NACC-Cloud couples National Weather Model GFSv16 data to a state-of-the-science CMAQ model for regional air quality modeling applications. NACC Cloud offers streamlined access to the near-real-time GFS forecasts NACC processed to generate the model-ready, meteorological input for any U.S. EPA Community Multiscale Air Quality (CMAQ ) domain and air quality application worldwide.
Background & Motivation for NACC-Cloud
Drs. Patrick Campbell, Rick Jiang, Zachary Moon, Sonny Zinn, and Youhua Tang (ARL-ASMD) co-authored a paper on “NOAA’s Global Forecast System Data in the Cloud for Community Air Quality Modeling”, which was published as an open-access article in the journal Atmosphere on July 4, 2023. The development and use of the NOAA-EPA Atmosphere-Chemistry Coupler (NACC)-Cloud Version 1 in this work are critical to provide the scientific community streamlined access to NOAA’s operational GFSv16 data and user-defined processing and download of model-ready, meteorological input for any regional Community Multiscale Air Quality (CMAQ) model domain worldwide. The NACC-Cloud system was implemented on the Amazon® Web Services High-Performance Computing platform, and results from this work show that the NACC-Cloud system is immediately beneficial to the air quality modeling community worldwide.
In February 2021, NOAA’s Environmental Monitoring Center (EMC) upgraded GFS model from v15.3 to v16, which included a number of upgrades such as the major switch to a FV3-based dynamical core (Figure 2) (Yang et al., 2020). Ultimately, these upgrades and availability of operational global meteorological data were the impetus in NOAA-ARL’s development of a new meteorological processor to couple GFSv16 to a state-of-the-science CMAQ model for regional air quality modeling applications at the NOAA National Weather Service. This was achieved via the development of the NOAA-EPA Atmosphere Chemistry Coupler (NACC) version 1 (NACC, i.e., “knack”, meaning an acquired skill), which is adapted from the US EPA’s Meteorology-Chemistry Interface Processor (MCIP) version 5 (Otte and Pleim, 2010). The NACC and CMAQ coupling (hereafter referred to as NACC-CMAQ) involves a number of structural and scientific advancements (Campbell et al., 2022), where NACC delivers the capability to couple the operational GFSv16 meteorological forecasts to CMAQ for air quality modeling applications in the scientific research community
NACC defines the computational domain for CMAQ, subsequently extracts meteorological model output and interpolates both horizontally and vertically on the computational domain that is prescribed, and processes all required meteorological fields for CMAQ. Meteorological fields such as atmospheric temperature, pressure, humidity, and winds are acquired directly from the meteorological model (i.e., “passed through”), while NACC also uses the available meteorological fields to compute additional fields that are required by the CMAQ but are not part of the meteorological model’s output stream (e.g., the Jacobian used for model coordinate transformations). The NACC outputs both static and dynamic files in I/O API format that contain geospatial and meteorological information used by CMAQ (Figure 1).
Updates to NACCv2 (https://github.com/noaa-oar-arl/NACC/releases/tag/v2.1.0, last access: 25 January 2023) also allow for processing meteorological LCC grid projections from NOAA’s Unified Forecast System (UFS), Limited Area Model (LAM), Short-Range Weather App model (https://ufs-srweather-app.readthedocs.io/en/develop/#, last access: 25 January 2023) for model-ready inputs to CMAQv5. In other words, the interpolation-based NACC can use various meteorological outputs to drive the CMAQ model, even if they are on different grids. A recent comparison of the use of NACC-CMAQ vs. WRF-CMAQ showed that using global GFSv16 meteorology with NACC to directly drive CMAQ via interpolation is feasible and yields reasonable chemical predictions compared to the commonly used WRF approach (Tang et al., 2022).
However, the global 3D, gridded GFSv16 data sets are very large (~ 10s of TBs/month), however, and thus it is very cumbersome to use basic transfer and processing tools for usage in the scientific modeling community. Thus, the use of the cloud in this work is critical to provide the scientific community streamlined access to the near-real-time GFS forecast output, and to facilitate user-defined NACC processing of GFS data to generate the model-ready, meteorological input for any CMAQ domain and air quality application worldwide (i.e., “NACC-Cloud”). Cloud computing and storage platforms are desirable as they are highly-customizable, on-demand, and much more scalable than traditional local servers. Such a cloud interface for GFS-driven CMAQ applications is not currently available, and would be very advantageous to the air quality scientific community and beyond (Figure 2).
The immediate users of NACC-Cloud are scientific researchers that desire to use NOAA’s operational GFS meteorological forecasts to drive regional CMAQ applications anywhere in the world. The typical use of a separate, regional weather model simulation is data and labor intensive, subject to physical inconsistencies from different lateral boundary and initial conditions when downscaling from global to regional scales, and is less scientifically rigorous than directly using NOAA’s operational GFS to drive air quality applications. NACC-Cloud will also allow for rapid applications of recent, near-real-time weather-driven air quality events (e.g., the Saharan “Godzilla” dust storm in June 2020; historic western U.S. “August Complex Fire” in August-September 2020) that can be adequately simulated using the full-chemistry CMAQ model.
The NACC-Cloud system (https://nacc.arl.noaa.gov/nacc/) has been implemented on the AWS HPC platform, and results show that the NACC-Cloud system is feasible, worthwhile, relatively affordable and scalable, and that the geospatial and meteorological outputs as I/O API format can be readily downloaded and used for any user-defined regional CMAQv5 application worldwide. Furthermore, the input global GFSv16 NetCDF files are now also publicly available on the NACC-Cloud AWS S3 Glacier IR location.
For More Information:
Campbell, P. C., Tang, Y., Lee, P., Baker, B., Tong, D., Saylor, R., Stein, A., Huang, J., Huang, H.-C., Strobach, E., McQueen, J., Pan, L., Stajner, I., Sims, J., Tirado-Delgado, J., Jung, Y., Yang, F., Spero, T. L., and Gilliam, R. C.: Development and evaluation of an advanced National Air Quality Forecasting Capability using the NOAA Global Forecast System version 16, Geosci. Model Dev., 15, 3281–3313, https://doi.org/10.5194/gmd-15-3281-2022, 2022.
Campbell, P.C.; Jiang, W.; Moon, Z.; Zinn, S.; Tang, Y. NOAA’s Global Forecast System Data in the Cloud for Community Air Quality Modeling. Atmosphere 2023, 14, 1110. https://doi.org/10.3390/atmos14071110
GitHub Link: https://nacc.arl.noaa.gov/nacc/