A Decadal Climate Service for Insurance: Skillful Multiyear Predictions of North Atlantic Hurricane Activity and U.S. Hurricane Damage

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ABSTRACT: North Atlantic Ocean hurricane activity exhibits significant variation on multiannual time scales. Advance knowledge of periods of high activity would be beneficial to the insurance industry as well as society in general. Previous studies have shown that climate models initialized with current oceanic and atmospheric conditions, known as decadal prediction systems, are skillful at predicting North Atlantic hurricane activity averaged over periods of two to ten years. We show that this skill also translates into skillful predictions of real-world U.S. hurricane damage. Using such systems, we have developed a prototype climate service for the insurance industry giving probabilistic forecasts of five-year-mean North Atlantic hurricane activity, measured by the total accumulated cyclone energy index, and five-year-total U.S. hurricane damage given in U.S. dollars. Rather than tracking hurricanes in the decadal systems directly, the forecasts use a relative temperature index known to be strongly linked to hurricane activity. Statistical relationships based on past forecasts of the index and observed hurricane activity and U.S. damage are then used to produce probabilistic forecasts. The predictions of hurricane activity and U.S. damage for the period twenty twenty to twenty-four are high, with approximately ninety-five percent probabilities of being above average. We note that skill in predicting the temperature index on which the forecasts are based has declined in recent years. More research is therefore needed to understand under which conditions the forecasts are most skillful.

SIGNIFICANCE STATEMENT: The purpose of this article is to explain the science and methods behind a recently developed prototype climate service that uses initialized climate models to give probabilistic forecasts of five-year-mean North Atlantic Ocean hurricane activity, as well as five-year-total associated U.S. hurricane damage. Although skill in predicting North Atlantic hurricane activity on this time scale has been known for some time, a key result in this article is showing that this also leads to predictability in real-world damage. These forecasts could be of benefit to the insurance industry and to society in general.

One. Introduction

When North Atlantic Ocean hurricanes reach land, the impacts can be devastating, including loss of life and widespread destruction of homes and infrastructure. They are also one of the leading causes of global insured losses: for example, in twenty seventeen, Hurricanes Harvey, Irma, and Maria contributed more than sixty percent of total global insured losses including all human-made and natural disasters, and Hurricane Katrina in two thousand five has the highest insured loss on record for a single event eighty-two billion dollars indexed to twenty seventeen.

North Atlantic hurricane activity is known to exhibit multiannual time scale variation.

example, there was notably low hurricane activity in the nineteen seventies to nineteen eighties, with associated low U.S. hurricane damage followed by a very active and damaging period from the mid-nineteen nineties to mid-two thousands. Prediction of hurricanes on multiannual time scales is therefore of potential use to insurance companies, allowing them to better prepare for periods of high activity. The five-year time scale is chosen in particular as it smooths out annual peaks in activity, and, since legislation prevents large swings in pricing on interannual time scales, it can therefore be used to inform longer-term pricing strategies. It also captures decadal variability, informing insurers how the current climate may differ from their historical records. In fact, following the costly two thousand four and two thousand five hurricane seasons, three major global catastrophe model vendors developed near-term five-year hurricane predictions for use by the insurance industry, demonstrating the clear market interest in predictions on this time scale. These predictions used expert elicitation, statistical models, and sea surface temperature trends, but when the high activity predicted for two thousand six to two thousand ten failed to materialize, two of the companies abandoned their efforts in this area.

To our knowledge, the insurance industry has not yet made use of initialized decadal predictions using physically based climate models, which in the following years were shown to be highly skillful in predicting North Atlantic tropical storm and hurricane activity. The skill comes from both external forcing and initialization with the current state of the ocean and atmosphere. For external forcing, the high anthropogenic aerosol levels in nineteen seventies to nineteen eighties are believed to have caused the hurricane drought in that period. Initialization, on the other hand, particularly enhances sea surface temperature skill in the North Atlantic subpolar gyre, a key region known to be related to North Atlantic tropical cyclone activity.

In this paper we describe how we have used a multimodel decadal prediction system ensemble to make probabilistic five-year forecasts of hurricane activity over the North Atlantic basin measured by the accumulated cyclone energy index and the associated U.S. damage measured in U.S. dollars, adjusted to twenty twenty. Rather than tracking tropical cyclones or hurricanes in the models directly, the forecasts use a relative temperature index known to be strongly linked to hurricane activity. An important aspect of this work is that the index is predicted from the fundamental dynamics of the climate model, unlike the aforementioned near-term predictions developed by the insurance industry that used statistical methods to predict sea surface temperatures. Statistical relationships between past forecasts hindcasts of the index and observed hurricane activity and U.S. damage are then used to produce probabilistic forecasts of these measures.

The rest of the paper is structured as follows: In section two we describe the model and observational data used for this study, and in section three we outline the statistical verification methods used. Section four describes the methods used to generate the ACE and damage forecasts and gives an assessment of their skill, and describes development of the final forecast product. In section five we discuss the limitations of the predictions and present the conclusions.

Two. Data

B. Hurricane and loss data

Three. Verification methods

Four. ACE and U.S. damage forecasts

a. Relative temperature index

B. ACE forecasts

c. U.S. damage forecasts

d. Forecast product

Five. Discussion and conclusions

Overview

The paper outlines a climate service leveraging initialized decadal prediction systems to forecast five-year projections of North Atlantic hurricane activity and associated U.S. damages. It aims to provide the insurance industry with valuable insights into potential high-activity periods to aid in risk management and pricing strategies.

Key Points

1The document presents a climate service for predicting hurricane activity and damage
2It highlights the role of initialized climate models in offering accurate forecasts
3Predictions indicate high likelihood of above-average hurricane activity for 2020-2024
4The forecasts are based on a relative temperature index linked to hurricane occurrences
5Ongoing research is emphasized to improve prediction skill for future forecasts.

Details

Authors: Julia F. Lockwood, Nick Dunstone, Leon Hermanson, Geoffrey R. Saville, Adam A. Scaife, Doug Smith, Hazel E. Thornton
Category: Environmental Studies

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