Search NASA⌕ Search

SEARCH · Search NASA

Results for “Weather Data”

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.

At least 253 records · Page 14

Initial Results from the Variable Intensity Sonic Boom Propagation Database

An extensive sonic boom propagation database with low- to normal-intensity booms (overpressures of 0.08 lbf/sq ft to 2.20 lbf/sq ft) was collected for propagation code validation, and initial results and flight research techniques are presented. Several arrays of microphones were used, including a 10 m tall tower to measure shock wave directionality and the effect of height above ground on acoustic level. A sailplane was employed to measure sonic booms above and within the atmospheric turbulent boundary layer, and the sailplane was positioned to intercept the shock waves between the supersonic airplane and the ground sensors. Sailplane and ground-level sonic boom recordings were used to generate atmospheric turbulence filter functions showing excellent agreement with ground measurements. The sonic boom prediction software PCBoom4 was employed as a preflight planning tool using preflight weather data. The measured data of shock wave directionality, arrival time, and overpressure gave excellent agreement with the PCBoom4-calculated results using the measured aircraft and atmospheric data as inputs. C-weighted acoustic levels generally decreased with increasing height above the ground. A-weighted and perceived levels usually were at a minimum for a height where the elevated microphone pressure rise time history was the straightest, which is a result of incident and ground-reflected shock waves interacting.

Haering, Edward A., Jr.↗

Johnson Space Center's Solar and Wind-Based Renewable Energy System

The NASA Johnson Space Center (JSC) in Houston, Texas has a Sustainability Partnership team that seeks ways for earth-based sustainability practices to also benefit space exploration research. A renewable energy gathering system was installed in 2007 at the JSC Child Care Center (CCC) which also offers a potential test bed for space exploration power generation and remote monitoring and control concepts. The system comprises: 1) several different types of photovoltaic panels (29 kW), 2) two wind-turbines (3.6 kW total), and 3) one roof-mounted solar thermal water heater and tank. A tie to the JSC local electrical grid was provided to accommodate excess power. The total first year electrical energy production was 53 megawatt-hours. A web-based real-time metering system collects and reports system performance and weather data. Improvements in areas of the CCC that were detected during subsequent energy analyses and some concepts for future efforts are also presented.

Vasquez, A.↗

The International Space Weather Initiative

The International Space Weather Initiative (ISWI) is a program of international cooperation aimed at understanding the external drivers of space weather. The ISWI program has its roots in the successful International Heliophysical Year (IHY) program that ran during 2007 - 2009 and will continue with those aspects that directly affect life on Earth. The primary objective of the ISWI program is to advance the space weather science by a combination of instrument deployment, analysis and interpretation of space weather data from the deployed instruments in conjunction with space data, and communicate the results to the public and students. Like the IHY, the ISWI will be a grass roots organization with key participation from national coordinators in cooperation with an international steering committee. This presentation outlines the ISWI program including its organizational aspects and proposed activities. The ISWI observatory deployment and outreach activities are highly complementary to the CAWSES II activities of SCOSTEP.

Nat, Gopalswamy↗

International Space Weather Initiative (ISWI)

The International Space Weather Initiative (ISWI) is an international scientific program to understand the external drivers of space weather. The science and applications of space weather has been brought to prominence because of the rapid development of space based technology that is useful for all human beings. The ISWI program has its roots in the successful International Heliophysical Year (IHY) program that ran during 2007 - 2009. The primary objective of the ISWI program is to advance the space weather science by a combination of instrument deployment, analysis and interpretation of space weather data from the deployed instruments in conjunction with space data, and communicate the results to the public and students. Like the IHY, the ISWI will be a grass roots organization with key participation from national coordinators in cooperation with an international steering committee. This talk outlines the ISWI program including its organization and proposed activities.

Gopalswamy, Nat↗

Optimizing Flight Departure Delay and Route Selection Under En Route Convective Weather

This paper presents a linear Integer Programming model for managing air traffic flow in the United States. The decision variables in the model are departure delays and predeparture reroutes of aircraft whose trajectories are predicted to cross weather-impacted regions of the National Airspace System. The model assigns delays to a set of flights while ensuring their trajectories are free of any conflicts with weather. In a deterministic setting, there is no airborne holding due to unexpected weather incursion in a flight s path. The model is applied to solve a large-scale traffic flow management problem with realistic weather data and flight schedules. Experimental results indicate that allowing rerouting can reduce departure delays by nearly 57%, but it is associated with an increase in total airborne time due to longer routes flown by aircraft. The computation times to solve this problem were significantly lower than those reported in the earlier studies.

Mukherjee, Avijit↗

NASA's STEREO Mission

NASA's STEREO (Solar TErrestrial RElations Observatory) mission consists of two nearly identical spacecraft hosting an array of in situ and imaging instruments for studying the sun and heliosphere. Launched in 2885 and in orbit about the Sun near 1 AU, the spacecraft are now swinging towards the farside of the sun. I will provide the latest information with regards to STEREO space weather data and also recent STEREO research.

Kucera, T. A.↗

Role of Meteorology in Flights of a Solar-Powered Airplane

In the summer of 2001, the Helios prototype solar-powered uninhabited aerial vehicle (UAV) [a lightweight, remotely piloted airplane] was deployed to the Pacific Missile Range Facility (PMRF), at Kauai, Hawaii, in an attempt to fly to altitudes above 100,000 ft (30.48 km). The goal of flying a UAV to such high altitudes has been designated a level-I milestone of the NASA Environmental Research Aircraft and Sensor Technology (ERAST) program. In support of this goal, meteorologists from NASA Dryden Flight Research Center were sent to PMRF, as part of the flight crew, to provide current and forecast weather information to the pilots, mission directors, and planners. Information of this kind is needed to optimize flight conditions for peak aircraft performance and to enable avoidance of weather conditions that could adversely affect safety. In general, the primary weather data of concern for ground and flight operations are wind speeds (see Figure 1). Because of its long wing span [247 ft (.75 m)] and low weight [1,500 to 1,600 lb (about 680 to 726 kg)], the Helios airplane is sensitive to wind speeds exceeding 7 kn (3.6 m/s) at the surface. Also, clouds are of concern because they can block sunlight needed to energize an array of solar photovoltaic cells that provide power to the airplane. Vertical wind shear is very closely monitored in order to prevent damage or loss of control due to turbulence.

Donohue, Casey↗

A Linear Programming Approach to the Development of Contrail Reduction Strategies Satisfying Operationally Feasible Constraints

A class of strategies has been proposed to reduce contrail formation in the United States airspace. A 3D grid based on weather data and the cruising altitude level of aircraft is adjusted to avoid the persistent contrail potential area with the consideration to fuel-efficiency. In this paper, the authors introduce a contrail avoidance strategy on 3D grid by considering additional operationally feasible constraints from an air traffic controller's aspect. First, shifting too many aircraft to the same cruising level will make the miles-in-trail at this level smaller than the safety separation threshold. Furthermore, the high density of aircraft at one cruising level may exceed the workload for the traffic controller. Therefore, in our new model we restrict the number of total aircraft at each level. Second, the aircraft count variation for successive intervals cannot be too drastic since the workload to manage climbing/descending aircraft is much larger than managing cruising aircraft. The contrail reduction is formulated as an integer-programming problem and the problem is shown to have the property of total unimodularity. Solving the corresponding relaxed linear programming with the simplex method provides an optimal and integral solution to the problem. Simulation results are provided to illustrate the methodology.

Wei, Peng↗

Development and Validation of a Computational Model for Predicting the Behavior of Plumes from Large Solid Rocket Motors

Exhaust plumes from large solid rocket motors fired at ATK's Promontory test site carry particulates to high altitudes and typically produce deposits that fall on regions downwind of the test area. As populations and communities near the test facility grow, ATK has become increasingly concerned about the impact of motor testing on those surrounding communities. To assess the potential impact of motor testing on the community and to identify feasible mitigation strategies, it is essential to have a tool capable of predicting plume behavior downrange of the test stand. A software package, called PlumeTracker, has been developed and validated at ATK for this purpose. The code is a point model that offers a time-dependent, physics-based description of plume transport and precipitation. The code can utilize either measured or forecasted weather data to generate plume predictions. Next-Generation Radar (NEXRAD) data and field observations from twenty-three historical motor test fires at Promontory were collected to test the predictive capability of PlumeTracker. Model predictions for plume trajectories and deposition fields were found to correlate well with the collected dataset.

Wells, Jason E.↗

Kennedy Space Center Spaceport Analysis

Until the Shuttle Atlantis' final landing on July 21, 2011, Kennedy Space Center (KSC) served as NASA's main spaceport, which is a launch and landing facility for rockets and spacecraft that are attempting to enter orbit. Many of the facilities at KSC were created to assist the Shuttle Program. One of the most important and used facilities is the Shuttle Landing Facility (SLF), This was the main landing area for the return of the shuttle after her mission in space. · However, the SLF has also been used for a number of other projects including straight-line testing by Gibbs Racing, weather data collection by NOAA, and an airfield for the KSC helicopters. This runway is three miles long with control tower at midfield and a fire department located at the end in care of an emergency. This facility, which was part of the great space race, will continue to be used for historical events as Kennedy begins to commercialize its facilities. KSC continues to be an important spaceport to the government, and it will transform into an important spaceport for the commercial industry as well. During my internship at KSC's Center Planning and Development Directorate, I had the opportunity to be a part of the negotiation team working on the agreement for Space Florida to control the Shuttle Landing Facility. This gave me the opportunity to learn about all the changes that are occurring here at Kennedy Space Center. Through various meetings, I discovered the Master Plan and its focus is to transform the existing facilities that were primarily used for the Shuttle Program, to support government operations and commercial flights in the future. This. idea is also in a new strategic business plan and completion of a space industry market analysis. All of these different documentations were brought to my attention and I. saw how they came together in the discussions of transitioning the SLF to a commercial operator, Space Florida. After attending meetings and partaking in discussions for the SLF Agreement, I formed the idea of a Spaceport Analysis as my over internship project. As previously stated, I had the opportunity to sit in on the market analysis meetings and read through the analysis itself. I suggested the creation of a Strengths Weaknesses Opportunities Threats (SWOT) analysis, which allows an individual to see an overview of the company's strengths and weaknesses alongside any industry opportunities and threats. After discussions with the lead writer of the new strategic business plan and getting approval, I took the action upon myself and created the Kennedy Space Center SWOT Analysis.

Wary, Samantha A.↗

MESA: Message-Based System Analysis Using Runtime Verification

In this paper, we present a novel approach and framework for run-time verication of large, safety critical messaging systems. This work was motivated by verifying the System Wide Information Management (SWIM) project of the Federal Aviation Administration (FAA). SWIM provides live air traffic, site and weather data streams for the whole National Airspace System (NAS), which can easily amount to several hundred messages per second. Such safety critical systems cannot be instrumented, therefore, verification and monitoring has to happen using a nonintrusive approach, by connecting to a variety of network interfaces. Due to a large number of potential properties to check, the verification framework needs to support efficient formulation of properties with a suitable Domain Specific Language (DSL). Our approach is to utilize a distributed system that is geared towards connectivity and scalability and interface it at the message queue level to a powerful verification engine. We implemented our approach in the tool called MESA: Message-Based System Analysis, which leverages the open source projects RACE (Runtime for Airspace Concept Evaluation) and TraceContract. RACE is a platform for instantiating and running highly concurrent and distributed systems and enables connectivity to SWIM and scalability. TraceContract is a runtime verication tool that allows for checking traces against properties specified in a powerful DSL. We applied our approach to verify a SWIM service against several requirements.We found errors such as duplicate and out-of-order messages.

Message-based System↗

Statistical Assessment of Cetacean Stranding Events in Cape Cod Area

Cetacean (whales, dolphins and porpoises) mass strandings are a longstanding mystery in the field of marine biology that continue to be recorded in coastal environments around the world. For each of these events, anywhere from a few to several hundred otherwise healthy animals strand in onshore environments, often for no apparent reason. While the causes of these events remain unclear, anthropogenic and naturogenic mechanisms have been suggested. We present results of an inter-disciplinary study that draws expertise from space weather, marine mammal biology and ecology, and marine mammal stranding response. This study assessed 16 years of cetacean stranding events in the Cape Cod (Massachusetts, USA) area concurrently with a large dataset of meteorological, geophysical, biological, oceanographic and space weather data to produce inferences about possible causes for these unexplained events.

Dolphi↗

Development of a Complete Landsat Evapotranspiration and Energy Balance Archive to Support Agricultural Consumptive Water Use Reporting and Prediction in the Central Valley, CA

Mapping evapotranspiration (ET) from agricultural areas in Californias Central Valley is critical for understanding historical consumptive use of surface and groundwater. In addition, long histories of ET maps provide valuable training information for predictive studies of surface and groundwater demands. During times of drought, groundwater is commonly pumped to supplement reduced surface water supplies in the Central Valley. Due to the lack of extensive groundwater pumping records, mapping consumptive use using satellite imagery is an efficient and robust way for estimating agricultural consumptive use and assessing drought impacts. To this end, we have developed and implemented an algorithm for automated calibration of the METRIC remotely sensed surface energy balance model on NASAs Earth Exchange (NEX) to estimate ET at the field scale. Using automated calibration techniques on the NEX has allowed for the creation of spatially explicit historical ET estimates for the Landsat archive dating from 1984 to the near present. Further, our use of spatial NLDAS and CIMIS weather data, and spatial soil water balance simulations within the NEX METRIC workflow, has helped overcome challenges of time integration between satellite image dates. This historical and near present time archive of agricultural water consumption for the Central Valley will be an extremely useful dataset for water use and drought impact reporting, and predictive analyses of groundwater demands.

valleys↗

TPSAS-NF1676L-29916-DND

The CCMC is a multi-agency partnership to enable, support and perform the research and development for next-generation space science and space weather models. NASA’s CCMC resources support a variety of activities in the US and international space science and engineering communities including - Access to sophisticated space science models - Access to space weather data and models - Applied science support, engineering tools, and program support

Joseph Minow↗

The Past and Future Changes in Climate of the Rice-Wheat Cropping Zone in Punjab, Pakistan

Agriculture is ranked top among Pakistan economic sectors vulnerable to the potential impacts of climate change. The agricultural production system is directly affected by weather inputs (temperature, solar radiation, and rainfall) that are projected to change in future (following increases in carbon dioxide and other greenhouse gasses). Although Climatic extremes such as drought, floods and heat waves, are expected to increase with detrimental consequences for agriculture and livestock production, yet changes in mean climates also pose challenges to sustainable development. This study presents climate change results for five districts within the major rice-wheat productivity zone of Punjab province in Pakistan. The results are focused on RCP8.5 mid-century (2040-2069) scenarios derived from five global climate models (GCMs) output and the Kharif (June-October) and Rabi (November-April) seasons. Analysis of recent historical weather data of Sialkot and Sheikhupura districts shows an increase in minimum temperatures and maximum temperatures and a large variation in rainfall. This temperature change and variability in rainfall are expected to enhance further as we approach 2050s. The mean maximum temperature is projected to increase by 2-2.5 ºC during the rice growing (Kharif) season and 2.4-2.7ºC during the wheat growing (Rabi) season. Rainfall during the rice growing season is more uncertain, with projections indicating an increase of 25%-35 % in the study region, while a minimal change is expected during the Rabi season. Climax of the rice growing season corresponds with the projected increase in monsoon intensity, leaving no doubt about the crop water demand satisfaction. However, a simultaneous increase in the day and night temperature may affect the growth and development of some critical phenological stages and thus could impact final yield.

Climate Change↗

Derivation and Testing of Consumptive Water Use Fraction for Specialty Crops

The Crop Consumptive Use Fraction (CCUF) expresses beneficial water use in the form of seasonal evapotranspiration of applied water (ETAW), relative to total irrigation volume. The metric is an indicator of the efficiency of agricultural water use and is a recommended component for preparation of agricultural water management plans in California. An FAO-56 based web application has been developed to facilitate retrospective evaluation of ETAW, and hence CCUF, at field level. The current application is optimized for prevailing climate in four of the state’s main growing regions: San Joaquin Valley, Sacramento Valley, Central Coast, and North Coast. User inputs include crop type, soil texture, irrigation method, daily irrigation volume, daily rainfall, and seasonal start/stop dates to define the analysis period. Time series of fractional green canopy cover (Fc), based on Landsat and Sentinel-2 Earth-resource satellite observations, are imported from NASA’s Satellite Irrigation Management Support (SIMS) system. Grass reference evapotranspiration (ETo) time series are accessed from Spatial CIMIS (California Irrigation Management Information System). Daily crop height (h) is estimated as a simple function of typical maximum height for the given crop type (from FAO-56) and Fc. A vegetation density coefficient (Kd) is derived from Fc and h. Stomatal control factors during mid-and late-season are applied to tree and vine crops. Typical values for minimum daily relative humidity and mean daily windspeed, derived from historical CIMIS weather data, are used to correct for regional deviations from standard climate (defined as RHmin=45%, windspeed =2m/s). The resulting daily basal crop coefficient (Kcb) represents the ET of a well-watered crop with minimal soil evaporation, relative to ETo. A soil water balance sub-model for the top 0.1 m is used to calculate daily evaporation coefficients (Ke). A second sub-model applies to the root zone to calculate crop water stress coefficients (Ks) and effective precipitation (Pe), which is the fraction of rainfall that is available for crop use. Those coefficients are combined with Kcb and ETo to calculate daily ETc. ETAW is then derived as cumulative ETc less cumulative Pe. For verification purposes, sensor installations were used to measure seasonal ETc in commercial fields for several annual and perennial specialty crops by soil water balance and energy balance methods. Model estimates of seasonal ETc show mean absolute error of <10% compared to the ground measurements.

Derivation↗

A Recursive Multi-step Machine Learning Approach for Airport Configuration Prediction

Airport configuration selection is a complex decision-making process that involves several operational and human factors. In this paper we propose a novel recursive multi-step machine learning (ML) approach to predict airport configuration. The multi-step approach guarantees stability of the predicted configuration by taking as input the configuration predicted at the previous time step. The features of the proposed model include weather data, future arrival and departure counts and current configuration. Due to the importance of arrival and departure counts in predicting the airport configuration, arrival counts are calculated using landing time predictions selected from physics-based landing time predictions available in FAA System Wide Information Management data feeds for each flight. The selection rules were developed and refined to select the most accurate time for different phases of flight. The proposed model predicts the airport configurations up to 6 hours ahead. In this paper we show the predictive performance of the proposed model for six major US airports, including Charlotte Douglas International Airport (CLT), Dallas/Fort Worth International Airport (DFW), John F. Kennedy International Airport (JFK), Newark Liberty International Airport (EWR), LaGuardia Airport (LGA) and Dallas Love Field Airport (DAL). We trained and evaluated models on 2019 and 2020 data in order to study the effect of the pandemic and how changes in traffic patterns affected the performance of the proposed model. Results are compared with a baseline assuming no airport configuration changes. In our results for DFW, we obtained a prediction accuracy of 89.3% for 3 hours ahead prediction, and 82.8% for 6 hours ahead when applied on 2019 data.

machine learning↗