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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

A regional simulation of marine boundary-layer clouds

A regional version of a two-layer model is used to simulate marine boundary-layer clouds over an area (20 deg - 42 deg and 117 - 145 deg W) of the eastern North Pacific. The large-scale conditions requried for the model are provided by European Centre for Medium-Range Weather Forecasts analyses and the Comprehensive Ocean-Atmosphere Data Set. The simulated cloud-top height and fractional cloudiness are compared with satellite data. The model predicts a realistic pattern of cloud-top height, although the heights appear to be overestimated in the southwest and underestimated along the eastern border of the domain. The overall simulated cloudiness is qualitatively comparable to the satellite derived, but the model predicts excessive cloudiness over cold ocean surfaces and insufficient cloudiness over an area centered at 30 deg N, 130 deg W. The possible causes for these discrepancies are discussed. Budget studies show that horizontal advection contributes substantially to the cloud-top height and cloud-layer moisture budgets. Thus, one may need to consider the effects of horizontal advection when validating steady-state solutions of a one-dimensional model. The simulated cloudiness is shown to be sensitive to large-scale subsidence, moisture above the clouds, and drizzle. An increase in the large-scale divergence by 2 x 10(exp -6)/sec decreases average cloudiness for the area by 30%. An increase in the moisture at 850 mb by 2 g/kg increases the cloudiness by 20%. The suppression of drizzle in the model increases the cloudiness by 34% and significantly changes its pattern.

Wang, Shouping↗
NASA NTRS2001

Recent Developments in DAO's Finite-Volume Data Assimilation System

The Physical-space/Finite-volume Data Assimilation System (fvDAS) is the next generation global atmospheric data assimilation system in development at the Data Assimilation Office at NASA's Goddard Space Flight Center. It is based on a new finite-volume general circulation model jointly developed by NASA and NCAR and on the Physical-Space Statistical Analysis System (PSAS) developed at the DAO. The data assimilation method implemented in CODAS incorporates a simplified version of the model bias estimation and correction algorithm, as described by Dee and da Silva (1998). In this talk we will briefly describe the general system formulation, and focus on the impact of 3 data types recently introduced, namely: 1) cloud tracks winds from the Multi-angle Imaging Spectrometer by the US Air Force, and 3) temperature and moisture information derived from GPS refractivity occultation measurements. The impact of these data types on observation-minus-6hr forecast (O-F) statistics, as well as 5-day forecast skills will be discussed. In addition we will assess the impact of cloud assimilation on top of the atmosphere radiation fields estimated from CERES measurements.

daSilva, Arlindo↗
NASA NTRS2009

Sensitivity of Short-Term Weather Forecasts to Assimilated AIRS Data: Implications for NPOESS Applications

The Atmospheric Infrared Sounder (AIRS) is acting as a heritage and risk reduction instrument for the Cross-track lnfrared Sounder (CrIS) to be flown aboard the NPP and NPOESS satellites. The hyperspectral nature of AIRS and CrIS provides high-quality soundings that, along with their asynoptic observation time over North America, make them attractive sources to fill the spatial and temporal data voids in upper air temperature and moisture measurements for use in data assimilation and numerical weather prediction. Observations from AlRS can be assimilated either as direct radiances or retrieved thermodynamic profiles, and the Short-Term Prediction Research and Transition (SPORT) Center at NASA's Marshall Space Flight Center has used both data types to improve short-term (0-48h), regional forecasts. The purpose of this paper is to share SPORT'S experiences using AlRS radiances and retrieved profiles in regional data assimilation activities by showing that proper handling of issues-including cloud contamination and land emissivity characterization-are necessary to produce optimal analyses and forecasts.

Zavodsky, Bradley↗
NASA NTRSDate not supplied

Implementing Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) Cloud-Clearing Algorithm into the NASA GEOS: Focus on the 2017 Atlantic Tropical Cyclone Season

Numerical Weather Prediction (NWP) centers assimilate cloud-free infrared (IR) radiances because the assimilation of all-sky IR radiances is not yet operationally achievable. The cloud-clearing procedure offers a simpler, but effective strategy that produces cloud-affected radiances suitable for assimilation in partially cloudy regions. Several studies conducted by this team have demonstrated that IR Cloud-Cleared Radiances (CCRs), if thinned more aggressively than clear-sky radiances, can improve analysis and forecasts, particularly in meteorologically active areas. However, CCRs are not used by operational centers due partly to the thought that the process of cloud-clearing may affect latency and introduce difficult-to-control external dependencies. This study presents the results of implementing an Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) cloud-clearing procedure into the NASA Goddard Earth Observing System (GEOS) to demonstrate the portability of the procedure. The AIRS and CrIS cloud-clearing algorithms have been deprived of external dependencies, made customizable to any specific model, and the computational efficiency has been improved via parallelization. The revised AIRS and CrIS cloud-clearing algorithms allow a customized choice of channel selection, the use of a user-specified model's fields as first guess, and can perform in real time. Data assimilation experiments with the hybrid 4DEnVar GEOS system were successfully performed for the 2017 tropical cyclones (TC) season with a focus on three major hurricanes (Harvey, Irma, and Maria). This study shows that assimilation of locally-generated CCRs have a positive impact on both global skill and TC representation, compared to the assimilation of AIRS and CrIS clear-sky radiances, and a comparable or slightly improved impact compared to assimilation of CCRs produced by external sources, such as NASA's Distributed Active Archive Centers and NOAA’s Comprehensive Large Array-data Stewardship System. The customization and computational efficiency of the revised procedure would enable its usability in a real-time forecast context.

Niama Boukachaba↗
NASA NTRS1985

Mesoscale-cloud scale simulation of convective response

The importance of mesoscale moisture information in the forecasting of weather events is being studied. A test is being prepared with the March 6, 1982 Vertical Atmospheric Sounder/Atmospheric Variability Experiment (VAS/AVE) case study to be run on the sub-synoptic scale model (SSM). Intracomparison of three carefully designed simulations should isolate the role of mesoscale information in the initial conditions for both moisture and vertical motion. Three simulations will be made for the period 1200Z 6 March to 0000Z 7 March starting with the regular synoptic time data of 1200Z. The distinction between the three cases arises from data manipulation at 1800Z midway through the forecast period. Comparison of results for the 1800Z to 0000Z time period will give the information desired.

Kopp, F. J.↗
NASA NTRS1987

Short-term forecasting of lightning based on the surface wind field at Kennedy Space Center

Cloud-to-ground lightning is related in time and space to surface convergence for 244 days during the summer over a 790 sqkm network. The method uses surface convergence, particularly the average over the area, to identify the potential for new, local thunderstorm growth, and can be used to specify the likely time and location of lightning during the life cycle of the convection. A threshold of 0.0000075/sec change in divergence is used to define a convergence event, and a separation of 30 min between flashes defines a lightning event. Time intervals are found to be on the order of 1 hr from beginning convergence to first flash, and (CH110) 2 hr from beginning convergence to the end of lightning. Major differences between the convergence-lightning relationships based on low-level mean onshore and offshore flow are noted.

Watson, Andrew I.↗
NASA NTRSDate not supplied

Machine Learning Algorithms for Aerosol and Cloud Detection Using CATS on the ISS

Clouds and aerosols are one of the largest uncertainties in understanding and forecasting the Earth’s changing climate system. The type and height of aerosols are important factors in determining the top-of-atmosphere (TOA) radiation budget, either direct reflection of solar radiation back to space and/or absorption of solar radiation. In addition to their impact on the Earth’s climate system, aerosols near the surface from wildfires, man-made pollution events, and dust storms are hazardous to human health. The phase and height of clouds also play a critical role in determining the role of clouds in the Earth’s climate system. Cirrus clouds in the upper troposphere can induce a significant daytime TOA warming effect, while liquid water clouds near the surface cause a large corresponding cooling effect. Lidar measurements provide accurate vertically resolved information about clouds and aerosols, including complex multi-layer scenes where passive sensors are challenged and at night, when passive sensors are unable to measure cloud and aerosol properties. The Cloud-Aerosol Transport System (CATS) is a lidar instrument that operated for 33 months on the International Space Station (ISS) at the 1064 nm wavelength to measure attenuated total backscatter and depolarization ratio. These fundamental measurements are used to derive “vertical feature mask” cloud and aerosol products, including layer top/base heights, layer geometrical thickness, aerosol type, and cloud phase. While space-based lidar systems like CATS provide cloud and aerosol vertical distributions that improve our understanding of the climate system, averaging of the daytime data from these sensors is required, at the expense of spatial resolution, to improve the daytime signal-to noise (SNR) and thus atmospheric layer detection. This presentation shows results from machine learning (ML) techniques that, when applied to CATS data: 1. improve the 1064 nm SNR 2. enable detection of atmospheric features during daytime with a horizontal resolution of 350 m or 5 km (compared to the 60 km required for standard CATS data products) 3. increase the number of atmospheric layers detected in the CATS data. A Convolutional Neural Network (CNN) trained using CATS standard data products also demonstrated the potential for improved cloud-aerosol discrimination, cloud phase, and aerosol typing compared to the operational CATS algorithms for cloud edges and complex near-surface scenes during daytime. The ML tools described in this paper can facilitate the development of smaller, low-cost lidar systems in the future and enable real-time accessibility of lidar data products from future lidar systems for monitoring and forecasting of hazardous events.

John Yorks↗
NASA NTRS2014

Weather Avoidance Guidelines for NASA Global Hawk High-Altitude UAS

NASA operates two Global Hawk unmanned aircraft systems for Earth Science research projects. In particular, they are used in the Hurricane and Severe Storm Sentinel (HS3) project during 2012, 2013, and 2014 to take measurements from the environment around tropical cyclones, and from directly above tropical cyclones. There is concern that strict adherence to the weather avoidance rules used in 2012 may sacrifice the ability to observe important science targets. We have proposed modifications to these weather avoidance rules that we believe will improve the ability to observe science targets without compromising aircraft safety. The previous guidelines, used in 2012, specified: Do not approach thunderstorms within 25 nm during flight at FL500 or below. When flying above FL500: Do not approach reported lightning within 25NM in areas where cloud tops are reported at FL500 or higher. Aircraft should maintain at least 10000 ft vertical separation from reported lightning if cloud tops are below FL500. No over-flight of cumulus tops higher than FL500. No flight into forecast or reported icing conditions. No flight into forecast or reported moderate or severe turbulence Based on past experience with high-altitude flights over tropical cyclones, we have recommended changing this guidance to: Do not approach thunderstorms within 25 nm during flight at FL500 or below. Aircraft should maintain at least 5000 ft vertical separation from significant convective cloud tops except: a) When cloud tops above FL500: In the event of reported significant lightning activity or indicators of significant overshooting tops, do not approach within 10-25 nm, depending on pilot discretion and advice from Mission Scientist. b) When cloud tops are below FL500, maintain 10000 ft separation from reported significant lightning or indicators of significant overshooting tops. No flight into forecasted or reported icing conditions. No flight into forecasted or reported moderate or severe turbulence The key changes have to do with overflight of high convective cloud tops and those producing lightning. Experience shows that most tropical oceanic convection (including that in tropical cyclones) is relatively gentle even if the cloud tops are quite high, and can be safely overflown. Exceptions are convective elements producing elevated lightning flash rates (more than just the occasional flash, which would trigger avoidance under the previous rules) and significant overshooting cloud tops.

Cecil, Daniel J.↗
NASA NTRS2015

Integrated Modeling of Aerosol, Cloud, Precipitation and Land Processes at Satellite-Resolved Scales

With support from NASA's Modeling and Analysis Program, we have recently developed the NASA Unified-Weather Research and Forecasting model (NU-WRF). NU-WRF is an observation-driven integrated modeling system that represents aerosol, cloud, precipitation and land processes at satelliteresolved scales. "Satellite-resolved" scales (roughly 1e25 km), bridge the continuum between local (microscale), regional (mesoscale) and global (synoptic) processes. NU-WRF is a superset of the National Center for Atmospheric Research (NCAR) Advanced Research WRF (ARW) dynamical core model, achieved by fully integrating the GSFC Land Information System (LIS, already coupled to WRF), the WRF/ Chem enabled version of the Goddard Chemistry Aerosols Radiation Transport (GOCART) model, the Goddard Satellite Data Simulation Unit (G-SDSU), and custom boundary/initial condition preprocessors into a single software release, with source code available by agreement with NASA/GSFC. Full coupling between aerosol, cloud, precipitation and land processes is critical for predicting local and regional water and energy cycles.

Satellite-resolved↗
NASA NTRS1967

ATS-I camera experiment successful.

Cloud photographs obtained on board ATS-I SATELLITE with camera equipped with reflecting telescope show feasibility of short-lived weather systems from synchronous altitude

SATELLITE PHOTOGRAPHY↗
NASA NTRS1972

Meteorological support to the West German-United States Barium Ion Cloud Project.

The objective of the Barium Ion Cloud Project was to study a barium ionized cloud released at an altitude of 5 earth radii. Accurate forecasting of weather conditions to prevail during the experiment period was critical to the project success. Good seeing conditions were required at all optical sites during the experiment. All meteorological support was the responsibility of the National Weather Service at Wallops Station, Virginia. Preliminary results confirm the scientists' theories of the magnetic fields and the existence of electric fields in the magnetosphere.

Westfall, R. R.↗
NASA NTRS1985

Hurricane Debby - An illustration of the complementary nature of VAS soundings and cloud and water vapor motion winds

The utility of VISSR Atmospheric Sounder (VAS) temperature and moisture soundings and cloud and water vapor motion winds in defining a storm and its surroundings at subsynoptic scales has been examined using a numerical analysis and prognosis system. It is shown that the VAS temperature and moisture data, which specify temperature and moisture well in cloud-free areas, are complemented by cloud and water vapor motion data generated in the cloudy areas. The cloud and water vapor 'winds' provide thermal gradient information for interpolating the soundings across cloudy regions. The loss of analysis integrity due to the reduction of VAS sounding density in the cloudy regions associated with synoptic activity is ameliorated by using cloud and water vapor motion winds. The improvement in numerical forecasts resulting from the addition of these data to the numerical analysis is recorded.

Le Marshall, J. F.↗
NASA NTRS2015

Spinoff 2015

Topics covered include: 3D Endoscope to Boost Safety, Cut Cost of Surgery; Audio App Brings a Better Night's Sleep Liquid Cooling Technology Increases Exercise Efficiency; Algae-Derived Dietary Ingredients Nourish Animals; Space Grant Research Launches Rehabilitation Chair; Vision Trainer Teaches Focusing Techniques at Home; Aircraft Geared Architecture Reduces Fuel Cost and Noise; Ubiquitous Supercritical Wing Design Cuts Billions in Fuel Costs; Flight Controller Software Protects Lightweight Flexible Aircraft; Cabin Pressure Monitors Notify Pilots to Save Lives; Ionospheric Mapping Software Ensures Accuracy of Pilots' GPS; Water Mapping Technology Rebuilds Lives in Arid Regions; Shock Absorbers Save Structures and Lives during Earthquakes; Software Facilitates Sharing of Water Quality Data Worldwide; Underwater Adhesives Retrofit Pipelines with Advanced Sensors; Laser Imaging Video Camera Sees through Fire, Fog, Smoke; 3D Lasers Increase Efficiency, Safety of Moving Machines; Air Revitalization System Enables Excursions to the Stratosphere; Magnetic Fluids Deliver Better Speaker Sound Quality; Bioreactor Yields Extracts for Skin Cream; Private Astronaut Training Prepares Commercial Crews of Tomorrow; Activity Monitors Help Users Get Optimum Sun Exposure; LEDs Illuminate Bulbs for Better Sleep, Wake Cycles; Charged Particles Kill Pathogens and Round Up Dust; Balance Devices Train Golfers for a Consistent Swing; Landsat Imagery Enables Global Studies of Surface Trends; Ruggedized Spectrometers Are Built for Tough Jobs; Gas Conversion Systems Reclaim Fuel for Industry; Remote Sensing Technologies Mitigate Drought; Satellite Data Inform Forecasts of Crop Growth; Probes Measure Gases for Environmental Research; Cloud Computing Technologies Facilitate Earth Research; Software Cuts Homebuilding Costs, Increases Energy Efficiency; Portable Planetariums Teach Science; Schedule Analysis Software Saves Time for Project Planners; Sound Modeling Simplifies Vehicle Noise Management; Custom 3D Printers Revolutionize Space Supply Chain; Improved Calibration Shows Images' True Colors; Micromachined Parts Advance Medicine, Astrophysics, and More; Metalworking Techniques Unlock a Unique Alloy; Low-Cost Sensors Deliver Nanometer-Accurate Measurements; Electrical Monitoring Devices Save on Time and Cost; Dry Lubricant Smooths the Way for Space Travel, Industry; and Compact Vapor Chamber Cools Critical Components.

Source record↗
NASA NTRS2018

Modeling Key Predictors of Airport Runway Configurations Using Learning Algorithms

Advanced traffic flow management automation will need accurate predictions of airport runway configurations. Terminal area weather and traffic demand are generally considered to be the most significant factors in predicting runway configuration. Weather information is forecasted across multiple features, including wind direction, wind speed, gusts, cloud ceilings, visibility, temperature, and precipitation, among many others. We use machine learning techniques on historical weather and runway data to determine weather features that correlate well with runway configurations. We analyze the predictive capability of weather features using different learning models trained on data from four major U.S. airports: Atlanta (ATL), Washington – Dulles (IAD), New York – Kennedy (JFK), and San Francisco (SFO). Wind direction alone is strongly correlated with runway configurations above all other examined factors, as expected. This correlation is the most significant component of the ~80% prediction accuracy in selecting between the two most frequently used runway configurations. However, individual airports show variations on how well the runway configuration decisions correlate with wind direction. While wind direction was identified as the most significant indicator of configuration decisions in ATL, IAD, and JFK, it did not emerge as such at SFO. Traffic demand was not found to be a strong factor in predicting runway configurations at any of the airports analyzed. In rare instances, when high demand cannot be accommodated within the current configuration, temporary changes are likely to be attributable to demand. However, these occurrences are so limited in number that their overall effect is not sufficient to consider traffic demand as a major indicator of runway configuration at the airports analyzed.

Bilimoria, Karl D.↗
NASA NTRSDate not supplied

Ice Cloud Observations and Science using Submillimeter-Wave Radiometry

Submillimeter-wave radiometers provide vital information on ice clouds and precipitation. These data are key for improving weather forecasting, particularly for disruptive winter storms, and for better understanding climate. Our airborne radiometer will provide data that will allow us to better use data from upcoming space missions with these types of sensors.

Ian Adams↗
NASA NTRS2006

Using Microwave Limb Sounder Data to Validate Model Ice Fields

MLS IWC overall tends to be higher relative to ECMWF after considering MLS track sampling and sensitivity (cutoff application). Disagreement tends to be accentuated over Indian and Western Pacific Oceans and over tropical landmasses. Large disagreement occur at upper level at 147 hPa but small at lower levels at 215 and 316 hPa suggesting the need to investigate the strength of model large-scale circulation and physics associated with the IWC formation. Future work includes: Present MMF/ECMWF Comparisons at AGU/Baltimore Session on MMF/Cloud Resolving Modeling, GMAO/GSFC & at the WPac/Bejing/AGU in Tao's Cloud-Radiation Session. Write-up Results on ECMWF/MLS Comparisons for GRL. Continue with MLS vs ECMWF Water Vapor & Temperature comparisons - will seek more interaction with other MLS colleagues. Investigate the Development of Biases in ECMWF Forecasts - i.e. in the actual model. Work with GMAO-5 development team regarding their cloud microphysics performance. Integrate CloudSat into IWC Analyses.

cloud ice↗
NASA NTRS2007

Improving Forecast Skill by Assimilation of Quality-controlled AIRS Temperature Retrievals under Partially Cloudy Conditions

The National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) on board the Aqua satellite has been long recognized as an important contributor towards the improvement of weather forecasts. At this time only a small fraction of the total data produced by AIRS is being used by operational weather systems. In fact, in addition to effects of thinning and quality control, the only AIRS data assimilated are radiance observations of channels unaffected by clouds. Observations in mid-lower tropospheric sounding AIRS channels are assimilated primarily under completely clear-sky conditions, thus imposing a very severe limitation on the horizontal distribution of the AIRS-derived information. In this work it is shown that the ability to derive accurate temperature profiles from AIRS observations in partially cloud-contaminated areas can be utilized to further improve the impact of AIRS observations in a global model and forecasting system. The analyses produced by assimilating AIRS temperature profiles obtained under partial cloud cover result in a substantially colder representation of the northern hemisphere lower midtroposphere at higher latitudes. This temperature difference has a strong impact, through hydrostatic adjustment, in the midtropospheric geopotential heights, which causes a different representation of the polar vortex especially over northeastern Siberia and Alaska. The AIRS-induced anomaly propagates through the model's dynamics producing improved 5-day forecasts.

Reale, O.↗
NASA NTRS2020

Assimilating All-Sky Microwave Radiance Data to Improve NASA GEOS Forecasts and Analysis

The NASA Global Modeling and Assimilation Office (GMAO) has been pursuing efforts to utilize all-sky (clear+cloudy+precipitating) MW radiance data and has developed a system to assimilate all-sky GPM Microwave Imager (GMI) radiance data in the Goddard Earth Observing System (GEOS) during the last PMM funding period. The system provides additional constraints on the analysis process near the storm regions and adjusts the geophysical parameters such as precipitation, cloud, moisture, surface pressure, and wind by combining information from GMI radiance measurements and model forecasts in an optimal manner. The system proved that assimilating the GMI all-sky radiance data improve the GEOS atmospheric analyses and forecasts. This all-sky data framework has been included in the GEOS Forward Processing (FP) system since July 11, 2018 and assimilates all-sky GMI data in real-time for GEOS global analysis and forecast production at the GMAO. We are currently extending this all-sky GMI radiance data assimilation system to assimilate more all-sky MW radiance data from other sensors such as the Microwave Humidity Sounder (MHS), the Advanced Technology Microwave Sounder (ATMS), the Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Microwave Scanning Radiometer 2 (AMSR2), and the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometery (SAPHIR) onboard the GPM constellation spacecrafts. Preliminary results from this extended all-sky system show increased benefit from cloud- and precipitation-affected MW radiances with much larger spatial and temporal coverages compared to the all-sky system assimilating GMI alone and improved GEOS forecast skills especially for lower tropospheric humidity fields.

Kim, Min-Jeong↗