Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Weather Research and 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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Lightning Tracking Tool for Assessment of Total Cloud Lightning within AWIPS II

Total lightning (intra‐cloud and cloud‐to‐ground) has been widely researched and shown to be a valuable tool to aid real‐time warning forecasters in the assessment of severe weather potential of convective storms. The trend of total lightning has been related to the strength of a storm's updraft. Therefore a rapid increase in total lightning signifies the strengthening of the parent thunderstorm. The assessment of severe weather potential occurs in a time limited environment and therefore constrains the use of total lightning. A tool has been developed at NASA's Short‐term Prediction Research and Transition (SPoRT) Center to assist in quickly analyzing the total lightning signature of multiple storms. The development of this tool comes as a direct result of forecaster feedback from numerous assessments requesting a real‐time display of the time series of total lightning. This tool also takes advantage of the new architecture available within the AWIPS II environment. SPoRT's lightning tracking tool has been tested in the Hazardous Weather Testbed (HWT) Spring Program and significant changes have been made based on the feedback. In addition to the updates in response to the HWT assessment, the lightning tracking tool may also be extended to incorporate other requested displays, such as the intra‐cloud to cloud‐to‐ground ratio as well as incorporate the lightning jump algorithm.

Burks, Jason E.↗
NASA NTRS2003

Use of MODIS/AIRS Direct Broadcast Data for Short Term Weather Forecasting

Operational weather forecasting relies heavily on real time data and modeling products for forecast preparation and dissemination of significant weather information to the public. The key to this success is access to real time data and integration of the data and products into weather decision support systems. NASA's Short-term Prediction Research and Transition (SPORT) Program has demonstrated this capability with MODIS and AIRS data through several local NWS Forecast Offices. This presentation will describe the use of real time EOS Direct Broadcast (DB) data in local weather forecast operations, highlight the utility of real time data from the EOS DB systems, and provide insight into how EOS DB data can have the most impact on the weather forecast community.

Jedlovec, Gary↗
NASA NTRS2011

Description and Status of the North Alabama Lightning Mapping Array

The North Alabama Lightning Mapping Array (LMA) is a network LMA detectors that detects and maps lightning using VHF radiation (TV Channel 5) in a region centered about Huntsville, Alabama that includes North Alabama, Central Tennessee and parts of Georgia and Mississippi. The North Alabama LMA has been in operation since late 2001, and has been providing real time data to regional National Weather Service (NSF) Weather Forecast Offices (WFOs) since mid 2003 through the NASA Short-term Prediction Research and Transition (SPoRT) center. Data from this network (as well as other from other LMA systems) are now being used to create proxy Geostationary Lightning Mapper (GLM) data sets for GOES-R risk reduction and algorithm development activities. In addition, since spring 2009 data are provided to the Storm Prediction Center in support of Hazardous Weather Testbed and GOES-R Proving Ground activities during the Spring Program. Description, status and plans will be discussed.

Blakeslee, Richard J.↗
DOE OSTI2023

Use of Shallow Ice Core Measurements to Evaluate and Constrain 1980–1990 Global Reanalyses of Ice Sheet Precipitation Rates

Abstract Sea‐level rise (SLR) projections by Earth System Models (ESMs) depend on ice sheet surface mass balances. Accurate, global atmosphere reanalyses would be ideal for providing equilibrated ice sheet model initial conditions in fully coupled ESM simulations. Here we present the first evaluation of 1980–1990 global reanalysis precipitation over Greenland and Antarctica that uses independent observations of net accumulation rates derived from shallow ice cores. Precipitation distributions from both the European Centre for Medium‐Range Weather Forecast's Reanalysis (ERA5) and the Modern‐Era Retrospective Analysis for Research and Applications (MERRA‐2) are highly correlated with contemporaneous co‐located net accumulation rates from Greenland ( r 2 > 0.95) and West Antarctica ( r 2 > 0.7). Three other commonly used reanalyses (WFDE5, CRUNCEP, and GSWP3) exhibit significantly weaker correlations on one or both ice sheets. Our findings imply that ESMs should use ERA5 or MERRA‐2 in data‐forced simulations to validate ice sheet model dynamics and precondition firn for SLR projections.

Schneider, Adam↗
DOE OSTI2026

The role of equatorial waves in triggering precipitation extremes in the Maritime Continent

This review offers a comprehensive analysis of convectively coupled equatorial waves (CCEWs) and their pivotal role in driving precipitation extremes across the Maritime Continent. It examines the current understanding of CCEWs, evaluates the performance of numerical models and forecasting techniques in predicting these phenomena, and pinpoints critical areas for improvement. The discussion centers on three key types of equatorial waves: equatorial Rossby waves, Kelvin waves, and mixed Rossby–gravity waves. By connecting scientific insights with practical forecasting applications, the review sheds light on the challenges of predicting these waves while identifying opportunities to advance both fundamental knowledge and forecasting accuracy. Designed as an educational resource, it targets operational forecasting centers, meteorologists, and researchers, aiming to enhance the prediction of extreme weather events in the region.

Maritime Continent↗
NASA NTRS2010

Regional Model Nesting Within GFS Daily Forecasts Over West Africa

The study uses the RM3, the regional climate model at the Center for Climate Systems Research of Columbia University and the NASA/Goddard Institute for Space Studies (CCSR/GISS). The paper evaluates 30 48-hour RM3 weather forecasts over West Africa during September 2006 made on a 0.5 grid nested within 1 Global Forecast System (GFS) global forecasts. September 2006 was the Special Observing Period #3 of the African Monsoon Multidisciplinary Analysis (AMMA). Archived GFS initial conditions and lateral boundary conditions for the simulations from the US National Weather Service, National Oceanographic and Atmospheric Administration were interpolated four times daily. Results for precipitation forecasts are validated against Tropical Rainfall Measurement Mission (TRMM) satellite estimates and data from the Famine Early Warning System (FEWS), which includes rain gauge measurements, and forecasts of circulation are compared to reanalysis 2. Performance statistics for the precipitation forecasts include bias, root-mean-square errors and spatial correlation coefficients. The nested regional model forecasts are compared to GFS forecasts to gauge whether nesting provides additional realistic information. They are also compared to RM3 simulations driven by reanalysis 2, representing high potential skill forecasts, to gauge the sensitivity of results to lateral boundary conditions. Nested RM3/GFS forecasts generate excessive moisture advection toward West Africa, which in turn causes prodigious amounts of model precipitation. This problem is corrected by empirical adjustments in the preparation of lateral boundary conditions and initial conditions. The resulting modified simulations improve on the GFS precipitation forecasts, achieving time-space correlations with TRMM of 0.77 on the first day and 0.63 on the second day. One realtime RM3/GFS precipitation forecast made at and posted by the African Centre of Meteorological Application for Development (ACMAD) in Niamey, Niger is shown.

Druyan, Leonard M.↗
NASA NTRS2014

AWIPS II Application Development, a SPoRT Perspective

The National Weather Service (NWS) is deploying its next‐generation decision support system, called AWIPS II (Advanced Weather Interactive Processing System II). NASA's Short‐term Prediction Research and Transition (SPoRT) Center has developed several software 'plug‐ins' to extend the capabilities of AWIPS II. SPoRT aims to continue its mission of improving short‐term forecasts by providing NASA and NOAA products on the decision support system used at NWS weather forecast offices (WFOs). These products are not included in the standard Satellite Broadcast Network feed provided to WFOs. SPoRT has had success in providing support to WFOs as they have transitioned to AWIPS II. Specific examples of transitioning SPoRT plug‐ins to WFOs with newly deployed AWIPS II systems will be presented. Proving Ground activities (GOES‐R and JPSS) will dominate SPoRT's future AWIPS II activities, including tool development as well as enhancements to existing products. In early 2012 SPoRT initiated the Experimental Product Development Team, a group of AWIPS II developers from several institutions supporting NWS forecasters with innovative products. The results of the team's spring and fall 2013 meeting will be presented. Since AWIPS II developers now include employees at WFOs, as well as many other institutions related to weather forecasting, the NWS has dealt with a multitude of software governance issues related to the difficulties of multiple remotely collaborating software developers. This presentation will provide additional examples of Research‐to‐Operations plugins, as well as an update on how governance issues are being handled in the AWIPS II developer community.

Burks, Jason E.↗
DOE OSTI2024

Incorrect computation of Madden-Julian oscillation prediction skill

The Madden–Julian oscillation (MJO) is a major tropical weather system and one of the largest sources of predictability for subseasonal-to-seasonal weather forecasts. Skillful prediction of the MJO has been a highly active area of research due to its large socio-economic impacts. Silini et al., herein S21, developed a machine learning model to predict the MJO, which they claimed to have an MJO prediction skill of 26–27 days over all seasons and 45 days for December–February (DJF) winter. If true, this would make the skill of their model competitive with that of the state-of-the-art dynamical MJO prediction systems at 20–35 days. However, here we show that the MJO prediction was calculated incorrectly in S21, which spuriously increased the performance of their model. Correctly computed skill of their model was substantially lower than that reported in S21; the skill for all seasons drops to 11–12 days and the skill for forecasts initialized during DJF drops to 15 days. Our findings clarify that the S21 machine learning model is not competitive with state-of-the-art numerical weather prediction models in predicting the MJO.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

A study of the effect of synoptic scale processes in GCM modelling

Research was conducted to help modeling groups at NASA to develop better weather forecasting and general circulation models (GCM) for activities relating to the meteorological uses of satellite data. The focus was on the physical processes that were being simulated by models: radiative effects and latent heat release associated with clouds; orographic influences; and heat transfer at the ocean and ice surfaces. An attempt was made to deduce the role of diabatic heating in North Atlantic cyclogenesis and in the global heat budget. Inferences were made in four studies: heat budget statistics from GCM assimilations; dynamics of north Atlantic cyclones; Cage-type energy budget calculations; and grid scale cloud formation. Mechanisms that were responsible for the variability and structure of the atmospheric on a hemispheric scale were studied by a hybrid of statistical analysis and theoretical modeling. Variability and structure are both related to synoptic scale processes through baroclinic and barotropic energy transformations.

Herman, Gerald F.↗
NASA NTRS2006

Advanced Air Data Systems for Commercial Aircraft

It is possible to get a crude estimate of wind speed and direction while driving a car at night in the rain, with the motion of the raindrop reflections in the headlights providing clues about the wind. The clues are difficult to interpret, though, because of the relative motions of ground, car, air, and raindrops. More subtle interpretation is possible if the rain is replaced by fog, because the tiny droplets would follow the swirling currents of air around an illuminated object, like, for example, a walking pedestrian. Microscopic particles in the air (aerosols) are better for helping make assessments of the wind, and reflective air molecules are best of all, providing the most refined measurements. It takes a bright light to penetrate fog, so it is easy to understand how other factors, like replacing the headlights with the intensity of a searchlight, can be advantageous. This is the basic principle behind a lidar system. While a radar system transmits a pulse of radiofrequency energy and interprets the received reflections, a lidar system works in a similar fashion, substituting a near-optical laser pulse. The technique allows the measurement of relative positions and velocities between the transmitter and the air, which allows measurements of relative wind and of air temperature (because temperature is associated with high-frequency random motions on a molecular level). NASA, as well as the National Oceanic and Atmospheric Administration (NOAA), have interests in this advanced lidar technology, as much of their explorative research requires the ability to measure winds and turbulent regions within the atmosphere. Lidar also shows promise for providing warning of turbulent regions within the National Airspace System to allow commercial aircraft to avoid encounters with turbulence and thereby increase the safety of the traveling public. Both agencies currently employ lidar and optical sensing for a variety of weather-related research projects, such as analyzing the water content of snow and forecasting lightning.

Source record↗
NASA NTRS2012

Transforming Community Access to Space Science Models

Researching and forecasting the ever changing space environment (often referred to as space weather) and its influence on humans and their activities are model-intensive disciplines. This is true because the physical processes involved are complex, but, in contrast to terrestrial weather, the supporting observations are typically sparse. Models play a vital role in establishing a physically meaningful context for interpreting limited observations, testing theory, and producing both nowcasts and forecasts. For example, with accurate forecasting of hazardous space weather conditions, spacecraft operators can place sensitive systems in safe modes, and power utilities can protect critical network components from damage caused by large currents induced in transmission lines by geomagnetic storms.

MacNeice, Peter↗
NASA NTRS2013

Suomi NPP VIIRS Prelaunch and On-orbit Geometric Calibration and Characterization

The Visible Infrared Imager Radiometer Suite (VIIRS) sensor was launched 28 October 2011 on the Suomi National Polarorbiting Partnership (SNPP) satellite. VIIRS has 22 spectral bands covering the spectrum between 0.412 m and 12.01 m, including 16 moderate resolution bands (M-bands) with a spatial resolution of 750 m at nadir, 5 imaging resolution bands (I-bands) with a spatial resolution of 375 m at nadir, and 1 day-night band (DNB) with a near-constant 750 m spatial resolution throughout the scan. These bands are located in a visible and near infrared (VisNIR) focal plane assembly (FPA), a short- and mid-wave infrared (SWMWIR) FPA and a long-wave infrared (LWIR) FPA. All bands, except the DNB, are co-registered for proper environmental data records (EDRs) retrievals. Observations from VIIRS instrument provide long-term measurements of biogeophysical variables for climate research and polar satellite data stream for the operational communitys use in weather forecasting and disaster relief and other applications. Well Earth-located (geolocated) instrument data is important to retrieving accurate biogeophysical variables. This paper describes prelaunch pointing and alignment measurements, and the two sets of on-orbit correction of geolocation errors, the first of which corrected error from 1,300 m to within 75 m (20 I-band pixel size), and the second of which fine tuned scan angle dependent errors, bringing VIIRS geolocation products to high maturity in one and a half years of the SNPP VIIRS on-orbit operations. Prelaunch calibration and the on-orbit characterization of sensor spatial impulse responses and band-to-band co-registration (BBR) are also described.

Geolocation↗
NASA NTRS2018

Improving NASA GEOS Atmospheric CO2 Simulations by Calibrating CASA Surface Fluxes with an Empirical Sink

With the adoption of the Paris climate accord, efforts to monitor and understand both anthropogenic and natural carbon sources and sinks are increasing across the world. Given their low latency and global coverage, satellite observations of atmospheric carbon dioxide (CO2) are poised to make important contributions to this field. The combination of satellite data and high resolution global models can be used to monitor changes in carbon fluxes and to evaluate the consistency of nationally reported emissions estimates in support of multiple stakeholder communities. However, a consistent challenge to such work has been the high latency of surface carbon flux estimates, which are often not available for a year or more. This presentation describes the construction of surface carbon flux estimates meant to improve the near real time simulation of atmospheric CO2 with NASA's Goddard Earth Observing System (GEOS) general circulation model. The surface flux estimates begin with a collection of bottom-up fluxes which incorporate satellite measurements in their construction, e.g. vegetation indices in the Carnegie-Ames-Stanford Approach (CASA) and nighttime lights in the Open-source Data Inventory for Anthropogenic CO2 (ODIAC). From there, we take the additional step of using an empirical sink to calibrate terrestrial net biospheric exchange (NBE) to estimated values from atmospheric inversion systems. This approach removes a known, systematic bias in predicted atmospheric mixing ratios. Using these fluxes in a free running simulation, the model is able to reproduce in situ measurements with the same skill as when it uses gridded fluxes from a flux inversion system. Using these fluxes as a prior in an assimilation system, e.g. one incorporating retrievals of column CO2 from the Orbiting Carbon Observatory 2 (OCO-2), allows the analysis to capture variability in CO2 on scales that would be missed otherwise. This approach supports NASA's capability to forecast atmospheric CO2 up to two weeks in advance by leveraging a GEOS system used to produce quasi-operational weather analyses and forecasts, providing a valuable new tool to the carbon monitoring research and applications communities.

Weir, B.↗
NASA NTRS2016

A Multi-Sensor Water Vapor, Temperature and Cloud Climate Data Record: Status of Our MEaSUREs 2012 Project

- Our primary objectives: Incorporate all A-Train water vapor, including small-scale, horizontal and vertical water vapor structure from MODIS (Moderate Resolution Imaging Spectroradiometer) and GPS (Global Positioning System); Use MODIS cloud classification that is collocated at the pixel-scale over the full AIRS/AMSU (Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit) swath; Extend summaries to PDFs (Probability Distribution Functions)/higher order moments of water vapor sorted by cloud classes; Establish robust, scale-dependent statistical relationships between cloud, temperature, and water vapor PDFs for the climate modeling community. - We will also: Update our current data record to new CloudSat/CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) cloud classification; Provide merged AIRS and MLS (Microwave Limb Sounder) water vapor profiles using averaging kernels; Include temperature and water vapor from models (ECMWF - European Centre for Medium-Range Weather Forecasts) and re-analyses (MERRA - Modern Era-Retrospective Analysis for Research and Applications); Classify METOP-A (Meteorological Operational Satellite-A) and NOAA (National Oceanic and Atmospheric Administration) satellite water vapor with AVHRR (Advanced Very High Resolution Radiometer) during SNOs (Solar Neutrino Oscillations); Compare with the NVAP-M (re-analysis and extension of the NASA Water Vapor Project (NVAP)) water vapor climatologies; Use existing data sources and mature algorithms, and document processing algorithms.

Fetzer, Eric↗
DOE OSTI2025

Arctic extreme precipitation changes from 1980 to 2022 in response to sea ice decline and enhanced atmospheric rivers

Arctic extreme precipitation (EP) broadly impacts permafrost degradation, glacier and snow cover changes, and ice sheet mass balance as well as ecosystems. However, investigation of EP spatiotemporal variations over the Arctic remains challenging, and their primary drivers are still poorly understood. Performance estimation of three state-of-the-art reanalysis products (Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA-5), and Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2)) against gauge-based precipitation observations reveals that MERRA-2 outperforms other reanalysis for Arctic EP changes. Based on MERRA-2 data, both annual EP amount and occurrence days averaged over the Arctic show statistically significant positive trends during 1980–2022 (3.37 ± 1.03 mm dec −1 and 0.42 ± 0.17 d dec −1 , respectively), with the most pronounced increase in the autumn. Spatial heterogeneity in annual and seasonal EP trends is found across the Arctic, with the largest positive annual trends of 30 mm dec −1 over the Bering Sea and the Denmark Strait. The significant EP increase is closely associated with intensified atmospheric rivers (ARs) and widespread decline in sea ice concentration (SIC). Specially, SIC and ARs are responsible for 12% and 50% of Arctic EP inter-annual variance, respectively, while ARs directly contribute 28.3% of the total annual EP amounts. These findings explain the mechanistic controls on Arctic EP, providing critical insights for projecting polar weather and climate extremes and their impacts on the Arctic environment.

atmospheric rivers↗
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 NTRS2012

An Overview of Scientific and Space Weather Results from the Communication/Navigation Outage Forecasting System (C/NOFS) Mission

The Communication/Navigation Outage Forecasting System (C/NOFS) Mission of the Air Force Research Laboratory is described. C/NOFS science objectives may be organized into three categories: (1) to understand physical processes active in the background ionosphere and thermosphere in which plasma instabilities grow; (2) to identify mechanisms that trigger or quench the plasma irregularities responsible for signal degradation; and (3) to determine how the plasma irregularities affect the propagation of electromagnetic waves. The satellite was launched in April, 2008 into a low inclination (13 deg), elliptical (400 x 850 km) orbit. The satellite sensors measure the following parameters in situ: ambient and fluctuating electron densities, AC and DC electric and magnetic fields, ion drifts and large scale ion composition, ion and electron temperatures, and neutral winds. C/NOFS is also equipped with a GPS occultation receiver and a radio beacon. In addition to the satellite sensors, complementary ground-based measurements, theory, and advanced modeling techniques are also important parts of the mission. We report scientific and space weather highlights of the mission after nearly four years in orbit

Pfaff, R.↗
NASA NTRS2011

Development and Testing of Operational Dual-Polarimetric Radar Based Lightning Initiation Forecast Techniques

Lightning is one of Earth s natural dangers, destructive not only to life but also physical property. According to the National Weather Service, there are on average 58 lightning fatalities each year, with over 300 related injuries (NWS 2010). The ability to forecast lightning is critical to a host of activities ranging from space vehicle launch operations to recreational sporting events. For example a single lightning strike to a Space Shuttle could cause billions of dollars of damage and possible loss of life. While forecasting that provides longer lead times could provide sporting officials with more time to respond to possible threatening weather events, thus saving the lives of player and bystanders. Many researchers have developed and tested different methods and tools of first flash forecasting, however few have done so using dual-polarimetric radar variables and products on an operational basis. The purpose of this study is to improve algorithms for the short-term prediction of lightning initiation through development and testing of operational techniques that rely on parameters observed and diagnosed using C-band dual-polarimetric radar.

Woodard, Crystal↗