CURRENT RESEARCH PROJECTS

Last Updated: December 23, 2020

Our research focuses on better understanding the chemical composition of the atmosphere, its perturbation by human activity, and the implications for life on Earth. We use advanced models of atmospheric composition to interpret observations from satellites, aircraft, ground networks, and other platforms. We view our models as part of an integrated observing system to increase fundamental knowledge and address pressing environmental issues.


We have a large number of ongoing projects at any given time, addressing broad research themes:

Air quality | Chemistry | Climate & health | Methane | Model development | Machine learning & data science

AIR QUALITY (subgroup leaders:Ke Li, Shixian Zhai) CHEMISTRY (subgroup leaders: Kelvin Bates, Viral Shah) CLIMATE AND HEALTH (subgroup leader: Loretta Mickley) METHANE (subgroup leaders: Xiao Lu, Zhen Qu) MODEL DEVELOPMENT (subgroup leader: Sebastian Eastham) MACHINE LEARNING & DATA SCIENCE (subgroup leaders: Daniel Varon, Makoto Kelp, Drew Pendergrass)

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Project Descriptions


nigeria TROPOSPHERIC OXIDANTS

BACKGROUND:

Tropospheric oxidants (ozone and OH) are of central importance for global atmospheric chemistry. The hydroxyl radical (OH) is the main atmospheric oxidant responsible for removal of atmospheric gases yet we have little understanding of its long-term trends. Ozone is a major greenhouse gas in the middle/upper troposphere, a toxic gas at the surface, and the primary source of OH, but the factors controlling its global trend are poorly understood. Chemical production and loss of ozone and OH involve complex nonlinear mechanisms coupled to transport on all scales. Better understanding this chemistry holds the key to quantifying human influence.

OBJECTIVES:

  • Develop a new method for monitoring global OH;
  • Better understand nonlinearity in global ozone chemistry and its implications for ozone sources;
  • Better understand global ozone trends.

APPROACH:

  • Explore the potential to monitor tropospheric OH and its trend using satellite observations of atmospheric methane;
  • Develop a new conceptual model for the budget of tropospheric ozone;
  • Conduct decadal GEOS-Chem simulations to interpret observed ozone trends.

PEOPLE: Kelvin Bates, Elise Penn, Xiao Lu, Nadia Colombi

REFERENCES:

  • Bates, K.H., and D.J. Jacob, An expanded definition of the odd oxygen family for tropospheric ozone budgets: implications for ozone lifetime and stratospheric influence, Geophys. Res. Lett., 47, e2019GL084486, 2020. https://doi.org/10.1029/2019GL084486. [PDF]

  • Zhang, Y., D.J. Jacob, J.D. Maasakkers, M.P. Sulprizio, J. Sheng, R. Gautam, and J. Worden, Monitoring global OH concentrations using satellite observations of atmospheric methane , Atmos. Chem. Phys., 18, 15959-15973, 2018. [PDF]

SUPPORT: NASA ACMAP, NASA IDS, NSF Fellowship to Elise Penn

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nigeria TROPOSPHERIC HALOGEN CHEMISTRY

BACKGROUND:

Recent observations indicate high tropospheric concentrations of halogen radicals, leading to oxidant chains and catalytic cycles that have important implications for the global budgets of the main tropospheric oxidants (ozone and OH), the oxidation of mercury, and aerosol formation. Halogen chemistry has in general not been included in global models of tropospheric chemistry because the underlying processes are not well understood.

OBJECTIVES:

  • Develop a comprehensive understanding of stratospheric-tropospheric Cl-Br-I chemistry for implementation in global models;
  • Examine the general implications for tropospheric chemistry.

APPROACH:

  • Implement a comprehensive representation of halogen chemistry in the GEOS-Chem global model;
  • Evaluate it with observations for halogen radicals and their reservoirs;
  • Quantify the effects on tropospheric ozone, OH, and related species, and the consistency with atmospheric observations of these species.

PEOPLE: Xuan Wang (now at City U. of Hong Kong)

COLLABORATORS: Sebastian Eastham (MIT), Mat Evans and Tomas Sherwen (U. York), Becky Alexander (U. Washington)

REFERENCES:

  • Improving chemical mechanisms for regional/global models in support of US air quality management: application to the GEOS-Chem model , presented by Daniel Jacob at the Kick-off Meeting for the EPA STAR Chemical Mechanisms for Air Quality Modeling Program (remote), December 16, 2020. [PPT]

  • Wang, X., D.J. Jacob, X. Fu, T. Wang, M. Le Breton, M. Hallquist, Z. Liu, E.E. McDuffie, and H. Liao, Effects of anthropogenic chlorine on PM2.5 and ozone air quality in China , Environ. Sci. Technol., 54, 9908-9916, 2020. [PDF]

SUPPORT: EPA, JLAQC

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fires AIR QUALITY IN CHINA

BACKGROUND:

Air quality in China is among the worst in the world and the Chinese government has declared a "war on air pollution" involving massive controls on emissions. Newly installed surface air quality networks together with satellite observations allow us to track the evolution of Chinese air quality and the responses to emission controls, to better understand the factors controlling particulate matter and ozone pollution, and to make recommendations for future emission control strategies.

OBJECTIVES:

  • Understand the effects of anthropogenic emissions, chemical processes, and other factors in determining ozone and PM air quality and its trends in China;
  • Make recommendations for improving air quality.

APPROACH:

  • Analyze and model data from Chinese air quality networks;
  • Use machine learning to relate satellite observations to air quality;
  • Conduct model simulations to project the responses to emission controls.

PEOPLE: Ke Li, Jonathan Moch, Shixian Zhai, Drew Pendergrass

REFERENCES:

  • Air quality trends in China: a chemical perspective , seminar by Daniel Jacob at U. Montana, November 2, 2020. [PPT]

  • Li, K., D.J. Jacob, L. Shen, X. Lu, I. De Smedt, and H. Liao, 2013–2019 increases of surface ozone pollution in China: anthropogenic and meteorological influences, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-298, in review, 2020. [PDF]

  • Wang, J., J. Li, J. Ye, J. Zhao, Y. Wu, J. Hu, D. Liu, D. Nie, F. Shen, X. Huang, D. Huang, D. Ji, X. Sun, W. Xu, J. Guo, S. Song, Y. Qin, P. Liu, J.R. Turner, H.C. Lee, S. Hwang, H. Liao, S.T. Martin, Q. Zhang, M. Chen, Y. Sun, X. Ge, and D.J. Jacob, Fast sulfate formation from oxidation of SO2 by NO2 and HONO observed in Beijing haze, Nature Comm., 11, 2844, 2020. [PDF]

  • Zhai, S., D.J. Jacob, X. Wang, L. Shen, K. Li, Y. Zhang, K. Gui, T. Zhao, and H. Liao, Fine particulate matter (PM2.5) trends in China, 2013-2018: separating contributions from anthropogenic emissions and meteorology, Atmos. Chem. Phys., 19, 11031-11041, 2019. [PDF]

SUPPORT: JLAQC, Samsung

COLLABORATORS: Hong Liao (NUIST), Junfeng Wang (Harvard)

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fires AIR QUALITY IN KOREA

BACKGROUND:

Both PM and ozone air quality in South Korea are very bad. PM is not improving and ozone is getting worse. This poor air quality and its trends are not well understood, including the relative contributions from domestic emissions and transboundary pollution transport. Geostationary observations of aerosol optical depth (AOD) and new geostationary chemical observations from the GEMS satellite instrument launched in 2020 should enable major advances in our understanding and help advise Korea air quality policy.

OBJECTIVES:

  • Understand the factors controlling PM and ozone pollution in Korea through analysis of surface and aircraft observations;
  • Interpret satellite observations of AOD and use them to infer surface PM concentrations.

APPROACH:

  • Use the GEOS-Chem model and WRF-GC to interpret observations from the AirKorea surface measurement network and from the NASA KORUS-AQ aircraft campaign;
  • Analyze and model geostationary AOD observations;
  • Apply machine learning methods to related observed AODs to surface PM air quality;
  • Integrate information from satellites, aircraft, sondes, and surface network data to understand the factors contolling ozone over Korea.

PEOPLE: Shixian Zhai, Nadia Colombi, Jared Brewer, Drew Pendergrass, Haipeng Lin, Ellie Beaudry

REFERENCES:

  • Improved understanding of PM2.5 in Korea and China , presented by Daniel Jacob at the Samsung PM2.5 Strategic Research Program review (remote), November 11, 2020. [PPT]

  • Towards an improved understanding of factors affecting ozone pollution in East Asia , presented by Nadia Colombi at the EPS G1 Symposium, September 4, 2020. [PPT]

SUPPORT: Samsung

COLLABORATORS: Rokjin Park (SNU), Jhoon Kim (Yonsei U.)

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fires BACKGROUND CONTRIBUTIONS TO AIR QUALITY

BACKGROUND:

As the public health and environmental damage from air pollution become more apparent and air quality standards tighten, there is increasing interest in the role of background contributions to air pollution. This background may include natural sources but also pollution transported on intercontinental scales. It can be sufficiently high to make the meeting of air quality standards problematic. Furthermore, this background complicates the interpretation of satellite observations to provide information on local air quality.

OBJECTIVES:

  • Better understand the sources and chemical processes contribution to the background;
  • Quantify the background contributions to pollutant concentrations and their trends;
  • Resolve the background contributions to satellite measurements of air quality.

APPROACH:

  • Determine the concentrations and sources of free tropospheric NO2 for improved retrievals of NO2 from space and improved inference of NOx emissions;
  • Determine the contribution of the free troposphere to the high concentrations of surface ozone observed in East Asia;
  • Assess background contributions to different criteria pollutants and mercury in the US.

PEOPLE: Viral Shah, Nadia Colombi, Zhen Qu, Elise Penn

REFERENCES:

  • Shen, L., D.J. Jacob, X. Liu, G. Huang, K. Li, and H. Liao, An evaluation of the ability of the Ozone Monitoring Instrument (OMI) to observe boundary layer ozone pollution across China: application to 2005-2017 ozone trends, Atmos. Chem. Phys., 19, 6551-6560, 2019. [PDF]

  • Silvern, R.F., D.J. Jacob, L.J. Mickley, M.P. Sulprizio, K.R. Travis, E.A. Marais, R.C. Cohen, J.L. Laughner, S. Choi, J. Joiner, and L.N. Lamsal, Using satellite observations of tropospheric NO2 columns to infer long-term trends in US NOx emissions: the importance of accounting for the free tropospheric NO2 background, Atmos. Chem. Phys., 19, 8863–8878, https://doi.org/10.5194/acp-19-8863-2019, 2019. [PDF]

SUPPORT: NASA Aura, EPA, Samsung

COLLABORATORS: Joanna Joiner, Nicholas Krotkov, Lol Lamsal, Songyeon Choi (NASA/GSFC). Eloise Marais (University College London), Folkert Boersma (KNMI)

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PRB ORGANIC CHEMISTRY

BACKGROUND:

The atmospheric chemistry of volatile organic compounds (VOCs) has major implications for oxidant concentrations and for formation of organic aerosol. VOCs are emitted from a range of biogenic and anthropogenic sources. They undergo various oxidation cascades in the atmosphere, producing increasingly substituted and cleaved compounds, terminating eventually in the formation of CO2, the formation of secondary organic aerosol (SOA) or the removal by deposition. Most of the species and reactions involved have never been measured and must be inferred indirectly. Multigenerational products of VOC oxidation may be responsible for an "organic soup" in the remote troposphere that is suggested by observations but not understood at all. Representing organic chemistry in models is a major challenge.

OBJECTIVES:

  • Develop state-of-science chemical mechanisms for atmospheric organics that can be practically implemented in models;
  • Determine the implications of these mechanisms for the effects of different VOCs on ozone, OH, aerosols;
  • Improve understanding of the budgets of oxygenated organics.

APPROACH:

  • Develop oxidation mechanisms for different VOCs (isoprene, terpenes, aromatics, ethylene), test them in box models and in GEOS-Chem;
  • Use GEOS-Chem to study the resulting impacts of VOC emissions for air quality and global atmospheric chemistry;
  • Interpret observations of oxygenated organics in the remote troposphere from the ATom aircraft campaign.

PEOPLE: Kelvin Bates, Ke Li, Jared Brewer, Ellie Beaudry

REFERENCES:

  • Improving chemical mechanisms for regional/global models in support of US air quality management: application to the GEOS-Chem model , presented by Daniel Jacob at the Kick-off Meeting for the EPA STAR Chemical Mechanisms for Air Quality Modeling Program (remote), December 16, 2020. [PPT]

  • Bates, K.H., Jacob, D.J., Wang, S., Hornbrook, R.S., Apel, E.C., Kim, M.J., Millet, D.B., Wells, K.C., Chen, X., Brewer, J.F., Ray, E.A., Diskin, G.S., Commane, R., Daube, B.C. and Wofsy, S.C., The global budget of atmospheric methanol: new constraints on secondary, oceanic, and terrestrial source, submitted to J. Geophys. Res. – Atmos., 2021. [PDF]

SUPPORT: EPA, NASA ACMAP, JLAQC

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PRB MERCURY CHEMISTRY

BACKGROUND:

Mercury deposition to ecosystems results in accumulation of toxic forms of mercury up the food chain. Mercury is emitted to the atmosphere mostly as Hg(0), and is oxidized in the atmosphere to Hg(II) which can be rapidly deposited but also reduced back to Hg(0). Understanding atmospheric Hg(0)/Hg(II) redox chemistry is crucial to predicting the patterns of mercury deposition and the subsequent biogeochemical cycling.

OBJECTIVES:

  • Better understand the atmospheric redox chemistry of mercury;
  • Determine the implications for mercury deposition to ecosystems and subsequent biogeochemical cycling.

APPROACH:

  • Simulate detailed mercury chemistry in the GEOS-Chem atmospheric model coupled to ocean and terrestrial mercury reservoirs;
  • Use this model to interpret global atmospheric observations of mercury.

PEOPLE: Viral Shah

COLLABORATORS: Elsie Sunderland and Colin Thackray (Harvard), Alfonso Saiz-Lopez (CSIC), Ted Dibble (Syracuse)

REFERENCES:

  • Improving chemical mechanisms for regional/global models in support of US air quality management: application to the GEOS-Chem model , presented by Daniel Jacob at the Kick-off Meeting for the EPA STAR Chemical Mechanisms for Air Quality Modeling Program (remote), December 16, 2020. [PPT]

SUPPORT: EPA

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CH4 METHANE EMISSION INVENTORIES

BACKGROUND:

Methane is the second most important anthropogenic greenhouse gas after CO2. It is particularly important for near-term (~20 years) climate change. Methane is emitted by a wide range of processes including oil/gas systems, livestock, landfills, wastewater, rice cultivation, and wetlands. The magnitudes of these sources, their spatial distributions, and their temporal trends are poorly understood. Improving the "bottom-up" inventories that relate emissions to activity levels is imperative for climate policy. This can be done by using state-of-science activity and emission factor data, evaluating the resulting inventories with atmospheric observations through "top-down"inverse analyses, and using the results of these inverse analyses to further improve the emission inventories. This partnership between bottom-up and top-down approaches is key to improving understanding of methane emissions in a way that can enable policy action.

OBJECTIVES:

  • Develop policy-relevant, high-resolution global methane emission inventories from fuel exploitation;
  • Develop global methane emission inventories from aquatic systems including hydroelectric and other reservoirs, and coastal environments including estuaries;
  • Construct gridded policy-relevant anthropogenic emission inventories for the US, Canada, and Mexico to be evaluated and improved with atmospheric observations.

APPROACH:

  • Estimate emissions and their distributions using best available data for activities and emission factors;
  • Use ancillary data as from satellites to inform the distribution of emissions;
  • Work with climate agencies in the US, Canada, and Mexico to construct gridded versions of their national inventories.

PEOPLE:   Tia Scarpelli, Melissa Sulprizio, Shayna Grossman, Candice Chen

COLLABORATORS: Bram Maasakkers (SRON), Kyle Delwiche (Stanford), Colin Thackray and Elsie Sunderland (Harvard)

REFERENCES:

  • Scarpelli, T.R., D.J. Jacob, C.A. Octaviano Villasana, I.F. Ramirez Hernandez, P.R. Cardenas Moreno, E.A. Cortes Alfaro, M.A. Garcia Garcia, and D. Zavala-Araiza, A gridded inventory of anthropogenic methane emissions from Mexico based on Mexico's National Inventory of Greenhouse Gases and Compounds, Environ. Res. Lett., 15, 105015, 2020. [PDF]

  • Scarpelli, T.R., D.J. Jacob, J.D. Maasakkers, M.P. Sulprizio, J.-X. Sheng, K. Rose, L. Romeo, J.R. Worden, and G. Janssens-Maenhout, A global gridded (0.1o x 0.1o) inventory of methane emissions from fuel exploitation based on national reports to the United Nations Framework Convention on Climate Change, Earth System Sci. Data, 12, 563-575, 2020. [PDF]

SUPPORT: NASA CMS, NASA IDS, NASA AIST, NDSEG fellowship to Tia Scarpelli

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CH4 INVERSE ANALYSES OF ATMOSPHERIC METHANE OBSERVATIONS

BACKGROUND:

Atmospheric observations of methane from satellites and suborbital platforms (surface sites, ships, aircraft)can test emission inventories and tell us why methane is increasing. This involves statistical inversion of chemical transport models that relate emissions to concentrations. A rapidly growing fleet of satellites is providing global continuous observations of methane that can deliver powerful constraints on methane emissions worldwide. Highly accurate suborbital observations provide an important complement to the satellite data.

OBJECTIVES:

  • Quantify and attribute regional methane emissions and trends using satellite and suborbital observations.
  • Detemine the sources responsible for the current rise in methane.
  • Detemine whether trends in the OH radical (the main methane sink) could be implicated in driving methane trends.

APPROACH:

  • Use GOSAT satellite observations for 2009-present to constrain global methane emissions, their trends, and OH concentrations (the main methane sink);
  • Use TROPOMI satellite observations for 2018-present to infer current methane emissions globally and from specific regions with high resolution;
  • Develop new inverse methods to exploit the high density of observations from TROPOMI;
  • Determine the complementary information from satellite observations in the thermal IR (AIRS, CrIS) and from surface observations (NOAA network);
  • Develop a cloud-hosted unified methane inversion (UMI) workflow for inferring methane emissions from TROPOMI data.

PEOPLE: Xiao Lu, Bram Maasakkers, Melissa Sulprizio, Yuzhong Zhang, Hannah Nesser, Elise Penn, Lu Shen, Zhen Qu, Jiawei Zhuang, Daniel Varon, Margaux Winter

COLLABORATORS: Anthony Bloom (JPL), John Worden (JPL), Riley Duren (U. Arizona), Arlyn Andrews (NOAA), Dylan Jones (U. Toronto), Ritesh Gautam (EDF), Cynthia Randles (Exxon-Mobil)

REFERENCES:

  • Global distribution of methane emissions: an inverse analysis of 2019 observations from TROPOMI , presented by Zhen Qu at the 1st GEOS-Chem Europe meeting (GCE1) (remote), September 1, 2020. [PDF]

  • Using satellite observations to quantify methane emissions from the global scale down to point sources , presented by Daniel Jacob at the Exxon-Mobile Methane Research External Speaker Series(remote), July 8, 2020. [PPT]

  • Shen, L., D. Zavala-Araiza, R. Gautam, M. Omara, T. Scarpelli, J. Sheng, M.P. Sulprizio, J. Zhuang, Y. Zhang, Z. Qu, X. Lu, S. Hamburg, and D.J. Jacob, Unravelling a large methane emission discrepancy in Mexico using satellite observations , submitted to Remote Sensing of the Environment, 2021. [PDF]

  • Nesser, H., D.J. Jacob, J.D. Maasakkers, T.R. Scarpelli, M.P. Sulprizio, Y. Zhang, and C.H. Rycroft, Reduced-cost construction of Jacobian matrices for high-resolution inversions of satellite observations of atmospheric composition , Atm. Meas. Tech. Discuss,[preprint] https://doi.org/10.5194/amt-2020-451, in review, 2021. [PDF]

  • Zhang, Y., D.J. Jacob, X. Lu, J.D. Maasakkers, T.R. Scarpelli, J.-X. Sheng, L. Shen, Z. Qu, M.P. Sulprizio, J. Chang, A.A. Bloom, S. Ma, J. Worden, R.J. Parker, and H. Boesch, Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations, Atmos. Chem. Phys. Discuss., in review, 2021. [PDF]

  • Maasakkers, J.D., D.J. Jacob, M.P. Sulprizio, T.R. Scarpelli, H. Nesser, J. Sheng, Y. Zhang, X. Lu, A.A. Bloom, K.W. Bowman, J.R. Worden, and R.J. Parker, 2010-2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT satellite observations of atmospheric methane , Atmos. Chem. Phys. Discuss., in review, 2021. [PDF]

  • Lu, X., D.J. Jacob, Y. Zhang, J.D. Maasakkers, M.P. Sulprizio, L. Shen, Z. Qu, T.R. Scarpelli, H. Nesser, R.M. Yantosca, J. Sheng, A. Andrews, R.J. Parker, H. Boesch, A.A. Bloom, S. Ma, Global methane budget and trend, 2010-2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH4 ObsPack) and satellite (GOSAT) observations, Atmos. Chem. Phys. Discuss, in review, 2021. [PDF]

SUPPORT: NASA CMS, NASA IDS, NASA AIST, NOAA, Exxon-Mobil, NSF fellowship to Elise Penn

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CH4 DETECTING METHANE POINT SOURCES FROM SPACE

BACKGROUND:

Anthropogenic emissions of methane come from a very large number of relatively small point sources including coal mine vents, oil/gas production and processing facilities, stockyards, landfills, etc. These sources have highly variable emissions, and can spike under abnormal conditions. Satellites provide a unique vantage point for global continuous monitoring of point sources. Several new instruments with high pixel resolution hold particular promise.

OBJECTIVES:

  • Develop retrieval methods for mapping atmospheric methane plumes from fine-scale satellite data;
  • Infer point source emissions from the plume observations;
  • Use the new generation of hyperspectral land surface imagers to detect methane point sources.

APPROACH:

  • Conduct large-eddy simulations of point sources to test different algorithms for retrieving emission rates from plume observations;
  • Use GHGSat satellite observations to detect and quantify point sources, alone and with TROPOMI support;
  • Determine the ability of imaging spectrometers (PRISMA, Sentinel-2) to detect methane plumes and quantify point sources;
  • Use machine-learning methods to enable methane plume detection over variable surface environments.

PEOPLE: Daniel Varon, Jack Bruno

COLLABORATORS: Jason McKeever, Dylan Jervis, David Gains, and Stephane Germain (GHGSat, Inc.), Riley Duren (U. Arizona), Dan Cusworth (JPL)

REFERENCES:

  • Identifying methane point sources in high-resolution satellite imagery using neural networks , presented by Jack Bruno at the EPS G1 Symposium, September 4, 2020. [PPT]

  • Varon, D.J., D.J. Jacob, D. Jervis, and J. McKeever, Quantifying time-averaged methane emissions from individual coal mine vents with GHGSat-D satellite observations, submitted to Environ. Sci. Technol., 2020. [PDF]

  • Varon, D.J., D. Jervis, J. McKeever, I. Spence, D. Gains, and D.J. Jacob, High-frequency monitoring of anomalous methane point sources with multispectral Sentinel-2 satellite observations, Atmos. Meas. Tech. Discuss., [preprint], https://doi.org/10.5194/amt-2020-477, in review, 2021. [PDF]

  • Varon, D.J., J. McKeever, D. Jervis, J.D. Maasakkers, S. Pandey, S. Houweling, I. Aben, T.R. Scarpelli, and D.J. Jacob, Satellite discovery of anomalously large methane point sources from oil/gas production, Geophys. Res. Lett., 46, https://doi.org/10.1029/ 2019GL083798, 2019.[PDF]

SUPPORT: GHGSat, Inc., NASA CMS

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ESMF GEOS-CHEM AS CHEMICAL MODULE FOR WEATHER/CLIMATE MODELS AND DATA ASSIMILATION

BACKGROUND:

Weather and climate models generally do not include detailed atmospheric chemistry because of the perceived complexity and computational cost. Yet atmospheric chemistry is key to climate forcing and feedbacks, air quality forecasting, and chemical data assimilation. The GEOS-Chem "off-line" chemical transport model developed and used by a large atmospheric chemistry community worldwide can be used as an "on-line" stand-alone module to handle chemistry in weather and climate models. This provides a state-of-science chemistry capability to these models that is referenceable, easily maintained, and has large community backing. GEOS-Chem includes a powerful emissions modeling component, HEMCO, that can be used to serve emissions in climate and weather models independently of the chemistry.

OBJECTIVES:

  • Implement GEOS-Chem as a chemical module in a wide range of weather and climate models, using exactly the same scientific code base as in the off-line GEOS-Chem chemical transport model;
  • Exploit this capability in the NASA GEOS climate model for global composition forecasting, aerosol-weather intractions, and data assimilation;
  • Exploit this capability in the NCAR CESM model for study of chemistry-climate-ecosystems interactions.

APPROACH:

  • Contribute to development of the GEOS composition forecasts (GEOS-CF) powered by GEOS-Chem;
  • Apply GEOS-Chem within the GEOS climate model to study feedbacks of air quality on weather;
  • Develop the GEOS-Chem interface with CESM, and compare GEOS-Chem and CAM-Chem atmospheric chemistry simulations within the same CESM framework;
  • Develop HEMCO as a stand-alone tool to serve emissions in the CESM and other climate models;
  • Implement GEOS-Chem in the next-generation NCAR CESM (SIMA), emphasizing modularity in architecture.

PEOPLE:   Lizzie Lundgren, Jonathan Moch, Haipeng Lin, Drew Pendergrass

COLLABORATORS: Seb Eastham and Thibaud Fritz (MIT), Steven Pawson (NASA/GSFC), Christoph Keller (NASA/GSFC), Louisa Emmons (NCAR)

REFERENCES:

  • Unifying atmospheric chemistry modeling using data: Development of the Harmonized Emissions Component 3.0 , presented by Haipeng Lin at the EPS G1 Symposium, September 4, 2020. [PDF]

  • Aerosol-radiation interactions in China in winter using a coupled chemistry-climate model , presented by Jonathan Moch at the 1st GEOS-Chem Europe meeting (GCE1) (remote), September 2, 2020. [PDF]

  • GEOS-Chem atmospheric chemistry model: current capabilities, future developments, and partnership with GMAO , Seminar by Daniel Jacob at the NASA Global Modeling and Assimilation Office, Greenbelt, Maryland, September 17, 2019. [PPT (no movies)]

SUPPORT: NSF, NASA MAP

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Scale GEOS-CHEM ON THE CLOUD

BACKGROUND:

Cloud computing can allow GEOS-Chem users worldwide to run the model with no local hardware or systems support, and no installation or compilation of the code. Users can instead access the standard configuration of the model through the cloud and execute it for their application. They can also download the model and its environment from the cloud, ensuring compatibility with their local system. This has many advantages in terms of computing cost, model access, user support, reproducibility of results, and traceability of the standard model.

OBJECTIVES:

  • Develop capability to run GEOS-Chem and host its input databases on the cloud.

APPROACH:

  • Work with Amazon Web Services (AWS) and GEOS-Chem users to develop a successful business model for costing cloud usage;
  • Extend the cloud capability to the multi-node GCHP environment to enable massively parallel simulations;
  • Extend the cloud capability to GEOS-Chem coupled with WRF (WRF-GC).

PEOPLE: Will Downs, Jiawei Zhuang, Judit Flo-Gaya, Haipeng Lin

COLLABORATORS: Amazon Web Services, Tzung-May Fu (SUSTEC), Hong Liao (NUIST), Randall Martin (Washington U.)

REFERENCES:

  • Zhuang, J., D.J. Jacob, H. Lin, E.W. Lundgren, R.M. Yantosca, J. Flo Gaya, M.P. Sulprizio, S.D. Eastham, and K. Jorissen, Enabling high-performance cloud computing for Earth science modeling on over a thousand cores: application to the GEOS-Chem atmospheric chemistry model , JAMES, 12, e2020MS002064, 2020. [PDF]

  • Zhuang, J., D.J. Jacob, J. Flo-Gaya, R.M. Yantosca, E.W. Lundgren, M.P. Sulprizio, and S.D. Eastham, Enabling immediate access to Earth science models through cloud computing: application to the GEOS-Chem model, Bull. Amer. Met. Soc., https://doi.org/10.1175/BAMS-D-18-0243.1, 2019. [PDF]

SUPPORT: NASA ACMAP, NASA AIST, NASA fellowship to Jiawei Zhuang

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Scale ADAPTIVE METHODS AND MACHINE LEARNING FOR CHEMICAL SOLVERS

BACKGROUND:

Chemical mechanisms for atmospheric chemistry include hundreds of species interacting by kinetic equations on time scales ranging from less than a second to many years. Integration of these equations with numerical solvers is extremely expensive. This limits the level of chemical detail that can be afforded in atmospheric chemistry models, the spatial resolution of these models, and the inclusion of atmospheric chemistry in Earth System Models.

OBJECTIVE:

  • Speed up the chemical solvers used in global atmospheric chemistry models.

APPROACH:

  • Develop and adaptive method to reduce the mechanism locally while maintaining accuracy;
  • Use machine-learning algorithms to reduce computation costs by orders of magnitude.

PEOPLE: Lu Shen, Makoto Kelp

COLLABORATORS: Christoph Keller (NASA/GSFC), Nathan Kutz (U. Washington)

REFERENCES:

  • Shen, L., D.J. Jacob, M. Santillana, K. Bates, J. Zhuang, and W. Chen, A machine learning-guided adaptive algorithm to reduce the computational cost of atmospheric chemistry in Earth System models: application to GEOS-Chem version 12.0.0 and v12.9.1, submitted to Geophys. Model Dev., 2021. [PDF]

  • Kelp, M.M., D.J. Jacob, J.N. Kutz, J.D. Marshall, and C.W. Tessum, Toward stable, general machine-learned models of the atmospheric chemical system, J. Geophys. Res. – Atmos., 125, https://doi.org/10.1029/2020JD032759, 2020. [PDF]

SUPPORT: NASA MAP, EPA

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