Skilful multi-year predictions of Atlantic hurricane frequency

Smith, Doug; Eade, Rosie; Dunstone, Nick; Fereday, David; Murphy, James M.; Pohlmann, Holger; Scaife, Adam A.

doi:10.1038/ngeo1004

Cited by 262 publications

(284 citation statements)

References 30 publications

Supporting

Mentioning

258

Contrasting

Unclassified

Order By: Relevance

“…We note, however, that the Southern Oscillation index by itself is a relatively poor predictor of cyclone activity (Table 2), possibly because it lacks the global warming signal. The weaker positive relationship between the SSTs over the Atlantic subpolar gyre and k, has been mechanistically related to reduced wind shear and increased precipitation in the MDR (34). A warm subpolar gyre produces a reduced temperature gradient with the equator, a reduced northward heat transport (34), and an anomalously warm SST in the MDR (35).…”

Section: Resultsmentioning

confidence: 99%

Projected Atlantic hurricane surge threat from rising temperatures

Grinsted

Moore

Jevrejeva

2013

Proc. Natl. Acad. Sci. U.S.A.

189

163

View full text Add to dashboard Cite

Detection and attribution of past changes in cyclone activity are hampered by biased cyclone records due to changes in observational capabilities. Here, we relate a homogeneous record of Atlantic tropical cyclone activity based on storm surge statistics from tide gauges to changes in global temperature patterns. We examine 10 competing hypotheses using nonstationary generalized extreme value analysis with different predictors (North Atlantic Oscillation, Southern Oscillation, Pacific Decadal Oscillation, Sahel rainfall, Quasi-Biennial Oscillation, radiative forcing, Main Development Region temperatures and its anomaly, global temperatures, and gridded temperatures). We find that gridded temperatures, Main Development Region, and global average temperature explain the observations best. The most extreme events are especially sensitive to temperature changes, and we estimate a doubling of Katrina magnitude events associated with the warming over the 20th century. The increased risk depends on the spatial distribution of the temperature rise with highest sensitivity from tropical Atlantic, Central America, and the Indian Ocean. Statistically downscaling 21st century warming patterns from six climate models results in a twofold to sevenfold increase in the frequency of Katrina magnitude events for a 1°C rise in global temperature (using BNU-ESM, BCC-CSM-1.1, CanESM2, HadGEM2-ES, INM-CM4, and NorESM1-M).climate change | hazard | flood P redicting how cyclone activity will change in a warmer world has proven to be an elusive target (1, 2). There are competing factors that may influence whether tropical cyclone activity will strengthen or weaken. Warmer sea surface temperatures (SSTs) are favorable to tropical cyclones. However, global warming may also increase vertical wind shear, which is unfavorable for cyclones (3), although some studies find this is a minor effect (4). Dynamical downscaling of Atlantic tropical cyclones tend to show fewer but more intense events, but the results are not consistent between models (5, 6). Studies that use the relationship between cyclone activity and sea surface temperatures in the Main Development Region (MDR) in general show a high sensitivity to warming (7-11). However, other authors propose that cyclones are sensitive to MDR warming relative to the tropical mean (3,(12)(13)(14)(15). This alternative hypothesis is supported by some process model output (3,16,17). Projections based on relative MDR (rMDR) relationships show little increase over the 21st century (14,17).Observational bias in cyclone records (9,18,19) has made it hard to distinguish between competing hypotheses for 21st century cyclone activity. In this paper, we use a homogeneous record of cyclone surge activity since 1923 (20) to estimate how the frequency of extreme surges changes with spatial warming patterns. We develop a nonstationary extreme value model of the probability distribution of hurricane surge threat as a function of spatial warming patterns. This allows us to project changes in probability of even ...

show abstract

Section: Resultsmentioning

confidence: 99%

Projected Atlantic hurricane surge threat from rising temperatures

Grinsted

Moore

Jevrejeva

2013

Proc. Natl. Acad. Sci. U.S.A.

189

163

View full text Add to dashboard Cite

show abstract

“…The hindcasts assessed here (not the same as those for CMIP5), are from an updated version of DePreSys (Smith et al 2010) that employs an ensemble of nine variants of the model, sampling parameterization uncertainties through perturbations to poorly constrained atmospheric and surface parameters. HadCM3 was also updated to include a fully interactive representation of the sulphur cycle, and flux adjustments to restrict the development of regional biases in sea surface temperature and salinity (Collins et al 2010).…”

Section: Model Data Used In This Assessmentmentioning

confidence: 99%

“…To illustrate the differences in skill that can arise between different prediction systems, the results for two different hindcast prediction experiments are presented in this paper. The first is the perturbed physics hindcasts from Hadley Centre using an updated version of the DePreSys prediction system (Smith et al 2010). The second is the set of hindcasts from the Canadian Climate Centre using CanCM4 ).…”

Section: Model Data Used In This Assessmentmentioning

confidence: 99%

A verification framework for interannual-to-decadal predictions experiments

Goddard¹,

et al. 2012

View full text Add to dashboard Cite

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model's ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic

show abstract

“…For simulations, we use historical and RCP4.5 runs from 44 different GCMs from the CMIP5 archive [Taylor et al, 2012;Bi et al, 2013;Xin et al, 2013;Ji et al, 2014;von Salzen et al, 2013;Meehl et al, 2012;Hurrell et al, 2012;Scoccimarro et al, 2011;Voldoire et al, 2013;Rotstayn et al, 2010;Hazeleger et al, 2010;Li et al, 2013;Delworth et al, 2006;Donner et al, 2011;Schmidt et al, 2014;Smith et al, 2010;Collins et al, 2011;Jones et al, 2011;Volodin et al, 2010;Dufresne et al, 2013;Hourdin et al, 2013;Sakamoto et al, 2012;Watanabe et al, 2010Watanabe et al, , 2011Giorgetta et al, 2013;Yukimoto et al, 2012;Bentsen et al, 2013], and from the 100 realization single-model large ensemble of the MPI-ESM [Giorgetta et al, 2013]. The large ensemble uses the model version MPI-ESM1.1 in low resolution (LR) configuration, with resolution T63 and 47 vertical levels in the atmosphere and 1.5 ∘ resolution and 40 vertical levels in the ocean.…”

Section: Datamentioning

confidence: 99%

Internal variability in simulated and observed tropical tropospheric temperature trends

Suárez-Gutiérrez

Thorne

et al. 2017

Geophysical Research Letters

View full text Add to dashboard Cite

We explore the extent to which internal variability can reconcile discrepancies between observed and simulated warming in the upper tropical troposphere. We compare all extant radiosonde‐based estimates for the period 1958–2014 to simulations from the Coupled Model Intercomparison Project phase 5 multimodel ensemble and the 100 realization Max Planck Institute large ensemble. We consider annual mean temperatures and all available 30‐and 15‐year trends. Most observed trends fall within the ensemble spread for most of the record, and trends calculated over 15‐year periods show better agreement than 30‐year trends, with generally larger discrepancies for the older observational products. The simulated amplification of surface warming aloft in the troposphere is consistent with observations, and the linear correlation between surface and simultaneous tropospheric warming trends decreases with trend length. We conclude that trend differences between observations and simulations of tropical tropospheric temperatures are dominated by observational uncertainty and chaotic internal variability rather than by systematic errors in model performance.

show abstract

Skilful multi-year predictions of Atlantic hurricane frequency

Cited by 262 publications

References 30 publications

Projected Atlantic hurricane surge threat from rising temperatures

Projected Atlantic hurricane surge threat from rising temperatures

A verification framework for interannual-to-decadal predictions experiments

Internal variability in simulated and observed tropical tropospheric temperature trends

Contact Info

Product

Resources

About