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

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

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

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

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

Tropical Cyclones and Climate Change

Since the Eighth International Workshop on Tropical Cyclones (IWTC-8), held in December 2014, progress has been made in our understanding of the relationship between tropical cyclone (TC) characteristics, climate and climate change. New analysis of observations has revealed trends in the latitude of maximum TC intensity and in TC translation speed. Climate models are demonstrating an increasing ability to simulate the observed TC climatology and its regional variations. The limited representation of air-sea interaction processes in most climate simulations of TCs remains an issue. Consensus projections of future TC behavior continue to indicate decreases in TC numbers, increases in their maximum intensities and increases in TC-related rainfall. Future sea level rise will exacerbate the impact of storm surge on coastal regions, assuming all other factors equal. Studies have also begun to estimate the effect on TCs of the climate change that has occurred to date. Recommendations are made regarding future research directions

Tropical cyclones and climate change

Recent research has strengthened the understanding of the links between climate and tropical cyclones (TCs) on various timescales. Geological records of past climates have shown century-long variations in TC numbers. While no significant trends have been identified in the Atlantic since the late 19th century, significant observed trends in TC numbers and intensities have occurred in this basin over the past few decades, and trends in other basins are increasingly being identified. However, understanding of the causes of these trends is incomplete, and confidence in these trends continues to be hampered by a lack of consistent observations in some basins. A theoretical basis for maximum TC intensity appears now to be well established, but a climate theory of TC formation remains elusive. Climate models mostly continue to predict future decreases in global TC numbers, projected increases in the intensities of the strongest storms and increased rainfall rates. Sea level rise will likely contribute toward increased storm surge risk. Against the background of global climate change and sea level rise, it is important to carry out quantitative assessments on the potential risk of TC-induced storm surge and flooding to densely populated cities and river deltas. Several climate models are now able to generate a good distribution of both TC numbers and intensities in the current climate. Inconsistent TC projection results emerge from modeling studies due to different downscaling methodologies and warming scenarios, inconsistencies in projected changes of large-scale conditions, and differences in model physics and tracking algorithms

Globally Gridded Satellite (GridSat) Observations for Climate Studies

Geostationary satellites have provided routine, high temporal resolution Earth observations since the 1970s. Despite the long period of record, use of these data in climate studies has been limited for numerous reasons, among them: there is no central archive of geostationary data for all international satellites, full temporal and spatial resolution data are voluminous, and diverse calibration and navigation formats encumber the uniform processing needed for multi-satellite climate studies. The International Satellite Cloud Climatology Project set the stage for overcoming these issues by archiving a subset of the full resolution geostationary data at approx.10 km resolution at 3 hourly intervals since 1983. Recent efforts at NOAA s National Climatic Data Center to provide convenient access to these data include remapping the data to a standard map projection, recalibrating the data to optimize temporal homogeneity, extending the record of observations back to 1980, and reformatting the data for broad public distribution. The Gridded Satellite (GridSat) dataset includes observations from the visible, infrared window, and infrared water vapor channels. Data are stored in the netCDF format using standards that permit a wide variety of tools and libraries to quickly and easily process the data. A novel data layering approach, together with appropriate satellite and file metadata, allows users to access GridSat data at varying levels of complexity based on their needs. The result is a climate data record already in use by the meteorological community. Examples include reanalysis of tropical cyclones, studies of global precipitation, and detection and tracking of the intertropical convergence zone

Our Globally Changing Climate

Since the Third U.S. National Climate Assessment (NCA3) was published in May 2014, new observations along multiple lines of evidence have strengthened the conclusion that Earth's climate is changing at a pace and in a pattern not explainable by natural influences. While this report focuses especially on observed and projected future changes for the United States, it is important to understand those changes in the global context (this chapter). The world has warmed over the last 150 years, especially over the last six decades, and that warming has triggered many other changes to Earth's climate. Evidence for a changing climate abounds, from the top of the atmosphere to the depths of the oceans. Thousands of studies conducted by tens of thousands of scientists around the world have documented changes in surface, atmospheric, and oceanic temperatures; melting glaciers; disappearing snow cover; shrinking sea ice; rising sea level; and an increase in atmospheric water vapor. Rainfall patterns and storms are changing, and the occurrence of droughts is shifting