Description
Extreme precipitation events, including heavy rains and floods, have profound economic impacts, causing widespread damage to infrastructure, agriculture, and homes. The immediate costs of repair and recovery can be substantial, disrupting transportation, utilities, and business operations. The extreme precipitation product identifies areas across that have historically had the highest risk of extreme precipitation.
Technical Description
The global Extreme Precipitation Historical Risk v2 product captures the historical risks of extreme precipitation events across the globe. This product identifies extreme precipitation events characterized by both extreme absolute magnitude and extreme relative to the typical precipitation patterns of a specific location. For instance, while London, UK may experience frequent rain events, they are less common in Phoenix, US. To achieve this, thresholds were established based on relevant scientific literature. This product can be used to assess the frequency of extreme precipitation at different locations, or to identify relative risk across different regions at a single time horizon.
This dataset contains the following fields:
- extreme_precipitation_frequency: Frequencies of extreme precipitation occurrence at pixel locations over the historical baseline period used for calculation. This looks at the frequencies of extreme precipitation occurrence at pixel locations over the period of record used for calculation. For instance, a value of 0.5 would indicate that half of the days were under extreme precipitation conditions for that location. This is a value between 0.0 and 1.0.
- extreme_precipitation_risk_class: The extreme precipitation risk classification for each value. Values are integers from 1 to 5 representing the following classes: Very Low Risk (1), Low Risk (2), Moderate Risk (3), High Risk (4), and Very High Risk (5). Values are categorized using the 44th, 67th, 84th, and 94th percentiles of the extreme_precipitation_frequency field, exclusive of '0' values.