Search NASA⌕ Search

SEARCH · Search NASA

Results for “Atmospheric Radiation Program”

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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Data management and scientific integration within the Atmospheric Radiation Measurement Program

The Atmospheric Radiation Measurement (ARM) Program has been developed by the U.S. Department of Energy with the goal to improve the predictive capabilities of General Circulation Models (GCM's) in their treatment of clouds and radiative transfer effects. To achieve this goal, three experimental testbeds were designed for the deployment of instruments that will collect atmospheric data used to drive the GCM's. Each site, known as a Cloud and Radiation Testbed (CART), consists of a highly available, redundant data system for the collection of data from a variety of instrumentation. The first CART site was deployed in April 1992 in the Southern Great Plains (SGP), Lamont, Oklahoma, with the other two sites to follow in September 1995 in the Tropical Western Pacific and in 1997 on the North Slope of Alaska. Approximately 400 MB of data are transferred per day via the Internet from the SGP site to the ARM Experiment Center at Pacific Northwest Laboratory in Richland, Washington. The Experiment Center is central to the ARM data path and provides for the collection, processing, analysis, and delivery of ARM data. Data are received from the CART sites from a variety of instrumentation, observational systems, amd external data sources. The Experiment Center processes these data streams on a continuous basis to provide derived data products to the ARM Science Team in near real-time while providing a three-month running archive of data. A primary requirement of the ARM Program is to preserve and protect all data produced or acquired. This function is performed at Oak Ridge National Laboratory where leading edge technology is employed for the long-term storage of ARM data. The ARM Archive provides access to data for participation outside of the ARM Program. The ARM Program involves a collaborative effort by teams from various DOE National Laboratories, providing multi-disciplinary areas of expertise. This paper will discuss the collaborative methods in which the ARM teams translate the scientific goals of the Program into data products. By combining atmospheric scientists, systems engineers, and software engineers, the ARM Program has successfully designed and developed an environment where advances in understanding the parameterizations of GCM's can be made.

Gracio, Deborah K.↗
DOE OSTI2021

Aerosol Activation in Radiation Fog at the Atmospheric Radiation Program Southern Great Plains Site

Environmental supersaturation is a key parameter in the formation of fog and clouds, yet it cannot be measured directly and must be inferred. Calculating the ambient supersaturation in fog requires knowledge of the aerosol hygroscopicity as well as particle size distribution, and relatively few values have been reported in the literature. Here we use κ-Köhler theory to derive aerosol activation properties based on particle hygroscopicity and dry particle size distributions, and then estimate the effective peak supersaturation during eight cases of radiative fog at the Southern Great Plains site in rural north-central Oklahoma, USA. The mean hygroscopicity parameter κ of particles likely to act as cloud condensation nuclei varied from 0.14 to 0.43. Ambient effective peak supersaturation during the fog episodes was between 0.01%–0.07%, with most values below 0.04%. Furthermore, the minimum 50% dry activation diameter generally ranged between 300–400 nm with little activation of particles with diameters below 300 nm.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Lidar Development for the Atmospheric Radiation Measurement (ARM) Program

The Atmospheric Radiation Measurement (ARM) Program was initiated by the Department of Energy's Atmospheric and Climate Research Division (DOE/ACRD) to improve parameterizations of cloud radiative effects in general circulation models of the Earth's climate. The Instrument Development Program (IDP), a major component of ARM, is directed toward the improvement of radiometric and remote sensing instrumentation pertinent to near real-time characterizations of atmospheric parameters. The ultimate goal of this program is to provide state-of-the-art instruments suitable for installation and extended use in ARM's field measurement component, the Cloud and Radiation Testbed (CART).

Griffin, J.↗
NASA NTRS2001

Full-Time, Eye-Safe Cloud and Aerosol Lidar Observation at Atmospheric Radiation Measurement Program Sites: Instruments and Data Analysis

Atmospheric radiative forcing, surface radiation budget, and top of the atmosphere radiance interpretation involves a knowledge of the vertical height structure of overlying cloud and aerosol layers. During the last decade, the U.S. Department of Energy through I the Atmospheric Radiation Measurement (ARM) program has constructed four long- term atmospheric observing sites in strategic climate regimes (north central Oklahoma, In Barrow. Alaska, and Nauru and Manus Islands in the tropical western Pacific). Micro Pulse Lidar (MPL) systems provide continuous, autonomous observation of all significant atmospheric cloud and aerosol at each of the central ARM facilities. Systems are compact and transmitted pulses are eye-safe. Eye-safety is achieved by expanding relatively low-powered outgoing Pulse energy through a shared, coaxial transmit/receive telescope. ARM NIPL system specifications, and specific unit optical designs are discussed. Data normalization and calibration techniques are presented. A multiple cloud boundary detection algorithm is also described. These techniques in tandem represent an operational value added processing package used to produce normalized data products for Cloud and aerosol research and the historical ARM data archive.

Campbell, James R.↗
NASA NTRS2012

Cloud Droplet Size and Liquid Water Path Retrievals From Zenith Radiance Measurements: Examples From the Atmospheric Radiation Measurement Program and the Aerosol Robotic Network

The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Network (AERONET) routinely monitor clouds using zenith radiances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a water-absorbing wavelength (i.e. 1640 nm) with a nonwater-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g/sq m and horizontal resolution of 201m, the retrieval method underestimates the mean effective radius by 0.8 m, with a root-mean-squared error of 1.7 m and a relative deviation of 13 %. For actual observations with a liquid water path less than 450 gm.2 at the ARM Oklahoma site during 2007-2008, our 1.5 min-averaged retrievals are generally larger by around 1 m than those from combined ground-based cloud radar and microwave radiometer at a 5min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 m and the relative deviation of 22% are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11% with satellite observations and have a negative bias of 1 m. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

Chiu, J. C.↗
NASA NTRS2006

Application of Aerosol Hygroscopicity Measured at the Atmospheric Radiation Measurement Program's Southern Great Plains Site to Examine Composition and Evolution

A Differential Mobility Analyzer/Tandem Differential Mobility Analyzer (DMA/TDMA) was used to measure submicron aerosol size distributions, hygroscopicity, and occasionally volatility during the May 2003 Aerosol Intensive Operational Period (IOP) at the Central Facility of the Atmospheric Radiation Measurement Program's Southern Great Plains (ARM SGP) site. Hygroscopic growth factor distributions for particles at eight dry diameters ranging from 0.012 micrometers to 0.600 micrometers were measured throughout the study. For a subset of particle sizes, more detailed measurements were occasionally made in which the relative humidity or temperature to which the aerosol was exposed was varied over a wide range. These measurements, in conjunction with backtrajectory clustering, were used to infer aerosol composition and to gain insight into the processes responsible for evolution. The hygroscopic growth of both the smallest and largest particles analyzed was typically less than that of particles with dry diameters of about 0.100 micrometers. It is speculated that condensation of secondary organic aerosol on nucleation mode particles is largely responsible for the minimal hygroscopic growth observed at the smallest sizes considered. Growth factor distributions of the largest particles characterized typically contained a nonhygroscopic mode believed to be composed primarily of dust. A model was developed to characterize the hygroscopic properties of particles within a size distribution mode through analysis of the fixed size hygroscopic growth measurements. The performance of this model was quantified through comparison of the measured fixed size hygroscopic growth factor distributions with those simulated through convolution of the size-resolved concentration contributed by each of the size modes and the mode-resolved hygroscopicity. This transformation from sizeresolved hygroscopicity to mode-resolved hygroscopicity facilitated examination of changes in the hygroscopic properties of particles within a size distribution mode that accompanied changes in the sizes of those particles. This model was used to examine three specific cases in which the sampled aerosol evolved slowly over a period of hours or days.

Gasparini, Roberto↗
DOE OSTI2022

Correcting for filter-based aerosol light absorption biases at the Atmospheric Radiation Measurement program's Southern Great Plains site using photoacoustic measurements and machine learning

Abstract. Measurement of light absorption of solar radiation by aerosols is vital for assessing direct aerosol radiative forcing, which affects local and global climate. Low-cost and easy-to-operate filter-based instruments, such as the Particle Soot Absorption Photometer (PSAP), that collect aerosols on a filter and measure light attenuation through the filter are widely used to infer aerosol light absorption. However, filter-based absorption measurements are subject to artifacts that are difficult to quantify. These artifacts are associated with the presence of the filter medium and the complex interactions between the filter fibers and accumulated aerosols. Various correction algorithms have been introduced to correct for the filter-based absorption coefficient measurements toward predicting the particle-phase absorption coefficient (Babs). However, the inability of these algorithms to incorporate into their formulations the complex matrix of influencing parameters such as particle asymmetry parameter, particle size, and particle penetration depth results in prediction of particle-phase absorption coefficients with relatively low accuracy. The analytical forms of corrections also suffer from a lack of universal applicability: different corrections are required for rural and urban sites across the world. In this study, we analyzed and compared 3 months of high-time-resolution ambient aerosol absorption data collected synchronously using a three-wavelength photoacoustic absorption spectrometer (PASS) and PSAP. Both instruments were operated on the same sampling inlet at the Department of Energy's Atmospheric Radiation Measurement program's Southern Great Plains (SGP) user facility in Oklahoma. We implemented the two most commonly used analytical correction algorithms, namely, Virkkula (2010) and the average of Virkkula (2010) and Ogren (2010)–Bond et al. (1999) as well as a random forest regression (RFR) machine learning algorithm to predict Babs values from the PSAP's filter-based measurements. The predicted Babs was compared against the reference Babs measured by the PASS. The RFR algorithm performed the best by yielding the lowest root mean square error of prediction. The algorithm was trained using input datasets from the PSAP (transmission and uncorrected absorption coefficient), a co-located nephelometer (scattering coefficients), and the Aerosol Chemical Speciation Monitor (mass concentration of non-refractory aerosol particles). A revised form of the Virkkula (2010) algorithm suitable for the SGP site has been proposed; however, its performance yields approximately 2-fold errors when compared to the RFR algorithm. To generalize the accuracy and applicability of our proposed RFR algorithm, we trained and tested it on a dataset of laboratory measurements of combustion aerosols. Input variables to the algorithm included the aerosol number size distribution from the Scanning Mobility Particle Sizer, absorption coefficients from the filter-based Tricolor Absorption Photometer, and scattering coefficients from a multiwavelength nephelometer. The RFR algorithm predicted Babs values within 5 % of the reference Babs measured by the multiwavelength PASS during the laboratory experiments. Thus, we show that machine learning approaches offer a promising path to correct for biases in long-term filter-based absorption datasets and accurately quantify their variability and trends needed for robust radiative forcing determination.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

The Atmospheric Radiation Measurement Program May 2003 Intensive Operations Period Examining Aerosol Properties and Radiative Influences: Preface to Special Section

Atmospheric aerosols influence climate by scattering and absorbing radiation in clear air (direct effects) and by serving as cloud condensation nuclei, modifying the microphysical properties of clouds, influencing radiation and precipitation development (indirect effects). Much of present uncertainty in forcing of climate change is due to uncertainty in the relations between aerosol microphysical and optical properties and their radiative influences (direct effects) and between microphysical properties and their ability to serve as cloud condensation nuclei at given supersaturations (indirect effects). This paper introduces a special section that reports on a field campaign conducted at the Department of Energy Atmospheric Radiation Measurement site in North Central Oklahoma in May, 2003, examining these relations using in situ airborne measurements and surface-, airborne-, and space-based remote sensing.

Ferrare, Richard↗
NASA NTRS1988

NASA earth science and applications division: The program and plans for FY 1988-1989-1990

Described here are the Division's research goals, priorities and emphases for the next several years and an outline of longer term plans. Included are highlights of recent accomplishments, current activities in FY 1988, research emphases in FY 1989, and longer term future plans. Data and information systems, the Geodynamics Program, the Land Processes Program, the Oceanic Processes Program, the Atmospheric Dynamics and Radiation Program, the Atmospheric Chemistry Program, and space flight programs are among the topic covered.

Source record↗
DOE OSTI2022

Trends in Downwelling Longwave Radiance Over the Southern Great Plains

Downwelling longwave radiation is an important part of the surface energy budget. Spectral trends in the downwelling longwave radiance (DLR) provide insight into the radiative drivers of climate change. In this research, we process and analyze a 23-year DLR record measured by the Atmospheric Emitted Radiance Interferometer (AERI) at the U.S. Department of Energy Atmospheric Radiation Program Southern Great Plains (SGP) site. Two AERIs were deployed at SGP with an overlapping observation period of about 10 years, which allows us to examine the consistency and accuracy of the measurements and to account for discrepancies between them due to errors associated with the instruments themselves. We then analyzed the all-sky radiance trends in DLR, which are associated with the surface warming trend at SGP during this same period and also the complex changes in meteorological conditions. For instance, the observed radiance in the CO2 absorption band follows closely the near-surface air temperature variations. The significant positive radiance trends in weak absorption channels, such as in the wings of the CO 2 band and in the weak absorption channels in the H 2 O vibration-rotational band, show earlier detectability of climate change. The magnitude of the radiance trend uncertainty in the DLR record mainly results from internal climate variability rather than from measurement error, which highlights the importance of continuing the DLR spectral measurements to unambiguously detect and attribute climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Investigation of Dynamic and Physical Processes in the Upper Troposphere and Lower Stratosphere

Research under this Cooperative Agreement has been funded by several NASA Earth Science programs: the Atmospheric Effects of Radiation Program (AEAP), the Upper Atmospheric Research Program (UARP), and most recently the Atmospheric Chemistry and Modeling Assessment Program (ACMAP). The purpose of the AEAP was to understand the impact of the present and future fleets of conventional jet traffic on the upper troposphere and lower stratosphere, while complementary airborne observations under UARP seek to understand the complex interactions of dynamical and chemical processes that affect the ozone layer. The ACMAP is a more general program of modeling and data analysis in the general area of atmospheric chemistry and dynamics, and the Radiation Sciences program.

Selkirk, Henry B.↗
NASA NTRS1985

Fundamental remote sensing science research program: The Scene Radiation and Atmospheric Effects Characterization Project

The Scene Radiation and Atmospheric Effects Characterization (SRAEC) Project was established within the NASA Fundamental Remote Sensing Science Research Program to improve our understanding of the fundamental relationships of energy interactions between the sensor and the surface target, including the effect of the atmosphere. The current studies are generalized into the following five subject areas: optical scene modeling, Earth-space radiative transfer, electromagnetic properties of surface materials, microwave scene modeling, and scatterometry studies. This report has been prepared to provide a brief overview of the SRAEC Project history and objectives and to report on the scientific findings and project accomplishments made by the nineteen principal investigators since the project's initiation just over three years ago. This annual summary report derives from the most recent annual principal investigators meeting held January 29 to 31, 1985.

Deering, D. W.↗
NASA NTRS1983

Improving our understanding of the remote sensing process

Plans for two fundamental research programs aimed at improving an understanding of the physics and mathematics of remote sensing are discussed. The first program, Scene Radiation and Atmospheric Research Program, is concerned with developing the capability to determine biophysical attributes of terrestrial scenes through an improved understanding of the relationships between those properties and remotely sensed radiation. The research issues in the second program, Mathematical Pattern Recognition and Image Analysis, are discussed with reference to the following five categories: preprocessing, digital image representation, object scene inference, computational structures, and continuing studies.

Calabrese, M. A.↗
NASA NTRS2012

Assessing Spectral Shortwave Cloud Observations at the Southern Great Plains Facility

The Atmospheric Radiation Measurement (ARM) program (now Atmospheric System Research) was established, in part, to improve radiation models so that they could be used reliably to compute radiation fluxes through the atmosphere, given knowledge of the surface albedo, atmospheric gases, and the aerosol and cloud properties. Despite years of observations, discrepancies still exist between radiative transfer models and observations, particularly in the presence of clouds. Progress has been made at closing discrepancies in the spectral region beyond 3 micron, but the progress lags at shorter wavelengths. Ratios of observed visible and near infrared cloud albedo from aircraft and satellite have shown both localized and global discrepancies between model and observations that are, thus far, unexplained. The capabilities of shortwave surface spectrometry have been improved in recent years at the Southern Great Plains facility (SGP) of the ARM Climate Research Facility through the addition of new instrumentation, the Shortwave Array Spectroradiometer, and upgrades to existing instrumentation, the Shortwave Spectroradiometer and the Rotating Shadowband Spectroradiometer. An airborne-based instrument, the HydroRad Spectroradiometer, was also deployed at the ARM site during the Routine ARM Aerial Facility Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign. Using the new and upgraded spectral observations along with radiative transfer models, cloud scenes at the SGP are presented with the goal of characterizing the instrumentation and the cloud fields themselves.

McBride, P. J.↗
NASA NTRS1997

Cloud Radiation Forcings and Feedbacks: General Circulation Model Tests and Observational Validation

Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors' numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative. A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive. These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model. together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean-Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.

Lee,Wan-Ho↗
DOE OSTI2020

Updraft and Downdraft Core Size and Intensity as Revealed by Radar Wind Profilers: MCS Observations and Idealized Model Comparisons

This study explores the updraft and downdraft properties of mature stage mesoscale convective systems (MCSs) in terms of draft core width, shape, intensity, and mass flux characteristics. The observations use extended radar wind profiler (RWP) and surveillance radar datasets from the U.S. Department of Energy Atmospheric Radiation Measurement program for midlatitude (Oklahoma, USA) and tropical (Amazon, Brazil) sites. MCS drafts behave qualitatively similar to previous aircraft and RWP cloud summaries. The Oklahoma MCSs indicate larger and more intense convective up- and downdraft cores, and greater mass flux than Amazon MCS counterparts. However, similar size-intensity relationships and draft vertical profile behaviors are observed for both regions. Additional similarities include weak positive correlations between core intensity and core width (correlation coefficient r ~ 0.5), and increases in draft intensity with altitude. A model-observational intercomparison for draft properties (core width, intensity, mass flux) is also performed to illustrate the potential usefulness of statistical observed draft characterizations. Idealized simulations with the Weather Research and Forecasting model aligned with midlatitude MCS conditions are performed at model grid spacings (?x) that range from 4 km to 250 m. It is shown that the simulations performed at ?x = 250 m at similar mature MCS lifecycle stages are those that exhibit draft intensity, width, mass flux, and shape parameter performances best matching with observed properties.

radar, arm, wind profiler, goamazon↗