A new mesoscale convective system (MCS) database covering the contiguous United States east of the Rocky Mountains has been released for the years 2004 to 2016. The database details the life cycle evolution of individual MCS events along with a suite of MCS properties, such as precipitation, three-dimensional (3D) characteristics, and propagation speeds.
This long-term, high-resolution database is a principal investigator data product that can be used to understand relationships between atmospheric environments and MCS characteristics, as well as impacts of MCSs on hydroclimate and severe weather events. The database adds context to data from the Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) atmospheric observatory and can help users evaluate and improve earth system and numerical weather prediction models.
To produce the MCS database, researchers applied an updated version of the FLEXible object TRacKeR (FLEXTRKR) algorithm (Feng et al. 2018) to NASA Global MergedIR satellite infrared brightness temperature data and the GridRad mosaic 3D Next-Generation Radar (NEXRAD) data set. The algorithm is detailed in Feng et al. (2019).
The FLEXTRKR algorithm first identifies and tracks large cold cloud systems associated with deep convection using satellite infrared brightness temperature data. FLEXTRKR subsequently identifies MCSs using radar-defined convective features and precipitation features. Convective features are identified using the Storm Labeling in Three Dimensions classification (Starzec et al. 2017). Precipitation features are contiguous areas with a rain rate exceeding 1 mm h-1.
An MCS is defined as a large cold cloud system (area greater than 6×104 km2) containing: 1) a precipitation feature with a major axis longer than 100 kilometers; 2) a convective feature with radar reflectivity greater than 45 dBZ at any vertical level; and 3) both conditions 1) and 2) are met continuously for at least six hours.
The MCS database has 1-hour time resolution and 4-kilometer spatial resolution. The data sets are in netCDF formats.
Please refer to the README data documentation for more details on how to use the data sets.
Scientists can begin using the MCS database now. More information about the database can be found on the data source web page or in Feng et al. (2019).
For questions or to report data problems, please contact Zhe Feng.
Data can be referenced as doi:10.5439/1571643.
References: Feng Z, RA Houze Jr., LR Leung, F Song, JC Hardin, J Wang, WI Gustafson Jr., and CR Homeyer. 2019. “Spatiotemporal Characteristics and Large-Scale Environments of Mesoscale Convective Systems East of the Rocky Mountains.” Journal of Climate, 32(21), 7303-7328, https://doi.org/10.1175/JCLI-D-19-0137.1.
Feng Z, LR Leung, RA Houze Jr., S Hagos, J Hardin, Q Yang, B Han, and J Fan. 2018. “Structure and Evolution of Mesoscale Convective Systems: Sensitivity to Cloud Microphysics in Convection-Permitting Simulations Over the United States.” Journal of Advances in Modeling Earth Systems, 10(7), 1470-1494, https://doi.org/10.1029/2018MS001305.
Starzec Z, CR Homeyer, and GL Mullendore. 2017. “Storm Labeling in Three Dimensions (SL3D): A Volumetric Radar Echo and Dual-Polarization Updraft Classification Algorithm.” Monthly Weather Review, 145(3), 1127-1145, https://doi.org/10.1175/MWR-D-16-0089.1.# # #
ARM is a DOE Office of Science user facility operated by nine DOE national laboratories.