’t have the capacity to evaluate the deluge of datasets that are returned by today’s search tools.

search↗
NASA NTRS1995

Classification of rain regimes by the three-dimensional properties of reflectivity fields

An automated scheme to characterize precipitation echoes within small windows in the radar field is presented and applied to previously subjectively classified tropical rain cloud systems near Darwin, Australia. The classification parameters are (a) E(sub e), effective efficiency, as determined by cloud-top and cloud-base water vapor saturation mixing ratios; (b) BBF, brightband fraction, as determined by the fraction of the radar echo area in which the maximal reflectivity occurs within +/- 1.5 km of the 0 C isotherm level; and (c) del(sub r) Z, radial reflectivity gradients (dB/km). These classification criteria were applied to tropical rain cloud systems near Darwin, Australia, and to winter convective rain cloud systems in Israel. Both sets of measurements were made with nearly identical networks of C-band radars and rain gauge networks. The results of the application of these objective classification criteria to several independently predetermined rain regimes in Darwin have shown that better organized rain systems have smaller del(sub r) Z and larger BBF. Similarly, smaller del(sub r)Z and larger BBF were also observed from maritime rain cloud systems, as compared to continental rain cloud systems with the same degree of organization. Continental rain cloud system, regardless of their degree of organization, have larger depths, as expressed by E(sub e). The rainfall analyses presented in this study are based exclusively on rain gauge measurements, while radar information was used only to classify the individual gauge measurements.

Rosenfeld, Daniel↗
NASA NTRS2016

Global Precipitation Measurement (GPM) and International Space Station (ISS) Coordination for CubeSat Deployments to Minimize Collision Risk

The Global Precipitation Measurement Mission (GPM) is a joint U.S. and Japan mission to observe global precipitation, extending the Tropical Rainfall Measuring Mission (TRMM), which was launched by H-IIA from Tanegashima in Japan on February 28TH, 2014 directly into its 407km operational orbit. The International Space Station (ISS) is an international human research facility operated jointly by Russia and the USA from NASA's Johnson Space Center (JSC) in Houston Texas. Mission priorities lowered the operating altitude of ISS from 415km to 400km in early 2105, effectively placing both vehicles into the same orbital regime. The ISS has begun a program of deployments of cost effective CubeSats from the ISS that allow testing and validation of new technologies. With a major new asset flying at the same effective altitude as the ISS, CubeSat deployments became a serious threat to GPM and therefore a significant indirect threat to the ISS. This paper describes the specific problem of collision threat to GPM and risk to ISS CubeSat deployment and the process that was implemented to keep both missions safe from collision and maximize their project goals.

Pawloski, James H.↗
NASA NTRS2018

Global Precipitation Measurement (GPM) Core Satellite & International Space Station (ISS) Coordination for CubeSat Deployments to Minimize Collision Risk

The Global Precipitation Measurement Mission (GPM) is a joint U.S. and Japan mission to observe global precipitation, extending the Tropical Rainfall Measuring Mission (TRMM) data set, which was launched by H-IIA from Tanegashima in Japan on February 28TH, 2014 directly into its 407km operational orbit. The International Space Station (ISS) is an international human research facility operated jointly by Russia and the USA from NASA's Johnson Space Center (JSC) in Houston Texas. Mission priorities lowered the operating altitude of ISS from 415km to 400km in early 2015, effectively placing both vehicles into the same orbital regime. The ISS has begun a program of deployments of cost effective CubeSats from the ISS that allow testing and validation of new technologies. With a major NASA asset flying at the same effective altitude as the ISS, CubeSat deployments became a serious threat to GPM and therefore a significant indirect threat to the ISS. This presentation describes the specific problem of collision threat to GPM and risk to ISS CubeSat deployment, the process that was implemented to keep both missions safe from collision and maximize their project goals, and the history of the process since implementation.

GPM↗