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At least 1,297 records · Page 72
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Inferring Ozone Production in an Urban Atmosphere using Measurements of Peroxynitric Acid

Observations of peroxynitric acid (HO2NO2) obtained simultaneously with those of NO and NO2 provide a sensitive measure of the ozone photochemical production rate. We illustrate this technique for constraining the ozone production rate with observations obtained from the NCAR C-130 aircraft platform during the Megacity Initiative: Local and Global Research Observations (MILAGRO) intensive in Mexico during the spring of 2006. Sensitive and selective measurements of HO2NO2 were made in situ using chemical ionization mass spectrometry (CIMS). Observations were compared to modeled HO2NO2 concentrations obtained from the NASA Langley highly-constrained photochemical time-dependent box model. The median observed-to-calculated ratio of HO2NO2 is 1.18. At NOx levels greater than 15 ppbv, the photochemical box model underpredicts observations with an observed-to-calculated ratio of HO2NO2 of 1.57. As a result, we find that at high NOx, the ozone production rate calculated using measured HO2NO2 is faster than predicted using accepted photochemistry. Inclusion of an additional HOx source from the reaction of excited state NO2 with H2O or reduction in the rate constant of the reaction of OH with NO2 improves the agreement.

Spencer, K. M.↗
NASA NTRS1993

Circulation anomaly mechanisms in the tropical Atlantic sector during the northeast Brazil rainy season - Results from the GISS general circulation model

The paper examines the effect of the SST pattern in the tropical Atlantic on the overlying atmosphere from a 7-yr run of the GCM of the Goddard Institute for Space Studies (GISS) (period 1980-1986) and in comparison to upper air analyses of the ECMWF, surface ship observations and wind fields, and rainfall measurements in northeast Brazil. The GCM simulation reproduces the thermal and hydrostatic forcing of SST on the meridional gradients of lower-tropospheric thickness and pressure in the proper sense, albeit more weakly than observed. The modeled meridional wind component follows the meridional pressure gradient in the proper sense, but mean and range are smaller than observed, and the modeled interannual variability is not entirely consistent with observational evidence. Overall, the GISS GCM seems to reproduce reasonably well the response of lower-tropospheric thickness and near-surface pressure to SST, while the simulation of wind and rainfall is somewhat deficient.

Hastenrath, Stefan↗
NASA NTRS1999

Ozone Budgets from a Global Chemistry/ Transport Model and Comparison to Observations from POLARIS

The objective of the Photochemistry of Ozone Loss in the Arctic Region in Summer (POLARIS) field mission was to obtain data to better characterize the summertime seasonal decrease of ozone at mid to high latitudes. The decrease in ozone occurs mainly in the lower stratosphere and is expected to result from in situ chemical destruction. Instrumented balloons and aircraft were used in POLARIS, along with satellites, to measure ozone and chemical species which are involved with stratospheric ozone chemistry. In order to close the seasonal ozone budget, however, ozone transport must also be estimated. Comparison to a global chemistry and transport model (CTM) of the stratosphere indicates how well the summertime ozone loss processes are simulated and thus how well we can predict the ozone response to changing amounts of chemical source gases. Moreover, the model gives insight into the possible relative magnitude of transport contributions to the seasonal ozone decline. Initial comparison to the Goddard CTM, which uses transport winds and temperatures from meteorological data assimilation, shows a high ozone bias in the model and an attenuated summertime ozone loss cycle. Comparison of the model chemical partitioning, and ozone catalytic loss rates to those derived from measurements shows fairly close agreement both at ER-2 altitudes (20 km) and higher. This suggests that the model transport is too active in resupplying ozone to the high latitude region, although chemistry failings cannot be completely ruled out. Comparison of ozone and related species will be shown along with a full diagnosis of the model ozone budget and its possible sources of error.

Kawa, S. Randy↗
NASA NTRS1998

Ozone Budgets from a Global Chemistry/Transport Model and Comparison to Observations from POLARIS

The objective of the Photochemistry of Ozone Loss in the Arctic Region in Summer (POLARIS) field mission was to obtain data to better characterize the summertime seasonal decrease of ozone at mid to high latitudes. The decrease in ozone occurs mainly in the lower stratosphere and is expected to result from in situ chemical destruction. Instrumented balloons and aircraft were used in POLARIS, along with satellites, to measure ozone and chemical species which are involved with stratospheric ozone chemistry. In order to close the seasonal ozone budget, however, ozone transport must also be estimated. Comparison to a global chemistry and transport model (CTM) of the stratosphere indicates how well the summertime ozone loss processes are simulated and thus how well we can predict the ozone response to changing amounts of chemical source gases. Moreover, the model gives insight into the possible relative magnitude of transport contributions to the seasonal ozone decline. Initial comparison to the Goddard CTM, which uses transport winds and temperatures from meteorological data assimilation, shows a high ozone bias in the model and an attenuated summertime ozone loss cycle. Comparison of the model chemical partitioning and ozone catalytic loss rates to those derived from measurements shows fairly close agreement both at ER-2 altitudes (20 km) and higher. This suggests that the model transport is too active in resupplying ozone to the high latitude region, although chemistry failings cannot be completely ruled out. Comparison of ozone and related species will be shown along with a full diagnosis of the model ozone budget and its possible sources of error.

Kawa, S. Randolph↗
NASA NTRS2008

Eta Carinae: An Astrophysical Laboratory

In the 1840s, Eta Carinae, a massive binary near the end of its hydrogen burning cycle, ejected at least ten solar masses of material rich in nitrogen at the expense of carbon and oxygen. The resultant chemistry has led to a most peculiar mix of metals, molecules and dust. We identify thousands of nebular absorption lines of ions including Fe, Ni, V, Sr, Sc and molecules including H2, CH, OH, but no CO. Today we see a wind-enshrouded massive binary in the center of an expanding neutral hourglass and skirt. A similar ionized internal structure is associated with a lesser ejection of the 1890s. Both systems respond to the 5.54-year modulation of X-ray and ultraviolet radiation as the less massive, hotter companion plunges through the extended wind of the more massive, cooler primary. Observations and models are being brought together to understand the properties of the wind-enshrouded central binary. In turn we are learning much atomic spectroscopy, what molecules form in oxygen-and carbon-deprived environments and potentially about a dust that is quite different from the interstellar dust. As the next periastron occurs in January 2009, a number of observing teams are preparing to test these models with new observations.

Gull, T.↗
DOE OSTI2020

Integrating field observations and process-based modeling to predict watershed water quality under environmental perturbations

Watersheds play a critical role in supplying water resources needed for human use and ecosystem health. Understanding and predicting how, when, and where changes in the quantity and quality of water resources occur under different environmental stresses including extreme events is crucial for sustainable management of water resources under a changing environment. However, few studies have attempted to quantify or identify the factors and process interactions controlling the impact of extreme events across water-shed systems. Only few large-scale studies include coordinated monitoring and modeling efforts, which limits our ability to assess the large-scale impact of extreme events on water supply and quality. Methods are lacking to propagate uncertainty in process understanding through an integrated hydro-biogeochemical model framework and evaluate its importance, thus failing to take full advantage of the information potentially available through transformative advances in characterization technologies from high-resolution mass spectrometry to airborne and satellite-based remote sensing. There are consequent risks to our nations water security and to human and ecosystem health that may become exacerbated with the increasing frequency of extreme events that is projected for the coming decades. This paper reviews the current status of watershed science for both water quantity and quality and identifies critical gaps in our current knowledge and modeling capability in addressing the emergent needs in predicting watershed hydrologic and biogeochemical responses (i.e., water quantity and quality) under natural and anthropogenic perturbations. We highlight the need to (1) understand how environmental perturbations including extreme events like floods and droughts propagate through watershed systems and assess their short- and long-term impacts on watershed biogeochemistry, water quality and their recovery pathways; (2) develop and improve a watershed water quality model that reflects the state of scientific understanding gained from observations; and (3) construct a data-model fusion system for watershed characterization, process identification, and mechanistic model parameterization. A large base of modeling, monitoring and data capabilities have been built by various federal government agencies given the relevance of water to their critical missions. An emerging need is to build an integrated national capability for watershed water availability and quality that can address water-related missions across multiple federal agencies.

13 HYDRO ENERGY↗
DOE OSTI2023

Optimization and Evaluation of Stochastic Unified Convection Using Single-Column Model Simulations at Multiple Observation Sites

We extend the previously developed stochastic unified convection scheme (UNICON) for shallow convection to deep convection by parameterizing the impact of mesoscale organized flow on updraft properties. The extended stochastic UNICON parameterizes thermodynamic properties of updrafts at the near-surface as a multivariate Gaussian distribution, where the variances of the distribution are the summation of variances from non-organized turbulence and mesoscale organized flow. The distribution of updraft radius is parameterized as a power-law distribution with a scale break which is parameterized as a linear function of the strength of mesoscale organized flow. The proposed parameterization is validated using a series of large-eddy simulations of deep convection. The free parameters introduced in the formulation of stochastic UNICON are optimized using 10 cases of single-column model simulations over the ocean. Stochastic UNICON with the optimized parameters significantly reduces the biases of thermodynamic profiles and surface precipitation rates simulated in the original UNICON for tropical convection cases. The simulation of the variation in anomalies of temperature and moisture associated with the Madden-Julian oscillation is also improved. The overall improvements in simulated thermodynamic profiles are found to be due to the increased heating and drying tendencies by convective processes in stochastic UNICON. An additional simulation of an idealized deep convection case shows that stochastic UNICON produces enhanced cloud variabilities with dependency on updraft radius, indicating its ability to represent the coexistence of shallow and deep convection.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

The faint young Sun paradox: an observational test of an alternative solar model

We report the results of deep observations at radio (3.6 cm) wavelengths of the nearby solar-type star pi 01 Ursa Majoris with the Very Large Array (VLA) intended to test an alternative theory of solar luminosity evolution. The standard model predicts a solar luminosity only 75% of the present value and surface temperatures below freezing on Earth and Mars at 4 Ga, seemingly in conflict with geologic evidence for liquid water on these planets. An alternative model invokes a compensatory mass loss through a declining solar wind that results in a more consistent early luminosity. The free-free emission from an enhanced wind around nearby young Sun-like stars should be detectable at microwave frequencies. Our observations of pi 01 UMa, a 300 million year-old solar-mass star, place an upper limit on the mass loss rate of 4-5 x 10(-11) M(solar) yr-1. Total mass loss from such a star over 4 Gyr would be less than 6%. If this star is indeed an analog of the early Sun, it casts doubt on the alternative model as a solution to the faint young Sun paradox, particularly for Mars.

NASA Discipline Exobiology↗
NASA NTRS2020

Study of Antarctic Blowing Snow Storms Using MODIS and CALIOP Observations With a Machine Learning Model

As a common phenomenon over Antarctica, blowing snow (BLSN), especially the large BLSN storms, play an important role in the Antarctic surface mass balance, radiation budget, and planetary boundary layer processes. This study presents the work on BLSN storm identification and analysis with observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite. Spectral analysis shows that BLSN identification is feasible with MODIS daytime data. A random forest machine learning model is developed and observations from the Cloud‐Aerosol Lidar with Orthogonal Polarization are used for training. Model performance results show that machine‐learning based classification can achieve over 90% overall accuracy when classifying MODIS pixels into cloud, clear, and BLSN categories. The machine learning model is applied to MODIS observations during the month of October 2009 for BLSN storm analysis. Results show that the size of BLSN storms has a large spectrum and can reach hundreds of thousands km2. The MODIS based BLSN storm frequency map extends the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations coverage limit from 82°S to the South Pole. A BLSN storm belt, which extends from the South Pole region to the coastal area between 130°E and 160°E along the Transantarctic Mountains, provides a potential pathway of snow transport. These results are important in improving the understanding of BLSN impact on Antarctic surface mass balance and boundary layer processes.

Antarctic↗
DOE OSTI2021

Anthropogenic Perturbations to the Atmospheric Molybdenum Cycle

Abstract Molybdenum (Mo) is a key cofactor in enzymes used for nitrogen (N) fixation and nitrate reduction, and the low availability of Mo can constrain N inputs, affecting ecosystem productivity. Natural atmospheric Mo aerosolization and deposition from sources such as desert dust, sea‐salt spray, and volcanoes can affect ecosystem function across long timescales, but anthropogenic activities such as combustion, motor vehicles, and agricultural dust have accelerated the natural Mo cycle. Here we combined a synthesis of global atmospheric concentration observations and modeling to identify and estimate anthropogenic sources of atmospheric Mo. To project the impact of atmospheric Mo on terrestrial ecosystems, we synthesized soil Mo data and estimated the global distribution of soil Mo using two approaches to calculate turnover times. We estimated global emissions of atmospheric Mo in aerosols (<10 μm in diameter) to be 23 Gg Mo yr −1 , with 40%–75% from anthropogenic sources. We approximated that for the top meter of soil, Mo turnover times range between 1,000 and 1,000,000 years. In some industrialized regions, anthropogenic inputs have enhanced Mo deposition 100‐fold, lowering the soil Mo turnover time considerably. Our synthesis of global observational data, modeling, and a mass balance comparison with riverine Mo exports suggest that anthropogenic activity has greatly accelerated the Mo cycle, with potential to influence N‐limited ecosystems.

Wong, Michelle Y.↗
NASA NTRS2011

Satellite Observations and Chemistry Climate Models - A Meandering Path Towards Better Predictions

Knowledge of the chemical and dynamical processes that control the stratospheric ozone layer has grown rapidly since the 1970s, when ideas that depletion of the ozone layer due to human activity were put forth. The concept of ozone depletion due to anthropogenic chlorine increase is simple; quantification of the effect is much more difficult. The future of stratospheric ozone is complicated because ozone is expected to increase for two reasons: the slow decrease in anthropogenic chlorine due to the Montreal Protocol and its amendments and stratospheric cooling caused by increases in carbon dioxide and other greenhouse gases. Prediction of future ozone levels requires three-dimensional models that represent physical, photochemical and radiative processes, i.e., chemistry climate models (CCMs). While laboratory kinetic and photochemical data are necessary inputs for a CCM, atmospheric measurements are needed both to reveal physical and chemical processes and for comparison with simulations to test the conceptual model that CCMs represent. Global measurements are available from various satellites including but not limited to the LIMS and TOMS instruments on Nimbus 7 (1979 - 1993), and various instruments on the Upper Atmosphere Research Satellite (1991 - 2005), Envisat (2002 - ongoing), Sci-Sat (2003 - ongoing) and Aura (2004 - ongoing). Every successful satellite instrument requires a physical concept for the measurement, knowledge of physical chemical properties of the molecules to be measured, and stellar engineering to design an instrument that will survive launch and operate for years with no opportunity for repair but providing enough information that trend information can be separated from any instrument change. The on-going challenge is to use observations to decrease uncertainty in prediction. This talk will focus on two applications. The first considers transport diagnostics and implications for prediction of the eventual demise of the Antarctic ozone hole. The second focuses on the upper stratosphere, where ozone is predicted to increase both due to chlorine decrease and due to temperature decrease expected as a result of increased concentrations Of CO2 and other greenhouse gases. Both applications show how diagnostics developed from global observations are being used to explain why the ozone response varies among CCM predictions for stratospheric ozone in the 21st century.

Douglass, Anne R.↗
DOE OSTI2021

All-sky aerosol direct radiative effects at the ARM SGP site

All-sky aerosol direct radiative effect (DRE) was estimated for the first time at the Atmospheric Radiation Measurement Southern Great Plains site using multi-year ground-based observations. The NASA Langley Fu-Liou radiation model was employed. Observed inputs for the radiation model include aerosol and cloud vertical extinction profile from Raman lidar; spectral aerosol optical depth, single-scattering albedo, and asymmetry factor from Aerosol Robotic Network; cloud water content profiles from radars; temperature and water vapor profiles from radiosondes; and surface shortwave spectral albedo from radiometers. A cloudy-sky radiative closure experiment was performed. The relative mean differences between modeled and observed surface downwelling shortwave total fluxes were 6% (7%) for transparent (opaque) cloudy-skies. The estimated annual mean all-sky aerosol DRE is -2.13±0.54W m -2 at the top of atmosphere (TOA) and -5.95±0.87 W m -2 at the surface, compared to -3.00±0.58 W m -2 AND -6.85±1.00 W m -2 , respectively, under clear-sky conditions. The seasonal cycle of all-sky aerosol DRE is similar to that of the clear-sky, except with secondary influences of the clouds: The cloud radiative effect is strongest (most negative) in the spring, which reduces the all-sky aerosol DRE. The relative uncertainties in all-sky aerosol DRE due to measurement errors are generally comparable to those in clear-sky conditions except for the aerosol single-scattering albedo. Finally, the TOA all-sky aerosol DRE relative uncertainty due to aerosol single-scattering albedo uncertainty is larger than that in clear-sky, leading to a larger total relative uncertainty. The measurement errors in cloud properties have small effects on the all-sky aerosol DRE.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2003

Latent Heating Retrieval from TRMM Observations Using a Simplified Thermodynamic Model

A procedure for the retrieval of hydrometeor latent heating from TRMM active and passive observations is presented. The procedure is based on current methods for estimating multiple-species hydrometeor profiles from TRMM observations. The species include: cloud water, cloud ice, rain, and graupel (or snow). A three-dimensional wind field is prescribed based on the retrieved hydrometeor profiles, and, assuming a steady-state, the sources and sinks in the hydrometeor conservation equations are determined. Then, the momentum and thermodynamic equations, in which the heating and cooling are derived from the hydrometeor sources and sinks, are integrated one step forward in time. The hydrometeor sources and sinks are reevaluated based on the new wind field, and the momentum and thermodynamic equations are integrated one more step. The reevalution-integration process is repeated until a steady state is reached. The procedure is tested using cloud model simulations. Cloud-model derived fields are used to synthesize TRMM observations, from which hydrometeor profiles are derived. The procedure is applied to the retrieved hydrometeor profiles, and the latent heating estimates are compared to the actual latent heating produced by the cloud model. Examples of procedure's applications to real TRMM data are also provided.

Grecu, Mircea↗
DOE OSTI2021

Dry Deposition of Atmospheric Aerosols: Approaches, Observations, and Mechanisms

Aerosols are liquid or solid particles suspended in the atmosphere, typically with diameters on the order of nanometers to microns. These particles impact air quality and the radiative balance of the planet. Dry deposition is a key process for the removal of aerosols from the atmosphere and plays an important role in controlling the lifetime of atmospheric aerosols. Dry deposition is driven by turbulence and shows a strong dependence on particle size. This review summarizes the mechanisms behind aerosol dry deposition, including measurement approaches, field observations, and modeling studies. We identify several gaps in the literature, including deposition over the cryosphere (i.e., snow and ice surfaces) and the ocean; in addition, we highlight new techniques to measure black carbon fluxes. While recent advances in aerosol instrumentation have enhanced our understanding of aerosol sources and chemistry, dry deposition and other loss processes remain poorly investigated.

Chemistry↗
NASA NTRS1984

Exploring the use of structural models to improve remote sensing agricultural estimates

Satellite estimates of agricultural characteristics often are not sufficiently precise for reliable use in small geographical regions. The precision of estimates of agricultural characteristics such as crop proportions and leaf area indexes can be increased by modeling ground observations as a function of satellite estimates. Linear regression models using least squares estimators of the model parameters are most often advocated as an appropriate methodology; however, least squares estimation requires that the predictor variables are measured without error, an unreasonable assumption for this application. An alternative estimation methodology which assumes that both the response variables (ground observations) and the predictor variables (satellite estimates) are measured with error involves the use of linear structural models. The application of linear structural models to the estimation of agricultural characteristics using satellite spectral measurements is examined.

Gunst, R. F.↗
NASA NTRS2010

Dst Index in the 2008 GEM Modeling Challenge - Model Performance for Moderate and Strong Magnetic Storms

The GEM 2008 modeling challenge efforts are expanding beyond comparing in-situ measurements in the magnetosphere and ionosphere to include the computation of indices to be compared. The Dst index measures the largest deviations of the horizontal magnetic field at 4 equatorial magnetometers from the quiet-time background field and is commonly used to track the strength of the magnetic disturbance of the magnetosphere during storms. Models can calculate a proxy Dst index in various ways, including using the Dessler-Parker Sckopke relation and the energy of the ring current and Biot-Savart integration of electric currents in the magnetosphere. The GEM modeling challenge investigates 4 space weather events and we compare models available at CCMC against each other and the observed values of Ost. Models used include SWMF/BATSRUS, OpenGGCM, LFM, GUMICS (3D magnetosphere MHD models), Fok-RC, CRCM, RAM-SCB (kinetic drift models of the ring current), WINDMI (magnetosphere-ionosphere electric circuit model), and predictions based on an impulse response function (IRF) model and analytic coupling functions with inputs of solar wind data. In addition to the analysis of model-observation comparisons we look at the way Dst is computed in global magnetosphere models. The default value of Dst computed by the SWMF model is for Bz the Earth's center. In addition to this, we present results obtained at different locations on the Earth's surface. We choose equatorial locations at local noon, dusk (18:00 hours), midnight and dawn (6:00 hours). The different virtual observatory locations reveal the variation around the earth-centered Dst value resulting from the distribution of electric currents in the magnetosphere during different phases of a storm.

Rastaetter, Lutz↗
DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1986

Thermofluid analysis of the SSME preburner using a gas-gas diffusion model for oxygen and hydrogen combustion at supercritical pressures

The paper discusses the thermofluid analysis of the Space Shuttle Main Engine (SSME) fuelside preburner. The governing equations have been solved numerically to predict flow, heat transfer, mixing, and combustion. A two-fluid approach is adopted in which oxygen is regarded as one fluid and hydrogen is regarded as the other fluid. The chemical kinetics is assumed to be very fast so that combustion is primarily controlled by the rate of mixing between oxygen and hydrogen. The preburner pressure is much greater than the critical pressures of oxygen and hydrogen; hence, a gas-gas diffusion model (rather than an evaporation model) has been developed to compute the rate of interphase mixing. Empirical correlations have been incorporated to account for the effect of slip on the interphase exchange. A sensitivity study has been performed with various model parameters. It is observed that the model can predict possibility of incomplete combustion and local regions of high temperatures under steady operating conditions. Some of these anomalies have been observed in actual tests, and the numerical model is useful for understanding possible causes and remedies. At least some measurements are needed for quantitative verification of the model.

Prakash, C.↗