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Contributions of atmospheric factors to the variability of the calculated theoretical maximum potential intensity (MPI) of tropical cyclones (TCs) over the North Atlantic are explored using the 6-hourly atmospheric reanalysis and TC best track data from 1980 to 2015. The results show that for a given sea surface temperature (SST), the calculated theoretical MPI between the medians of top 10% and bottom 10% samples can vary by as large as 10-15 m/s, which accounts for 20-25% of the median of the MPI. It is shown that the drier (moister) and colder (warmer) environment favors higher (lower) MPI, and the TC-MPI is more sensitive to atmospheric temperature at lower SSTs but more sensitive to atmospheric humidity at higher SSTs. Results from sensitivity experiments show that the tropospheric temperature and humidity profiles and the outflow layer temperature are all responsible for the MPI variability, but their relative importance vary with SST. The atmospheric humidity accounts for 12-13 (7-11) m/s at SSTs over (below) 28 degrees C, the tropospheric temperature accounts for about 7-12 (5-6) m/s at SSTs below (above) 28 degrees C, and the outflow temperature accounts for 7-8 m/s almost independent of SST. These results strongly suggest that the modulation of MPI by synoptic variability needs to be considered when MPI is calculated and used as a predictor/parameter in operational TC intensity prediction schemes, especially for strong TCs. Some other implications of the results are also discussed.

Plain Language Summary Contributions of atmospheric factors to the variability of the theoretical maximum potential intensity (MPI) of tropical cyclones (TCs) over the North Atlantic are explored using the 6-hourly atmospheric reanalysis and TC best track data from 1980 to 2015. The results show that for a given sea surface temperature (SST), the theoretical MPI between the medians of top 10% and bottom 10% samples can vary by as large as 10-15 m/s, which accounts for 20-25% of the median of the MPI. It is shown that the drier (moister) and colder (warmer) environment favors higher (lower) MPI, and the MPI is more sensitive to atmospheric temperature at lower SSTs but more sensitive to atmospheric humidity at higher SSTs. Results strongly suggest that the modulation of MPI by synoptic variability needs to be considered when MPI is calculated and used as a predictor in operational TC intensity prediction schemes, especially for strong TCs.