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At least 361 records · Page 20

Residual Study: Testing Jupiter Atmosphere Models Against Juno MWR Observations

The Juno spacecraft provides unique close-up views of Jupiter underneath the synchrotron radiation belts while circling Jupiter in its 53-day orbits. The microwave radiometer (MWR) onboard measures Jupiter thermal radiation at wavelengths between 1.37 and 50 cm, penetrating the atmosphere to a pressure of a few hundred bars and greater. The mission provides the first measurements of Jupiter's deep atmosphere, down to ~250 bars in pressure, constraining the vertical distributions of its kinetic temperature and constituents. As a result, vertical structure models of Jupiter's atmosphere may now be tested by comparison with MWR data. Taking into account the MWR beam patterns and observation geometries, we test several published Jupiter atmospheric models against MWR data. Our residual analysis confirms Li et al.'s (2017, https://doi.org/10.1002/2017GL073159) result that ammonia depletion persists down to 50–60 bars where ground-based Very Large Array was not able to observe. We also present an extension of the study that iteratively improves the input model and generates Jupiter brightness temperature maps which best match the MWR data. A feature of Juno's north-to-south scanning approach is that latitudinal structure is more easily obtained than longitudinal, and the creation of optimum two-dimensional maps is addressed in this approach.

Zhimeng Zhang↗

Stable Simulation of the Community Atmosphere Model Using Machine‐Learning Physical Parameterization Trained With Experience Replay

In recent years, machine learning (ML) models have been used to improve physical parameterizations of general circulation models (GCMs). A significant challenge of integrating ML models into GCMs is the online instability when they are coupled for long‐term simulation. We present a new strategy that demonstrates robust online stability when the physical parameterization package of an atmospheric GCM is replaced by a deep ML model. The method uses experience replay with a multistep training scheme of the ML model in which the model's own output at the previous time step is used in the training. Predicted physics tendencies in the replay buffer with the most recent errors in the training iterations are reused, making the ML model learn from its own errors. The training method reduces the gap between the offline and online environments of the ML model. The method is used to train the ML model as the physical parameterization of the Community Atmosphere Model (CAM5) with training data from the Multi‐scale Modeling Framework high resolution simulations. Three 6‐year online simulations of the CAM5 are carried out by using the ML physics package. The simulated spatial distributions of precipitation, surface temperature and zonally averaged atmospheric fields demonstrate overall better accuracy than that of the standard CAM5 and benchmark model even without the use of additional physical constraints or tuning. This work is the first to demonstrate a solution to address the online instability problem in climate modeling with ML physics by using experience replay.

54 ENVIRONMENTAL SCIENCES↗

Effect of molecular anisotropy on the intensity and degree of polarization of light scattered from model atmospheres

Computations of the properties of sunlight scattered from models of the earth-atmosphere system are presented to show the effect of molecular anisotropy on the intensity, flux, and degree of polarization of the scattered light. The values of these parameters change significantly when the anisotropy factor is neglected in the molecular optical thickness and scattering phase matrix. However, if the Rayleigh scattering optical thickness is kept constant and the molecular anisotropy factor is included only in the Rayleigh phase matrix, the flux does not change, the intensity changes by a small amount, but the changes in the degree of polarization are still significant.

Bahethi, O. P.↗

Atmospheric Models for Aerocapture Systems Studies

Aerocapture uses atmospheric drag to decelerate into captured orbit from interplanetary transfer orbit. This includes capture into Earth orbit from, for example, Lunar-return or Mars-return orbit. Eight Solar System destinations have sufficient atmosphere for aerocapture to be applicable - three of the rocky planets (Venus, Earth, and Mars), four gas giants (Jupiter, Saturn, Uranus, and Neptune), and Saturn's moon Titan. These destinations fall into two groups: (1) The rocky planets, which have warm surface temperatures (approx. 200 to 750 K) and rapid decrease of density with altitude, and (2) the gas giants and Titan, which have cold temperatures (approx. 70 to 170 K) at the surface or 1-bar pressure level, and slow rate of decrease of density with altitude. The height variation of average density with altitude above 1-bar pressure level for the gas giant planets is shown. The periapsis density required for aerocapture of spacecraft having typical values of ballistic coefficient (a measure of mass per unit cross-sectional area) is also shown. The aerocapture altitudes at the gas giants would typically range from approx. 150 to 300 km. Density profiles are compared for the rocky planets with those for Titan and Neptune. Aerocapture at the rocky planets would occur at heights of approx. 50 to 100 km. For comparison, typical density and altitudes for aerobraking operations (circularizing a highly elliptical capture orbit, using multiple atmospheric passes) are also indicated.

Justus, C. G.↗

Predictability of a coupled ocean-atmosphere model

A study is presented to determine the limits on the predictability of the coupled ocean-atmosphere system. Following the classical methods developed for atmospheric predictability studies, the model used is one of the simplest that realistically reproduces many of the important features of the observed interannual variability of sea surface temperature in the tropical Pacific Ocean when forced by observed wind stresses. As no reasonable analysis is available for all the fields, initial conditions for these prediction experiments were taken from a model control run in which the ocean model was forced by the observed surface winds. The atmospheric component of the coupled model is not capable of accurately simulating the large-scale components of the observed wind stress.

Goswami, B. N.↗

Assessment of Current MACCS Capabilities for Modeling Atmospheric Physical and Chemical Transformations

The physical and chemical transformation during atmospheric transport of radionuclides released into the environment has the possibility of impacting consequence modeling results. Accordingly, this report identifies physical and chemical transformations that may occur following release of chemically reactive radioactive species, how those transformations may affect modeling of consequences of release to the atmosphere and identifies current capabilities – in both MACCS and other state-of-practice atmospheric transport and dispersions models– to model those transformations. It was found that the inclusion of physical and chemical transformations is currently very limited in current state-of-practice codes for atmospheric dispersion of radionuclides. State-of-practice atmospheric dispersion codes appear to be typically limited to simulating either physical-chemical transformations or radioactive transformations, but not both. A state-of-practice atmospheric dispersion code capable of performing parallel physical, chemical, and radioactive transformation was not identified. A few atmospheric dispersion codes capable of modeling physical and chemical transport of specific species such as tritium or uranium hexafluoride were identified. Consequently, there is currently no information available that clearly suggests updates to the MACCS code are needed to bring it up to state-of-practice. However, investigations concluded that the MACCS computational framework can currently accommodate multiple physical/chemical forms in one simulation. Additionally, with some major assumptions, the computational framework in MACCS can accommodate parallel physical-chemical and radioactive transformations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Modeling the Atmospheric Structure and Dynamics of the Martian Atmosphere

Models of the general circulation and climate system of Mars have reached a high level of maturity, but observations to validate them have lacked the kind of global and temporal coverage required. However, we are now on the verge of a new era in Mars exploration as Mars Global Surveyor, and the now enroute Mars Climate Orbiter, will provide daily global coverage of the atmosphere for two Mars years. In the coming years, data from these missions will test the predictions of general circulation models (GCM's) whose results have perhaps become too accepted as truth. This talk will review what GCM's tell us about Mars, what their weaknesses are, and what the latest results imply for their future. Additional information is contained in the original extended abstract.

Haberle, R. M.↗

Atmospheric model development in support of SEASAT. Volume 1: Summary of findings

Atmospheric analysis and prediction models of varying (grid) resolution were developed. The models were tested using real observational data for the purpose of assessing the impact of grid resolution on short range numerical weather prediction. The discretionary model procedures were examined so that the computational viability of SEASAT data might be enhanced during the conduct of (future) sensitivity tests. The analysis effort covers: (1) examining the procedures for allowing data to influence the analysis; (2) examining the effects of varying the weights in the analysis procedure; (3) testing and implementing procedures for solving the minimization equation in an optimal way; (4) describing the impact of grid resolution on analysis; and (5) devising and implementing numerous practical solutions to analysis problems, generally.

Kesel, P. G.↗

Solar proton events as tests for the fidelity of middle atmosphere models

Ozone depletions associated with solar proton events have now been observed in nine events: November 1969, January and September 1971, August 1972, June and August 1979, October 1981, and July and December 1982. Since the proton fluxes during these events are fairly well known from satellite observations, modelers have been able to compare model predictions with observations of ozone behavior during these events to test the validity of atmospheric photochemical models. Ozone decreases initially follow approximately their theoretically predicted behavior below about 45 km (where NOx is thought to cause the ozone decrease), but after about two weeks the observed decrease appears to be larger than the computed decrease. Above 45 km, where HOx is thought to cause the ozone decrease, the picture of model validity is not as clear. The observed ozone decreases between about 45 and 60 km are substantially more than that predicted by present photochemical models while between about 60 and 85 km the observed ozone decrease is approximately equal to that predicted.

Jackman, Charles H.↗

Machine Learning Application to Atmospheric Chemistry Modeling

Atmospheric chemistry is a high-dimensionality, large-data problem and thus may be suited to machine-learning algorithms. We show here the potential of a random forest regression algorithm to replace the gas-phase chemistry solver in the GEOS-Chem chemistry model. In this proof-of-concept study, we used one month of model output to train random forest regression models to predict the concentrations of each long-lived chemical species after integration based upon the physical and chemical conditions before the chemical integration. The choice of prediction type has a strong impact on the skill of the regression model. We find best results from predicting the change in concentration for very long-lived species and the absolute concentration for shorter lived species. The skill of the machine learning algorithm is further improved by using a family approach for NO and NO2 rather than treating them independently.By replacing the numerical integrator with the random forest algorithm and running this model for one month, we find that the model is able to reproduce many of the features of the reference chemistry simulation. Replacing the integration methodology with a machine learning algorithm has the potential to be substantially faster. There are a wide range of applications for such an approach, e.g. to generate boundary conditions, for use in air quality forecasts or chemical data assimilation systems, etc.

Keller, Christoph A.↗

Mars global reference atmosphere model (Mars-GRAM)

Mars-GRAM is an empirical model that parameterizes the temperature, pressure, density, and wind structure of the Martian atmosphere from the surface through thermospheric altitudes. In the lower atmosphere of Mars, the model is built around parameterizations of height, latitudinal, longitudinal, and seasonal variations of temperature determined from a survey of published measurements from the Mariner and Viking programs. Pressure and density are inferred from the temperature by making use of the hydrostatic and perfect gas laws relationships. For the upper atmosphere, the thermospheric model of Stewart is used. A hydrostatic interpolation routine is used to insure a smooth transition from the lower portion of the model to the Stewart thermospheric model. Other aspects of the model are discussed.

Justus, C. G.↗

Laboratory studies of low-temperature reactions of C2H with C2H2 and implications for atmospheric models of Titan

Rate coefficients for the reaction C2H + C2H2 - C4H2 + H are measured over the temperature range 170-350 K. The reactions are carried out in a temperature variable flow cell. C2H radicals are produced by pulsed laser photolysis of C2H2 and a tunable infrared color-center laser is used to probe the transient removal of C2H in absorption to derive the rate coefficients. The rate coefficient is obtained and shown to be independent of temperature over the range 170-350 K. The reaction studied is of central importance for models of the photochemistry of the atmospheres of the outer planets, in particular for the satellite Titan, and the implications of the present results for these models are discussed.

Pedersen, Jens O. P.↗

CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Abstract. Numerical models used in weather and climate prediction take into account a comprehensive set of atmospheric processes (i.e., phenomena) such as the resolved and unresolved fluid dynamics, radiative transfer, cloud and aerosol life cycles, and mass or energy exchanges with the Earth's surface. In order to identify model deficiencies and improve predictive skills, it is important to obtain process-level understanding of the interactions between different processes. Conditional sampling and budget analysis are powerful tools for process-oriented model evaluation, but they often require tedious ad hoc coding and large amounts of instantaneous model output, resulting in inefficient use of human and computing resources. This paper presents an online diagnostic tool that addresses this challenge by monitoring model variables in a generic manner as they evolve within the time integration cycle. The tool is convenient to use. It allows users to select sampling conditions and specify monitored variables at run time. Both the evolving values of the model variables and their increments caused by different atmospheric processes can be monitored and archived. Online calculation of vertical integrals is also supported. Multiple sampling conditions can be monitored in a single simulation in combination with unconditional sampling. The paper explains in detail the design and implementation of the tool in the Energy Exascale Earth System Model (E3SM) version 1. The usage is demonstrated through three examples: a global budget analysis of dust aerosol mass concentration, a composite analysis of sea salt emission and its dependency on surface wind speed, and a conditionally sampled relative humidity budget. The tool is expected to be easily portable to closely related atmospheric models that use the same or similar data structures and time integration methods.

58 GEOSCIENCES↗

Insights on Simulating Summer Warming of the Great Lakes: Understanding the Behavior of a Newly Developed Coupled Lake-Atmosphere Modeling System

The Laurentian Great Lakes are the world's largest freshwater system and regulate the climate of the Great Lakes region, which has been increasingly experiencing climatic, hydrological, and ecological changes. An accurate mechanistic representation of the Great Lakes thermal structure in Regional Climate Models (RCMs) is paramount to studying the climate of this region. Currently, RCMs have primarily represented the Great Lakes through coupled one-dimensional (1D) column lake models; this approach works well for small inland lakes but is unable to resolve the realistic hydrodynamics of the Great Lakes and leads to inaccurate representations of lake surface temperature (LST) that influence regional climate and weather patterns. This work overcomes this limitation by developing a fully two-way coupled modeling system using the Weather Research and Forecasting model and a three-dimensional (3D) hydrodynamic model. The coupled model system resolves the interactive physical processes between the atmosphere, lake, and surrounding watersheds; and validated against a range of observational data. The model is then used to investigate the potential impacts of lake-atmosphere coupling on the simulated summer LST of Lake Superior. By evaluating the difference between our two-way coupled modeling system and our observation-driven modeling system, we find that coupled-lake atmosphere dynamics can lead to a higher LST during June-September through higher net surface heat flux entering the lake in June and July and a lower net surface heat flux entering the lake in August and September. The unstratified water in June distributes the entering surface heat flux throughout the water column leading to a minor LST increase, while the stratified waters of July create a conducive thermal structure for the water surface to warm rapidly under the higher incoming surface heat flux. This research provides insight into the coupled modeling system behavior, which is critical for enhancing our predictive understanding of the Great Lakes climate system.

54 ENVIRONMENTAL SCIENCES↗

Spectral and spatial energetics of the GISS model atmosphere

A calculation of the spectral and spatial energetics of the Goddard Institute for Space Studies (GISS) 9-level model of the global atmosphere is given. Results are presented from a model simulation of January 1973 and compared with previous model studies and an observational analysis for the Northern Hemisphere. The spectral analysis permits detailed study of those physical processes of scale larger than the grid spacing and allows indirect conclusions concerning unresolved subgrid-scale processes. Major conclusions for larger-than-grid-scale processes are that (1) the GISS model with a relatively coarse resolution of 4 deg latitude by 5 deg longitude produces significant nonlinear energy transfers; and (2) baroclinic conversion is large near planetary wave-number 6, but both the GISS model and another orographic model show a less peaked structure than nonorographic models and observations. A linear fit to the kinetic energy spectrum yields a power law of -2.6 in the wavenumber region 8 to 15. For subgrid-scale processes, the turbulence theory result of very small energy flux cascade is obtained.

Tenenbaum, J.↗

Spherically symmetric, expanding, non-LTE model atmospheres for novae during their early stages

In the continuum and line-blanketed models presented here, nova atmospheres are characterized by a very slow decrease of density with increasing radius. This feature leads to very large geometrical extensions so that there are large temperature differences between the inner and outer parts of the line-forming regions. The theoretical spectra show a large IR excess and a small Balmer jump which may be either in absorption or in emission. For the parameters considered (effective temperature of about 10 exp 4 K, L = 2 x 10 exp 4 solar luminosities, outer boundary density of about 3 x 10 exp -15 g cm exp -3, mass-loss rate of 10 exp -5 solar masses/yr), most lines are in absorption. The effects of changes in the abundances of the heavy elements on the emergent spectra are discussed. The strong unidentified features observed in ultraviolet spectra of novae are found in actuality to be regions of transparency within the Fe 'forest'. Ultraviolet spectra obtained from the IUE archives are displayed, and spectral synthesis of these spectra is done using the theoretical atmospheres.

Hauschildt, P. H.↗

Effects of a transient sea surface temperature anomaly on the energetics of the Mintz-Arakawa model atmosphere

The possible response of the atmosphere, as simulated by the two level Mintz-Arakawa global general circulation model, to a transient North Pacific sea surface temperature anomaly is investigated in terms of the energetics both in the spatial and wave number domains. Results indicate that the transient SST variations of reasonable magnitude in the North Pacific Ocean can induce a disturbing effect on the global energetics both in the spatial and wave number domains. The ability of the two level Mintz-Arakawa model to simulate the atmospheric energetics is also examined. Except in the tropics, the model exhibits a reasonable and realistic energy budget.

Chow, S. H.↗