Upper-tropospheric troughs and North American monsoon rainfall in a long-term track dataset
Igel, Matthew (2021), Upper-tropospheric troughs and North American monsoon rainfall in a long-term track dataset, Dryad, Dataset, https://doi.org/10.25338/B8VS7T
The North American monsoon (NAM) is frequently affected by transient, propagating upper tropospheric vorticity anomalies. Sometimes called Tropical Upper Tropospheric Troughs (TUTTs), these features have been shown to episodically enhance monsoon rainfall. Here we track long-lived TUTTs in 40 years of reanalysis data, producing composites and case studies from 340 TUTTs which last, on average, seven days as they move westward across the NAM region. TUTTs are thought to form from midlatitude Rossby wave breaking; case studies from our dataset support this theory. Composite TUTT cyclonic circulations are shown to stretch across about 10 degrees of longitude and extend from 100 hPa to 500 hPa. In a composite sense, it is shown that TUTTs track westward due to interaction of the induced vertical wind with the vorticity structure. Anomalous ascent wraps around the vortex center from the south at the surface to the east at the upper-tropospheric level of maximum vortex intensity. The upper level ascent is consistent with that derived for an adiabatic quasi-geostrophic vortex at upper levels. The kinematics of TUTTs and their propagation in a region of climatologically strong moisture gradients results in a convergence of low-level moisture southeast of the vortex center. TUTTs consequently can enhance anomalous precipitation to their southeast. The intensity of TRMM-measured precipitation when precipitation occurs is higher both south and east of TUTTs while the likelihood of precipitation occurring is higher both south and northwest of TUTTs.
3 files are included. "TUTTs.mat" and "TUTTs.txt" are output as from TempestExtremes with all criteria from Igel et al. (2021) applied. "StitchOutputfile.txt" is output as from the call below which includes disturbances which occur entirely in June and September.
This data was collected by running TempestExtremes with the following commands over the ERA5 dataset. The TempestExtreme identification call is: DetectNodes --in_data_list Inputfile --out Outputfile --searchbymin “streamfunction” --minlat 15 --maxlat 40 --minlon -120 --maxlon -90 –noclosedcontourcmd “Z,325.,4.0,1.0” --mergedist 5.0 . The command to stitch identified features in time is: StitchNodes --in Outputfile --out StitchOutputfile --maxgap 1 --minlength 67 --range 5.0.