Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Operational forecasting”

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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Stratospheric Analysis and Forecasting in the Northern Winter of 1999/2000: The NASA DAO's GEOS-3 System

An evaluation is presented of the performance in the northern winter 1999/2000 of the GEOS-3 troposphere-stratosphere data assimilation system (DAS). The impacts of the two main input data types are assessed: upper-air soundings (sondes) provide wind and temperature information and satellite-based (Tiros Operational Vertical Sounders: TOVS) give estimates of the thermal structure. It is shown that in the low stratosphere (300-70hPa) the analyses are generally slightly warmer than the sonde data, but colder than the TOVS data; this relationship reverses between 70 and 10 hPa. There are geographical biases, related to the spatial and temporal coverage of the observation types and to the statistical weights assigned to them in the DAS. Forecasts show a tendency to reduce zonal asymmetries in the atmospheric flow and to suppress stratospheric temperature minima. In the DAS, the analysis increments compensate for this, but it leads to important biases in the multi-day forecasts. The analysis increments are as large as the diabatic forcing in the lower polar stratosphere, indicating a substantial model bias. The results provide important insights into the roles of different data types and the circulation model in producing accurate analyses for studies of polar chemistry and physical processes.

Pawson, Steven↗
NASA NTRS1994

National facilities study. Volume 3: Mission and requirements model report

The National Facility Study (NFS) was initiated in 1992 by Daniel S. Goldin, Administrator of NASA as an initiative to develop a comprehensive and integrated long-term plan for future facilities. The resulting, multi-agency NFS consisted of three Task Groups: Aeronautics, Space Operations, and Space Research and Development (R&D) Task Groups. A fourth group, the Engineering and Cost Analysis Task Group, was subsequently added to provide cross-cutting functions, such as assuring consistency in developing an inventory of space facilities. Space facilities decisions require an assessment of current and future needs. Therefore, the two task groups dealing with space developed a consistent model of future space mission programs, operations and R&D. The model is a middle ground baseline constructed for NFS analytical purposes with excursions to cover potential space program strategies. The model includes three major sectors: DOD, civilian government, and commercial space. The model spans the next 30 years because of the long lead times associated with facilities development and usage. This document, Volume 3 of the final NFS report, is organized along the following lines: Executive Summary -- provides a summary view of the 30-year mission forecast and requirements baseline, an overview of excursions from that baseline that were studied, and organization of the report; Introduction -- provides discussions of the methodology used in this analysis; Baseline Model -- provides the mission and requirements model baseline developed for Space Operations and Space R&D analyses; Excursions from the baseline -- reviews the details of variations or 'excursions' that were developed to test the future program projections captured in the baseline; and a Glossary of Acronyms.

Source record↗
NASA NTRSDate not supplied

Impact Assessment of All-Sky TROPICS Microwave Observations on the NASA GEOS Analyses and Forecasts and Progress to Use the Data in the JEDI-GEOS Analysis System

The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of small satellites carrying state-of-art microwave temperature and humidity sounders with 12 channels between 91 GHz and 205 GHz frequency. Including TROPICS-pathfinder, launched on 30 June 2021, five TROPICS CubeSats operate and provide temperature and humidity data to NWP and atmospheric retrieval communities. This study is dedicated to evaluating the impact of the TROPICS satellite constellation microwave observations in numerical weather prediction (NWP) using the NASA Goddard Earth Observing System (GEOS). The TROPICS-01 (TROPICS-Pathfinder), TROPICS-03, TROPICS-05, and TROPICS-06 data in all-sky conditions over the ocean during the period of 25 July 2023 and 6 September 2023 are used for assessing forecast impacts on global NWP analysis and five-day forecasts. A series of experiments are carried out to measure the benefits of assimilating observations from only temperature sounders, water vapor sounders, and both sounders. Statistical analysis of the Observing System Experiments (OSEs) results has shown incremental improvements in global model forecast skills for critical geophysical parameters, including temperature, winds, and geopotential heights. The results demonstrate the potential of the TROPICS-like data to positively impact NWP by adding new information to the current observation and forecast system. In another set of experiments, the TROPICS-03, TROPICS-05, and TROPICS-06 data sets are added to the TROPICS-01 one by one to evaluate the impacts of increasing the revisit rate of TROPICS satellite measurements on NWP analysis for a tropical cyclone’s dynamical and microphysical structures. This study offers important insights into the capabilities of a new generation of small satellite microwave radiometers based on emerging technologies, including their unique measurements at 118 GHz and 205 GHz that are not available in traditional operational microwave sounders. Finally, the efforts to implement these new developments for TROPICS in the JEDI-GEOS atmospheric data assimilation system are in progress, and preliminary results from cycled JEDI-GEOS data assimilation experiments are presented.

Min-Jeong Kim↗
NASA NTRS1994

Interactive visualization of Earth and Space Science computations

Computers have become essential tools for scientists simulating and observing nature. Simulations are formulated as mathematical models but are implemented as computer algorithms to simulate complex events. Observations are also analyzed and understood in terms of mathematical models, but the number of these observations usually dictates that we automate analyses with computer algorithms. In spite of their essential role, computers are also barriers to scientific understanding. Unlike hand calculations, automated computations are invisible and, because of the enormous numbers of individual operations in automated computations, the relation between an algorithm's input and output is often not intuitive. This problem is illustrated by the behavior of meteorologists responsible for forecasting weather. Even in this age of computers, many meteorologists manually plot weather observations on maps, then draw isolines of temperature, pressure, and other fields by hand (special pads of maps are printed for just this purpose). Similarly, radiologists use computers to collect medical data but are notoriously reluctant to apply image-processing algorithms to that data. To these scientists with life-and-death responsibilities, computer algorithms are black boxes that increase rather than reduce risk. The barrier between scientists and their computations can be bridged by techniques that make the internal workings of algorithms visible and that allow scientists to experiment with their computations. Here we describe two interactive systems developed at the University of Wisconsin-Madison Space Science and Engineering Center (SSEC) that provide these capabilities to Earth and space scientists.

Hibbard, William L.↗
NASA NTRS2015

The String Stability of a Trajectory-Based Interval Management Algorithm in the Midterm Airspace

NASA's first Air Traffic Management (ATM) Technology Demonstration (ATD-1) was created to facilitate the transition of mature ATM technologies from the laboratory to operational use. The technologies selected for demonstration are the Traffic Management Advisor with Terminal Metering (TMA-TM), which provides precise time-based scheduling in the terminal airspace; Controller Managed Spacing (CMS), which provides terminal controllers with decision support tools enabling precise schedule conformance; and Interval Management (IM), which consists of flight deck automation that enables aircraft to achieve or maintain a precise spacing interval behind a target aircraft. As the percentage of IM equipped aircraft increases, controllers may provide IM clearances to sequences, or strings, of IM-equipped aircraft. It is important for these strings to maintain stable performance. This paper describes an analytic analysis of the string stability of the latest version of NASA's IM algorithm and a fast-time simulation designed to characterize the string performance of the IM algorithm. The analytic analysis showed that the spacing algorithm has stable poles, indicating that a spacing error perturbation will be reduced as a function of string position. The fast-time simulation investigated IM operations at two airports using constraints associated with the midterm airspace, including limited information of the target aircraft's intended speed profile and limited information of the wind forecast on the target aircraft's route. The results of the fast-time simulation demonstrated that the performance of the spacing algorithm is acceptable for strings of moderate length; however, there is some degradation in IM performance as a function of string position.

Swieringa, Kurt A.↗
NASA NTRS2015

Wind Information Uplink to Aircraft Performing Interval Management Operations

The accuracy of the wind information used to generate trajectories for aircraft performing Interval Management (IM) operations is critical to the success of an IM operation. There are two main forms of uncertainty in the wind information used by the Flight Deck Interval Management (FIM) equipment. The first is the accuracy of the forecast modeling done by the weather provider. The second is that only a small subset of the forecast data can be uplinked to the aircraft for use by the FIM equipment, resulting in loss of additional information. This study focuses on what subset of forecast data, such as the number and location of the points where the wind is sampled should be made available to uplink to the aircraft.

Ahmad, Nashat↗
NASA NTRS2014

Prediction of Adverse Events in Time Series Data Using ACCEPT (Adverse Condition and Critical Event Prediction Toolbox)

Abstract:An open-source toolbox called ACCEPT (Adverse Condition and Critical Event Prediction Toolbox) that operates from within the Matlab programming environment is introduced. The toolbox provides an open source, special-purpose functionality that can be used specifically for the prediction or forecasting of adverse events in time series data. It also provides a single, unifying framework in which to compare a variety of combinations of algorithmic approaches addressing this problem. The architectural framework also offers the flexibility for expansion to accommodate the newest, latest popular regression and detection methods for this particular problem, enabling the development of an infrastructure that can act as a proving ground platform for comparing new techniques to the state of the art. As such, its intention is to act as a catalyst in advancing the state of the art in technologies related to this problem. There are a variety of other toolboxes that offer similar capabilities and features, however they are either more suitable as general purpose machine learning toolboxes or are only available commercially or through agreements. ACCEPT fills that niche by offering visibility into a specific approach for addressing the adverse event prediction problem.

programming environments↗
NASA NTRSDate not supplied

Recent Developments in the Assimilation of Microwave and Radar Observations Into NWP Models

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗
NASA NTRSDate not supplied

Enhancing CRTM All-Sky Simulations and Implementation of A New Active Sensor Module

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗
NASA NTRSDate not supplied

CRTM Microwave Cloud Scattering Lookup Tables and Radar Simulator

Microwave observations play a very important role in improving the weather forecasts. Although these observations are routinely assimilated into NWP models in clear-sky conditions, assimilation of all-sky microwave observations is very limited. Two main factors contributing to this limitation are inaccuracy in the input cloud and hydrometeor profiles used as input to the radiative transfer model and also error in scattering calculations performed by the radiative transfer model itself. The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promise in calculating the scattering properties of particles with different shapes in the microwave frequencies. This presentation focuses on recent advancements in the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system are used to evaluate the scattering improvements. Additionally, the backscattering information from the DDA database was used to implement a radar simulator into CRTM. The radar operator takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗
NASA NTRS2024

Jefferson County Ecological Conservation: Quantifying the Effects of Hydrologic Restoration in the Camas National Wildlife Refuge and Mud Lake Wildlife Management Area

Wetlands in the Camas National Wildlife Refuge and Mud Lake Wildlife Management Area, a rare landscape feature in the Intermountain West, are crucial for migratory birds along the Pacific Flyway, yet these wetlands have experienced a noticeable decline in extent and inundation over the last 40+ years. Partners at the U.S. Fish and Wildlife Service and Idaho Department of Fish and Game have ongoing restoration efforts that are yet to be quantified. To assist these partners, we used NASA Earth observations to quantify change in wetland extent and determine if the restoration projects met the intended impact. The QA_PIXEL band from Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) was used to identify water. Landsat 8 OLI imagery was also used for classifying landcover in ArcGIS Pro for 2016 and 2020 and to forecast landcover in 2060 using TerrSet’s Land Change Modeler. We also compared lidar data from 2011 and 2019 to detect changes in vegetation height, ground elevation, and surface water levels, and Sentinel-2 Multispectral Instrument (MSI) imagery to detect changes in vegetation health. Classification results indicated overall accuracies over 84% and Kappa indices above 0.80, well surpassing random classification performance. From 2016 to 2020 our classifications showed an 825 acre increase in wetland extent, and our forecasted 2060 model showed a 2795 acre decrease. Combining our partners’ knowledge of the area with our analyses, we created a remote sensing workflow to enhance future monitoring and decision-making. This study demonstrated the feasibility of NASA Earth observations in quantifying wetlands, informing restoration projects, and supporting avian conservation.

Cassidy Bromka↗
NASA NTRS2017

Evaluation of Integrated Demand Management Looking into Strategic & Tactical Flow Management

The motivation behind Integrated Demand Management (IDM) research is to explore possible improvements to United States National Airspace System (NAS) performance that could be realized through procedural integration of strategic traffic flow management capabilities, such as the Collaborative Trajectory Options Program (CTOP), and tactical capabilities, such as Time Based Flow Management (TBFM). An initial IDM concept for clear weather operations was developed and evaluated for potential benefits, including efficiency, delay reduction, predictability and throughput, and to identify any major issues that might represent a showstopper for a fielded application. Newark Liberty International Airport (EWR) arrival operations provided a use case for concept development. EWR uses miles-in-trail (MIT) metering to regulate demand into TBFM during high volume operations, and short-haul flights are often penalized with excessive, last-minute ground delays when the overhead stream is saturated. IDM addresses this problem by replacing MIT conditioning with CTOP to better manage the demand delivery to the TBFM entry points. A quasi-real time high-fidelity simulation that would normally involve participants was conducted using heuristic-based procedures that mimicked operators behaviors instead. Five total conditions were compared: two baseline conditions with MIT delivery to TBFM entry points using two different TBFM settings; and three IDM conditions: one with airborne speed control using an Required Time of Arrival (RTA) capability, a second without RTA, and a third with no wind forecast errors. Results suggest that the IDM concept can deliver traffic more efficiently by shifting the delays from airborne to ground for both RTA and non-RTA conditions, while maintaining a target throughput rate. The results also suggest that with good predictability of airport capacity, excessive TBFM ground delay can be minimized by applying more strategic CTOP delay, increasing predictability for the airline operators. Overall, the results indicate that the implementation of an IDM concept under clear weather conditions can improve NAS system performance. Future IDM research aims to expand the concept to address demandcapacity imbalance d severe weather.

Time-Based Flow Management (TBFM)↗
NASA NTRS2009

Cold Season QPF: Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.

Molthan, A. L.↗
NASA NTRS2004

Meteor Outbursts and Storms from the Spacecraft Hazard Perspective

The recent Leonid meteor storms have propelled meteor shower forecasting from an idea into the realm of practical application, invoked several times per year by numerous spacecraft. This paper will describe shower activity predictions, which give zenith hourly rate (ZHR) as a function of time, and how these are translated into spacecraft risks. Common spacecraft meteor shower mitigation strategies will also be discussed, and the important issue as to when to implement such operations considered. It should be noted that, while the recent meteor storms did not result in the loss of a vehicle, there were a few spacecraft anomalies attributed to Leonid strikes, and the nature of these will be commented upon. Finally, we assess the current state of the art in shower forecasting, and take a look "down the road" at some possible outbursts in the near future.

Cooke, William↗
NASA NTRS2010

Developing Empirical Lightning Cessation Forecast Guidance for the Cape Canaveral Air Force Station and Kennedy Space Center

This research addresses the 45th Weather Squadron's (45WS) need for improved guidance regarding lightning cessation at Cape Canaveral Air Force Station and Kennedy Space Center (KSC). KSC's Lightning Detection and Ranging (LDAR) network was the primary observational tool to investigate both cloud-to-ground and intracloud lightning. Five statistical and empirical schemes were created from LDAR, sounding, and radar parameters derived from 116 storms. Four of the five schemes were unsuitable for operational use since lightning advisories would be canceled prematurely, leading to safety risks to personnel. These include a correlation and regression tree analysis, three variants of multiple linear regression, event time trending, and the time delay between the greatest height of the maximum dBZ value to the last flash. These schemes failed to adequately forecast the maximum interval, the greatest time between any two flashes in the storm. The majority of storms had a maximum interval less than 10 min, which biased the schemes toward small values. Success was achieved with the percentile method (PM) by separating the maximum interval into percentiles for the 100 dependent storms.

LDAR (LIGHTNING DETECTION AND RANGING)↗
NASA NTRS1978

On neutrons from the sun

A survey of all the experiments carried out over the past decade to verify theoretical predictions for the observation of solar neutrons is presented and discussed. The conclusions drawn from this discussion are: (1) the Solar Probe Mission is important in order to discover the low energy neutrons of solar origin; (2) this discovery is likely to carry very useful information about the nature, the locale, the lifetime and the mode of operation of the acceleration processes in the solar atmosphere; and (3) this information will lead to a rapid development of the science of solar meteorology and the more rapid forecasting of solar activity, on a long-term basis.

Ahluwalia, H. S.↗