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NASA NTRS2004

Comparisons of Observations with Results from 3D Simulations and Implications for Predictions of Ozone Recovery

Although chemistry and transport models (CTMs) include the same basic elements (photo- chemical mechanism and solver, photolysis scheme, meteorological fields, numerical transport scheme), they produce different results for the future recovery of stratospheric ozone as chlorofluorcarbons decrease. Three simulations will be contrasted: the Global Modeling Initiative (GMI) CTM driven by a single year\'s winds from a general circulation model; the GMI CTM driven by a single year\'s winds from a data assimilation system; the NASA GSFC CTM driven by a winds from a multi-year GCM simulation. CTM results for ozone and other constituents will be compared with each other and with observations from ground-based and satellite platforms to address the following: Does the simulated ozone tendency and its latitude, altitude and seasonal dependence match that derived from observations? Does the balance from analysis of observations? Does the balance among photochemical processes match that expected from observations? Can the differences in prediction for ozone recovery be anticipated from these comparisons?

Douglass, Anne R.↗

NASA NTRS2004

Ozone Measurements and a 3D Chemical Transport Model

We have used our three-dimensional chemical transport model (CTM) to calculate the expected reponse of stratospheric composition over the past 30 years to forcing by chlorine and bromine compounds, solar ultraviolet, and volcanic aerosols. The CTM uses off-line winds and temperatures fiom a 50-year run of the finite volume general circulation model (FVGCM). We compare the total column ozone and the ozone profile fiom the CTM output to a variety of data sources. These include a merged total ozone data set from TOMS and SBUV using the new version 8 algorithm. Total ozone fiom the CTM are compared to ground-station measurements of total ozone at specific locations. Ozone profiles are compared to satellite meausrements fiom SBUV, SAGE, and HALOE. Profiles are also compared to ozonesondes over several locations. The results of the comparisons are quantified by using a time-series statistical analysis to determine trends, solar cycle, and volcanic reponse in both the model and in the data. Initial results indicate that the model responds to forcings in a way that is similar to the observed atmospheric response. The model does seem to be more sensitive to the chlorine and bromine perturbation ihan is the data. Further details and comparisons wiii be discussed.

Stolarski, Richard S.↗

NASA NTRS2017

An Overview of Atmospheric Chemistry and Air Quality Modeling

This presentation will include my personal research experience and an overview of atmospheric chemistry and air quality modeling to the participants of the NASA Student Airborne Research Program (SARP 2017). The presentation will also provide examples on ways to apply airborne observations for chemical transport (CTM) and air quality (AQ) model evaluation. CTM and AQ models are important tools in understanding tropospheric-stratospheric composition, atmospheric chemistry processes, meteorology, and air quality. This presentation will focus on how NASA scientist currently apply CTM and AQ models to better understand these topics. Finally, the importance of airborne observation in evaluating these topics and how in situ and remote sensing observations can be used to evaluate and improve CTM and AQ model predictions will be highlighted.

Atmospheric↗

NASA NTRS2017

Daily Ambient Air Pollution Metrics for Five Cities: Evaluation of Data Fusion-Based Estimates and Uncertainties

Spatiotemporal characterization of ambient air pollutant concentrations is increasingly relying on the combination of observations and air quality models to provide well-constrained, spatially and temporally complete pollutant concentration fields. Air quality models, in particular, are attractive, as they characterize the emissions, meteorological, and physiochemical process linkages explicitly while providing continuous spatial structure. However, such modeling is computationally intensive and has biases. The limitations of spatially sparse and temporally incomplete observations can be overcome by blending the data with estimates from a physically and chemically coherent model, driven by emissions and meteorological inputs. We recently developed a data fusion method that blends ambient ground observations and chemical transport-modeled (CTM) data to estimate daily, spatially resolved pollutant concentrations and associatedcorrelations. In this study, we assess the ability of the data fusion method to produce daily metrics (i.e., 1-hr max, 8-hr max, and 24-hr average) of ambient air pollution that capture spatiotemporal air pollution trends for 12 pollutants (CO, NO2, NOx, O3, SO2, PM (sub10), PM (sub 2.5), and five PM (sub 2.5) components) across five metropolitan areas (Atlanta, Birmingham, Dallas, Pittsburgh, and St. Louis), from 2002 to 2008. Three sets of comparisons are performed: (1) the CTM concentrations are evaluated for each pollutant and metropolitan domain, (2) the data fusion concentrations are compared with the monitor data, (3) a comprehensive cross-validation analysis against observed data evaluates the quality of the data fusion model simulations across multiple metropolitan domains. The resulting daily spatial field estimates of air pollutant concentrations and uncertainties are not only consistent with observations, emissions, andmeteorology, but substantially improve CTM-derived results for nearly all pollutants and all cities, with the exception of NO2 for Birmingham. The greatest improvements occur for O3 and PM (sub 2.5). Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R-squared equal to 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM (sub 2.5)), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM (sub 10)). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

spatiotemporal fusion↗

NASA NTRS2018

GMI-IPS: Processing & Visualization Software Used in ATom DC-8 Aircraft Studies

NASA's Atmospheric Tomography Mission (ATom) deployed in each of the four seasons during 2016-2018, the DC-8 aircraft in order to establish global-scale datasets intended to improve the representation of chemically reactive gases in global atmospheric chemistry models (ACMs). The Global Modeling Initiative (GMI) executed simulations for each ATom flight using the GMI Chemistry Transport Model (GMI-CTM) to provide species concentrations of chemical gases along the DC-8 flight transects. To solve the problem of translating the GMI-CTM simulation data to the unique spatial resolutions of each ATom flight, the GMI ICARTT Processing Software (GMI-IPS) was developed.The GMI-IPS is written in Python and provides data processing, flight extraction, and visualization support for aircraft research projects using ICARTT format, which is a standard format for airborne instrument data. Additionally, the GMI-IPS interpolates global gridded model data from Hierarchical Data Format (HDF) to ICARTT compatible flight transects. Software classes for instruments and collections provided by the ATom DC-8 aircraft such as MER10, MMS, etc. are derived from a common base class. Other functionality provided by the GMI-IPS are: deriving missing flight entries along a transect, reading ICARTT entries from file, and providing Python data structures for storing flight and model information, and more.The GMI-IPS is GIT source controlled, has approximately 30,000 lines of code, and supports parallelization across data collections. It delivered GMI-CTM data for more than forty distinct DC-8 aircraft flights that took place under ATom. The output ICARTT files adhere to format standard V1.1, and pass the scan utility provided by NASA LaRC Airborne Science Data for Atmospheric Composition. This presentation will include a software and methods overview, and results from ATom, including assessments using the GMI-CTM showing how well observations from ATom flight transects represent a broader region.

Damon, M. R.↗

NASA NTRS2018

Bistable Collapsible Tubular Mast Booms

A promising candidate for deployable composite structures is the two-shelled Collapsible Tubular Mast (CTM) boom, which is to be employed on future solar sail and interplanetary small satellite platforms by the National Aeronautics and Space Administration (NASA). This is due to its two omega-shaped shells forming a closed-section which yields large stiffnesses that allowed for high dimensional stability. An inextensional analytical model describing the bending deformation mechanics of CTM booms was used to determine how design variables induce bistability, or the existence of two strain energy wells. Bistable booms were favorable due to low strain energy requirements for the coiled state and had more controllable deployment when compared to monostable booms. The effects of varying lamina material, laminate layup, and shell arc geometries between different inner and outer shell segments on the second strain energy well and stiffness properties were determined for cross-sections formed by circular segments. The full design space for two-shelled composite CTM booms was explored to evaluate the validity of the simple analytical model developed. Optimal CTM boom designs were manufactured and experimentally characterized for comparisons against model results. The model under-predicted the second stable coiled diameter of the complete two-shelled booms by 27-33% and as low as 3-8% for the individual shells wrapped alone.

Fernandez, Juan M.↗

NASA NTRS2019

The Effects of a 1998 Observing System Change on MERRA-2-Based Ozone Profile Simulations

Model simulations of ozone (O3) driven by meteorological reanalyses are useful for filling observational gaps and interpreting observed O3 variability and trends. However, the transport circulation of reanalysis products is impacted by changes to the observing system (the data assimilated into the reanalyses). We examine the impacts of these changes on simulated O3 from two models, Global Modeling Initiative (GMI) Chemistry Transport Model (GMI CTM) and Modern‐Era Retrospective Analysis for Research Applications version 2 (MERRA‐2) GMI Replay (M2 GMI Replay) simulation, using observations from global ozonesondes (>50,000 profiles) and satellites from 1980 to 2016. Both models are constrained by meteorology from the NASA MERRA‐2 reanalysis, and both use versions of NASA's GMI chemical mechanism. We focus on an observing system change affecting simulated O3 after 1998, associated with the assimilation of temperature and humidity data from new microwave profiling satellites. A large post‐1998 O3 increase, mainly confined to 15–20‐km altitude, of ~10 Dobson units (DU) in midlatitudes occurs in the GMI CTM, worsening the bias compared to observations. In contrast, an increase in M2 GMI Replay simulation O3 of ~10 DU is observed only near −60° latitude, reducing the bias compared to observations. The GMI CTM O3 high biases display a Quasi‐Biennial Oscillation (QBO)‐like periodicity that result from excessive transport from the tropical stratosphere to the midlatitude lower stratosphere during the QBO westerly phase. We quantify O3 discontinuities caused by MERRA‐2 observing system changes and demonstrate how the MERRA‐2 Global Modeling Initiative Replay simulation dampens the effects of these changes and QBO‐driven artifacts on simulated lower stratospheric and total O3. We caution against using simulations driven by a reanalysis to derive multidecadal O3 trends, especially prior to 1998.

Replay↗

NASA NTRS1998

Choosing Meteorological Input for the Global Modeling Initiative Assessment of High Speed Aircraft

The Global Modeling Initiative (GMI) science team is developing a three dimensional chemistry and transport model (CTM) to be used in assessment of the atmospheric effects of aviation. Requirements are that this model be documented, be validated against observations, use a realistic atmospheric circulation, and contain numerical transport and photochemical modules representing atmospheric processes. The model must also retain computational efficiency to be tractable to use for multiple scenarios and sensitivity studies. To meet these requirements, a facility model concept was developed in which the different components of the CTM are evaluated separately. The first use of the GMI model will be to evaluate the impact of the exhaust of supersonic aircraft on the stratosphere. The assessment calculations will depend strongly on the wind and temperature fields used by the CTM. Three meteorological data sets for the stratosphere are available to GMI: the National Center for Atmospheric Research Community Climate Model (CCM2), the Goddard Earth Observing System Data Assimilation System (GEOS DAS), and the Goddard Institute for Space Studies general circulation model (GISS). Objective criteria were established by the GMI team to identify the data set which provides the best representation of the stratosphere. Simulations of gases with simple chemical control were chosen to test various aspects of model transport. The three meteorological data sets were evaluated and graded based on their ability to simulate these aspects of stratospheric measurements. This paper describes the criteria used in grading the meteorological fields. The meteorological data set which has the highest score and therefore was selected for GMI is CCM2. This type of objective model evaluation establishes a physical basis for interpretation of differences between models and observations. Further, the method provides a quantitative basis for defining model errors, for discriminating between different models, and for ready re-evaluation of improved models. These in turn will lead to a higher level of confidence in assessment calculations.

Douglas, A. R.↗

NASA NTRS1999

Selecting Meteorological Input for the Global Modeling Initiative Assessments

The Global Modeling Initiative (GMI) science team has developed a three dimensional chemistry and transport model (CTM) to evaluate the impact of the exhaust of supersonic aircraft on the stratosphere. An important goal of the GMI is to test modules for numerical transport, photochemical integration, and model dynamics within a common framework. This work is focussed on the dependence of the overall assessment on the wind and temperature fields used by the CTM. Three meteorological data sets for the stratosphere were available to GMI: the National Center for Atmospheric Research Community Climate Model (CCM2), the Goddard Earth Observing System Data Assimilation System (GEOS-DAS), and the Goddard Institute for Space Studies general circulation model (GISS-2'). Objective criteria were established by the GMI team to evaluate which of these three data sets provided the best representation of trace gases in the stratosphere today. Tracer experiments were devised to test various aspects of model transport. Stratospheric measurements of long-lived trace gases were selected as a test of the CTM transport. This presentation describes the criteria used in grading the meteorological fields and the resulting choice of wind fields to be used in the GMI assessment. This type of objective model evaluation will lead to a higher level of confidence in these assessments. We suggest that the diagnostic tests shown here be used to augment traditional general circulation model evaluation methods.

Strahan, Susan↗

NASA NTRS1999

The Atmospheric Effects of HSCT Emissions Simulated by a 3-Wave Interactive Model

An interactive model which couples a semi-spectral dynamical model, a radiative transfer code and a two-dimensional chemistry transport model (2-D CTM), is used to assess the atmospheric effects of the High-Speed Civil Transport (HSCT) engine emissions. The residual mean meridional circulation, the zonal-mean temperature and the eddy diffusion coefficients are calculated using zonal means and three longest zonal waves of dynamical variables integrated in the semi-spectral dynamical model. They are used in the 2-D CTM to simulate the distribution of trace gases in the atmosphere. The simulated ozone is sent to the radiative transfer code to calculate the heating rates, which drive the dynamics. This radiative coupling connects the dynamical and photochemical processes and creates feedback when the atmosphere is perturbed. It is found that in most areas the ozone depletion caused by HSCT emissions calculated using the 3-wave model has the features similar to, but with significantly larger magnitude than that calculated by the AER 2-D CTM with prescribed transport parameters and temperature. The difference is mostly due to the differences in the circulation in the two models. The radiative feedback effects are investigated by comparing the ozone depletion calculated with the baseline dynamics and with the dynamics perturbed by the HSCT emissions. The feedback through changes in the residual mean meridional circulation and the eddy diffusion coefficients has moderate effects on the simulated ozone depletion. It reduced the ozone depletion by 20-30% in northern mid and high-latitudes. However, the feedback through changes in the zonal- mean temperature is negligible.

Shia, R.-L.↗

NASA NTRS1999

Choosing Meteorological Input for the Global Modeling Initiative Assessment of High Speed Aircraft

The Global Modeling Initiative (GMI) science team is developing a three dimensional chemistry and transport model (CTM) to be used in assessment of the atmospheric effects of aviation. Requirements are that this model be documented be validated against observations, use a realistic atmospheric circulation, and contain numerical transport and photochemical modules representing atmospheric processes. The model must also retain computational efficiency to be tractable to use for multiple scenarios and sensitivity studies. To meet these requirements, a facility model concept was developed in which the different components of the CTM are evaluated separately. The first use of the GMI model will be to evaluate the impact of the exhaust of supersonic aircraft on the stratosphere. The assessment calculations will depend strongly on the wind and temperature fields used by the CTM. Three meteorological data sets for the stratosphere are available to GMI: the National Center for Atmospheric Research Community Climate Model (CCM2), the Goddard Earth Observing System Data Assimilation System (GEOS DAS), and the Goddard Institute for Space Studies general circulation model (GISS). Objective criteria were established by the GMI team to identify the data set which provides the best representation of the stratosphere. Simulations of gases with simple chemical control were chosen to test various aspects of model transport. The three meteorological data sets were evaluated and graded based on their ability to simulate these aspects of stratospheric measurements. This paper describes the criteria used in grading the meteorological fields. The meteorological data set which has the highest score and therefore was selected for GMI is CCM2. This type of objective model evaluation establishes a physical basis for interpretation of differences between models and observations. Further, the method provides a quantitative basis for defining model errors, for discriminating between different models, and for ready re-evaluation of improved models. These in turn will lead to a higher level of confidence in assessment calculations.

Douglass, A. R.↗

NASA NTRS2002

Chemistry-Transport Modeling of the Satellite Observed Distribution of Tropical Tropospheric Ozone

We have compared the 14-year record of satellite derived tropical tropospheric ozone columns (TTOC) from the NIMBUS-7 Total Ozone Mapping Spectrometer (TOMS) to TTOC calculated by a chemistry-transport model (CTM). An objective measure of error, based on the zonal distribution of TTOC in the tropics, is applied to perform this comparison systematically. In addition, the sensitivity of the model to several key processes in the tropics is quantified to select directions for future improvements. The comparisons indicate a widespread, systematic (20%) discrepancy over the tropical Atlantic Ocean, which maximizes during austral Spring. Although independent evidence from ozonesondes shows that some of the disagreement is due to satellite over-estimate of TTOC, the Atlantic mismatch is largely due to a misrepresentation of seasonally recurring processes in the model. Only minor differences between the model and observations over the Pacific occur, mostly due to interannual variability not captured by the model. Although chemical processes determine the TTOC extent, dynamical processes dominate the TTOC distribution, as the use of actual meteorology pertaining to the year of observations always leads to a better agreement with TTOC observations than using a random year or a climatology. The modeled TTOC is remarkably insensitive to many model parameters due to efficient feedbacks in the ozone budget. Nevertheless, the simulations would profit from an improved biomass burning calendar, as well as from an increase in NOX abundances in free tropospheric biomass burning plumes. The model showed the largest response to lightning NOX emissions, but systematic improvements could not be found. The use of multi-year satellite derived tropospheric data to systematically test and improve a CTM is a promising new addition to existing methods of model validation, and is a first step to integrating tropospheric satellite observations into global ozone modeling studies. Conversely,the CTM may suggest improvements to evolving satellite retrievals for tropospheric ozone.

Peters, Wouter↗

NASA NTRS2004

The Latitude Dependence of the Effect of Pinatubo on Stratospheric Ozone

Statistical analysis of TOMS and SBLT total ozone data indicate that the eruption of Pinatubo in 1991 led to a significant decrease in ozone at northern midlatitudes with little or no effect at southern midlatitudes. We argue that this puzzling absence of a southern hemisphere effect may be an artifact of the statistical analysis. We have run a 3D CTM simulation of the past 30 years of stratospheric photochemistry with variable forcing due to chlorine/bromine compounds, solar ultraviolet radiation, and volcanic aerosols. This integration used winds from the FVGCM, which has similar interannual variability to the atmosphere. When this CTM output was examined with a standard time-series analysis, we found an effect of Pinatubo in the southern hemisphere, but not in the northern hemisphere. We then reran the CTM without volcanic aerosols. The subtraction of the two simulations indicated that, as expected, that Pinatubo affected both hemispheres in the model. This means that the northern hemisphere effect was in the model but did not show up in the statistical analysis. We also had an on-line parameterized chemical ozone tracer with seasonally repeating production and loss over the simulation. We used this as a dynamical surrogate to remove interannual variability from the original model output. The residual time series was then analyzed for the Pinatubo effect and we were able to find it in both hemispheres. We suggest that the combination of the two volcanoes, El Chichon and Pinatubo, with the solar cycle and interannual variability led to this problem of analysis in the northern hemisphere of our model. We furthermore suggest that a similar think may be occurring in the southern hemisphere of the data. An analysis of the atmosphere's southern hemisphere with a good dynamical surrogate may solve the mystery of the missing southern hemisphere effect of Pinatubo on ozone.

Stolarski, Richard S.↗

NASA NTRS2005

Separating the Chemical and Dynamical Contributions to the Ozone Change

Statistical analysis is used to extract the sensitivity of ozone to changes in stratospheric chlorine due to emissions of chlorofluorcarbons from the observed ozone record. The statistical analysis relies on a model that accounts for natural variations in ozone including the seasonal cycle, the solar cycle, variations in aerosols due to volcanic eruption, and the quasi- biennial oscillation, A noise term includes contributions to ozone variability due to inter-annual variability in the stratospheric circulation not due to the quasi-biennial oscillation, The residual circulation varies due to variability in planetary wave forcing, and studies using meteorological analyses show that the build-up of ozone over the winter is correlated with the planetary wave Eliassen-Palm flux. This variability in the residual circulation is not included in the statistical model, and contributes to the apparent ozone sensitivity to chlorine derived from observations for 1979 - 2000. We have investigated these relationships using multi-decadal simulations of our off-line chemistry and transport model (CTM). Our simulations use meteorological fields output from a 50 year simulation of a general circulation model (GCM). A 50 climatology specifies the sea surface temperatures to produce the GCM simulation. The CTM was used with these winds to produce two simulations, one in which the boundary conditions for chlorofluorcarbons and other source gases vary as specified for 1973-2022 by the Scenario A2 of the World Meteorological Organization ozone assessment, and the second with source gases fixed to their 1979 values. The same statistical analysis used to derive trends from observations is applied to the CTM output. When applied to the difference between the two simulations the statistical analysis provides a more precise measure of the ozone sensitivity to chlorine change. We are testing ways of including the interannual variability in the residual circulation in the statistical model so that we can derive the same result from the Scenario A2 simulation as is obtained when the statistical analysis is applied to the difference between the two simulations. This should provide direction as to how to account for the changes in ozone due to interannual variability in the residual circulation in the statistical model that is applied to the observed data record.

Douglass, Anne R.↗

NASA NTRS2017

Quantifying the Causes of Differences in Tropospheric OH Within Global Models

The hydroxyl radical (OH) is the primary daytime oxidant in the troposphere and provides the main loss mechanism for many pollutants and greenhouse gases, including methane (CH4). Global mean tropospheric OH differs by as much as 80% among various global models, for reasons that are not well understood. We use neural networks (NNs), trained using archived output from eight chemical transport models (CTMs) that participated in the Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols and Transport Model Intercomparison Project (POLMIP), to quantify the factors responsible for differences in tropospheric OH and resulting CH4 lifetime (Tau CH4) between these models. Annual average Tau CH4, for loss by OH only, ranges from 8.0 to 11.6 years for the eight POLMIP CTMs. The factors driving these differences were quantified by inputting 3-D chemical fields from one CTM into the trained NN of another CTM. Across all CTMs, the largest mean differences in Tau CH4 (Delta Tau CH4) result from variations in chemical mechanisms (Delta Tau CH4 = 0.46 years), the photolysis frequency (J) of O3 yields O(D-1) (0.31 years), local O3 (0.30 years), and CO (0.23 years). The Delta Tau CH4 due to CTM differences in NO(x) (NO + NO2) is relatively low (0.17 years), although large regional variation in OH between the CTMs is attributed to NO(x). Differences in isoprene and J(NO2) have negligible overall effect on globally averaged tropospheric OH, although the extent of OH variations due to each factor depends on the model being examined. This study demonstrates that NNs can serve as a useful tool for quantifying why tropospheric OH varies between global models, provided that essential chemical fields are archived.

Surface Measurements and Models↗

NASA NTRS2017

Importance of a Priori Vertical Ozone Profiles for TEMPO Air Quality Retrievals

Ozone (O3) is a toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address the limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME (Global Ozone Monitoring Experiment), GOME-2, and OMI (Ozone Monitoring Instrument). This algorithm is suggested to use a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB-Clim) O3 climatology). This study evaluates the TB-Clim dataset and model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time data assimilation model products (NASA GMAO's (Global Modeling and Assimilation Office) operational GEOS-5 (Goddard Earth Observing System, Version 5) FP (Forecast Products) model and reanalysis data from MERRA2 (Modern-Era Retrospective analysis for Research and Applications, Version 2)) and a full chemical transport model (CTM), GEOS-Chem. In this study, vertical profile products are evaluated with surface (0-2 kilometers) and tropospheric (0-10 kilometers) TOLNet (Tropospheric Ozone Lidar Network) observations and the theoretical impact of individual a priori profile sources on the accuracy of TEMPO O3 retrievals in the troposphere and at the surface are presented. Results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles, model-simulated profiles from a full CTM resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly and daily-averaged TOLNet observations. Furthermore, it is shown that when large surface O3 mixing ratios are observed, TEMPO retrieval values at the surface are most accurate when applying CTM a priori profile information compared to all other data products.

Priori↗

NASA NTRS2013

Analyzing Carbon Dioxide and Methane Emissions in California Using Airborne Measurements and Model Simulations

Greenhouse gas (GHG) concentrations have increased over the past decades and are linked to global temperature increases and climate change. These changes in climate have been suggested to have varying effects, and uncertain consequences, on agriculture, water supply, weather, sea-level rise, the economy, and energy. To counteract the trend of increasing atmospheric concentrations of GHGs, the state of California has passed the California Global Warming Act of 2006 (AB-32). This requires that by the year 2020, GHG (e.g., carbon dioxide (CO2) and methane (CH4)) emissions will be reduced to 1990 levels. To quantify GHG fluxes, emission inventories are routinely compiled for the State of California (e.g., CH4 emissions from the California Greenhouse Gas Emissions Measurement (CALGEM) Project). The major sources of CO2 and CH4 in the state of California are: transportation, electricity production, oil and gas extraction, cement plants, agriculture, landfills/waste, livestock, and wetlands. However, uncertainties remain in these emission inventories because many factors contributing to these processes are poorly quantified. To alleviate these uncertainties, a synergistic approach of applying air-borne measurements and chemical transport modeling (CTM) efforts to provide a method of quantifying local and regional GHG emissions will be performed during this study. Additionally, in order to further understand the temporal and spatial distributions of GHG fluxes in California and the impact these species have on regional climate, CTM simulations of daily variations and seasonality of total column CO2 and CH4 will be analyzed. To assess the magnitude and spatial variation of GHG emissions and to identify local “hot spots”, airborne measurements of CH4 and CO2 were made by the Alpha Jet Atmospheric eXperiment (AJAX) over the San Francisco Bay Area (SFBA) and San Joaquin Valley (SJV) in January and February 2013 during the Discover-AQ-CA study. High mixing ratios of GHGs were observed in-flight with a high degree of spatial variability. To provide an additional method to quantify GHG emissions, and analyze AJAX measurement data, the GEOS-Chem CTM is used to simulate SFBA/SJV GHG measurements. A nested-grid version of GEOS-Chem will be applied and utilizes varying emission inventories and model parameterizations to simulate GHG fluxes/emissions. The model considers CO2 fluxes from fossil fuel use, biomass/biofuel burning, terrestrial and oceanic biosphere exchanges, shipping and aviation, and production from the oxidation of carbon monoxide, CH4, and non-methane volatile organic carbons. The major sources of CH4 simulated in GEOS-Chem are domesticated animals, rice fields, natural gas leakage, natural gas venting/flaring (oil production), coal mining, wetlands, and biomass burning. Preliminary results from the comparison between available observations (e.g., AJAX and CALGEM CH4 emission maps) and GEOS-Chem results will be presented, along with a discussion of CO2 and CH4 source apportionment and the use of the GEOS-Chem-adjoint to perform inverse GHG modeling.

Johnson, Matthew S.↗

NASA NTRS2019

Inducing Bistability in Collapsible Tubular Masts Booms with Thin-Ply Composite Shells

Bistable rollable booms are favorable when a low strain energy requirement for the coiled state is imposed and have more controllable deployment when compared to monostable booms. An inextensional analytical model describing the bending deformation mechanics of Collapsible Tubular Mast (CTM) booms was used to determine how design variables induce bistability, or the existence of two strain energy wells in the rolled-up and unrolled states. The effects of varying lamina material, laminate layup, and shell arc geometries between different inner and outer shell segments on the second strain energy well and stiffness properties were determined for boom cross-sections formed by circular segments. The full design space for two-walled composite CTM booms was explored to evaluate the validity of the developed analytical model. Optimized CTM boom designs were experimentally characterized for comparisons against model results. The model under-predicted the stable coiled diameter of the co-cured two-walled booms by up to 8.9% and 23.4% for the individual thin shells wrapped alone.

Andrew J Lee↗