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- H31I-01: How Uncertain Are Our Estimates of Rare Precipitation Extremes? A Global Assessment of Data Injustice Using Station and Gridded Data
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NOLA CC
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Trinish Chatterjee, Columbia University (First Author, Presenting Author)
Radley Horton, Columbia University
Understanding the intensity of very rare extreme rainfall events is critical for flood planning and climate risk management. “Return periods” are commonly used to estimate how likely it is for a major storm to occur, such as a “1-in-5-year” or '1-in-100-year' rainfall. However, these estimates can be very uncertain, especially in parts of the world with few weather stations. This uncertainty may affect decision-making in regions that are already highly vulnerable to climate extremes. This study investigates how confident we can be in global estimates of these statistics for rainfall extremes. We use both station-based observations and gridded data products that fill in gaps where stations are missing, and account for changing extreme statistics in a warming world as well (i.e. stationary and non-stationary approaches). We plan to identify just how uncertain our estimates for return values can be based on data availability in leading publicly-available data products. We also compare extreme rainfall with extreme heat, which is often easier to quantify. Our findings aim to highlight areas of the world where rainfall extremes are most uncertain, and to emphasize the continued importance of maintaining strong station networks to “ground-truth” global climate datasets used in risk planning.
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