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At least 577 records · Page 32

Three dimensional global modeling of atmospheric CO2

The initial attempts to model the atmospheric CO2 distribution, including couplings to the ocean and biosphere as sources and sinks of atmospheric CO2, encourage the notion that this approach will lead to useful quantitative constraints on CO2 fluxes. Realization of this objective will require: (1) continued improvement in the realism of the global transport modeling; (2) extended timeline of atmospheric CO2 monitoring, which improved precision and improved definition of the uncertainties in the measured CO2 amounts; and (3) given an accurate knowledge of model capabilities and limitations and given a good understanding of CO2 observations and their limitations, there is a need for good ideas concerning what quantitative information on the carbon cycle can be inferred from global modeling.

Hanse, J.↗

[Global Atmospheric Chemistry/Transport Modeling and Data-Analysis]

This grant supported a global atmospheric chemistry/transport modeling and data- analysis project devoted to: (a) development, testing, and refining of inverse methods for determining regional and global transient source and sink strengths for trace gases; (b) utilization of these inverse methods which use either the Model for Atmospheric Chemistry and Transport (MATCH) which is based on analyzed observed winds or back- trajectories calculated from these same winds for determining regional and global source and sink strengths for long-lived trace gases important in ozone depletion and the greenhouse effect; (c) determination of global (and perhaps regional) average hydroxyl radical concentrations using inverse methods with multiple "titrating" gases; and (d) computation of the lifetimes and spatially resolved destruction rates of trace gases using 3D models. Important ultimate goals included determination of regional source strengths of important biogenic/anthropogenic trace gases and also of halocarbons restricted by the Montreal Protocol and its follow-on agreements, and hydrohalocarbons now used as alternatives to the above restricted halocarbons.

Prinn, Ronald G.↗

Importance of Radiative Transfer Models in Atmospheric Remote Sensing

Radiative transfer models (RTMs) play a significant role in the development of satellite instruments for remote sensing applications. These models simulate electromagnetic radiation's propagation through the atmosphere, providing valuable insights into atmosphere-radiation interactions. RTMs facilitate the optimization of satellite instrument designs, ensuring their ability to measure targeted atmospheric and surface properties accurately. Moreover, they aid in simulating instrument’s measurements under various atmospheric conditions, enabling calibration and validation processes to enhance data quality and reliability. RTMs are extensively used in the Observing System Simulation Experiments (OSSE), to generate synthetic observations. By incorporating RTMs into OSSE, we can assess the potential impact of future satellite missions, sensor configurations, and data assimilation techniques. This approach allows for the optimization of satellite instruments and constellations and the evaluation of their influence on weather forecasting, climate monitoring, and other Earth science applications. Another crucial application area of RT models is data assimilation, where they play a fundamental role in combining satellite observations with numerical models to improve atmospheric and environmental predictions. RTMs provide the link between observed radiances and atmospheric parameters, enhancing the accuracy of numerical models and generating more reliable forecasts for weather events, air quality assessments, and climate projections. Moreover, adapting RT models to capture the intricate radiation interactions within the Planetary Boundary Layer will significantly contribute to improving weather forecasting and climate change projections. Current community radiative transfer (RT) models are primarily developed and optimized for operational data assimilation of satellite observations. These models excel at assimilating satellite data into numerical weather prediction models to improve forecast accuracy. However, their focus on data assimilation limits their suitability for other important applications, such as satellite instrument development, OSSE, and Planetary Boundary Layer (PBL) studies. Moreover, for PBL studies, RT models need to be adapted to capture the intricate radiation interactions within this crucial atmospheric layer. Developing RT models that can represent the PBL's unique characteristics, such as surface interactions, will contribute significantly to understanding and predicting weather phenomena, air quality, and climate dynamics. This abstract provides a comprehensive overview of the current status of RT models and highlights their limitations concerning satellite instrument development, OSSE, and PBL studies. Addressing these shortcomings requires concerted efforts to enhance RT models' capabilities and expand their applications beyond data assimilation. By investing in research and development to improve these

Isaac Moradi↗

Atmospheric Chemistry Modeling and Air Quality Forecasting Using Machine Learning

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model.We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry.This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗

A line-blanketed model stellar atmosphere of Sirius

The method of artificial absorption edges is applied to a grid of model atmospheres to include the effects of hydrogen and metal line blanketing on the atmospheric structure. A best-fit model of Sirius is obtained which is free of the discrepancies inherent in unblanketed or partially blanketed models. All major spectral features calculated from the model agree with the corresponding observed features to within the observational uncertainty. Some additional properties of the models are discussed.

Fowler, J. W.↗

Accelerated complete-linearization method for calculating NLTE model stellar atmospheres

Two approaches to accelerating the method of complete linearization for calculating NLTE model stellar atmospheres are suggested. The first one, the so-called Kantorovich variant of the Newton-Raphson method, consists of keeping the Jacobi matrix of the system fixed, which allows us to calculate the costly matrix inversions only a few times and then keep them fixed during the subsequent computations. The second method is an application of the Ng acceleration. Both methods are extremely easy to implement with any model atmosphere code based on complete linearization. It is demonstrated that both methods, and especially their combination, yield a rapidly and globally convergent algorithm, which takes 2 to 5 times less computer time, depending on the model at hand and the required accuracy, than the ordinary complete linearization. Generally, the time gain is more significant for more complicated models. The methods were tested for a broad range of atmospheric parameters, and in all cases they exhibited similar behavior. Ng acceleration applied on the Kantorovich variant thus offers a significant improvement of the standard complete-linearization method, and may now be used for calculating relatively involved NLTE model stellar atmospheres.

Hubeny, I.↗

Comparison of modelled and empirical atmospheric propagation data

The radiometric integrity of TM thermal infrared channel data was evaluated and monitored to develop improved radiometric preprocessing calibration techniques for removal of atmospheric effects. Modelled atmospheric transmittance and path radiance were compared with empirical values derived from aircraft underflight data. Aircraft thermal infrared imagery and calibration data were available on two dates as were corresponding atmospheric radiosonde data. The radiosonde data were used as input to the LOWTRAN 5A code which was modified to output atmospheric path radiance in addition to transmittance. The aircraft data were calibrated and used to generate analogous measurements. These data indicate that there is a tendancy for the LOWTRAN model to underestimate atmospheric path radiance and transmittance as compared to empirical data. A plot of transmittance versus altitude for both LOWTRAN and empirical data is presented.

Schott, J. R.↗

Comparison of modelled and empirical atmospheric propagation data

The radiometric integrity of TM thermal infrared channel data was evaluated and monitored to develop improved radiometric preprocessing calibration techniques for removal of atmospheric effects. Modelled atmospheric transmittance and path radiance were compared with empirical values derived from aircraft underflight data. Aircraft thermal infrared imagery and calibration data were available on two dates as were corresponding atmospheric radiosonde data. The radiosonde data were used as input to the LOWTRAN 5A code which was modified to output atmospheric path radiance in addition to transmittance. The aircraft data were calibrated and used to generate analogous measurements. These data indicate that there is a tendency for the LOWTRAN model to underestimate atmospheric path radiance and transmittance as compared to empirical data. A plot of transmittance versus altitude for both LOWTRAN and empirical data is presented.

Schott, J. R.↗

Dynamic upper atmospheric force model on stabilized vehicles for a high-precision trajectory computer program

The upper atmosphere model draws heavily on the behavior of the earth's upper atmosphere which exhibits cyclic as well as irregular variations in density profile, temperature, pressure, and composition in unison with solar activities as deduced from the more recent land-based and satellite observations. The lift and drag model is designed specifically for inertially stabilized vehicles of the Mariner class, with possible extension to gravity gradient stabilized vehicles of the GEOS class. The model considers operation in the free molecular flow regimes with large Knudsen numbers. The vehicle is considered a composite structure with basic components having well-defined shapes, each with its own surface characteristics in terms of temperature, reflectivity, and accommodation of free stream molecules. The model takes into account both the calculation of precise aerodynamic force coefficients in terms of expansion of modified Bessel functions in speed ratios and angle of attack, and approximate force coefficients when the speed ratios approach infinity. Other considerations include specular and diffused reflectivity, shielding, and shadow effects.

Khatib, A. R.↗

Model for a clear atmosphere.

Clear atmosphere model based on path of sight equilibrium radiance and nonabsorption permitting integration of equation of transfer

Gordon, J. I.↗

Three-dimensional dynamical and chemical modelling of the upper atmosphere

Progress in coding a 3-D upper atmospheric model and in modeling the ozone perturbation resulting from the shuttle booster exhaust is reported. A time-dependent version of a 2-D model was studied and the sulfur cycle in the stratosphere was investigated. The role of meteorology in influencing stratospheric composition measurements was also studied.

Prinn, R. G.↗

Upper and Middle Atmospheric Density Modeling Requirements for Spacecraft Design and Operations

Presented and discussed are concerns with applications of neutral atmospheric density models to space vehicle engineering design and operational problems. The area of concern which the atmospheric model developers and the model users considered, involved middle atmosphere (50 to 90 km altitude) and thermospheric (above 90 km) models and their engineering application. Engineering emphasis involved areas such as orbital decay and lifetime prediction along with attitude and control studies for different types of space and reentry vehicles.

Davis, M. H.↗

Atmospheric analysis modeling in support of Seasat

Atmospheric objective analysis models were developed and tested in preparation for assessing the utility of Seasat data. Of the several discretionary procedures in such computer programs, the effects of three were examined and documented: (1) the effect of varying the weights in the pattern conserving techniques; (2) the effect of varying the data influence region; (3) the effect of including wind information in analysis of mass-structure variables. The problem of inserting bogus reports is also examined.

Langland, R. A.↗

Advanced Modeling Techniques to Study Anthropogenic Influences on Atmospheric Chemical Budgets

This research work is a collaborative effort between research groups at MCNC and the University of North Carolina at Chapel Hill. The overall objective of this research is to improve the level of understanding of the processes that determine the budgets of chemically and radiatively active compounds in the atmosphere through development and application of advanced methods for calculating the chemical change in atmospheric models. The research performed during the second year of this project focused on four major aspects: (1) The continued development and refinement of multiscale modeling techniques to address the issue of the disparate scales of the physico-chemical processes that govern the fate of atmospheric pollutants; (2) Development and application of analysis methods utilizing process and mass balance techniques to increase the interpretive powers of atmospheric models and to aid in complementary analysis of model predictions and observations; (3) Development of meteorological and emission inputs for initial application of the chemistry/transport model over the north Atlantic region; and, (4) The continued development and implementation of a totally new adaptive chemistry representation that changes the details of what is represented as the underlying conditions change.

Mathur, Rohit↗

New Atmospheric Turbulence Model for Shuttle Applications

An updated NASA atmospheric turbulence model, from 0 to 200 km altitude, which was developed to be more realistic and less conservative when applied to space shuttle reentry engineering simulation studies involving control system fuel expenditures is presented. The prior model used extreme turbulence (3 sigma) for all altitudes, whereas in reality severe turbulence is patchy within quiescent atmospheric zones. The updated turublence model presented is designed to be more realistic. The prior turbulence statistics (sigma and L) were updated and were modeled accordingly.

Justus, C. G.↗