Effects of tropical sea surface temperature variability on Northern Hemisphere tropical cyclone genesis

2021 ◽  
pp. 1-66
Author(s):  
Shuo Li ◽  
Wei Mei ◽  
Shang-Ping Xie

AbstractThis study quantifies the contributions of tropical sea surface temperature (SST) variations during the boreal warm season to the interannual-to-decadal variability in tropical cyclone genesis frequency (TCGF) over the Northern Hemisphere ocean basins. The first seven leading modes of tropical SST variability are found to affect basin-wide TCGF in one or more basins, and are related to canonical El Niño–Southern Oscillation (ENSO), global warming (GW), the Pacific Meridional Mode (PMM), Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO) and Atlantic Meridional Mode (AMM). These modes account for approximately 58%, 50% and 56% of the variance in basin-wide TCGF during 1969–2018 over the North Atlantic (NA), Northeast Pacific (NEP) and Northwest Pacific (NWP), respectively. The SST effect is weak on TCGF variability in the North Indian Ocean. The dominant SST modes differ among the basins: ENSO, the AMO, AMM and GW for the NA; ENSO and the AMO for the NEP; and the PMM, interannual AMO and GW for the NWP. A specific mode may have opposite effects on TCGF in different basins, particularly between the NA and NEP. Sliding-window multiple linear regression analyses show that the SST effects on basin-wide TCGF are stable in time in the NA and NWP, but strengthen after the mid-1970s in the NEP. The SST effects on local TC genesis and occurrence frequency are also explored, and the underlying physical mechanisms are examined by diagnosing a genesis potential index and its components.

2017 ◽  
Vol 30 (22) ◽  
pp. 9133-9145 ◽  
Author(s):  
Cécile L. Defforge ◽  
Timothy M. Merlis

Recent studies have reaffirmed a global threshold sea surface temperature (SST) of 26°C for tropical cyclone (TC) genesis. However, it is well understood that other thermodynamic variables influence TC genesis and that high SST in isolation is not a sufficient criterion for genesis. Here, a basin-by-basin analysis of the SST distributions in the five most active ocean basins is performed, which shows that there is no global SST threshold for TC genesis. The distributions of genesis SST show substantial variations between basins. Furthermore, analysis of the conditional probability of genesis for a given TC season main development region SST suggests that the SST bounds for TC genesis are largely determined by the climatological bounds of the basin and that the SST values within this environmental range have similar probabilities of genesis. The distribution of relative SST (the difference between local and tropical mean) and tropical cyclone potential intensity at TC genesis are more distinct from those of the TC season environment, consistent with their utility in TC genesis indices.


2020 ◽  
Vol 35 (4) ◽  
pp. 1221-1234
Author(s):  
Matthew B. Switanek ◽  
Joseph J. Barsugli ◽  
Michael Scheuerer ◽  
Thomas M. Hamill

AbstractMonthly tropical sea surface temperature (SST) data are used as predictors to make statistical forecasts of cold season (November–March) precipitation and temperature for the contiguous United States. Through the use of the combined-lead sea surface temperature (CLSST) model, predictive information is discovered not just in recent SSTs but also from SSTs up to 18 months prior. We find that CLSST cold season forecast anomaly correlation skill is higher than that of the North American Multimodel Ensemble (NMME) and the SEAS5 model from the European Centre for Medium-Range Weather Forecasts (ECMWF) when averaged over the United States for both precipitation and 2-m air temperature. The precipitation forecast skill obtained by CLSST in parts of the Intermountain West is of particular interest because of its implications for water resources. In those regions, CLSST dramatically improves the skill over that of the dynamical model ensembles, which can be attributed to a robust statistical response of precipitation in this region to SST anomalies from the previous year in the tropical Pacific.


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