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Tools

We use models alongside observational datasets to study atmospheric composition and climate.

Chemistry-climate modeling using the CESM2 family of models

Image: https://www.cesm.ucar.edu/

We use many different configurations of the Community Earth System Model version 2 (Danabasoglu et al., 2020), a CMIP6-generation model, to examine how atmospheric chemistry influences and is influenced by climate. Different configurations allow us to isolate and explore key variables, including interactive tropospheric and stratospheric chemistry versus prescribed atmospheric composition, fully coupled atmospheric physics versus fixed meteorology, and dynamic ocean–sea-ice coupling versus prescribed sea surface temperatures and sea-ice fields. The following configurations are currently used in our group:

  • ​CESM2(WACCM6) is the most comprehensive configuration of CESM2, with tropospheric and stratospheric chemistry and a modal aerosol scheme fully coupled to ocean and sea ice models.  This configuration was used to generate a 13-member initial-condition ensemble over the period 1950-2014, adding to the three ensemble members conducted by NCAR for CMIP6. These simulations serve as a basis for multiple ongoing projects. [Qindan, Xinyuan, Steph]

  • WACCM6 (atmosphere-only climate model; Gettelman et al., 2019).  This configuration offers a computationally less expensive approach to the fully coupled climate model.  For example, we are prescribing sea surface temperatures and sea ice fields taken from the CESM2-WACCM6 historical ensemble to conduct a series of sensitivity simulations for attributing tropospheric ozone trends to specific sources.  [Xinyuan]

  • MUSICA Version 0 (spectral element dynamical core, variable resolution grid) is nudged to reanalysis meteorology for air quality applications (Schwantes et al., 2022).  We are currently using the standard configuration with 1 degree horizontal resolution globally with two-way nesting to 14km over the contiguous United States. [Tao-ma]

  • CESM2(CAM6) is the standard "out-of-the-box" CESM configuration (Danabasoglu et al., 2020), featuring the "low-top" CAM6 atmosphere with a simple online aerosol scheme driven by offline oxidants (generated by WACCM6), coupled to ocean and sea ice models. [Steph]

  • CAM-chem includes fully interactive tropospheric chemistry within the CAM6 atmosphere (Emmons et al., 2020).  CAM-Chem is used for simulations of global tropospheric composition. The standard (default) configuration is with the MOZART-T1 chemical mechanism, along with a volatility basis set (VBS) parameterization for the formation of secondary organic aerosols (SOA) (Tilmes et al., 2019). We are prescribing sea surface temperature and sea ice at present day to conduct model simulations to investigate the OH and methane lifetime responses to climate warming. [Qindan]

  • CESM-GC leverages the modularity of the CESM framework by integrating key components from GEOS-Chem (Lin et al., 2024). Specifically, CESM-GC incorporates HEMCO (The Harmonized Emissions Component), the GEOS-Chem chemistry mechanisms, and photolysis schemes like FAST-JX and Cloud-J. This integration enables comparisons between different model configurations, enhancing our ability to evaluate the impact of uncertain atmospheric processes. [Lucas]

  • AquaChem (Zhu et al., in review) is an idealized aquaplanet configuration of CESM2 (e.g., Medeiros et al., 2016; Medeiros, 2020) with full complexity chemistry and simplified dynamics. This reduced complexity chemistry-climate model enables a broader exploration of the sensitivity of atmospheric composition to emissions and climate warming. [Qindan, Isabella]

GEOS-Chem model

The GEOS-Chem chemistry-transport model is a global model of atmospheric chemistry driven by assimilated meteorology. It has many users around the world who collaborate to keep it updated with the latest discoveries in atmospheric chemistry. We use GEOS-Chem to examine trends in atmospheric composition, source attribution during regional pollution events, and how emissions and chemistry control atmospheric composition. For example, we can use laboratory experiments and GEOS-Chem simulations to investigate formaldehyde formed from isoprene oxidation [Ursula] and wildfire chemistry [Joe].

Emulators

We develop first-principles reduced-order models and statistical emulators to accelerate computationally intensive calculations and improve our understanding of climate and atmospheric chemistry phenomena. These phenomena are often observed and simulated in complex models but are difficult to interpret due to the simultaneous interaction of many processes. By simplifying complex phenomena into mechanistic representations, we can investigate the role of specific processes and uncover why certain phenomena occur both in the real atmosphere and in comprehensive models. [Paolo]

Svante High-Performance Computing Cluster

We use the Svante cluster at MIT, housed at the Massachusetts Green High Performance Computing Center.  At present, Svante includes 140 compute nodes (over 5000 total cores), linked via a low-latency HDR infiniband network. The majority of compute nodes include Intel Xeon Gold CPUs with DDR4 or DDR5 RAM, which facilitates running high-resolution model simulations in reasonable walltimes. Svante’s storage capacity is over 8 PB, housing a large collection of external datasets with sufficient space for model simulation output.

GFDL CM3/AM3 Chemistry-Climate Model

Work at LDEO/Columbia used the CMIP5-generation NOAA GFDL general circulation model that includes fully coupled tropospheric and stratosphere chemistry in a single mechanism and aerosol-cloud interactions, coupled to a dynamic vegetation land model (LM3), either coupled to ocean and sea-ice models (CM3) or forced with sea surface temperatures and sea ice distributions (AM3).   AM3 includes an option to nudge the meteorology to “real” winds, enabling us to interpret “snapshot” observations and to evaluate model processes directly with measurements at specific locations and times in the same model used to simulate changes in atmospheric composition and climate.

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