The ASSA Climate Index is derived based on daily, high-resolution gridded Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), the Agricultural ECMWF Reanalysis 5 (AgERA5) and the ECMWF Reanalysis 5 (ERA5) data. Each component — extreme maximum temperatures, extreme minimum temperatures, precipitation, drought, hail, wildfire and a composite index — is evaluated on a grid level. The index components are expressed as standardised anomalies when comparing to the base period of 1 January 1991 to 31 December 2020. It measures the occurrence of extreme weather phenomena by calculating the fraction of exceedances per month that surpass a baseline threshold, providing a clear indication of unusual weather patterns.
We leverage the global gridded datasets AgERA5, ERA5 and CHIRPS. AgERA5 and ERA5 are produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) as part of the Copernicus Climate Change Service (C3S), and CHIRPS by the Climate Hazards Center (CHC) at the University of California, Santa Barbara.
For detailed information on the calculation of the ASSA Climate Index components, please download the technical documentation here.
The ASSA Climate Index measures standardized exceedances, which are expressed as the number of standard deviations a current value is above or below the baseline mean. This baseline mean is calculated from historical data spanning from 1991 to 2020, focusing on the typical frequency of extreme weather conditions for each month. By standardizing these exceedances, the index provides a clear, quantifiable measure of how weather conditions compare to historical norms. This approach allows users to easily assess climate conditions over time and in the context of established climate patterns, making it an invaluable industry tool for assessing and responding to climate risks. The ASSA Climate Index is designed for a wide array of applications and is intended to be used by actuaries, risk managers, policy makers, researchers.
Tracks anomalies based on the frequency of hot spells that exceed 3 consecutive days, vital for understanding the impact of heat stress on health and agriculture.
Tracks anomalies based on the frequency of cold spells that exceed 3 consecutive days, essential for risk assess- ments in energy demand, public health and agriculture.
Measures anomalies in 5-day cumulative rainfall measurements, highlighting the frequency of extreme precipitation events.
Assesses drought conditions based on the cumulative 365-day rainfall, crucial for water resource management and agricultural planning.
Tracks anomalies based on the frequency of days with atmospheric conditions favourable to hail, combining atmospheric instability, deep-layer wind shear and freezing-level height, relevant to property, motor and crop risk.
Tracks anomalies based on the frequency of days with hot, dry and windy fire weather, combining the Hot-Dry-Windy Index and the Canadian Fire Weather Index, relevant to property, agricultural and forestry risk.
Combines the standardized anomalies of the temperature, precipitation, drought and hail components to provide a composite view of climate extremes. Wildfire is not included, as it largely duplicates the Extreme Max Temperature signal.
The ASSA Climate Index quantifies the frequency of extreme weather conditions such as high and low temperatures, heavy rainfall, droughts, and conditions conducive to hail and wildfire. Each component reflects deviations from long-term averages, helping users understand and anticipate climate-related risks.
This data can be utilized for risk assessment, policy making, academic research, and business planning. It helps in understanding climate trends, preparing for extreme weather events, and developing strategies to mitigate climate-related impacts. With interactive data visualization tools and the option to download data, users of the ASSA Climate Index website have robust resources at their disposal. Additionally, users can link the downloaded data to their own exposure and risk data, enabling robust and localized climate impact analysis tailored to specific assets, sectors, or geographies.
The index is updated seasonally, ensuring that the data remains current and relevant for all users. This frequency supports timely analyses and decision-making processes.