Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Weather 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 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Boundary-Layer Cloud Modeling Challenges on the North Slope of Alaska

The accurate modeling and prediction of cloud base heights is critical for energy balance calculations and aviation operations, alike. Low-level (i.e., boundary-layer) Arctic clouds can be difficult to model, making prediction of formation and dissipation challenging. Primarily mixed-phase, these clouds typically contain low quantities of supercooled liquid water and often slowly precipitate relatively small amounts of moderately and heavily rimed snow particles. While this appears to be the predominant cloudy state on the North Slope of Alaska (NSA), the delicate balance of microphysical, dynamical, radiative, surface coupling, and advective processes can rapidly shift to heavy snow (with various degrees of riming) or to a complete dissipation of the cloud layer without any precipitation, depending on the dominant processes. Here we strive to disentangle these various processes. First, we compare the predictive performances of four different numerical weather models in forecasting the presence and base-heights of low-level clouds: the High-Resolution Rapid Refresh - Alaska (HRRR-AK) model, the Polar Weather Research and Forecasting (Polar WRF) model, the Unified Model (UM), and the European Centre for Medium-range Weather Forecasting (ECMWF) model. Initial results comparing model output at two U.S. Department of Energy Atmospheric Radiation Measurement (AMT) NSA sites, during the fall season in 2019 and 2022, show that the UM slightly outperforms the HRRR-AK in terms of accurately forecasting the presence of a low-level cloud layer (89% of the time). All models have a significant bias of 300 to 800 meters in forecasting cloud base height (lower than is observed); however, the UM and ECMWF models have the lowest biases. Finally, a case study for a particularly challenging April 2017 thin-cloud event is presented, wherein we compare the performance of four different bulk microphysical parameterization schemes using a higher-resolution large eddy simulation (LES) model, the WRF-LES. Initial results show that the Thompson scheme was the only one able to reproduce and sustain a substantial supercooled liquid layer, but it was unable to reproduce the transition from a deep, liquid-rich cloud to a thin layer with moderately and heavily rimed precipitation. This is the first step in linking simulated LES-scale riming processes with those parameterized at a coarser mesoscale model scale. This has important implications for forecasting low-level clouds in an operational environment, given the efficiency of the riming process.

cloud base heights↗
NASA NTRS2007

Washington D.C. Lightning Mapping Array Demonstration Project Risk Reduction for GOES Lightning Mapper Data

A 10-site, ground-based total lightning mapping array (LMA) has been installed in the Washington D.C. metropolitan area in 2006. The total lightning data from DC LMA are being processed in real-time and derived products are being provided to the forecasters of the National Weather Service (NWS) forecast office in Sterling, Virginia. The NWS forecasters are using the products to monitor convective activity along with conventional radar and satellite products. Operational experience with these products is intended to inform decision making in how to best utilize in NWS operations similar data available from the GOES Lightning Mapper. The paper will discuss specifics of the LMA as well as proposed research into use of total lightning data in predicting and warning for cloud-to-ground lightning.

Smith, Stephan B.↗
NASA NTRS2011

Evaluating the Impact of Atmospheric Infrared Sounder (AIRS) Data On Convective Forecasts

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting partners, including a number of National Weather Service (NWS) offices. SPoRT provides real-time NASA products and capabilities to its partners to address specific operational forecast challenges. The mission of SPoRT is to transition observations and research capabilities into operations to help improve short-term weather forecasts on a regional scale. Two areas of focus are data assimilation and modeling, which can to help accomplish SPoRT's programmatic goals of transitioning NASA data to operational users. Forecasting convective weather is one challenge that faces operational forecasters. Current numerical weather prediction (NWP) models that operational forecasters use struggle to properly forecast location, timing, intensity and/or mode of convection. Given the proper atmospheric conditions, convection can lead to severe weather. SPoRT's partners in the National Oceanic and Atmospheric Administration (NOAA) have a mission to protect the life and property of American citizens. This mission has been tested as recently as this 2011 severe weather season, which has seen more than 300 fatalities and injuries and total damages exceeding $10 billion. In fact, during the three day period from 25-27 April, 1,265 storms reports (362 tornado reports) were collected making this three day period one of most active in American history. To address the forecast challenge of convective weather, SPoRT produces a real-time NWP model called the SPoRT Weather Research and Forecasting (SPoRT-WRF), which incorporates unique NASA data sets. One of the NASA assets used in this unique model configuration is retrieved profiles from the Atmospheric Infrared Sounder (AIRS).The goal of this project is to determine the impact that these AIRS profiles have on the SPoRT-WRF forecasts by comparing to a current operational model and a control SPoRT-WRF model that does not contain AIRS profiles.

Kozlowski, Danielle↗
NASA NTRS2009

The UAH/NSSTC Advanced Radar for Meteorological and Operational Research (ARMOR)

The past four years have seen a marked enhancement in meteorological-radar infrastructure and radar-research capability at the University of Alabama-Huntsville (UAH) and National Space Science and Technology Center (NSSTC; a collaborative center supported by UAH, NASA-MSFC and USRA). This enhancement is due in part to the development of the ARMOR C-band dual-polarimetric radar facility (amongst other mobile radar facilities also discussed in this conference). The ARMOR radar, located at Huntsville International Airport, originated as a unique collaboration between university, government and broadcast meteorologists (the very first of its kind relative to concurrent operational, research and broadcast applications of dual-polarimetry). Contributions from each of these entities resulted in the upgrade of a surplus National Weather Service WSR-74C radar to a research-grade C-band polarimetric radar. The initial upgrade of the radar took place in late 2004 with WHNT-TV purchase and installation of a SIGMET (now Vaisala) Antenna Mounted Receiver (AMR), RVP8/RCP8 radar processor/antenna controller, new radome, and a new dual-polarimetric antenna feed. The AMR enabled simultaneous transmit and receive (STSR) capability and hence collection of dual-polarimetric moments. During the initial part of the AMR upgrade the original WSR74C antenna reflector and 250 kW magnetron-transmitter were used. In early 2005, a new 350 kW magnetron transmitter was purchased from Baron Services and installed. In October of 2006 a new high performance parabolic antenna and dual-pol feed (Seavey) were installed together with a new Orbit pedestal. ARMOR Radar control and data delivery are facilitated through the use of T-1 lines that run from the airport to both NSSTC and WHNT-TV in Huntsville. Under current operating protocols radar scanning and product development are completed at NSSTC, though meteorologists at WHNT-TV can also control the radar if desired. In its default scanning configuration the radar is operated 24/7 in an STSR polarimetric rain scan mode alternating with a surveillance scan on a 5-minute cycle; scans separated by 2.5 minutes. Every 2.5 minutes the raw data arrive at NSSTC where they are corrected in real time for attenuation and differential attenuation (using a constrained ZDR/Z-PHI approach) and new products are generated (e.g., rain maps, hydrometeor identification etc.). The raw and derived products are archived at NSSTC and also redistributed locally in real time over the network within NSSTC to the National Weather Service Forecast Office in Huntsville (collocated with NSSTC) for operational use. During periods of interesting weather the radar is often operated in full, sector, or RHI volume modes from NSSTC and coincident with UAH mobile radar or NWS NEXRAD radar platforms as needed.

Petersen, Walter A.↗
NASA NTRS2005

An Analysis of Peak Wind Speed Data from Collocated Mechanical and Ultrasonic Anemometers

This study focuses on a comparison of peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. The legacy mechanical wind instruments on CCAFS/KSC and VAFB weather towers are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. The wind tower networks on KSC/CCAFS and VAFB have 41 and 27 towers, respectively. Launch Weather Officers, forecasters, and Range Safety analysts at both locations need to understand the performance of the new wind sensors for a myriad of reasons that include weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The Legacy sensors measure wind speed and direction mechanically. The ultrasonic RSA sensors have no moving parts. Ultrasonic sensors were originally developed to measure very light winds (Lewis and Dover 2004). The technology has evolved and now ultrasonic sensors provide reliable wind data over a broad range of wind speeds. However, because ultrasonic sensors respond more quickly than mechanical sensors to rapid fluctuations in speed, characteristic of gusty wind conditions, comparisons of data from the two sensor types have shown differences in the statistics of peak wind speeds (Lewis and Dover 2004). The 45th Weather Squadron (45 WS) and the 30 WS requested the Applied Meteorology Unit (AMU) to compare data from RSA and Legacy sensors to determine if there are significant differences in peak wind speed information from the two systems.

Short, David A.↗
NASA NTRS2016

Risk-Hedged Approach for Re-Routing Air Traffic Under Weather Uncertainty

This presentation corresponds to: our paper explores a new risk-hedged approach for re-routing air traffic around forecast convective weather. In this work, flying through a more likely weather instantiation is considered to pose a higher level of risk. Current operational practice strategically plans re-routes to avoid only the most likely (highest risk) weather instantiation, and then tactically makes any necessary adjustments as the weather evolves. The risk-hedged approach strategically plans re-routes by minimizing the risk-adjusted path length, incorporating multiple possible weather instantiations with associated likelihoods (risks). The resulting model is transparent and is readily analyzed for realism and treated with well-understood shortest-path algorithms. Risk-hedged re-routes are computed for some example weather instantiations. The main result is that in some scenarios, relative to an operational-practice proxy solution, the risk-hedged solution provides the benefits of lower risk as well as shorter path length. In other scenarios, the benefits of the risk-hedged solution are ambiguous, because the solution is characterized by a tradeoff between risk and path length. The risk-hedged solution can be executed in those scenarios where it provides a clear benefit over current operational practice.

air traffic routing↗
NASA NTRS2012

How are Space Weather and Space Climate Connected to Solar Phenomena?

Many aspects of modern society are susceptible to space weather effects. Pertinent space weather effects include high-energy electromagnetic and particle radiation, changes of atmospheric drag, reduction of GPS accuracy or complete loss of GPS signals, communication outages, and the generation of potentially harmful DC currents in our electric power grid. Beginning in the early 1990s, researchers and government have been increasingly aware of the need to understand the causes of space weather, and to find ways to mitigate deleterious effects associated with it. New research and development programs have been created to address space weather primarily at NASA but also at other agencies. This investment has been very fruitful by generating a new class of entirely new space weather specification and forecast capabilities. This presentation provides an overview of space weather causes and effects, as well as of research and development to forecast and mitigate space weather effects. It will include a discussion of modern space weather analysis and forecasting, and conclude by pointing out paths into the future.

Hesse, Michael↗
NASA NTRS2002

Climate Prediction Sees Future Despite Chaos: Researchers Outside NASA use NCCS Resources for Studies

The air on this mostly sunny January day is crisp and the wind is blustery. The morning's National Weather Service 6-hour forecast had accurately predicted these conditions for the Baltimore-Washington area and the 2-3 day extended outlook was almost perfect. The previous week, the National Center for Environmental Prediction's (NCEP) 6-10 day temperature and precipitation outlook for the general trends for the' region was correct as well. However, no forecast could have predicted specific details about this day. It is 28.5 F in the sunshine bright enough for dark sunglasses, and windy enough to blow off a hat. Such details are impossible to foresee with any accuracy and are outside the scope of routine weather prediction. Equally difficult is accurately forecasting weather beyond about 2 weeks.

Source record↗
NASA NTRS2002

The North Alabama Lightning Mapping Array: Recent Results and Future Prospects

The North Alabama Lightning Mapping Array became operational in November 2001 as a principal component of a severe weather test bed to infuse new science and technologies into the short-term forecasting of severe and hazardous weather and the warning decision-making process. The LMA project is a collaboration among NASA scientists, National Weather Service (NWS) weather forecast offices (WFOs), emergency managers, and other partners. The time rate-of-change of storm characteristics and life-cycle trending are accomplished in real-time through the second generation Lightning Imaging Sensor Data Applications Display (LISDAD II) system, initially developed in T997 through a collaboration among NASA/MSFC, MIT/Lincoln Lab and the Melbourne, FL WFO. LISDAD II is now a distributed decision support system with a JAVA-based display application that allows anyone, anywhere to track individual storm histories within the Tennessee Valley region of the southeastern U.S. Since the inauguration of the LMA there has been an abundance of severe weather. During 23-24 November 2001, a major tornado outbreak was monitored by LMA in its first data acquisition effort (36 tornadoes in Alabama). Since that time the LMA has collected a vast amount of data on hailstorms and damaging wind events, non-tornadic supercells, and ordinary non-severe thunderstorms. In this paper we provide an overview of LMA observations and discuss future prospects for improving the short-term forecasting of convective weather.

Goodman, S. J.↗
NASA NTRS2003

Transition from Research to Operations: Assessing Value of Experimental Forecast Products within the NWSFO Environment

The NASA Short-term Prediction Research and Transition (SPoRT) Center seeks to accelerate the infusion of NASA Earth Science Enterprise (ESE) observations, data assimilation and modeling research into NWS forecast operations and decision-making. To meet long-term program expectations, it is not sufficient simply to give forecasters sophisticated workstations or new forecast products without fully assessing the ways in which they will be utilized. Close communication must be established between the research and operational communities so that developers have a complete understanding of user needs. In turn, forecasters must obtain a more comprehensive knowledge of the modeling and sensing tools available to them. A major goal of the SPoRT Program is to develop metrics and conduct assessment studies with NWS forecasters to evaluate the impacts and benefits of ESE experimental products on forecast skill. At a glance the task seems relatively straightforward. However, performing assessment of experimental products in an operational environment is demanding. Given the tremendous time constraints placed on NWS forecasters, it is imperative that forecaster input be obtained in a concise unobtrusive manor. Great care must also be taken to ensure that forecasters understand their participation will eventually benefit them and WFO operations in general. Two requirements of the assessment plan developed under the SPoRT activity are that it 1) Can be implemented within the WFO environment; and 2) Provide tangible results for BOTH the research and operational communities. Supplemental numerical quantitative precipitation forecasts (QPF) were chosen as the first experimental SPoRT product to be evaluated during a Pilot Assessment Program conducted 1 May 2003 within the Huntsville AL National Weather Service Forecast Office. Forecast time periods were broken up into six- hour bins ranging from zero to twenty-four hours. Data were made available for display in AWIPS on an operational basis so they could be efficiently incorporated into the forecast process. The methodology used to assess the value of experimental QPFs compared to available operational products is best described as a three-tier approach involving both forecasters and research scientists. Tier-one is a web-based survey completed by duty forecasters on the aviation and public desks. The survey compiles information on how the experimental product was used in the forecast decision making process. Up to 6 responses per twenty-four hours can be compiled during a precipitation event. Tier-two consists of an event post mortem and experimental product assessment performed daily by the NASA/NWS Liaison. Tier-three is a detailed breakdown/analysis of specific events targeted by either the NWS SO0 or SPoRT team members. The task is performed by both NWS and NASA research scientists and may be conducted once every couple of months. The findings from the Pilot Assessment Program will be reported at the meeting.

Lapenta, William M.↗
NASA NTRS2010

Projected Applications of a "Climate in a Box" Computing System at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

The NASA Short-term Prediction Research and Transition (SPoRT) Center focuses on the transition of unique observations and research capabilities to the operational weather community, with a goal of improving short-term forecasts on a regional scale. Advances in research computing have lead to "Climate in a Box" systems, with hardware configurations capable of producing high resolution, near real-time weather forecasts, but with footprints, power, and cooling requirements that are comparable to desktop systems. The SPoRT Center has developed several capabilities for incorporating unique NASA research capabilities and observations with real-time weather forecasts. Planned utilization includes the development of a fully-cycled data assimilation system used to drive 36-48 hour forecasts produced by the NASA Unified version of the Weather Research and Forecasting (WRF) model (NU-WRF). The horsepower provided by the "Climate in a Box" system is expected to facilitate the assimilation of vertical profiles of temperature and moisture provided by the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard NASA s Aqua and Terra satellites provide high-resolution sea surface temperatures and vegetation characteristics. The development of MODIS normalized difference vegetation index (NVDI) composites for use within the NASA Land Information System (LIS) will assist in the characterization of vegetation, and subsequently the surface albedo and processes related to soil moisture. Through application of satellite simulators, NASA satellite instruments can be used to examine forecast model errors in cloud cover and other characteristics. Through the aforementioned application of the "Climate in a Box" system and NU-WRF capabilities, an end goal is the establishment of a real-time forecast system that fully integrates modeling and analysis capabilities developed within the NASA SPoRT Center, with benefits provided to the operational forecasting community.

Jedlovec, Gary J.↗
NASA NTRS1985

A new convective parameterization scheme for global models

A convective adjustment scheme is presented for parameterization of the vertical temperature and moisture structure for large-scale numerical weather models. The temperature and moisture structure is adjusted toward observed quasi-equilibrium structures to maintain a realistic vertical temperature and moisture structure in grid-scale global models during convection. Two reference thermodynamic structures are modeled analytically to account for shallow and deep convection. The thermodynamic structure obtained is permitted to change as a function of large-scale advective terms, radiation and surface fluxes. The reference profiles are applied when an energy integral provides a description of the shallow or deep convective processes occurring. Comparisons with GATE, BOMEX and ATEX data and a 10 day forecast for weather over the tropical ocean illustrate the climate and precipitation forecast accuracy improvements available with the adjustment scheme relative to standard parameterization schemes.

Miller, M. J.↗
NASA NTRS2021

Assimilation of Lidar Planetary Boundary Layer Height Observations

Lidar backscatter and wind retrievals of the planetary boundary layer height (PBLH) are assimilated into 22 hourly forecasts from the NASA Unified - Weather and Research Forecast (NU-WRF) model during the Plains Elevated Convection Convection at Night (PECAN) campaign on July 11, 2015 in Greensburg, Kansas, using error statistics collected from the model profiles to compute the necessary covariance matrices. Two separate forecast runs using different PBL physics schemes were employed, and comparisons with 6 independent radiosonde profiles were made for each run. Both of the forecast runs accurately predicted the PBLH and the state variable profiles within the planetary boundary layer during the early morning, and the assimilation had a small impact during this time. In the late afternoon, the forecast runs showed decreased accuracy as the convective boundary layer developed. However, assimilation of the Doppler lidar PBLH observations were found to improve the temperature and V velocity profiles relative to independent radiosonde profiles. Water vapor was overcorrected, leading to increased differences with independent data. Errors in the U velocity were made slightly larger. The computed forecast error covariances between the PBLH and state variables were found to rise in the late afternoon, leading to the larger improvements in the afternoon. This work represents the first effort to assimilate PBLH into forecast states using ensemble methods.

Andrew Tangborn↗
NASA NTRS2000

STS-106 Countdown Status Briefing

George Diller, NASA Public Affairs, introduces Jeff Spaulding, NASA Test Director, Scott Higginbotham, KSC Payload Manager, and Ed Priselac, Shuttle Weather Officer. Mr. Spaulding discusses the successful countdown thus far and some of the prelaunch activities. Mr. Higginbotham describes the stow operations and possible changes in the payload configuration. Mr. Priselac forecasts good weather for the upcoming launch. The men then answer questions from the press.

Source record↗
NASA NTRS2004

Analysis of Droplet Size during the Ice Accumulation Phase Of Flight Testing

There are numerous hazards associated with air travel. One of the most serious dangers to the pilot and passengers safety is the result of flying into conditions which are conducive to the formation of ice on the surface of an aircraft. Being a pilot myself I am very aware of the dangers that Icing can pose and the effects it can have on an airplane. A couple of the missions of the Icing branch is to make flying safer with more research to increase our knowledge of how ice effects the aerodynamics of an airfoil, and to increase are knowledge of the weather for better forecasting. The Icing Branch uses three different tools to determine the aerodynamic affects that icing has on a wing. The Icing research tunnel is an efficient way to test various airfoils in a controlled setting. To make sure the data received from the wind tunnel is accurate the Icing branch conducts real flight tests with the DHC-6 Twin Otter. This makes sure that the methods used in the wind tunnel accurately model what happens on the actual aircraft. These two tools are also compared to the LEWICE code which is a program that models the ice shape that would be formed on an airfoil in the particular weather conditions that are input by the user. One benefit of LEWICE is that it is a lot cheaper to run than the wind tunnel or flight tests which make it a nice tool for engineers designing aircraft that don t have the money to spend on icing research. Using all three of these tools is a way to cross check the data received from one and check it against the other two. industries, but it is also looked at by weather analysts who are trying to improve forecasting methods. The best way to avoid the troubles of icing encounters is to not go into it in the first place. By looking over the flight data the analyst can determine which conditions will most likely lead to an icing encounter and then this information will aid forecasters when briefing the pilots on the weather conditions. am looking at the weather data from certain flights and analyzing the type of precipitation that the plane is flying through. During flight tests there is a probe on the bottom of the aircraft that gathers information on the size and shape of the particles that it is flying through. The data can then be viewed on a computer. After grouping the weather into certain groups we can then pick certain groups which we think should be analyzed farther. The goal is to remove all the ice particles because they do not contribute to the icing on an aircraft. We use a 2D analyzer which measures the droplet size and categorizes the drops into bins of certain sizes. We can then look at what the characteristics of the weather that we were flying through such as the temperature and dew point and compare this with the size of the drops that the 2D analyzer measured. We can then look at what type and shape of ice that formed on the wing during this time period. Having this data will help us to reproduce these conditions using LEWICE and the wind tunnel. Having consistency among the tests will make things more accurate. With respect to weather forecasting we will be able to learn which conditions can lead to icing. Better accuracy in weather reporting will lead to fewer run-ins with icing which will also lead to fewer accidents.

Miller, Eric James↗
NASA NTRS2011

Upgrade Summer Severe Weather Tool

The goal of this task was to upgrade to the existing severe weather database by adding observations from the 2010 warm season, update the verification dataset with results from the 2010 warm season, use statistical logistic regression analysis on the database and develop a new forecast tool. The AMU analyzed 7 stability parameters that showed the possibility of providing guidance in forecasting severe weather, calculated verification statistics for the Total Threat Score (TTS), and calculated warm season verification statistics for the 2010 season. The AMU also performed statistical logistic regression analysis on the 22-year severe weather database. The results indicated that the logistic regression equation did not show an increase in skill over the previously developed TTS. The equation showed less accuracy than TTS at predicting severe weather, little ability to distinguish between severe and non-severe weather days, and worse standard categorical accuracy measures and skill scores over TTS.

Watson, Leela↗