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At least 199 records · Page 11

Daily and Hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We distributed monthly GFED3 emissions during 2003-2009 on a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) active fire observations. We found that patterns of daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of bunting in savannas. On diurnal timescales, our analysis of the GOES active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top-down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

Attribution of the causes of atmospheric trace gas and aerosol variability often requires the use of high resolution time series of anthropogenic and natural emissions inventories. Here we developed an approach for representing synoptic- and diurnal-scale temporal variability in fire emissions for the Global Fire Emissions Database version 3 (GFED3). We disaggregated monthly GFED3 emissions during 2003.2009 to a daily time step using Moderate Resolution Imaging Spectroradiometer (MODIS) ]derived measurements of active fires from Terra and Aqua satellites. In parallel, mean diurnal cycles were constructed from Geostationary Operational Environmental Satellite (GOES) Wildfire Automated Biomass Burning Algorithm (WF_ABBA) active fire observations. Daily variability in fires varied considerably across different biomes, with short but intense periods of daily emissions in boreal ecosystems and lower intensity (but more continuous) periods of burning in savannas. These patterns were consistent with earlier field and modeling work characterizing fire behavior dynamics in different ecosystems. On diurnal timescales, our analysis of the GOES WF_ABBA active fires indicated that fires in savannas, grasslands, and croplands occurred earlier in the day as compared to fires in nearby forests. Comparison with Total Carbon Column Observing Network (TCCON) and Measurements of Pollution in the Troposphere (MOPITT) column CO observations provided evidence that including daily variability in emissions moderately improved atmospheric model simulations, particularly during the fire season and near regions with high levels of biomass burning. The high temporal resolution estimates of fire emissions developed here may ultimately reduce uncertainties related to fire contributions to atmospheric trace gases and aerosols. Important future directions include reconciling top ]down and bottom up estimates of fire radiative power and integrating burned area and active fire time series from multiple satellite sensors to improve daily emissions estimates.

Mu, M.↗

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 1: Development of models predicting surface shelter temperatures

Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate and site-specific data to represent the local landscape. Global monthly mean temperature models were developed using data from over 5000 stations available in the Global Historical Climate Network (GHCN). Monthly maximum, mean, and minimum temperature models for the United States were also developed using data from over 1000 stations available in the U.S. Cooperative (COOP) Network and comparative monthly mean temperature models were developed using over 1150 U.S. stations in the GHCN. Three-, six-, and full-variable models were developed for comparative purposes. Inferences about the variables selected for the various models were easier for the GHCN models, which displayed month-to-month consistency in which variables were selected, than for the COOP models, which were assigned a different list of variables for nearly every month. These and other results suggest that global calibration is preferred because data from the global spectrum of physical processes that control surface temperatures are incorporated in a global model. All of the models that were developed in this study validated relatively well, especially the global models. Recalibration of the models with validation data resulted in only slightly poorer regression statistics, indicating that the calibration list of variables was valid. Predictions using data from the validation dataset in the calibrated equation were better for the GHCN models, and the globally calibrated GHCN models generally provided better U.S. predictions than the U.S.-calibrated COOP models. Overall, the GHCN and COOP models explained approximately 64%-95% of the total variance of surface shelter temperatures, depending on the month and the number of model variables. In addition, root-mean-square errors (rmse's) were over 3 C for GHCN models and over 2 C for COOP models for winter months, and near 2 C for GHCN models and near 1.5 C for COOP models for summer months.

Epperson, David L.↗

Experimental verification of a progressive damage model for composite laminates based on continuum damage mechanics

Progressive failure is a crucial concern when using laminated composites in structural design. Therefore the ability to model damage and predict the life of laminated composites is vital. The purpose of this research was to experimentally verify the application of the continuum damage model, a progressive failure theory utilizing continuum damage mechanics, to a toughened material system. Damage due to tension-tension fatigue was documented for the IM7/5260 composite laminates. Crack density and delamination surface area were used to calculate matrix cracking and delamination internal state variables, respectively, to predict stiffness loss. A damage dependent finite element code qualitatively predicted trends in transverse matrix cracking, axial splits and local stress-strain distributions for notched quasi-isotropic laminates. The predictions were similar to the experimental data and it was concluded that the continuum damage model provided a good prediction of stiffness loss while qualitatively predicting damage growth in notched laminates.

Coats, Timothy William↗

Wind-Optimal Cruise Airspeed for a Multirotor Aircraft in Urban Air Mobility

This paper first investigates the effect of wind on the wind-optimal (minimum-energy) cruise airspeed for a NASA-proposed conceptual multirotor aircraft for the urban air mobility environment. Next, energy consumption and flight duration results are compared for flying at the wind-optimal airspeed and best-range airspeed on a great-circle cruise segment under different wind conditions. Finally, the difference in energy consumption when flying to meet the assigned required time of arrival based on actual wind conditions vs. predicted wind conditions are examined and compared for the two airspeed modes (wind-optimal and best-range) for different values of wind magnitude uncertainty. The results show operational benefits of flying at the wind-optimal cruise airspeed compared to the best-range airspeed, especially understrong headwind conditions from both an energy consumption and flight duration perspective.The results also show that flying at wind-optimal airspeed under wind magnitude uncertainty has lower variability and higher predictability of energy consumption than flying at best-range airspeed.

Urban Air Mobility↗

Long and Short Term Geomagnetic Prediction (Chapter 19)

Prediction of geomagnetic variability depends on the accuracy of geomagnetic field modeling, dynamical modeling of source regions that contribute to geomagnetic signals, and advanced assimilation algorithms that combine effectively the results of geomagnetic field and dynamic models to make accurate estimates of the dynamic states of the sources and, therefore, accurate forecast of geomagnetic variations. In this chapter we provide an overview of recent research efforts in these three research areas, focusing primarily on geomagnetic variations from the dynamic outer core and from solar and lunar tidal effects, but also including a review of relevant research results and developments. Prediction of weak but periodic tidal phenomena, and of strong but chaotic secular variation (SV) showcases two very important new developments which will lead to new opportunities in geomagnetic research and application.

Weijia Kuang↗

Study of oxygen gas production phenomenon during stand and discharge in silver-zinc batteries

Standard production procedures for manufacturing silver zinc batteries are evaluated and modified to reduce oxygen generation during open circuit stand and discharge. Production predictions of several variable combinations using analysis models are listed for minimum gassing, with emphasis on the concentration of potassium hydroxide in plate formation. A recommendation for work optimizing the variables involved in plate processing is included.

Source record↗

The aeronomy of odd nitrogen in the thermosphere. II - Twilight emissions

A model developed for the aeronomy of odd nitrogen in the thermosphere is used to analyze rocket measurements of N(4S) and NO densities. Data from Atmosphere Explorer were used to develop a consistent reaction kinetics model for odd nitrogen chemistry. It is concluded that most NO(+) dissociative recombination events must produce N(2D), that N(2D) is quenched by O at a rate of 1 trillionth cu cm per sec, and that the atmospheric O2 quenching rate of N(2D) is consistent with the laboratory rate. The major quenching agent of N(2D) between 140 and 220 km is atomic oxygen, and this reaction is the major source of N(4S). Peak N(4S) densities of about (20-60) million per cu cm at 140-150 km are predicted, with the variability being indicative of the model sensitivity to a factor of 2 change in the O/O2 ratio in the thermosphere.

Strobel, D. F.↗

A computationally fast one-dimensional diffusion-photochemistry model of SST wakes

A computational technique applicable to analysis of supersonic transport (SST) wake photochemistry and diffusion is presented. Sensitivity studies of SST effluent effects upon ozone depletion are facilitated by the computational rapidity of the method. The article compares results from other studies and predictions of some variables related to global NOx input. Results indicate that the NO/NO2 ratio in an SST wake at photochemical equilibrium is a sensitive function of photolysis rates.

Matloff, G. L.↗

The X-ray and optical characteristics of the cataclysmic variables V794 Aquilae

Observations of V794 Aql have revealed features that are consistent with its inclusion in the class of cataclysmic variables. The features include: (1) a 0.1-4.5 keV luminosity of 5 x 10 to the 30th ergs/sec for a d-value of 100 pc, with a hardness ratio of 11; (2) blue colors; (3) 0.5 mag variability on 40-min time scales, and 3.0 mag variability on the time scale of one day; and (4) a weak He II 4686 A, which argues against classification of V794 Aql as an AM Her-type variable. It is predicted that V794 Aql has a period shorter than six hours, with a strong possibility for eclipses, and is a strong UV emission source.

Szkody, P.↗

Profile modeling for crop discrimination

A complete automatic unsupervised classification approach has been developed to estimate the proportion of corn, soybeans, and other crops in a Landsat 5-by-6-nanometer segment. The technique involves extracting crop growth variables that are predictable from agromet models, it provides a signature extension not possible before. The technique has been applied in 3 years (1978-1980) for 56 segments and shows neither a year-to-year effect nor any geographic effect. The results to date are considered far better than those obtainable from any other currently available technique. Nontheless, the technique can be improved to reduce the bias.

Badhwar, G. D.↗

Fatigue damage analysis under variable amplitude cycling

This paper explores the suitability of a recently proposed mean stress parameter and introduces a nonlinear damage accumulation procedure. Data covering a range of positive and negative stress ratios from +0.6 to -2.66, for several aluminum alloys and steels, are assembled and shown to be well correlated by a simple damage parameter. A nonlinear damage accumulation postulate is advanced to replace the usual linear procedure. Results of critical experiments performed to assess the suitability of the postulate are introduced and shown to support a non-linear criterion. The implications of this work related to variable amplitude life prediction are discussed.

Leis, B. N.↗

Testing the radiometric stability of HCMM thermal infrared data

A study conducted to test the radiometric stability of thermal infrared (TIR) data from the heat-capacity mapping mission (HCMM) satellites is considered. The radiance values associated with various land use and cover types in a regional study area centered on Washington, D.C. are examined. The study shows that for three different day TIR-data sets, the relative ranking of mean thermal values associated with five Level I and three Level II land-use/land-cover categories remains constant over time. Although HCMM predicted temperatures show variability up to 5 C from ground observed temperatures, the thermal measurements recorded by the satellite are fairly stable as indicators of surface temperature. A method for combining HCMM thermal data and Landsat multispectral scanner (MSS) data to improve the classification of Level I land-cover categories, and in particular the separability of urban and nonurban areas is described. A merged HCMM-MSS data set is found to yield the best results in terms of thematic-map accuracy.

Witt, R. G.↗

Dynamic and static initialization of a mesoscale model using VAS satellite data

Various mesoscale weather forecast model initialization procedures were tested in seven simulation forecasts for a 12 hr period in July 1981. Attention was given to the impacts of using as input radiosonde data, VISSR Atmospheric Sounder (VAS) data and a combination of VAS and data from a smoothed global analysis. The data were assimilated with successive correction objective analysis procedures. The model had a 60 km horizontal grid-length resolution, 14 layers in the vertical, and accounted for short- and long-wave energy in the surface energy budget but not in the atmosphere. Conventional data were used for the mass and moisture fields. The trials showed that VAS data enhanced the predictions of the temperature and mass variables, while winds were least accurately predicted when VAS data were entered in the initializations. Finally, statically initialized precipitation forecasts from radiosonde and/or VAS data exhibited equal skill.

Beauchamp, J. G.↗

Least squares linear lags and limited memory filters

Pure autoregressive (AR) models which are linear in the short term, that is when a variable can be predicted by linear regression on a limited number of past observations, are discussed. When evenly spaced observations are available, a fixed set of AR coefficients can be calculated independent of the data. For filtering purposes, such a lag structure can be implemented recursively with an efficient algorithm. The method of computing variance recursively is also derived. A complete algorithm is presented in the appendix.

Discenza, Joseph H.↗

Probabilistic composite micromechanics

Probabilistic composite micromechanics methods are developed that simulate expected uncertainties in unidirectional fiber composite properties. These methods are in the form of computational procedures using Monte Carlo simulation. A graphite/epoxy unidirectional composite (ply) is studied to demonstrate fiber composite material properties at the micro level. Regression results are presented to show the relative correlation between predicted and response variables in the study.

Stock, T. A.↗

A probabilistic approach to composite micromechanics

Probabilistic composite micromechanics methods are developed that simulate expected uncertainties in unidirectional fiber composite properties. These methods are in the form of computational procedures using Monte Carlo simulation. A graphite/epoxy unidirectional composite (ply) is studied to demonstrate fiber composite material properties at the micro level. Regression results are presented to show the relative correlation between predicted and response variables in the study.

Stock, T. A.↗

IECON '87: Industrial applications of control and simulation; Proceedings of the 1987 International Conference on Industrial Electronics, Control, and Instrumentation, Cambridge, MA, Nov. 3, 4, 1987

Recent advances in control-system design and simulation are discussed in reviews and reports. Among the topics considered are fast algorithms for generating near-optimal binary decision programs, trajectory control of robot manipulators with compensation of load effects via a six-axis force sensor, matrix integrators for real-time simulation, a high-level control language for an autonomous land vehicle, and a practical engineering design method for stable model-reference adaptive systems. Also addressed are the identification and control of flexible-limb robots with unknown loads, adaptive control and robust adaptive control for manipulators with feedforward compensation, adaptive pole-placement controllers with predictive action, variable-structure strategies for motion control, and digital signal-processor-based variable-structure controls.

Hartley, Tom T.↗