Multiannual forecasts of Atlantic U.S. tropical cyclone wind damage potential

Caron, Louis-Philippe; Hermanson, Leon; Doblas‐Reyes, F. J.

doi:10.1002/2015gl063303

Cited by 24 publications

(13 citation statements)

References 39 publications

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“…In the Atlantic Ocean, the AMV is the dominant mode of decadal climate variability and has been linked to several climate impacts over Europe, North America and the Sahel (Zhang and Delwoth, 2006;Sutton and Dong, 2012;Ruprich-Robert et al, 2017 as well as to Atlantic tropical cyclones (e.g. Caron et al, 2015Caron et al, , 2018. Both PRED and HIST are capable of skilfully predicting the AMV, and they show better performance than a persistence forecast (except for the forecast range from 1 to 4 years in HIST), as shown by the ACC (Fig.…”

Section: Skill For the Main Ocean Modes Of Variabilitymentioning

confidence: 97%

Assessment of a full-field initialized decadal climate prediction system with the CMIP6 version of EC-Earth

et al. 2021

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Abstract. In this paper, we present and evaluate the skill of an EC-Earth3.3 decadal prediction system contributing to the Decadal Climate Prediction Project – Component A (DCPP-A). This prediction system is capable of skilfully simulating past global mean surface temperature variations at interannual and decadal forecast times as well as the local surface temperature in regions such as the tropical Atlantic, the Indian Ocean and most of the continental areas, although most of the skill comes from the representation of the external radiative forcings. A benefit of initialization in the predictive skill is evident in some areas of the tropical Pacific and North Atlantic oceans in the first forecast years, an added value that is mostly confined to the south-east tropical Pacific and the eastern subpolar North Atlantic at the longest forecast times (6–10 years). The central subpolar North Atlantic shows poor predictive skill and a detrimental effect of initialization that leads to a quick collapse in Labrador Sea convection, followed by a weakening of the Atlantic Meridional Overturning Circulation (AMOC) and excessive local sea ice growth. The shutdown in Labrador Sea convection responds to a gradual increase in the local density stratification in the first years of the forecast, ultimately related to the different paces at which surface and subsurface temperature and salinity drift towards their preferred mean state. This transition happens rapidly at the surface and more slowly in the subsurface, where, by the 10th forecast year, the model is still far from the typical mean states in the corresponding ensemble of historical simulations with EC-Earth3. Thus, our study highlights the Labrador Sea as a region that can be sensitive to full-field initialization and hamper the final prediction skill, a problem that can be alleviated by improving the regional model biases through model development and by identifying more optimal initialization strategies.

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Section: Skill For the Main Ocean Modes Of Variabilitymentioning

confidence: 97%

Assessment of a full-field initialized decadal climate prediction system with the CMIP6 version of EC-Earth

et al. 2021

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“…More recently, Caron et al showed that multi‐year prediction of Atlantic hurricane activity by CMIP5 models in hindcast mode had modest positive skill, even after accounting for persistence in the climate shift that occurred in 1994–1995. The potential for predicting possible wind damage related to hurricanes along the U.S. coast using a multi‐model ensemble of initialized global climate models has also been recently demonstrated . Decadal predictability of TC activity is a new field and it is expected that more modeling groups will explore this topic in the next few years.…”

Section: Current State‐of‐the‐art Global Climate Models: From Intrasementioning

confidence: 99%

Tropical cyclones in climate models

Camargo

Wing

2015

WIREs Climate Change

116

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In this review, we provide a historical overview of the simulation of tropical cyclones (TCs) in climate models, from the first attempts in the 1970s to the current state-of-the-art models. We discuss the status of TC simulation across multiple time scales, from intraseasonal, seasonal, and decadal, to climate change. One of the limitations on the simulation of TCs in climate models has been, and continues to be, balancing the high resolution necessary to accurately simulate TCs themselves with the need to run simulations for many years and using many ensemble members. Several approaches to inferring TC activity indirectly, rather than relying on the models own under-resolved TCs, are reviewed, including the use of TC genesis indices based on the large-scale environment and downscaling methods such as the use of regional climate models and statistical-dynamical techniques. We also provide an update on the status of climate change projections from the current class of models, where it is feasible to directly track the model's TCs. While there has been great progress in the capability of climate models to simulate TCs and provide useful forecasts and projections across multiple time scales, there remains much work to be done. We list some of the sources of uncertainty and model sensitivity, describe where improvements are necessary, and provide a few suggestions for promising research directions. of the development of a tropical cyclone in ECHAM3 with resolution T106 (left panel) and T42 (right panel). (Adapted from Ref 17 with permission. Made available under the terms of the Creative Commons Attribution 4.0 International (CC_BY) License) Advanced Review wires.wiley.com/climatechange 214

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“…Although the aforementioned climate variables are arguably the most well‐known modulators of Atlantic tropical cyclone activity, hurricane activity has also been linked to the North Atlantic Oscillation (NAO) [ Elsner and Kocher , ; Elsner et al , ; Villarini et al , ], the 11 year solar cycle [ Hodges and Elsner , ; Elsner and Jagger , ], natural and anthropogenic tropospheric aerosols [ Dunstone et al , ; Evan et al , , ], and the North Atlantic subpolar gyre temperature [ Smith et al , ; Dunstone et al , ; Caron et al , ].…”

Section: Introductionmentioning

confidence: 99%

Reanalysis of climate influences on Atlantic tropical cyclone activity using cluster analysis

2017

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We analyze, using Poisson regressions, the main climate influences on North Atlantic tropical cyclone activity. The analysis is performed using not only various time series of basin‐wide storm counts but also various series of regional clusters, taking into account shortcomings of the hurricane database through estimates of missing storms. The analysis confirms that tropical cyclones forming in different regions of the Atlantic are susceptible to different climate influences. We also investigate the presence of trends in these various time series, both at the basin‐wide and cluster levels, and show that, even after accounting for possible missing storms, there remains an upward trend in the eastern part of the basin and a downward trend in the western part. Using model selection algorithms, we show that the best model of Atlantic tropical cyclone activity for the recent past is constructed using Atlantic sea surface temperature and upper tropospheric temperature, while for the 1878–2015 period, the chosen covariates are Atlantic sea surface temperature and El Niño–Southern Oscillation. We also note that the presence of these artificial trends can impact the selection of the best covariates. If the underlying series shows an upward trend, then the mean Atlantic sea surface temperature captures both interannual variability and the upward trend, artificial or not. The relative sea surface temperature is chosen instead for stationary counts. Finally, we show that the predictive capability of the statistical models investigated is low for U.S. landfalling hurricanes but can be considerably improved when forecasting combinations of clusters whose hurricanes are most likely to make landfall.

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Multiannual forecasts of Atlantic U.S. tropical cyclone wind damage potential

Cited by 24 publications

References 39 publications

Assessment of a full-field initialized decadal climate prediction system with the CMIP6 version of EC-Earth

Assessment of a full-field initialized decadal climate prediction system with the CMIP6 version of EC-Earth

Tropical cyclones in climate models

Reanalysis of climate influences on Atlantic tropical cyclone activity using cluster analysis

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