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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

The development and validation of a simple snow model for the GISS GCM

Five years of meteorological and hydrological data from a typical New England watershed where winter snow cover is significant were used to drive and validate two off-line land surface schemes suitable for use in the Goddard Institute for Space Studies (GISS) general circulation model (GCM): a baseline scheme that does not model the physics of a snowpack and therefore, neglects the insulating properties of snow cover; and a modified scheme in which a three-layer snowpack is modeled. Comparing baseline model results with validation data reveals several model deficiencies. Surface radiation temperatures could not adequately be modeled and the ground froze to unreasonable depths. Furthermore, because of ground cooling resulting from large surface heat fluxes to the atmosphere from the uninsulated surface, deeper model layers did not unfreeze until midsummer. As such, the normal hydrologic processes of runoff, ground water infiltration, and movement, etc., are compromised for a good part of the year. With the inclusion of a simple three-layer snow model into the baseline model, not only are the ground and surface radiation temperatures adequately modeled but all the features of snowpack ripening that characterize pack growth/ablation are simulated.

Lynch-Stieglitz, Marc↗
NASA NTRS1987

Multiple dipole eddies in the Alaska Coastal Current detected with Landsat thematic mapper data

Seventeen dipole eddies, including five large, well-formed ones, three second-generation eddies, and two double eddies, were observed in the Alaska Coastal Current near Kayak Island in one single scene of the Landsat thematic mapper (TM) on April 22, l985. The digital Landsat TM satellite data were computer analyzed to extract details in the near coastal circulation in the northern Gulf of Alaska. Enhancement techniques were applied to the visible and thermal IR bands. The features are evident only in the visible bands because of the ability of these bands to detect the distribution of sediments in the near surface. These eddies did not have a significant thermal signature.The sources of these sediments are the glacial streams found throughout the Gulf of Alaska coast. Eddies of this configuration and frequency have never been observed here previously. However, the oceanographic and meteorological conditions are typical for this time of year. These eddies should be important to the cross-shelf mixing processes in the Alaska Coastal Current and are an indicator that the flow here can be unstable at certain times of the year.

Ahlnas, Kristina↗
NASA NTRSDate not supplied

Spaceborne Lidar Retrievals of PM2.5 for Air Quality Studies and Applications

Fine particulate matter (PM2.5) substantially contributes to air pollution and negatively affects human health. While many studies have investigated the use of passive column-integrated aerosol optical depth to infer surface PM2.5, the use of lidar observations for air quality characterization is not nearly as extensive. Lidar measurements are critical, however, due to the vertical aerosol information they provide, including near the surface. In this presentation, we first provide an overview of various lidar-based approaches for estimating PM2.5 concentrations and then discuss how lidar measurements can assist other air quality applications. For example, estimates of PM2.5 have been obtained in a physics-based approach through CALIOP near-surface aerosol extinction retrievals, assumptions on the mass extinction efficiency, and incorporating other parameters (an aerosol hygroscopic growth factor and PM2.5/PM10 ratio). Application of this algorithm over the contiguous United States (CONUS) from 2006 to 2018 yielded larger PM2.5 values over the eastern and western CONUS (~10-15 μg/m³) and lower PM2.5 levels in the central CONUS (~5 μg/m³). These spatial patterns were similar to those from gridded PM2.5 concentrations obtained through in situ measurements at ground stations operated by the US Environmental Protection Agency. In another approach, the Cloud Aerosol Transport System (CATS) lidar was used with the Goddard Earth Observing System (GEOS) model in a 1D ensemble-based variational technique to obtain PM2.5 over the US and Europe, and the spatial patterns of the CATS/GEOS based PM2.5 concentrations generally captured those from surface stations (with corresponding hourly EPA PM2.5 vs CATS PM2.5 statistics of R=0.4 and bias=1.5 μg/m³). In our recent work, as part of the Models, In situ, and Remote sensing of Aerosols (MIRA) Working Group, we have applied both the CALIOP and CATS/GEOS based approaches over the highly polluted country of India during the post-monsoon season (September-October 2016). We derived elevated levels of two-month mean PM2.5 (~100 μg/m³) in northern India, especially near New Delhi. These high PM2.5 concentrations in the Indo-Gangetic plain are driven in large part from the seasonal burning of crop residue and meteorological conditions typical at this time of the year, such as low wind speeds and a shallow boundary layer. While the satellite-derived PM2.5 moderately replicates (R = ~0.7-0.9) the spatial variability in the two-month mean of surface in situ PM2.5 from monitoring sites operated by the Central and State Pollution Control Boards, we show results from specific scenes for which there are large deviations between the satellite-derived PM2.5 and in situ measurements. Other current work on this topic focuses on developing PM2.5 estimates using airborne high spectral resolution lidar measurements through machine learning regression algorithms and involves several parameters (e.g., aerosol extinction, color ratio, lidar ratio). Application of this method over major metropolitan areas in the US and Asia have resulted in high correlations (R = 0.93) with surface measurements. This airborne lidar approach can be adapted to spaceborne lidar measurements, and all three of these approaches can be applied to ESA’s EarthCARE Atmospheric Lidar instrument, setting the stage for the future Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land Atmosphere System (CALIGOLA) mission. Ultimately, beyond estimates of PM2.5, the aerosol vertical distribution from lidars can benefit studies involving passive sensor approaches for PM2.5 proxies (including from geostationary satellites), wildfire smoke plume injection heights, volcanic emissions (e.g., ash height retrievals), and aerosol/air quality model assimilation, evaluation, and forecasts.

Travis D Toth↗
NASA NTRSDate not supplied

Effect of Baseline Period on Quantification of Climate Extremes over the United States

Extreme weather events, including heatwaves, heavy precipitation, and drought, have a large impact on society through human health, destruction of infrastructure, ecological change, and economic losses. Reanalyses such as NASA’s Modern Era Retrospective Analysis, version 2 (MERRA-2) are a valuable tool for analyzing past extreme events to determine their underlying causes and how extremes have changed over the past four decades. The detection of extreme events relies on a threshold for precipitation or temperature that is derived using a reference period, which can then be used to determine how extreme an event was or what the return period is. Operational centers typically use a 30-year climatology period that shifts in time every ten years, while the World Meteorological Organization suggests that the maximum amount of data should be included for the detection of extreme events due to their rare occurrence. As global and regional climate continues to change, the interpretation of extreme events is reliant on the baseline period that is used for the underlying thresholds and can be a source of uncertainty for the policy making community. Three baseline periods – 1981-2010, 1991-2020, and 1981-2020 – will be used to compute percentiles of temperature and precipitation across the contiguous United States and will then by employed to determine monthly indices representing heatwaves, cold spells, and extreme precipitation events. A spatial and temporal analysis of the resulting extreme weather indices will demonstrate the appropriateness for each baseline period for the evaluation of extreme events.

Extremes↗
NASA NTRS1999

Aircraft NO(x) had no Unique Fingerprint on Sonex; Lightning Dominated Fresh NO(x) Sources

Key questions to which SONEX was directed were the following: Can aircraft corridors be detected? Is there a unique tracer for aircraft NO(x)? Can a "background" NO(x) (or NO(y) be defined? What fraction of NO(x) measured during SONEX was from aircraft? How representative was SONEX of the North Atlantic in 1997 and how typical of other years? We attempt to answer these questions through species-species correlations, probability distribution functions (PDFs), and meteorological history. There is not a unique aircraft tracer, largely due to the high variability of air mass origins and tracer ratios, which render "average" quantities meaningless. The greatest NO and NO(y) signals were associated with lightning and convective NO sources. Well-defined background CO, NO(y) and NO(y)/ozone ratio appear in subsets of two cross-track flights with subtropical origins and five flights with predominantly mid-latitude air. Forty percent of the observations on these 7 flights showed NO(y)/ozone to be above background, evidently due to unreacted NO(x). This NO(x) is a combination of aircraft, lightning and surface pollution injected by convection. The strongly subtropical signatures in SONEX observations, confirmed by pv (potential vorticity) values along flight tracks, argues for most of the unreacted NO(x) originating from lightning. Potential vorticity statistics along SONEX flight tracks in 1992-1998, and for the North Atlantic as a whole, show the SONEX meteorological environment to be representative of the North Atlantic flight corridor in the October-November period.

Thompson, A.↗
NASA NTRS2021

Contribution of Meteorological Downscaling to Skill and Precision of Seasonal Drought Forecasts

Research in meteorological prediction on sub-seasonal to seasonal (S2S) timescales has seen growth in recent years. Concurrent with this, demand for seasonal drought forecasting has risen. While there is obvious synergy between these fields, S2S meteorological forecasting has typically focused on low resolution global models, while the development of drought can be sensitive to the local expression of weather anomalies and their interaction with local surface properties and processes. This suggests that downscaling might play an important role in the application of meteorological S2S forecasts to skillful forecasting of drought. Here, we apply the Generalized Analog Regression Downscaling (GARD) algorithm to downscale meteorological hindcasts from the NASA Goddard Earth Observing System (GEOS) global S2S forecast system. Downscaled meteorological fields are then applied to drive offline simulations with the Catchment Land Surface Model (CLSM) to forecast United States Drought Monitor (USDM) style drought indicators derived from simulated surface hydrology variables. We compare the representation of drought in these downscaled hindcasts to hindcasts that are not downscaled, using the North American Land Data Assimilation System Phase 2 (NLDAS-2) dataset as an observational reference. We find that downscaling using GARD improves hindcasts of temperature and temperature anomalies, but the results for precipitation are mixed and generally small. Overall, GARD downscaling led to improved hindcast skill for total drought across the Contiguous United States (CONUS), and improvements were greatest for extreme (D3) and exceptional (D4) drought categories.

Ryan A Zamora↗
NASA NTRS1985

Application of satellite data to tropic/subtropic moisture coupling

The objective is to develop analysis tools for use of satellite data to interpret synoptic-scale systems in data-void regions. Interim goals are to: (1) quantify the synoptic information content of satellite data; and (2) utilize these data in the diagnosis of moisture bursts in the eastern tropical Pacific Ocean. Researchers developed and implemented a statistical procedure for using TIROS N microwave data to infer infrared channel data for overcast conditions; they used the same procedure for deducing full TIROS N channel radiance profiles from NOAA 5 VTPR channel data over regions where the TIROS N data are missing. An empirical orthogonal function analysis of twice-daily channel radiance fields over the tropical eastern Pacific was completed. The vertically oriented eigenfunctions were interpreted in terms of typical meteorological events. The horizontal distribution of the eigenfunction amplitudes relates these meteorological signals to moisture bursts. A pair of moisture burst climatologies is complete: one of four years using infrared imagery (including the highly anomalous 1982 to 83 cold season); the other implementing 850 to 200 mb wind analyses in conjunction with GOES imagery. A number of different evaluations of the synoptic evolution of moisture fields (enhanced infrared imagery, moisture channel data, FGGE humidity analysis, and in situ station and sounding observations) are compared. All have limitations; all can be utilized together; all together are still less than adequate in the tropical Pacific.

Mcguirk, J. P.↗
NASA NTRS1988

The morphology and meteorology of Southern Hemisphere spring total ozone mini-holes

The purpose of this paper is to describe the properties of mini-hole events. Both Total Ozone Mapping Spectrometer (TOMS) data and National Meteorological Center (NMC) meteorological analyses will be used to determine the horizontal, vertical and temporal characteristics of the mini-holes. Mini-holes are rapidly developing (1 to 5 days), small horizontal scale (1000 to 3000 km) features which appear in the polar total ozone field during September and October of each year. Typically, a total of 1 to 6 mini-holes appear each year in either the Palmer penninsula region or over the East Antarctica ice sheet. The mini-holes do not develop over these two regions, but they intensify most dramatically there (possibly associated with the local orography). The mini-holes are associated with cold pools of air in the lower stratosphere, anti-cyclonic (geopotential height highs) disturbances to their west, high potential vorticity slightly to the east, and strong northward flow. These meteorological features are baroclinic, having a distinct westward tilt with increasing altitude.

Newman, Paul A.↗
NASA NTRS2017

Meteorological Drivers of Cold Temperatures in the Western Pacific TTL

During the recent October 2016 aircraft sampling mission of the Tropical Tropopause Layer (POSIDON -- Pacific Oxidants, Sulfur, Ice, Dehydration, and cONvection), Western Pacific October TTL temperatures were anomalously cold due to a combination of La Nina conditions and a very stationary convective pattern. POSIDON also had more October Tropical Cyclones than typical, and tropical cyclones have substantial negative TTL temperatures associated with them. This paper investigates how meteorology in the troposphere drives TTL temperatures, and how these temperatures, coupled with the circulation, produce TTL clouds. We will also compare October TTL cloud distributions in different years, examining the relationship of clouds to October temperature anomalies.

Pfister, Leonhard↗
NASA NTRSDate not supplied

Three Years of Airborne Observations During NASA Activate: A Statistical Summary of Chemical, Optical, and Microphysical Aerosol Properties Over the Western North Atlantic Ocean

Airborne observations are critical to understanding Earth’s climate system and surface-level air quality by providing both spatial and vertical information that is not possible through ground measurement networks or satellite observations. Airborne platforms allow assessments of long-range transport, vertical redistribution, boundary-layer dynamics, and cloud-aerosol-interactions that are critical to model evaluation and satellite validation. Still, the high cost and effort of aircraft operations can limit measurement campaigns to short, focused time periods. Multiple deployments are often necessary for seasonal comparisons, and results can be limited if target phenomenon are infrequent. Subsequent analyses typically focus on case studies, especially if deployment conditions are climatologically anomalous. The NASA ACTIVATE (Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment) mission was designed to overcome these limitations by operating semi-continuously over multiple months during multiple seasons. Flight plans were intentionally simple, repetitive, and systematic to provide a statistically robust dataset that could be utilized similarly to a ground-network. Here, we present an overview of three years (2020-2022) of aerosol measurements from the NASA HU-25 Falcon aircraft supporting the ACTIVATE mission. Data from 179 flights were considered, the majority of which were based at NASA Langley Research Center and flown locally over the Wester North Atlantic Ocean just east of Hampton, VA, USA. Airmass characteristics tended to transition from continental outflow near the coast to mostly marine over the open ocean. Seasonal, diurnal, spatial, and vertical trends in aerosol microphysical, optical, and chemical properties are discussed in the context of synoptic scale meteorology. Statistical benefits of the ACTIVATE sampling strategy are discussed with regard to future model evaluation.

Luke D Ziemba↗
NASA NTRS1988

Use of operational analyses to study the dynamics of troposphere-stratosphere interactions in polar regions

Operational analyses produced by large weather centers have been used in the past to monitor various aspects of the general circulation as well as address dynamical questions. For a number years researchers have been monitoring National Meteorological Center (NMC) analyses at 100 millibars because it is the level from which stratospheric analyses are built. In particular, they closely examined the pressure-work term at that level which is an important parameter related to the forcing of the stratosphere by the troposphere. Rapid fluctuations typically seen in this quanity during the months of July-November, and similarly noted by Randel et al., (1987) may raise some concern about the quality of the analyses. Researchers investigated the behavior of the term mainly responsible for these variations, namely the eddy flux of heat, and furthermore have corroborated the presence of these variations in contemporaneous analyses produced by the European Centre for Medium Range Forecasts (ECMWF). Researchers demonstrated that fluctuations in standing eddy heat fluxes, related to the forcing of the stratosphere by the troposphere, agree in two largely independent meteorological analyses. Researchers believe, that these fluctuations are mostly real.

Salstein, David A.↗
NASA NTRS2004

Tower Mesonetwork Climatology and Interactive Display Tool

Forecasters at the 45th Weather Squadron and Spaceflight Meteorology Group use data from the tower network over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to evaluate Launch Commit Criteria, and issue and verify forecasts for ground operations. Systematic biases in these parameters could adversely affect an analysis, forecast, or verification. Also, substantial geographical variations in temperature and wind speed can occur under specific wind directions. To address these concerns, the Applied Meteorology Unit (AMU) developed a climatology of temperatures and winds from the tower network, and identified the geographical variation and significant tower biases. The mesoclimate is largely driven by the complex land-water interfaces across KSC/CCAFS. Towers with close proximity to water typically had much warmer nocturnal temperatures and higher wind speeds throughout the year. The strongest nocturnal wind speeds occurred from October to March whereas the strongest mean daytime wind speeds occurred from February to May. These results of this project can be viewed by forecasters through an interactive graphical user interface developed by the AMU. The web-based interface includes graphical and map displays of mean, standard deviation, bias, and data availability for any combination of towers, variables, months, hours, and wind directions.

Case, Jonathan L.↗
NASA NTRS1977

Description and review of global measurements of atmospheric species from GASP

Aerosol composition data were collected with a NASA F-106 aircraft. Present measurements include ozone, carbon monoxide, water vapor, aerosol and condensation nuclei number densities, sulphates, nitrates, and the chlorofluoromethanes. Meteorological and flight parameters are also recorded for use in data analysis. The present aircraft operations obtain data between 6 and 13.5 km from 65 degree N between Europe and the north Pacific, and from 23 degree S over South America and 42 degree S over New Zealand. Typical constituent data from the aircraft operations during the first one and a half years are presented. Instrumentation is discussed.

Gauntner, D. J.↗
NASA NTRS1977

Description and review of global measurements of atmospheric species from GASP

A large volume of atmospheric constituent data is being collected in the global airlanes by specially equipped B-747 aircraft. This NASA program also obtains data from the similarly equipped NASA CV-990 aircraft during dedicated flights such as a recent near pole-to-pole latitude survey mission. Aerosol composition data are also collected with a NASA F-106 aircraft. Present measurements include ozone, carbon monoxide, water vapor, aerosol and condensation nuclei number densities, sulphates, nitrates, and the chlorofluoromethanes. Meteorological and flight parameters are also recorded for use in data analysis. The present aircraft operations obtain data between 6 and 13.5 km from 65 deg N between Europe and the North Pacific, and from 23 deg S over South America and 42 deg S over New Zealand. Typical constituent data from the aircraft operations during the first one and a half years are presented. Instrumentation is discussed.

Gauntner, D. J.↗
NASA NTRS1998

The Marshall Automated Wind Algorithm for Geostationary Satellite Wind Applications

The Marshall Automated Wind (MAW) algorithm was developed over a decade ago in support of specialized studies of mesoscale meteorology. In recent years, the algorithm has been generalized to address global climate issues and other specific objectives related to NASA missions. The MAW algorithm uses a tracking scheme which minimizes image brightness temperature differences in a sequence of satellite images to determine feature displacement (winds). With the appropriate methodology accurate satellite derived winds can be obtained from visible, infrared, and water vapor imagery. Typical errors are less than 4 m/s but depend on the quality and control constraints used in post-processing. Key to this success is the judicious use of template size and search area used for tracking, image resolution and time sampling, and selection of appropriate statistical constraints which may vary with image type and desired application. The conference paper and subsequent poster will provide details of the technique and examples of its application.

Jedlovec, Gary J.↗
NASA NTRS1998

NASA/FAA/NCAR Supercooled Large Droplet Icing Flight Research: Summary of Winter 1996-1997 Flight Operations

During the winter of 1996-1997, a flight research program was conducted at the NASA-Lewis Research Center to study the characteristics of Supercooled Large Droplets (SLD) within the Great Lakes region. This flight program was a joint effort between the National Aeronautics and Space Administration (NASA), the National Center for Atmospheric Research (NCAR), and the Federal Aviation Administration (FAA). Based on weather forecasts and real-time in-flight guidance provided by NCAR, the NASA-Lewis Icing Research Aircraft was flown to locations where conditions were believed to be conducive to the formation of Supercooled Large Droplets aloft. Onboard instrumentation was then used to record meteorological, ice accretion, and aero-performance characteristics encountered during the flight. A total of 29 icing research flights were conducted, during which "conventional" small droplet icing, SLD, and mixed phase conditions were encountered aloft. This paper will describe how flight operations were conducted, provide an operational summary of the flights, present selected experimental results from one typical research flight, and conclude with practical "lessons learned" from this first year of operation.

Miller, Dean↗
NASA NTRSDate not supplied

A Quantitative Analysis on the Use of Supervised Machine Learning in Earth Science

Recent review papers (Ball et al., 2017; Reichstein et al., 2019) have investigated the opportunities and challenges in applying supervised machine learning (ML) techniques to Earth science problems. A common challenge is the lack of training (or labeled) data. Supervised ML, and especially deep learning (DL), require large training datasets. While there are large, open access Earth science archives, the data typically require preprocessing in preparation for supervised ML, frequently including manual labeling. Our objective is to understand the landscape of supervised ML in the Earth sciences, including which research communities have most rapidly adopted supervised ML, which algorithms are applied, and what data are used to train these algorithms. We conducted a literature survey of Earth science papers published during the last 10 years in journals from the American Geophysical Union (AGU), American Meteorological Society (AMS), the Institute of Electrical and Electronics Engineers(IEEE), and the Society of Photo-Optical Instrumentation Engineers (SPIE). We identified papers containing the terms ML, DL, or the names of individual supervised ML algorithms. "Earth science" is an additional required search term for IEEE and SPIE. We investigate trends in supervised ML usage during the 10-year study period, and manually analyzed AGU papers from 2018-2019 to enable deep-dive statistics.

Katrina S Virts↗
NASA NTRS2001

Seasonal Snow Extent and Snow Volume in South America Using SSM/I Passive Microwave Data

Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Special Sensor Microwave Imagers (SSM/I) on board Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1992-1998, both snow cover extent and snow depth (snow mass) were investigated during the winter months (May-August) in the Patagonia region of Argentina. Since above normal temperatures in this region are typically above freezing, the coldest winter month was found to be not only the month having the most extensive snow cover but also the month having the deepest snows. For the seven-year period of this study, the average snow cover extent (May-August) was about 0.46 million sq km and the average monthly snow mass was about 1.18 x 10(exp 13) kg. July 1992 was the month having the greatest snow extent (nearly 0.8 million sq km) and snow mass (approximately 2.6 x 10(exp 13) kg).

Foster, James L.↗