Search NASA⌕ Search

SEARCH · Search NASA

Results for “COMMUNITY ATMOSPHERE MODEL”

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 991 records · Page 55

SST Improvements in the NASA GMAO Weather Analysis and Prediction System

It is well known that the sea surface temperature (SST) exhibits a diurnal cycle. Since January 2017, the NASA GMAO's Weather Analysis & Prediction System (https://gmao.gsfc.nasa.gov/weather_prediction/) includes a model for this diurnal cycle, a cool-skin layer and assimilates for skin SST. Data assimilation for the skin SST is carried out along with the 3-D state of the atmosphere, primarily using infrared radiance measurements, that are sensitive to the cool-skin and diurnal warming. In the context of Numerical Weather Prediction (NWP), this implies that the skin SST from our system is tightly coupled to the overlaying atmosphere and constrained by all the available atmospheric and surface-sensitive observations (in situ and satellite brightness temperatures). Comparisons of the SST diurnal cycle with other SST retrievals (SEVIRI (Spinning Enhanced Visible & InfraRed Imager) and AMSR-2 (Advanced Microwave Scanning Radiometer-2)) has shown mostly similar diurnal variation, however, the former decays at a faster rate. This poster presents our SST plus atmosphere assimilation methodology, and recent improvements to the skin SST model to address the known issues. Global, hourly estimates of the cool-skin and diurnal warm layer fields would be of interest to the SST retrieval community.

Akella, Santha↗

The Epic Chronicle of Designing Cassini's Titan Flyby Altitudes

The selection and optimization of Titan flyby altitudes for NASA's Cassini mission at Saturn has traveled a long, fascinating, and often torturous sixteen-year path - starting in 2001, when pre-arrival trajectory design decisions had to be made, through April of 2017 when Cassini's last, and arguably most critical, low flyby takes place. The chronicle of designing and updating the Titan flyby altitudes have twists and turns enough to satisfy a full-length novel or feature film, including: critical design decision-making before arrival with multiple atmospheric models, high uncertainties, and limited data; early flybys that seemed to show trends that weren't there; use and misuse of statistical analysis; unexpected surprises with limited reaction time; navigation of a scientific, engineering, and management community with a wide array of inherent biases; and consideration of a variety of project risk postures in a high-scrutiny, high-impact, high-reward environment.

Bittner, Molly↗

Forecasting Space Weather Events for a Neighboring World

Shortly after NASA's Mars Atmosphere and Volatile EvolutioN mission (MAVEN) spacecraft entered Mars' orbit on 21 September 2014, scientists glimpsed the Martian atmosphere's response to a front of solar energetic particles (SEPs) and an associated coronal mass ejection (CME). In response to some solar flares and CMEs, streams of SEPs burst from the solar atmosphere and are further accelerated in the interplanetary medium between the Sun and the planets. These particles deposit their energy and momentum into anything in their path, including the Martian atmosphere and MAVEN particle detectors. MAVEN scientists had been alerted to the likely CME-Mars encounter by a space weather prediction system that had its origins in space weather forecasting for Earth but now forecasts space weather for Earth's neighboring planets. The two Solar Terrestrial Relations Observatory spacecraft and Solar Heliospheric Observatory observed a CME on 26 September, with a trajectory that suggested a Mars intercept. A computer model developed for solar wind prediction, the Wang-Sheeley-Arge-Enlil cone model [e.g., Zheng et al., 2013; Parsons et al., 2011], running in real time at the Community Coordinated Modeling Center (CCMC) located at NASA Goddard since 2006, showed the CME propagating in the direction of Mars (Figure 1). According to MAVEN particle detectors, the disturbance and accompanying SEP enhancement at the leading edge of the CME reached Mars at approximately 17 hours Universal Time on 29 September 2014. Such SEPs may have a profound effect on atmospheric escape - they are believed to be a possible means for driving atmospheric loss. SEPs can cause loss of Mars' upper atmosphere through several loss mechanisms including sputtering of the atmosphere. Sputtering occurs when atoms are ejected from the atmosphere due to impacts with energetic particles.

space weather↗

ESMValTool (v1.0) – a community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP

A community diagnostics and performance metrics tool for the evaluation of Earth system models (ESMs) has been developed that allows for routine comparison of single or multiple models, either against predecessor versions or against observations. The priority of the effort so far has been to target specific scientific themes focusing on selected essential climate variables (ECVs), a range of known systematic biases common to ESMs, such as coupled tropical climate variability, monsoons, Southern Ocean processes, continental dry biases, and soil hydrology–climate interactions, as well as atmospheric CO 2 budgets, tropospheric and stratospheric ozone, and tropospheric aerosols. The tool is being developed in such a way that additional analyses can easily be added. A set of standard namelists for each scientific topic reproduces specific sets of diagnostics or performance metrics that have demonstrated their importance in ESM evaluation in the peer-reviewed literature. The Earth System Model Evaluation Tool (ESMValTool) is a community effort open to both users and developers encouraging open exchange of diagnostic source code and evaluation results from the Coupled Model Intercomparison Project (CMIP) ensemble. This will facilitate and improve ESM evaluation beyond the state-of-the-art and aims at supporting such activities within CMIP and at individual modelling centres. Ultimately, we envisage running the ESMValTool alongside the Earth System Grid Federation (ESGF) as part of a more routine evaluation of CMIP model simulations while utilizing observations available in standard formats (obs4MIPs) or provided by the user.

58 GEOSCIENCES↗

Multicentury changes in ocean and land contributions to the climate-carbon feedback

Improved constraints on carbon cycle responses to climate change are needed to inform mitigation policy, yet our understanding of how these responses may evolve after 2100 remains highly uncertain. Using the Community Earth System Model (v1.0), we quantified climate-carbon feedbacks from 1850 to 2300 for the Representative Concentration Pathway 8.5 and its extension. In three simulations, land and ocean biogeochemical processes experienced the same trajectory of increasing atmospheric CO 2 . Each simulation had a different degree of radiative coupling for CO 2 and other greenhouse gases and aerosols, enabling diagnosis of feedbacks. In a fully coupled simulation, global mean surface air temperature increased by 9.3 K from 1850 to 2300, with 4.4 K of this warming occurring after 2100. Excluding CO 2 , warming from other greenhouse gases and aerosols was 1.6 K by 2300, near a 2 K target needed to avoid dangerous anthropogenic interference with the climate system. Ocean contributions to the climate-carbon feedback increased considerably over time and exceeded contributions from land after 2100. The sensitivity of ocean carbon to climate change was found to be proportional to changes in ocean heat content, as a consequence of this heat modifying transport pathways for anthropogenic CO 2 inflow and solubility of dissolved inorganic carbon. By 2300, climate change reduced cumulative ocean uptake by 330 Pg C, from 1410 Pg C to 1080 Pg C. Land fluxes similarly diverged over time, with climate change reducing stocks by 232 Pg C. Regional influence of climate change on carbon stocks was largest in the North Atlantic Ocean and tropical forests of South America. Our analysis suggests that after 2100, oceans may become as important as terrestrial ecosystems in regulating the magnitude of the climate-carbon feedback.

54 ENVIRONMENTAL SCIENCES↗

The Community Climate System Model Version 4

The fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all the CCSM components, and documents fully coupled pre-industrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1{sup o} results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4{sup o} resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in the CCSM4 producing El Nino/Southern Oscillation variability with a much more realistic frequency distribution than the CCSM3, although the amplitude is too large compared to observations. They also improve the representation of the Madden-Julian Oscillation, and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the deep ocean density structure, especially in the North Atlantic. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than the CCSM3, and the Arctic sea ice concentration is improved in the CCSM4. An ensemble of 20th century simulations runs produce an excellent match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally-averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4 C. This is consistent with the fact that the CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of short-wave and long-wave cloud forcings.

54 ENVIRONMENTAL SCIENCES↗

Computer modeling of pulsed CO2 lasers for lidar applications

The object of this effort is to develop code to enable the accurate prediction of the performance of pulsed transversely excited (TE) CO2 lasers prior to their construction. This is of particular benefit to the NASA Laser Atmospheric Wind Sounder (LAWS) project. A benefit of the completed code is that although developed specifically for the pulsed CO2 laser much of the code can be modified to model other laser systems of interest to the lidar community. A Boltzmann equation solver has been developed which enables the electron excitation rates for the vibrational levels of CO2 and N2, together with the electron ionization and attachment coefficients to be determined for any CO2 laser gas mixture consisting of a combination of CO2, N2, CO, He and CO. The validity of the model has been verified by comparison with published material. The results from the Boltzmann equation solver have been used as input to the laser kinetics code which is currently under development. A numerical code to model the laser induced medium perturbation (LIMP) arising from the relaxation of the lower laser level has been developed and used to determine the effect of LIMP on the frequency spectrum of the LAWS laser output pulse. The enclosed figures show representative results for a laser operating at 0.5 atm. with a discharge cross-section of 4.5 cm to produce a 20 J pulse with aFWHM of 3.1 microns. The first four plots show the temporal evolution of the laser pulse power, energy evolution, LIMP frequency chirp and electric field magnitude. The electric field magnitude is taken by beating the calculated complex electric field and beating it with a local oscillator signal. The remaining two figures show the power spectrum and energy distribution in the pulse as a function of the varying pulse frequency. The LIMP theory has been compared with experimental data from the NOAA Windvan Lidar and has been found to be in good agreement.

Spiers, Gary D.↗

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model to Evaluate Juniperus spp. Pollen Phenology and Dispersal

Pollen can be transported great distances. Van de Water et. al. reported Juniperus spp. pollen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust. We are modifying the DREAM model to incorporate pollen transport. Pollen release will be estimated based on MODIS derived phenology of Juniperus spp. communities. Ground based observational records of pollen release timing and quantities will be used as verification. This information will be used to support the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.

Luvall, J. C.↗

Use of MODIS Satellite Images and an Atmospheric Dust Transport Model To Evaluate Juniperus spp. Pollen Phenology and Dispersal

Pollen can be transported great distances. Van de Water et. al., 2003 reported Juniperus spp. pollen was transported 200-600 km. Hence local observations of plant phenology may not be consistent with the timing and source of pollen collected by pollen sampling instruments. The DREAM (Dust REgional Atmospheric Model, Nickovic et al. 2001) is a verified model for atmospheric dust transport modeling using MODIS data products to identify source regions and quantities of dust. We are modifying the DREAM model to incorporate pollen transport. Pollen release will be estimated based on MODIS derived phenology of Juniperus spp. communities. Ground based observational records of pollen release timing and quantities will be used as verification. This information will be used to support the Centers for Disease Control and Prevention's National Environmental Public Health Tracking Program and the State of New Mexico environmental public health decision support for asthma and allergies alerts.

Luvall, J. C.↗

Mesoscale to Microscale Coupling for a Wind Ramp Case over Complex Terrain

Within the wind energy community, it has become increasingly important to simulate realistic weather events at high fidelity in order to improve wind turbine design, wind farm efficiency, and power forecasting. One of the major difficulties in simulating atmospheric events with numerical models at high fidelity is in accurately transitioning from the mesoscale to the microscale. The mesoscale flow, when input into the large-eddy simulation (LES) domain, will be free of resolved turbulence; needing sufficient time and space (known as fetch) for resolved-scale turbulence to develop. In order to reduce this fetch, several methods exist in which the temperature field, wind field, or both, are stochastically perturbed in order to accelerate the generation of turbulence. However, for cases involving complex terrain, it remains unclear if these perturbation processes are necessary, and if the interaction of the flow over the terrain, alone, is sufficient to generate adequate turbulence. In this study, a wind ramp event observed at the National Wind Technology Center (NWTC) outside of Boulder, CO is simulated first with a mesoscale model and then, using the simulated mesoscale solution as initial and boundary conditions, within a microscale LES solver. The mesoscale solution generated by the Weather Research and Forecasting (WRF) model accurately captures the wind ramp event with only a slight temporal shift and a small temperature bias when compared to the meteorological towers in the NWTC site. This information is then taken as the initial and boundary conditions within the Simulator for Wind Farm Applications (SOWFA) microscale LES model with varying terrain inputs. These inputs include the high-resolution (roughly 30 m grid spacing) terrain data from the Shuttle Radar Topography Mission (SRTM) (Figure 1a), as well as, three intermediate terrain resolution data sets produced by applying a uniform convolution window to the SRTM data with varying window sizes (Figure 1b-d). These are compared to the WRF terrain data interpolated to the high-resolution microscale grid (Figure 1e) in order to determine the impact of low-resolution (about 1 km grid spacing) terrain data on turbulence generation. The wind field is compared at several heights and distances along the dominant wind flow axis between each of the terrain cases. It is found that the development of turbulence across the domain is accelerated as terrain information increases in fidelity. Further, because this ramp event at the location of interest is largely influenced by the interaction of the short-wave trough with the terrain, as the topographic information decreases in fidelity the accuracy of the ramp event is decreased. To make generalizations and describe the benefits and shortcomings of this approach, several of the existing perturbation techniques are employed and compared to that of turbulence generation through topographic features.

17 WIND ENERGY↗

Additional Metadata Guidelines to Improve the Structure and Usability of HDF and NetCDF Files

The Hierarchical Data Format (HDF) and Network Common Data Form (NetCDF) are data file formats created to aid users in the creation or use of scientific data. These file formats are useful for handling large data volumes and hosting extensive metadata as global attributes or variables and are popular with the modeling community. HDF and NetCDF files are largely used with remote sensing data and have been used to support measurements from numerous campaigns, from satellite to aircraft or ground and mobile based measurements. The files from airborne field studies, however, vary greatly in terms of the file structure and the amount and content of metadata. Information relevant to the file that can be useful to the user such as the data producer, location where data was taken, variable descriptions, or information about the instrument might not be included in the file. This metadata might be present in another file in the dataset containing the same data using the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) format. Recently, the Aerosols, Clouds, and their Interactions for Earth System Models (MACIE) group started a grassroots effort to develop a set of requirements for the HDF and NetCDF files for field studies, aiming to make the data products more interoperable and usable. Particularly, these requirements seek to make the files more compliant to Climate and Forecast (CF) metadata conventions and to standardize the file structure and the global and variable attributes. These requirements would help to ensure that HDF and NetCDF files contain adequate metadata to better support their use for research, e.g., the modeling community, and to enhance the usability and interoperability of data for research communities at large. To be presented are the details of the MACIE requirements as well as examples of the implementation of these requirements for merge files and lidar observation data files.

Sean Leavor↗

Implications of weak near-term climate policies on long-term mitigation pathways

While the international community has set a target to limit global warming to no more than 2°C above pre-industrial levels, only a few concrete climate policies and measures to reduce greenhouse gas (GHG) emissions have been implemented. We use a set of three global integrated assessment models to analyze the implications of current climate policies on long-term mitigation targets. We define a weak-policy baseline scenario, which extrapolates the current policy environment by assuming that the global climate regime remains fragmented and that emission reduction efforts remain unambitious in most of the world’s regions. In this scenario, GHG concentrations stabilize at approximately 650 ppm CO2e, which clearly falls short of the international community’s long-term climate target. We investigate the cost and achievability of the stabilization of atmospheric GHG concentrations at 450 ppm CO2e by 2100, if countries follow the weak policy pathway until 2020 or 2030, before global cooperative action is taken to pursue the long-term mitigation target. Despite weak near-term action, a 450 ppm CO2e target is achievable in all the models. However, we find that a deferral of ambitious action exacerbates the challenges of low stabilization. Specifically, weak near-term action leads to (a) higher temporary overshooting of radiative forcing, (b) faster and more aggressive transformations of energy systems after target adoption, (c) more stranded investments in fossil-based capacities, and (d) higher long-term mitigation costs and carbon prices._

Luderer, Gunnar↗

A model for diurnal patterns of carbon fixation in a Precambrian microbial mat based on a modern analog

Microbial mat communities are one of the first and most prevalent biological communities known from the Precambrian fossil record. These fossil mat communities are found as laminated sedimentary rock structures called stromatolites. Using a modern microbial mat as an analog for Precambrian stromatolites, a study of carbon fixation during a diurnal cycle under ambient conditions was undertaken. The rate of carbon fixation depends primarily on the availability of light (consistent with photosynthetic carbon fixation) and inorganic carbon, and not nitrogen or phosphorus. Atmospheric PCO2 is thought to have decreased from 10 bars at 4 Ga (10(9) years before present) to approximately 10(-4) bars today, implying a change in the availability of inorganic carbon for carbon fixation. Experimental manipulation of levels of inorganic carbon to levels that may have been available to Precambrian mat communities resulted in increased levels of carbon fixation during daylight hours. Combining these data with models of daylength during the Precambrian, models are derived for diurnal patterns of photosynthetic carbon fixation in a Precambrian microbial mat community. The models suggest that, even in the face of shorter daylengths during the Precambrian, total daily carbon fixation has been declining over geological time, with most of the decrease having occurred during the Precambrian.

Review↗

Progress and Challenges in Quantifying Wildfire Smoke Emissions, Their Properties, Transport, and Atmospheric Impacts

Wildfire is a natural and integral ecosystem process that is necessary to maintain species composition, structure, and ecosystem function. Extreme fires have been increasing over the last decades, which have a substantial impact on air quality, human health, the environment, and climate systems. Smoke aerosols can be transported over large distances, acting as pollutants that affect adjacent and distant downwind communities and environments. Fire emissions are a complicated mixture of trace gases and aerosols, many of which are short‐lived and chemically reactive, and this mixture affects atmospheric composition in complex ways that are not completely understood. We present a review of the current state of knowledge of smoke aerosol emissions originating from wildfires. Satellite observations, from both passive and active instruments, are critical to providing the ability to view the large‐scale influence of fire, smoke, and their impacts. Progress in the development of fire emission estimates to regional and global chemical transport models has advanced, although significant challenges remain, such as connecting ecosystems and fuels burned with dependent atmospheric chemistry. Knowledge of the impact of smoke on radiation, clouds, and precipitation has progressed and is an essential topical research area. However, current measurements and parameterizations are not adequate to describe the impacts on clouds of smoke particles (e.g., CNN, INP) from fire emissions in the range of representative environmental conditions necessary to advance science or modeling. We conclude by providing recommendations to the community that we believe will advance the science and understanding of the impact of fire smoke emissions on human and environmental health, as well as feedback with climate system.

I N Sokolik↗

Forest response to rising CO 2 drives zonally asymmetric rainfall change over tropical land

Understanding how anthropogenic CO 2 emissions will influence future precipitation is critical for sustainably managing ecosystems, particularly for drought-sensitive tropical forests. Although tropical precipitation change remains uncertain, nearly all models from the Coupled Model Intercomparison Project Phase 5 predict a strengthening zonal precipitation asymmetry by 2100, with relative increases over Asian and African tropical forests and decreases over South American forests. Here we show that the plant physiological response to increasing CO 2 is a primary mechanism responsible for this pattern. Applying a simulation design in the Community Earth System Model in which CO 2 increases are isolated over individual continents, we demonstrate that different circulation, moisture and stability changes arise over each continent due to declines in stomatal conductance and transpiration. The sum of local atmospheric responses over individual continents explains the pan-tropical precipitation asymmetry. Our analysis suggests that South American forests may be more vulnerable to rising CO 2 than Asian or African forests.

54 ENVIRONMENTAL SCIENCES↗

Tropical Convective Transition Statistics and Causality in the Water Vapor–Precipitation Relation

Abstract Previous work by various authors has pointed to the role of lower-free-tropospheric humidity in affecting the onset of deep convection in the tropics. Empirical relationships between column water vapor (CWV) and precipitation have been inferred to result from these effects. Evidence from previous work has included deep convective conditional instability calculations for entraining plumes, in which the lower-free-tropospheric environment affects the onset of deep convection due to the differential impact on buoyancy of turbulent entrainment of dry versus moist air. The relationship between deep convection and water vapor is, however, a two-way interaction because convection also moistens the free troposphere. The present study adds an additional line of evidence toward fully establishing the causality of the precipitation–water vapor relationship. Parameter perturbation experiments using the coupled Community Earth System Model (CESM) with high-time-resolution output are analyzed for a set of statistics for the transition to deep convection, coordinated with observational diagnostics for the Green Ocean Amazon (GOAmazon) campaign and tropical western Pacific Atmospheric Radiation Measurement (ARM) sites. For low values of entrainment in the deep convective scheme, these statistics are radically altered and the observed pickup of precipitation with CWV is no longer seen. In addition to helping cement the dominant direction of causality in the fast-time-scale precipitation–CWV relationship, the results point to impacts of entrainment on the climatology. Because at low entrainment convection can fire before tropospheric moistening, the climatological values of relative humidity are lower than observed. These findings can be consequential to biases in simulated climate and to projections of climate change.

54 ENVIRONMENTAL SCIENCES↗

CoCoMET v1.0: a unified open-source toolkit for atmospheric object tracking and analysis

Advances in performance and analysis capabilities have accelerated the development of object tracking algorithms for atmospheric research. This has resulted in a growing number of studies using Lagrangian tracking techniques to analyze the evolution of atmospheric phenomena and the underlying processes. However, the increasing complexity and variety of tracking algorithms present a steep learning curve for new users and make it difficult for existing users to compare algorithm performance. We introduce CoCoMET (Community Cloud Model Evaluation Toolkit), an open-source toolkit that addresses these issues. CoCoMET simplifies the process of running multiple tracking algorithms simultaneously and analyzing objects in both model and observational datasets by specifying parameters in a single configuration file. It standardizes input data from different sources into a consistent format and unifies the tracking output across algorithms. CoCoMET enhances the functionality of existing tracking methods by calculating additional properties such as cell growth and dissipation rates, perimeter, surface area, convexity, and irregularity. In addition, CoCoMET includes a novel method for identifying mergers and splits in 2D and 3D tracks and supports the integration of Eulerian/stationary datasets external to the tracking data for process studies. Its potential utility is demonstrated through examples of model intercomparison, model evaluation against observations, and comparisons between tracking algorithms. Designed for open-source environments, CoCoMET will continue to expand with future releases, incorporating more input data types and tracking algorithms.

54 ENVIRONMENTAL SCIENCES↗

Spatial Growth Modeling and High Resolution Remote Sensing Data Coupled with Air Quality Modeling to Assess the Impact of Atlanta, Georgia on the Local and Regional Environment

The growth of cities, both in population and areal extent, appears as an inexorable process. Urbanization continues at a rapid rate, and it is estimated that by the year 2025, 60 percent of the world s population will live in cities. Urban expansion has profound impacts on a host of biophysical, environmental, and atmospheric processes within an urban ecosystems perspective. A reduction in air quality over cities is a major result of these impacts. Because of its complexity, the urban landscape is not adequately captured in air quality models such as the Community Multiscale Air Quality (CMAQ) model that is used to assess whether urban areas are in attainment of EPA air quality standards, primarily for ground level ozone. This inadequacy of the CMAQ model to sufficiently respond to the heterogeneous nature of the urban landscape can impact how well the model predicts ozone levels over metropolitan areas and ultimately, whether cities exceed EPA ozone air quality standards. We are exploring the utility of high-resolution remote sensing data and urban spatial growth modeling (SGM) projections as improved inputs to a meteorological/air quality modeling system focusing on the Atlanta, Georgia metropolitan area as a case study. These growth projections include business as usual and smart growth scenarios out to 2030. The growth projections illustrate the effects of employing urban heat island mitigation strategies, such as increasing tree canopy and albedo across the Atlanta metro area, which in turn, are used to model how air temperature can potentially be moderated as impacts on elevating ground-level ozone, as opposed to not utilizing heat island mitigation strategies. The National Land Cover Dataset at 30m resolution is being used as the land use/land cover input and aggregated to the 4km scale for the MM5 mesoscale meteorological model and the CMAQ modeling schemes. Use of these data has been found to better characterize low density/suburban development as compared with USGS lkm land use/land cover data that have traditionally been used in modeling. Air quality prediction for future scenarios to 2030 is being facilitated by land use projections using a spatial growth model. Land use projections were developed using the 2030 Regional Transportation Plan developed by the Atlanta Regional Commission, the regional planning agency for the area. This allows the Georgia Environmental Protection Division to evaluate how these transportation plans will affect future air quality. The coupled SGM and air quality modeling approach provides insight on what the impacts of Atlanta s growth will be on the local and regional environment and exists as a mechanism that can be used by policy makers to make rational decisions on urban growth and sustainability for the metropolitan area in the future.

Quattrochi, Dale A.↗