Aqua AMSR-E, MODIS, MESH, and MERRA-2 matched dataset
Bang, Sarah; Itterly, Kyle; Scarino, Benjamin; Bedka, Kristopher; Cecil, Daniel
- Publisher
- Zenodo
- Language
- en
Abstract
Potentially severe storm cases over CONUS are identified where the contiguous MESH95 local maxima exceeds 10 mm, spaced by at least 28 km2, based on GridRad suite version 4.2 (Homeyer and Bowman 2021). Matched overpasses with Aqua are determined by the Langley Automated Sensor Inter-Calibration System (LASICS), enabling collocation of MESH cells, AMSR-E, and MODIS data within ±15 minutes (Gopalan et al. 2021). For each MESH cell observed, passive-microwave polarization corrected temperature (PCT)-defined features (PCTFs) are defined using a thresholding boundary of 200 K in the 89-GHz PCT. Using a 200 K 89-GHz PCT threshold isolates deeper convection, which is our focus of study (Mohr and Zipser 1996; Mohr et al. 1999; Cecil 2009). Summary characteristics (10-89 GHz PCT, areas, maxima and minima) are saved for each PCTF. From 2002 to 2011, we identified 45,157 MESH cells that were likely observed by Aqua. 12,062 of these are uniquely matched to an AMSR-E PCTF, using a +/-15 minute matching window and selecting the nearest MESH centroid within 35 km radius from the minimum 37-GHz PCT pixel. Besides the PCTF characteristics, MODIS cloud-top parameters are extracted from the most extreme MODIS IR Tb – MERRA-2 tropopause temperature (IRMT) pixel within a 27-km square centered on each MESH cell centroid after parallax correction. For areal IR-derived metrics (e.g., frequency of prominent anvil pixels and area of cold cloud with IR Tb pixels below 225 K), the 27-km square is centered on the most extreme IRMT pixel that is assigned to each MESH cell. Lastly, following the method of Murillo et al. (2021), Fisher’s linear discriminant analysis (LDA; Wilks 2019) is applied to each MESH cell using MERRA-2 total precipitable water (TPW) and 0-6 km wind shear to flag probable MESH false alarms, which tend to occur in high TPW and low shear environments (Murillo et al. 2021). These steps result in 2,845 storms satisfying the MESH, PCTF, and OT criteria.
Full text
MODIS IR-derived cloud-top parameters, AMSR-E passive-microwave parameters, MERRA-2 convective parameters, and MESH cell characteristics stored for each PF. Parameter Description Units MODIS IR-derived parameters OT probability Overshooting top probability % Embedded cold spot – anvil brightness temperature difference Brightness temperature diff between coldest pixel and mean anvil background K OT area Area of OT Probability ≥ 50% within 27 km2 km2 Embedded cold spot area Area of pixels for each ECS region km2 IR – tropopause temperature difference MODIS IR Tb – MERRA-2 tropopause temperature K Tropopause height for GOES OT detection Blended MERRA-2 lapse rate tropopause and equivalent potential vorticity tropopause km Cloud-top height km Anvil mean height Average cloud-top height of pixels with IR anvil rating ≥ 20 within 27 km2 km Anvil frequency Percentage of pixels with IR anvil rating ≥ 20 within 27 km2 % Area of cold cloud Area of pixels with IR Tb < 225 K within 27 km2 km2
AMSR-E passive microwave parameters Minimum PCT in PF At 10, 19, 37, and 89 GHz K Maximum PCT in PF At 10, 19, 37, and 89 GHz K Adjusted minimum PCT in PF At 10, 19, and 37 GHz histogram adjusted to TRMM K Adjusted maximum PCT in PF At 10, 19, and 37 GHz histogram adjusted to TRMM K Number of 89 GHz pixels in PF below PCT temperature thresholds < 100, 125, 150, 175, and 200 K Unitless Number of 37 GHz pixels in PF below PCT temperature thresholds < 200, 225, 250, and 275 K Unitless 37 GHz PCT at minimum 19 GHz PCT For graupel investigation K DC Score Deep convection score (0-1), from Bang and Cecil (2021) Unitless Probability of hail from various algorithms 19 GHz only, 37 GHz only, BC 2019 (Bang and Cecil 2019) %
GridRad MESH cell characteristics Mean MESH in cell 75th and 95th percentile MESH mm Maximum MESH in cell 75th and 95th percentile MESH mm Area of MESH95 in cell Exceeding 10, 25, 50, and 75 mm km2 MERRA-2 convective parameters from model-level proximity soundings Convectively available potential energy Surface-based, and 1000-m mixed layer parcel J kg-1 WMAXSHEAR Most unstable parcel’s maximum theoretical updraft speed x 0-6-km bulk wind shear (and effective wind shear) m2 s-2 Convective inhibition Surface-based, and 1000-m mixed layer parcel J kg-1 Total precipitable water mm Lapse rate 700-500-hPa, 0-1-km, 0-3-km C km-1 Bulk wind shear 0-6-km and 0-1-km layers m s-1 Lifted condensation level Mixed-layer parcel m Equilibrium level temperature Surface-based parcel m Storm relative helicity 0-3-km and 0-1-km for rightand left-movers m2 s-2
Energy helicity index 0-3-km and 0-1-km for rightand left-movers m2 s-2 SWEAT Severe Weather Threat Index (National Weather Service) Unitless SCP Supercell Composite Parameter (Thompson et al. 2004) m2 s-2 STP Significant Tornado Parameter (Thompson et al. 2004) m2 s-2 References Bang, S. D., and D. J. Cecil, 2019: Constructing a multifrequency passive microwave hail retrieval and climatology in the GPM domain. J. Appl. Meteorol. Climatol., 58, 1889–1904, https://doi.org/10.1175/JAMC-D-19-0042.1. ——, and ——, 2021: Testing passive microwave-based hail retrievals using GPM DPR Ku-band radar. J. Appl. Meteorol. Climatol., 60, 255–271, https://doi.org/10.1175/JAMC-D-20-0129.1. National Weather Service: Env Parameters and Indices. Accessed 10 September 2025, https://www.weather.gov/lmk/indices. Thompson, R., R. Edwards, and C. Mead, 2004: An update to the supercell composite and significant tornado parameters. 22nd Conference on Severe Local Storms, American Meteorological Society.
