Hurricane track variability and secular potential intensity trends

Sea surface temperature in the tropical North Atlantic has been shown to co-vary with hurricane activity on a broad range of time-scales. One general hypothesis for this observed relationship is based on the theory of potential intensity (PI) whereby the local ambient environment determines the maximum intensity that a hurricane can achieve. Under this theory, climate change and resultant changes in PI can affect the distribution of hurricane intensities by modulating the upper extreme values. Indeed, PI averaged over the tropical North Atlantic during the hurricane season has been increasing in concert with sea surface temperature, which introduces an expectation for a secular upward shift in the distribution of hurricane intensities. However, hurricane tracks also largely determine the local storm-ambient environment and thus track variability introduces additional ambient PI variability. Here we show that this additional variance removes the observed secular trend in mean summertime tropical North Atlantic PI, and there is no tacit expectation that hurricanes have become stronger based solely on PI theory. The observed trends in integrated metrics such as hurricane power dissipation are then more likely to be caused by changes in storm frequency and duration due to broader scale regional variability than secular intensity changes due solely to ambient thermodynamics

Past and Projected Changes in Western North Pacific Tropical Cyclone Exposure

The average latitude where tropical cyclones (TCs) reach their peak intensity has been observed to be shifting poleward in some regions over the past 30 years, apparently in concert with the independently observed expansion of the tropical belt. This poleward migration is particularly well observed and robust in the western North Pacific Ocean (WNP). Such a migration is expected to cause systematic changes, both increases and decreases, in regional hazard exposure and risk, particularly if it persists through the present century. Here, it is shown that the past poleward migration in the WNP has coincided with decreased TC exposure in the region of the Philippine and South China Seas, including the Marianas, the Philippines, Vietnam, and southern China, and increased exposure in the region of the East China Sea, including Japan and its Ryukyu Islands, the Korea Peninsula, and parts of eastern China. Additionally, it is shown that projections of WNP TCs simulated by, and downscaled from, an ensemble of numerical models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) demonstrate a continuing poleward migration into the present century following the emissions projections of the representative concentration pathway 8.5 (RCP8.5). The projected migration causes a shift in regional TC exposure that is very similar in pattern and relative amplitude to the past observed shift. In terms of regional differences in vulnerability and resilience based on past TC exposure, the potential ramifications of these future changes are significant. Questions of attribution for the changes are discussed in terms of tropical belt expansion and Pacific decadal sea surface temperature variability

Past and Future Hurricane Intensity Change along the U.S. East Coast

The ocean and atmosphere in the North Atlantic are coupled through a feedback mechanism that excites a dipole pattern in vertical wind shear (VWS), a metric that strongly controls Atlantic hurricanes. In particular, when tropical VWS is under the weakening phase and thus favorable for increased hurricane activity in the Main Development Region (MDR), a protective barrier of high VWS inhibits hurricane intensification along the U.S. East Coast. Here we show that this pattern is driven mostly by natural decadal variability, but that greenhouse gas (GHG) forcing erodes the pattern and degrades the natural barrier along the U.S. coast. Twenty-first century climate model projections show that the increased VWS along the U.S. East Coast during decadal periods of enhanced hurricane activity is substantially reduced by GHG forcing, which allows hurricanes approaching the U.S. coast to intensify more rapidly. The erosion of this natural intensification barrier is especially large following the Representative Concentration Pathway 8.5 (rcp8.5) emission scenario

Large-Scale Circulation and Climate Variability

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis

Longwave emission trends over Africa and implications for Atlantic hurricanes

Author Posting. © American Geophysical Union, 2017. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 44 (2017): 9075–9083, doi:10.1002/2017GL073869.The latitudinal gradient of outgoing longwave radiation (OLR) over Africa is a skillful and physically based predictor of seasonal Atlantic hurricane activity. The African OLR gradient is observed to have strengthened during the satellite era, as predicted by state-of-the-art global climate models (GCMs) in response to greenhouse gas forcing. Prior to the satellite era and the U.S. and European clean air acts, the African OLR gradient weakened due to aerosol forcing of the opposite sign. GCMs predict a continuation of the increasing OLR gradient in response to greenhouse gas forcing. Assuming a steady linear relationship between African easterly waves and tropical cyclogenesis, this result suggests a future increase in Atlantic tropical cyclone frequency by 10% (20%) at the end of the 21st century under the RCP 4.5 (8.5) forcing scenario.J.P.D., K.B.K., and L.Z. Acknowledge support from the Strategic Environmental Research and Development Program (SERDP) (RC-2336).2018-03-0

On the changes in number and intensity of North Atlantic tropical cyclones

Bayesian statistical models were developed for the number of tropical cyclones and the rate at which these cyclones became hurricanes in the North Atlantic. We find that, controlling for the cold tongue index and the North Atlantic oscillation index, there is high probability that the number of cyclones has increased in the past thirty years; but the rate at which these storms become hurricanes appears to be constant. We also investigate storm intensity by measuring the distribution of individual storm lifetime in days, storm track length, and Emanuel's power dissiptation index. We find little evidence that the distribution of individual storm intensity is changing through time. Any increase in cumulative yearly storm intensity and potential destructiveness, therefore, is due to the increasing number of storms and not due to any increase in the intensity of individual storms.Comment: 24 pages, 9 figure

Reply to “Comments on ‘Monitoring and Understanding Trends in Extreme Storms: State of Knowledge’”

We welcome the comments of Landsea (2015, hereafter L15) and we1 applaud his efforts toward reanalyzing past tropical cyclone data in the Atlantic (Landsea et al. 2008, 2012, 2014; Hagen et al. 2012). However, L15 does not substantially change the conclusions stated in Kunkel et al. (2013, hereafter K13). L15 voices two main concerns: 1. The U.S. landfalling hurricane time series considered by K13 is dated. 2. The U.S. landfall record exhibits multidecadal variability that places the changes since 1970 into a larger perspective than K13 provided. Related to this concern, L15 introduces assertions about the relationship between U.S. landfall variability and basinwide North Atlantic variability

Stratified statistical models of North Atlantic basin-wide and regional tropical cyclone counts

Using the historical Atlantic tropical cyclone record, this study examines the empirical relationships between climate state variables and Atlantic tropical cyclone counts. The state variables considered as predictors include indices of the El Niño/Southern Oscillation and Northern Atlantic Oscillation, and both “local” and “relative” measures of Main Development Region sea surface temperature. Other predictors considered include indices measuring the Atlantic Meridional Mode and the West African monsoon. Using all of the potential predictors in a forward stepwise Poisson regression, we examine the relationships between tropical cyclone counts and climate state variables. As a further extension on past studies, both basin-wide named storm counts and cluster analysis time series representing distinct flavors of tropical cyclones, are modeled. A wide variety of cross validation metrics reveal that basin-wide counts or sums over appropriately chosen clusters may be more skillfully modeled than the individual cluster series. Ultimately, the most skillful models typically share three predictors: indices for the main development region sea surface temperatures, the El Niño/Southern Oscillation, and the North Atlantic Oscillation