Next Generation Hurricane Model

Save billions for your company

Next Generation Hurricane Model

Save billions for your company

The Problem

Long-term catastrophe risk assessment lacks real-time capabilities, and its key assumptions are being challenged

Current catastrophe models primarily rely on the construction of historical event sets, which involve examining past events and assuming that catastrophe patterns remain stable over the long term. Ultimately, premium pricing is determined based on historical loss data. This pricing approach does not explore the intrinsic mechanisms of meteorology, making it difficult to adapt to the uncertainties brought about by climate change and unable to use current realities to make predictions about the future.

Inadequate disaster prevention and loss reduction services for corporate clients, with insufficient advance warning time

Currently, public meteorological service departments struggle to provide accurate and longer-lead-time extreme weather warnings. This results in slower catastrophe response from insurance companies, hindering effective disaster prevention, loss reduction, and customer service quality.

Our Approach

Short-term deterministic forecasting of multi-level atmospheric and surface variables

Provides a 15-day global weather forecast with 6-hour intervals and a 25 km resolution. The model predictions cover 69 meteorological elements, spanning 13 key isobaric levels for upper-air parameters as well as surface weather elements.

Long-term probabilistic forecasting of wind speed distributions

Provides the occurrence probability and severity distribution of hurricane occurrences for the next year, assisting in insurance and reinsurance pricing, and enabling proactive planning for other related business arrangements.

Long-term Application: 2017 Hurricane Activity Forecast

The figure shows the difference in wind speed at the 99th percentiles between 2017 and 2016. Red indicates a higher hurricane risk in 2017 compared to 2016. As clearly shown in the figure, the Gulf of Mexico faced a higher hurricane risk in 2017 than in 2016, and this prediction was validated by subsequent facts.

Imagine if your company had used our model back in 2016 - you could have pull back from the Gulf and saved millions during "HIM" in 2017

Catastrophes AI

Next Generation Hurricane Model

Next Generation Hurricane Model

The Problem

Long-term catastrophe risk assessment lacks real-time capabilities, and its key assumptions are being challenged

Inadequate disaster prevention and loss reduction services for corporate clients, with insufficient advance warning time

Our Approach

Short-term deterministic forecasting of multi-level atmospheric and surface variables

Long-term probabilistic forecasting of wind speed distributions

Short-term Application: 2017 Hurricane Track Prediction

Long-term Application: 2017 Hurricane Activity Forecast

Contact Us

Get in Touch

Interested in how we provide the data?

Catastrophes AI

Next Generation Hurricane Model

Next Generation Hurricane Model

The Problem

Long-term catastrophe risk assessment lacks real-time capabilities, and its key assumptions are being challenged

Inadequate disaster prevention and loss reduction services for corporate clients, with insufficient advance warning time

Our Approach

Short-term deterministic forecasting of multi-level atmospheric and surface variables

Long-term probabilistic forecasting of wind speed distributions

Short-term Application: 2017 Hurricane Track Prediction

Long-term Application: 2017 Hurricane Activity Forecast

Contact Us

Get in Touch

Interested in how we provide the data?

Catastrophes AI

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