ClimateTech startup powered by weather data

The ClimateTech startups powered by the weather data differ a lot one from another.

Here we compare the offering in one dimension - the time horizon of the product.

A few examples cited here include the nowcasting, the seasonal and the multi-year time scale.

Short-term weather predictions : "nowcasting"

Precision agriculture and wind power supply forecasts require super detailed real-time weather forecast data. Weather forecasts guide the irrigation, the timing of the construction works, and also support the real-time electricity trading. For these applications the weather data is updated every 5-to-15 minutes. The focus is typically on one single geography. The term "nowcasting" refers to this super high resolution detailed forecast for a very limited time window of less than one hour.

Seasonal climate predictions

The flood insurance pricing and agricultural commodity trading bet on seasonal time scales. Seasonal rainfall anomalies are then translated into corn yield volumes for each specific region. This is quite impressive how the seasonal forecasts for the agricultural commodities drive the global maritime transport logistics two months ahead!

Climate scientists from the leading research institutions have created very specific climate models trained to generate high quality seasonal forecasts. These models capture the teleconnections between consequent months.

Multi-year climate risk volatility in changing climate

Credit risk evaluation and asset diversification within the portfolio require a strategic vision of climate risks over much longer horizons - over years and even over decades. Forward-looking climate risk modeling is the hardest piece.

Hydropower construction, adaptation to coastal inundation due to sea level rise, planning of water retention basins for wildfire and for drought mitigation - these are the massive projects requiring the collaboration between?the governmental funds and the institutional investors.

Very long time series of climate data over 10-50-100-300 years are created and validated during the international?and governmental multi-year projects such as the Coupled Model Intercomparison Project Phase 6 (CMIP6). Super-computing capacities are required to generate the petabytes of climate data: historical and forward-looking. And even with the super-computing capacities - it takes years to run one Global Climate Model over a 300-500-year time frame. During these international experiments about 120 super-computers are kept busy full time to run the climate models.

The resulting product of the Global Climate Model - temperature - wind speed - covers the entire planet, all countries and oceans, vertically within the entire atmospheric and through the entire oceanic profile.

It is important to understand that each climate model is an institutional model (IPSL, Met Office Hadley Centre) supported by entire research community of the country. These Global Climate Models are not the home-made models (!), but the high-level national projects. The total budgets for each Global Climate Model are billions of dollars.

The climate stress testing by leading banks are based on these Global Climate Model data.

Weather Trade Net integrates this Global Climate Model data to provide the TCFD-aligned physical climate risk assessment. The hourly temperatures, wind and precipitation are recalculated into hazards - storms, floods, droughts, wildfire. The process consists of the back-testing and the forward-looking hazard detection using AI-powered algorithms. While the huge piece of the recipe - the hourly temperature - is freely available, the overall process of wildfire and flood modeling is technically a big step forward. This is where the Weather Trade Net brings the added value.

Another component of the unique offering is the comprehensible, straightforward and efficient data packaging. Weather Trade Net translates the probability of climate hazards (the return period of cold stress and heat waves) into risk metrics inspired by the insurance pricing logic : NO RISK - INSURABLE - UNINSURABLE

NO RISK means that most likely there is no need for any specific risk management process for a given hazard type, selected geography.

INSURABLE - means this type of hazard exists, it is well known, the volatility of the risk is moderate and without major "surprise" component

UNINSURABLE - means the risk transfer (hedging / insurance) would be probably either very expensive, either unavailable for this type of hazard, selected geography. This could be (a) due to permanent high risk level, or (b) due to occurrence of catastrophic events.

The technology behind each weather-driven project is a huge part of the solution. The multi-year climate risk assessment requires a powerful parallel computing. Parallel AI-powered hazard modeling puts the restrictions on the file's structure and the storage technology. The technical requirements explain why the climate data providers typically focus on one specific time frame : either the short term horizon, either the mid-term, either the long-term risk assessment. There is no one-size fits all.?

In the?context of the NET ZERO target, it happened that the vast majority (99%) of?ClimateTech startups?focus on CO2 emissions and carbon markets. So typically when you tell an investor that you are founder of a ClimateTech startup, they refer you to CO2 accounting right away.

To note, even if the carbon-related topics fall into a?ClimateTech innovation space, there is nothing about the weather data within these projects.?It is not the same exercise to calculate the corporate CO2 emissions and the flood risk for each building.

While CO2 accounting and carbon trading seem to be quite an over-saturated innovation space with?a huge competition, there is still a gap in weather-driven offering. Users have different needs (TCFD reporting, risk management, premium pricing, credit risk assessment, etc.) and need different data providers - with different data frequency, granularity (spatial resolution), metrics, spatial coverage (worldwide - vs - country level - vs - regional), etc.

Weather Trade Net aggregates the best scientific data into the risk scores to support TCFD- and CSRD-aligned corporate compliance and audit.

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