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      Hurricane Risk in a Changing Climate 

      Development of a Simple, Open-Source Hurricane Wind Risk Model for Bermuda with a Sensitivity Test on Decadal Variability


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          A hurricane-catastrophe model was developed for assessing risk associated with hurricane winds for Bermuda by combining observational knowledge with property value and exposure information. The sensitivity of hurricane wind risk to decadal variability of events was tested. The historical record of hurricanes passing within 185 km of Bermuda was created using IBTrACS. A representative exposure dataset of property values was developed by obtaining recent governmental Annual Rental Value data, while Miller et al. (Weather Forecast 28:159–174, 2013) provided a vulnerability relationship between increasing winds and damage. With a probabilistic approach, new events for 10,000 years were simulated for three different scenarios using (1) the complete record of annual TC counts; (2) two high-frequency periods and; (3) two low-frequency periods. Exceedance probability curves were constructed from event loss tables, focusing on aggregating annual losses from damaging events. Expected losses of low-frequency scenarios were less than losses of high-frequency scenarios or when the whole historical record was used. This framework suffers from uncertainties due to different assumptions and biases within IBTrACS. Small data sizes limit our ability to conduct a formal model validation and results should be interpreted in this context. In the future, sensitivity tests on the different components of the model will be performed.

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          A signature of persistent natural thermohaline circulation cycles in observed climate

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            Mortality in Puerto Rico after Hurricane Maria

            Quantifying the effect of natural disasters on society is critical for recovery of public health services and infrastructure. The death toll can be difficult to assess in the aftermath of a major disaster. In September 2017, Hurricane Maria caused massive infrastructural damage to Puerto Rico, but its effect on mortality remains contentious. The official death count is 64.
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              Ocean impact on decadal Atlantic climate variability revealed by sea-level observations.

              Decadal variability is a notable feature of the Atlantic Ocean and the climate of the regions it influences. Prominently, this is manifested in the Atlantic Multidecadal Oscillation (AMO) in sea surface temperatures. Positive (negative) phases of the AMO coincide with warmer (colder) North Atlantic sea surface temperatures. The AMO is linked with decadal climate fluctuations, such as Indian and Sahel rainfall, European summer precipitation, Atlantic hurricanes and variations in global temperatures. It is widely believed that ocean circulation drives the phase changes of the AMO by controlling ocean heat content. However, there are no direct observations of ocean circulation of sufficient length to support this, leading to questions about whether the AMO is controlled from another source. Here we provide observational evidence of the widely hypothesized link between ocean circulation and the AMO. We take a new approach, using sea level along the east coast of the United States to estimate ocean circulation on decadal timescales. We show that ocean circulation responds to the first mode of Atlantic atmospheric forcing, the North Atlantic Oscillation, through circulation changes between the subtropical and subpolar gyres--the intergyre region. These circulation changes affect the decadal evolution of North Atlantic heat content and, consequently, the phases of the AMO. The Atlantic overturning circulation is declining and the AMO is moving to a negative phase. This may offer a brief respite from the persistent rise of global temperatures, but in the coupled system we describe, there are compensating effects. In this case, the negative AMO is associated with a continued acceleration of sea-level rise along the northeast coast of the United States.

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                September 16 2022
                : 143-160


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