The North Atlantic Hurricane Model is part of EQECAT's global multi-peril catastrophe modeling platform, RQE™ (Risk Quantification & Engineering). The risk model is updated biennially and continues to set standards of scientific rigor in tropical cyclone risk modeling. The model can be used for:
Hurricane risk in the north Atlantic ocean and surrounding region accounts for the largest portion of catastrophe insurance premiums in the world. In 2003, EQECAT introduced the North Atlantic Hurricane Model - the first comprehensive basin-wide model covering the US, the Caribbean, Bermuda, and the Gulf of Mexico to address regional risk quantification and correlation for this peril.
The North Atlantic Hurricane Model features include:
The catastrophe risk model covers:
For the US: Model results can be calculated for wind only or wind and hurricane induced flooding. Hurricane flooding consists of high resolution characterization of storm surge and the incremental damage due to hurricane induced rainfall and associated flooding.
EQECAT's North Atlantic Hurricane Model is a probabilistic model that uses historical hurricane data available from 1900 to 2009. Its robust probabilistic set includes approximately 110,000 events. In addition, 300,000 simulation years cover gaps in the historical data set to provide a consistent, credible, and realistic view of hurricane risk, particularly for low-probability, high-consequence events. The model also accounts for temporal clustering of hurricane events. The probabilistic set is evaluated against the historical data set for completeness and validation.
Hurricane landfall intensity and locations vary by region and are based on climatology. EQECAT’s unique approach to uncertainty is especially relevant to regions experiencing infrequent hurricane landfalls. Our robust methodology, which retains the full breadth of uncertainty through each step of the model calculation and reports multiple loss outcomes for any one event, allows re/insurers to avoid surprises, gain confidence in decisions related to low probability events that have significant financial consequences, and set rational expectations about risk.
The model provides a near-term view of risk based on warm Atlantic multi-decadal oscillation (AMO) time series. EQECAT research has identified a strong link between the cycles of the AMO and the risk of catastrophic hurricane winds onshore for the continental US. Partitioning the historic data set into “warm” and “cold” years has enabled modelers to develop a conditional “near-term” model that reduces the uncertainty in the assessment of tropical storm risk. The strong increase in major Atlantic storms that are formed and supported by the warm AMO phase preferentially affect the US Atlantic Coast, most notably, Florida, the Southeast, and Mid-Atlantic states. Currently, the North Atlantic hurricane activity is in the warm AMO cycle, and the model will be attuned to reflect the cool AMO time series when the cool phase of the AMO sets in.
The North Atlantic Hurricane Model uses NOAA/NWS methods enhanced by a number of additional state-of-the-art components to calculate the geographic pattern of peak gust winds and their accompanying probabilistic distributions for each event. The model incorporates all of the key hurricane parameters probabilistically, including:
The enhanced wind field model is a high-resolution time-stepping model, computing the wind field at 15-minute intervals and capturing 16 wind directions, providing refined treatment of land use and land cover information. The model calculates wind speed at specific latitudes and longitudes in coastal areas. The surface roughness modifications applied are based on land use/land cover data at a 30-meter resolution, and topographic roughness is applied based on data at a 500-meter resolution. The gust factor is dependent on surface roughness conditions and is also applied probabilistically.
The storm surge model is a numerical finite-element model, considering bathymetry and wind stress. For each historical or stochastic event, the probabilistic distribution of storm surge inundation depth is calculated for each location using the probabilistic distributions of all significant storm and location parameters. Inundation is modeled in two zones: the high-velocity zone where wave action and debris can severely damage structures, and farther inland, where the primary concern is flooding as opposed to structural damage. Flooding as a result of hurricane rainfall is included. The rainfall footprint is based on the parameters of the storm, distance to coast, location, and historical flood damage data.
EQECAT’s demand Surge is based on the demand and supply for construction materials and labor in the affected region. It is defined as the response of the construction labor and materials market (supply) to a massive increase in the need for materials and labor for immediate repairs (demand). In addition, the economic factors undergo constant change. EQECAT regularly updates the supply-side database for demand surge.
EQECAT uses an engineering approach, claims data, and expert opinion to develop the vulnerability functions within the model. Damage from wind and storm surge is calculated using a series of vulnerability functions specific to construction type and occupancy. Vulnerability functions are created to calculate damage impacts for different building heights (low-, mid-, and high-rise). EQECAT vulnerability functions are based on historically observed damage, experimental research conducted by Professors Kishor Mehta and James McDonald at Texas Tech, and structural calculations performed by EQECAT engineers.
| Claims data is from all major storms, including: | ||||
|
Hugo (1989) |
Andrew (1992) |
Charley (2004) |
Frances (2004) |
Ivan (2004) |
|
Jeanne (2004) |
Katrina (2005) |
Rita (2005) |
Wilma (2005) |
Ike (2008) |
The model also takes into account regional impacts of the 2001 Florida Building Code as required by Florida Commission on Hurricane Loss Projection Methodology certification.
Specifications for the North Atlantic Hurricane Model include:
Separate, independent vulnerability functions are used for calculating losses for each coverage type. Time-element vulnerability functions are a function of structural and contents damage. The model calculates damage to:
Includes detailed risk differentiation, enabling import and evaluation of risks geocoded to:
When input data is provided at aggregate levels, the model adds refinement to loss results by disaggregating data to finer resolutions points based on weighted distribution of values for the purpose of analysis and risk estimation
EQECAT regularly updates the quality of information captured for structure types and building design codes to ensure that they are accurately represented in the model. The North Atlantic Hurricane Model incorporates claims data from over 13 million policies, with a total exposure of about $2.2 trillion, for 18 hurricanes since 1983. The model also leverages claims data from all major storms 1954 – 1994, via the Natural Hazard Research Service (NHRS). In addition, the model incorporates new observations from post-disaster field surveys to calibrate the model.
The hazard and vulnerability modules have undergone stringent review by internationally-recognized scientific experts. Old Dominion University NOAA visiting scientist Robert Tuleya, formerly with the Geophysical Fluid Dynamics Laboratory Hurricane group and presently developing and upgrading the next generation Hurricane Weather and Research Forecast system (HWRF), reviewed EQECAT’s hurricane wind field model.
Lines of business include:
The model is certified by the Florida Commission Hurricane Loss Projection Methodology (FCHLPM) since the inception of the certification process in 1997.
With a full suite of representative structure types, and dozens of occupancy categories for each line of business, the model differentiates risk across hundreds of combinations, and allows only realistic pairings of occupancy and construction. A common set of structure types and occupancies is available worldwide. Our technical documentation provides guidance on structure type selection.
Risk metrics include OEP and AEP loss exceedance curves, AAL, TVAR, and simulations of historical events. Reporting of results supports multiple levels of refinement such as:
The landfall series reports provide risk exposure and loss estimates based on storm severity. Different peril components (wind only, wind and flood) can be modeled to obtain model results with or without the demand surge component.
In addition, RQE’s Year Loss Table (YLT) uniquely features three-dimensional output:
Instead of reporting mean losses with standard deviations, each loss in the YLT represents one possible outcome for the associated event. This allows users to retain the full distribution of uncertainty when using model output in dynamic financial analysis and capital modeling. Conventional event loss results and other risk metrics can be derived from the YLT with arithmetic or simple database queries. YLT and event loss results are supported at the portfolio level. Other risk metrics are supported at multiple levels of refinement: from total aggregate portfolio results to detailed output by policy and site.
All major insurance policy structures and reinsurance treaty types are modeled.
The model provides a wide variety of output options, including several statistical reports.
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North Atlantic Hurricane Model Fact Sheet
(PDF 415 KB)
June 20, 2011
CatWatch Report
Beatriz and Tropical Storm Six
North Atlantic Hurricane Model Near-Term Model
(PDF 649 KB)