Test Cases
Benchmark Test Case Downloads
Benchmark input and output data to test the build of CMAQ version 5.4 are available from the CMAS Center Data Warehouse Google Drive and the Registry of Open Data on Amazon Web Services (AWS). The benchmark data set is a two day simulation for July 1-2, 2018 on a 100 column x 105 row x 35 layer 12-km resolution domain over the northeast U.S. Benchmark input includes all files needed to run base CMAQ, WRF-CMAQ, CMAQ-ISAM or CMAQ-DDM-3D. Similarly the output includes reference output for all four types of model simulations.
In addition, a full set of inputs for 2018 are provided for the 12US1 domain (299 column x 459 row x 35 layer, 12-km horizontal grid spacing) on AWS, including emissions compatible with both the CB6r5 and CRACMM chemical mechanisms. Note that the 12US1 inputs are netCDF-4/HDF5 compressed files to substantially reduce file sizes. Through testing at the EPA, we’ve noticed that certain simulations encounter model crashes from reading in large amounts of compressed netCDF data. A work around for those cases is uncompressing the data manually via nccopy 1 or m3cple (compiled with HDF5) before running the CMAQ simulation.
File type | File name (DOI or Download Link) | File Size |
---|---|---|
Two day input data |
Metadata, DOI, and download instructions (Dataverse Link) CMAQv5.4_2018_12NE3_Benchmark_2Day_Input.tar.gz (Google Drive Link | AWS link) |
10.3 Gb |
Two day output data | CMAQv5.4_2018_12NE3_Benchmark_2Day_Output.tar.gz (Google Drive Link | AWS link) | 13.9 Gb |
Annual 2018 input data |
Metadata, DOI, and links to data for CB6r5 case (Dataverse Link) Metadata, DOI, and links to data for CRACMM case (Dataverse Link) |
Additional Input Data
Use the following links to download additional input data depending on the needs of your CMAQ simulation.
The National Emissions Inventory (NEI) Modeling Platforms
The National Emissions Inventory (NEI) is a comprehensive and detailed estimate of air emissions of criteria pollutants, criteria precursors, and hazardous air pollutants from air emissions sources. The NEI is released every three years based primarily upon data provided by State, Local, and Tribal air agencies for sources in their jurisdictions and supplemented by data developed by the US EPA.
The NEI modeling platforms are the full set of emissions inventories, other data files, software tools, and scripts that process the emissions into the form needed for air quality modeling. Each emissions modeling platform supports air quality modeling of a historic year and one or more later years. Each platform relies on a version of the NEI for most of its data, although some adjustments are made, including augmenting with additional data and temporal and spatial tuning to support air quality modeling.
Fire Emissions
Fire emissions require fire location, burned areas, and detailed fuel load information. Examples of where to find these types of datasets are proved below. All of these information sources can be used to estimate fire emissions. An example of a tool that can be used to generate fire emissions is the US Forest Service BlueSky modeling framework. BlueSky modularly links a variety of independent models of fire information, fuel loading, fire consumption, fire emissions, and smoke dispersion. SmartFire Version 2 is one component of the BlueSky modeling framework used to reconcile fire information from multiple sources. Using these tools and estimating fire emissions can be quite complex so datasets of fire emissions have been created for the community. Examples of these datasets is the Fire Inventory from the National Center for Atmospheric Research or the Global Fire Emissions Database.
- Fire location:
- Burn area estimates:
- National Interagency Fire Center Open Data Site (formally available through the Geospatial Multi-Agency Coordination website)
- U.S. National Historical Fire Perimeters Data Basin Dataset
- Fuel loading estimates:
- Tool for generating fire emissions:
- Pre-generated fire emissions datasets:
Processing Spatial Data
Information on how to create consistent geospatial data for CMAQ inputs using the Spatial Allocator (SA) utility.