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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Multipath induced errors in meteorological Doppler/interferometer location systems

One application of an RF interferometer aboard a low-orbiting spacecraft to determine the location of ground-based transmitters is in tracking high-altitude balloons for meteorological studies. A source of error in this application is reflection of the signal from the sea surface. Through propagating and signal analysis, the magnitude of the reflection-induced error in both Doppler frequency measurements and interferometer phase measurements was estimated. The theory of diffuse scattering from random surfaces was applied to obtain the power spectral density of the reflected signal. The processing of the combined direct and reflected signals was then analyzed to find the statistics of the measurement error. It was found that the error varies greatly during the satellite overpass and attains its maximum value at closest approach. The maximum values of interferometer phase error and Doppler frequency error found for the system configuration considered were comparable to thermal noise-induced error.

Wallace, R. G.↗
NASA NTRS1977

UTSI atmospheric science program

Two areas of research were carried out concerned with meteorological and environmental inputs to aviation systems. One effort dealt with the investigation of wind fields about bluff geometries typical of buildings or other man made obstructions to the surface wind and the behavior of craft flying through these disturbed wind fields. The second effort was the definition and mathematical models of atmospheric wind shear associated with thunderstorms, stable boundary layers, and synoptic fronts. These mathematical models can be utilized in flight simulators to train pilots and flight crews and to develop instrumentation for landing in adverse wind shear conditions.

Frost, W.↗
NASA NTRS1980

An airborne system for detection of volcanic surface deformations

A technique is proposed for measuring volcanic deformation on the order of centimeters per day to centimeters per year. An airborne multifrequency pulsed radar, tracking passive ground reflectors spaced at 1 kilometer intervals over a 50 square kilometer area is employed. Identification of targets is accomplished by Doppler and range resolution techniques, with final relative position measurements accomplished by phase comparison of multifrequency signals. Atmospheric path length errors are corrected by an airborne refractometer, meteorological instruments, or other refractive index measuring devices. Anticipated system accuracy is 1-2 cm, with measuring times on the order of minutes. Potential problems exist in the high intrinsic data assimilation rate required of the system to overcome ground backscatter noise.

Lunine, J.↗
NASA NTRS2006

The Application of Satellite-Derived, High-Resolution Land Use/Land Cover Data to Improve Urban Air Quality Model Forecasts

Local and state agencies are responsible for developing state implementation plans to meet National Ambient Air Quality Standards. Numerical models used for this purpose simulate the transport and transformation of criteria pollutants and their precursors. The specification of land use/land cover (LULC) plays an important role in controlling modeled surface meteorology and emissions. NASA researchers have worked with partners and Atlanta stakeholders to incorporate an improved high-resolution LULC dataset for the Atlanta area within their modeling system and to assess meteorological and air quality impacts of Urban Heat Island (UHI) mitigation strategies. The new LULC dataset provides a more accurate representation of land use, has the potential to improve model accuracy, and facilitates prediction of LULC changes. Use of the new LULC dataset for two summertime episodes improved meteorological forecasts, with an existing daytime cold bias of approx. equal to 3 C reduced by 30%. Model performance for ozone prediction did not show improvement. In addition, LULC changes due to Atlanta area urbanization were predicted through 2030, for which model simulations predict higher urban air temperatures. The incorporation of UHI mitigation strategies partially offset this warming trend. The data and modeling methods used are generally applicable to other U.S. cities.

Quattrochi, D. A.↗
NASA NTRS2018

Simulation and Prediction of Warm Season Drought in North America

This presentation presents our recent work on model simulation and prediction of warm season drought in North America. The emphasis will be on the contribution from the leading modes of subseasonal atmospheric circulation variability, which are often present in the form of stationary Rossby waves. Here we take advantage of the results from observations, reanalyses, and simulations and reforecasts performed using the NASA Goddard Earth Observing System (GEOS-5) atmospheric and coupled General Circulation Model (GCM). Our results show that stationary Rossby waves play a key role in Northern Hemisphere (NH) atmospheric circulation and surface meteorology variability on subseasonal timescales. In particular, such waves have been crucial to the development of recent short-term warm season heat waves and droughts over North America (e.g. the 1988, 1998, and 2012 summer droughts) and northern Eurasia (e.g., the 2003 summer heat wave over Europe and the 2010 summer drought and heat wave over Russia). Through an investigation of the physical processes by which these waves lead to the development of warm season drought in North America, it is further found that these waves can serve as a potential source of drought predictability. In order to properly represent their effect and exploit this source of predictability, a model needs to correctly simulate the Northern Hemisphere (NH) mean jet streams and be able to predict the sources of these waves. Given the NASA GEOS-5 AGCM deficiency in simulating the NH jet streams and tropical convection during boreal summer, an approach has been developed to artificially remove much of model mean biases, which leads to considerable improvement in model simulation and prediction of stationary Rossby waves and drought development in North America. Our study points to the need to identify key model biases that limit model simulation and prediction of regional climate extremes, and diagnose the origin of these biases so as to inform modeling group for model improvement.

Rossby Waves↗
NASA NTRS2010

Understanding the Transport of Patagonian Dust and Its Influence on Marine Biological Activity in the South Atlantic Ocean

Modeling and remote sensing techniques were applied to examine the horizontal and vertical transport pathways of Patagonian dust and quantify the effect of soluble-iron- laden mineral dust deposition on marine primary productivity in the South Atlantic Ocean (SAO) surface waters. The global chemistry transport model GEOS-Chem, implemented with an iron dissolution scheme, was applied to evaluate the atmospheric transport and deposition of mineral dust and bioavailable iron during two dust outbreaks originating in the source regions of Patagonia. In addition to this "rapidly released" iron, offline calculations were also carried out to estimate the amount of bioavailable iron leached during the residence time of dust in the ocean mixed layer. Model simulations showed that the horizontal and vertical transport pathways of Patagonian dust plumes were largely influenced by the synoptic meteorological patterns of high and low pressure systems. Model-predicted horizontal and vertical transport pathways of Patagonian dust over the SAO were in reasonable agreement with remotely-sensed data. Comparison between remotely-sensed and offline calculated ocean surface chlorophyll-a concentrations indicated that, for the two dust outbreaks examined in this study, the deposition of bioavailable iron in the SAO through atmospheric pathways was insignificant. As the two dust transport episodes examined here represent typical outflows of mineral dust from South American sources, our study suggests that the atmospheric deposition of mineral dust is unlikely to induce large scale marine primary productivity and carbon sequestration in the South Atlantic sector of the Southern Ocean.

Johnson, Matthew↗
NASA NTRS2011

CEOS Land Surface Imaging Constellation Mid-Resolution Optical Guidelines

The LSI community of users is large and varied. To reach all these users as well as potential instrument contributors this document has been organized by measurement parameters of interest such as Leaf Area Index and Land Surface Temperature. These measurement parameters and the data presented in this document are drawn from multiple sources, listed at the end of the document, although the two primary ones are "The Space-Based Global Observing System in 2010 (GOS-2010)" that was compiled for the World Meteorological Organization (WMO) by Bizzarro Bizzarri, and the CEOS Missions, Instruments, and Measurements online database (CEOS MIM). For each measurement parameter the following topics will be discussed: (1) measurement description, (2) applications, (3) measurement spectral bands, and (4) example instruments and mission information. The description of each measurement parameter starts with a definition and includes a graphic displaying the relationships to four general land surface imaging user communities: vegetation, water, earth, and geo-hazards, since the LSI community of users is large and varied. The vegetation community uses LSI data to assess factors related to topics such as agriculture, forest management, crop type, chlorophyll, vegetation land cover, and leaf or canopy differences. The water community analyzes snow and lake cover, water properties such as clarity, and body of water delineation. The earth community focuses on minerals, soils, and sediments. The geo-hazards community is designed to address and aid in emergencies such as volcanic eruptions, forest fires, and large-scale damaging weather-related events.

Keyes, Jennifer P.↗
NASA NTRS1990

Lidar instruments proposed for Eos

Lidar, an acronym for light detection and ranging, represents a class of instruments that utilize lasers to send probe beams into the atmosphere or onto the surface of the Earth and detect the backscattered return in order to measure properties of the atmosphere or surface. The associated technology has matured to the point where two lidar facilities, Geodynamics Laser Ranging System (GLRS), and Laser Atmospheric Wind Sensor (LAWS) were accepted for Phase 2 studies for Eos. A third lidar facility Laser Atmospheric Sounder and Altimeter (LASA), with the lidar experiment EAGLE (Eos Atmospheric Global Lidar Experiment) was proposed for Eos. The generic lidar system has a number of components. They include controlling electronics, laser transmitters, collimating optics, a receiving telescope, spectral filters, detectors, signal chain electronics, and a data system. Lidar systems that measure atmospheric constituents or meteorological parameters record the signal versus time as the beam propagates through the atmosphere. The backscatter arises from molecular (Rayleigh) and aerosol (Mie) scattering, while attenuation arises from molecular and aerosol scattering and absorption. Lidar systems that measure distance to the Earth's surface or retroreflectors in a ranging mode record signals with high temporal resolution over a short time period. The overall characteristics and measurements objectives of the three lidar systems proposed for Eos are given.

Grant, William B.↗
NASA NTRS2011

Evaluating the Impacts of NASA/SPoRT Daily Greenness Vegetation Fraction on Land Surface Model and Numerical Weather Forecasts

The NASA Short-term Prediction Research and Transition (SPoRT) Center develops new products and techniques that can be used in operational meteorology. The majority of these products are derived from NASA polar-orbiting satellite imagery from the Earth Observing System (EOS) platforms. One such product is a Greenness Vegetation Fraction (GVF) dataset, which is produced from Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA EOS Aqua and Terra satellites. NASA SPoRT began generating daily real-time GVF composites at 1-km resolution over the Continental United States (CONUS) on 1 June 2010. The purpose of this study is to compare the National Centers for Environmental Prediction (NCEP) climatology GVF product (currently used in operational weather models) to the SPoRT-MODIS GVF during June to October 2010. The NASA Land Information System (LIS) was employed to study the impacts of the new SPoRT-MODIS GVF dataset on land surface models apart from a full numerical weather prediction (NWP) model. For the 2010 warm season, the SPoRT GVF in the western portion of the CONUS was generally higher than the NCEP climatology. The eastern CONUS GVF had variations both above and below the climatology during the period of study. These variations in GVF led to direct impacts on the rates of heating and evaporation from the land surface. The second phase of the project is to examine the impacts of the SPoRT GVF dataset on NWP using the Weather Research and Forecasting (WRF) model. Two separate WRF model simulations were made for individual severe weather case days using the NCEP GVF (control) and SPoRT GVF (experimental), with all other model parameters remaining the same. Based on the sensitivity results in these case studies, regions with higher GVF in the SPoRT model runs had higher evapotranspiration and lower direct surface heating, which typically resulted in lower (higher) predicted 2-m temperatures (2-m dewpoint temperatures). The opposite was true for areas with lower GVF in the SPoRT model runs. These differences in the heating and evaporation rates produced subtle yet quantifiable differences in the simulated convective precipitation systems for the selected severe weather case examined.

Bell, Jordan R.↗
NASA NTRSDate not supplied

Challenges in Observing, Modeling, and Forecasting the June 2023 Smoke Event Over the Northeast United States

In the first week of May 2023, boreal Canada began an early start to the biomass burning season when fires erupted across Alberta and western Saskatchewan. Smoke entered the troposphere and spread across the United States as biomass burning emissions in Canada quadrupled the prior maximum since the onset of the MODIS satellite record. Adding to the already existing smoke, wildfires ignited in Quebec on June 2, 2023, producing a heavy plume of aerosol over the northeastern part of the continent. Meteorological factors, including an area of low pressure situated, nearly stationary, over Maine, transported the smoke into a densely populated corridor containing the cities of Washington, DC, Baltimore, Philadelphia, and New York City. Air quality alerts became widespread as near-surface levels of fine particulate matter (PM2.5) exceeded harmful levels due the low altitude of the smoke plume. Forecasting the smoke transport and impacts of such events requires a complex combination of observed initial conditions for meteorology and aerosols, knowledge of the emissions from wildfires, and a state-of-the-art Earth System model that couples these components together. Using a case-study perspective with the Goddard Earth Observing System (GEOS), challenges associated with near real time forecasting of the smoke plume are presented. Analyzed and forecasted aerosol optical depth will be evaluated using available satellite and AERONET observations, while surface aerosol will be assessed relative to observations of PM2.5. Lacking real time estimates of biomass burning emissions for inputs to our forecast model, particular attention is given to the use of day-old biomass burning emissions throughout the forecast period covering the first ten days in June 2023, and the resulting reduction in forecast skill will be quantified.

Allison Collow↗
NASA NTRSDate not supplied

Challenges in Observing, Modeling, and Forecasting the June 2023 Smoke Event over the Northeast United States

In the first week of May 2023, boreal Canada began an early start to the biomass burning season when fires erupted across Alberta and western Saskatchewan. Smoke entered the troposphere and spread across the United States as biomass burning emissions in Canada quadrupled the prior maximum since the onset of the MODIS satellite record. Adding to the already existing smoke, wildfires ignited in Quebec on June 2, 2023, producing a heavy plume of aerosol over the northeastern part of the continent. Meteorological factors, including an area of low pressure situated, nearly stationary, over Maine, transported the smoke into a densely populated corridor containing the cities of Washington, DC, Baltimore, Philadelphia, and New York City. Air quality alerts became widespread as near-surface levels of fine particulate matter (PM2.5) exceeded harmful levels due the low altitude of the smoke plume. Forecasting the smoke transport and impacts of such events requires a complex combination of observed initial conditions for meteorology and aerosols, knowledge of the emissions from wildfires, and a state-of-the-art Earth System model that couples these components together. Using a case-study perspective with the Goddard Earth Observing System (GEOS ), challenges associated with near real time forecasting of the smoke plume are presented. Analyzed and forecasted aerosol optical depth will be evaluated using available satellite and AERONET observations, while surface aerosol will be assessed relative to observations of PM2.5. Lacking real time estimates of biomass burning emissions for inputs to our forecast model, particular attention is given to the use of day-old biomass burning emissions throughout the forecast period covering the first ten days in June 2023, and the resulting reduction in forecast skill will be quantified.

Allison Collow↗
NASA NTRS1977

Advanced Meteorological Temperature Sounder (AMTS) study

The results of a system definition study (theoretical) for an Advanced Meteorological Temperature Sounder (AMTS) is described. From the data the atmospheric temperature and humidity profiles can be determined over the entire earth's surface with a spatial resolution of 45 km. x 45 km; amounts and type of cloud cover as well as surface temperatures of the earth are also determined. The major purpose of the study was to determine the feasibility of cooling twenty-eight detectors to the 80-90 Kelvin region by means of a radiative cooler. Other related considerations were achieving high signal-to-noise ratios, maximizing optical throughput through the grating spectrometer, and reducing preamplifier noise. A detailed optical design of an f/5 Ebert-Fastie spectrometer was carried out to verify that image quality is adequate; field lenses near the spectrometer focal plane were designed to image the grating onto the smallest size detectors for each channel.

Source record↗
NASA NTRS2002

Evaluation of Refractivity Profiles from CHAMP and SAC-C GPS Radio Occultation

The GeoForschungsZentrum's Challenging Minisatellite Payload for Geophysical Research and Application (CHAMP, Germany-US) and the Comision Nacional de Actividades Especiales' Satelite de Aplicaciones Cientificas-C (SAC-C, Argentina-US) missions are the first missions to carry a second-generation Blackjack Global Positioning System (GPS) receiver. One of the new features of this receiver is its ability to sense the lower troposphere closer to the surface than the proof-of-concept GPS Meteorology experiment (GPS/MET). Since their launch, CHAMP and SAC-C have collected thousands of GPS radio occultations, representing a wealth of measurements available for data assimilation and Numerical Weather Prediction (NWP). In order to evaluate the refractivity data derived by the Jet Propulsion Laboratory (JPL) from raw radio occultation measurements, we use Data Assimilation Office (DAO) 6-hour forecasts as an independent state of the atmosphere. We compare CHAMP and SAC-C refractivity (processed by JPL) with refractivity calculated from the DAO global fields of temperature, water vapor content and humidity. We show statistics of the differences as well as histograms of the differences.

Poli, Paul↗
NASA NTRS2009

Phase Fluctuations at Goldstone Derived from 1-Year Site Testing Interferometer Data

A two-element site test interferometer has been deployed at the NASA Deep Space Network (DSN) tracking complex in Goldstone, California, since May 2007. The interferometer system consists of two offset-fed 1.2 m parabolic reflectors which monitor atmospheric-induced amplitude and phase fluctuations on an unmodulated beacon signal (20.199 GHz) broadcast from a geostationary satellite (Anik F2). The geometry of the satellite and the ground-based infrastructure imposes a 48.5 elevation angle with a separation distance of 256 m along an east-west baseline. The interferometer has been recording phase fluctuation data, to date, for 1 yr with an overall system availability of 95 percent. In this paper, we provide the cumulative distribution functions (CDFs) for 1 year of recorded data, including phase rms, spatial structure function exponent, and surface meteorological measurements: surface wind speed, relative humidity, temperature, barometric pressure, and rain rate. Correlation between surface measurements, phase rms, and amplitude rms at different time scales are discussed. For 1 year, phase fluctuations at the DSN site in Goldstone, are better than 23 for 90 percent of the time (at 48.5 elevation). This data will be used to determine the suitability of the Goldstone site as a location for the Next Generation Deep Space Network.

Nessel, James A.↗
NASA NTRS1983

Objective analysis and assimilation of observational data from FGGE

An objective analysis scheme is presented for the assimilation of meteorological data in which wind, geopotential height, and relative humidity are analyzed on mandatory pressure levels, and surface pressure and temperature are reduced to sea level for analysis. The present analysis/forecast system demonstrates a reasonable degree of forecast skill over the Northern Hemisphere for an ensemble of five-day integrations during the First Special Observing Period of the First GARP Global Experiment (FGGE) The vertical motion field shows outstanding agreement with the large scale synoptic pattern for the sample analysis presented, and the mean meridional circulation portrayed in the FGGE analysis is in close agreement with observational estimates.

Baker, W. E.↗
NASA NTRS1989

Remote sensing of atmosphere and oceans; Proceedings of Symposium 1 and of the Topical Meeting of the 27th COSPAR Plenary Meeting, Espoo, Finland, July 18-29, 1988

Papers are presented on the contribution of space remote sensing observations to the World Climate Research Program and the Global Change Program, covering topics such as space observations for global environmental monitoring, experiments related to land surface fluxes, studies of atmospheric composition, structure, motions, and precipitation, and remote sensing for oceanography, observational studies of the atmosphere, clouds, and the earth radiation budget. Also, papers are given on results from space observations for meteorology, oceanography, and mesoscale atmospheric and ocean processes. The topics include vertical atmospheric soundings, surface water temperature determination, sea level variability, data on the prehurricane atmosphere, linear and circular mesoscale convective systems, Karman vortex clouds, and temporal patterns of phytoplankton abundance.

Raschke, E.↗
NASA NTRS2010

Agricultural Productivity Forecasts for Improved Drought Monitoring

Water stresses on agricultural crops during critical phases of crop phenology (such as grain filling) has higher impact on the eventual yield than at other times of crop growth. Therefore farmers are more concerned about water stresses in the context of crop phenology than the meteorological droughts. However the drought estimates currently produced do not account for the crop phenology. US Department of Agriculture (USDA) and National Oceanic and Atmospheric Administration (NOAA) have developed a drought monitoring decision support tool: The U.S. Drought Monitor, which currently uses meteorological droughts to delineate and categorize drought severity. Output from the Drought Monitor is used by the States to make disaster declarations. More importantly, USDA uses the Drought Monitor to make estimates of crop yield to help the commodities market. Accurate estimation of corn yield is especially critical given the recent trend towards diversion of corn to produce ethanol. Ethanol is fast becoming a standard 10% ethanol additive to petroleum products, the largest traded commodity. Thus the impact of large-scale drought will have dramatic impact on the petroleum prices as well as on food prices. USDA's World Agricultural Outlook Board (WAOB) serves as a focal point for economic intelligence and the commodity outlook for U.S. WAOB depends on Drought Monitor and has emphatically stated that accurate and timely data are needed in operational agrometeorological services to generate reliable projections for agricultural decision makers. Thus, improvements in the prediction of drought will reflect in early and accurate assessment of crop yields, which in turn will improve commodity projections. We have developed a drought assessment tool, which accounts for the water stress in the context of crop phenology. The crop modeling component is done using various crop modules within Decision Support System for Agrotechnology Transfer (DSSAT). DSSAT is an agricultural crop simulation system, which integrates the effects of soil, crop phenotype, weather, and management options. It has been in use for more than 15 years by researchers, growers and has become a de-facto standard in crop modeling communities spanning over 100 countries. The meteorological forcings to DSSAT are provided by NASA s National Land Data Assimilation System (NLDAS) datasets. NLDAS is a framework that incorporates atmospheric forcing and land parameter values along with land surface models to diagnose and predict the state of the land surface.

Limaye, Ashutosh↗
NASA NTRS2001

Global Surface Solar Energy Anomalies Including El Nino and La Nina Years

This paper synthesizes past events in an attempt to define the general magnitude, duration, and location of large surface solar anomalies over the globe. Surface solar energy values are mostly a function of solar zenith angle, cloud conditions, column atmospheric water vapor, aerosols, and surface albedo. For this study, solar and meteorological parameters for the 10-yr period July 1983 through June 1993 are used. These data were generated as part of the Release 3 Surface meteorology and Solar Energy (SSE) activity under the NASA Earth Science Enterprise (ESE) effort. Release 3 SSE uses upgraded input data and methods relative to previous releases. Cloud conditions are based on recent NASA Version-D International Satellite Cloud Climatology Project (ISCCP) global satellite radiation and cloud data. Meteorological inputs are from Version-I Goddard Earth Observing System (GEOS) reanalysis data that uses both weather station and satellite information. Aerosol transmission for different regions and seasons are for an 'average' year based on historic solar energy data from over 1000 ground sites courtesy of Natural Resources Canada (NRCan). These data are input to a new Langley Parameterized Shortwave Algorithm (LPSA) that calculates surface albedo and surface solar energy. That algorithm is an upgraded version of the 'Staylor' algorithm. Calculations are performed for a 280X280 km equal-area grid system over the globe based on 3-hourly input data. A bi-linear interpolation process is used to estimate data output values on a 1 X 1 degree grid system over the globe. Maximum anomalies are examined relative to El Nino and La Nina events in the tropical Pacific Ocean. Maximum year-to-year anomalies over the globe are provided for a 10-year period. The data may assist in the design of systems with increased reliability. It may also allow for better planning for emergency assistance during some atypical events.

Whitlock, C. H.↗