Towards Quantifying the Uncertainty in Estimating Observed Scaling Rates. Issue 12 (18th June 2022)

• Record Type: Journal Article
• Authors: Ali, Haider; Fowler, Hayley J.; Pritchard, David; Lenderink, Geert; Blenkinsop, Stephen; Lewis, Elizabeth
• Is Part Of: Geophysical research letters. Volume 49:Issue 12(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-06-18
• Subjects: rain‐gauge data -- extreme precipitation -- dewpoint temperature -- quality‐control -- scaling -- observed precipitation; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2022GL099138
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: Short‐duration precipitation extremes (PE) increase at a rate of around 7%/K explained by the Clausius‐Clapeyron relationship. Previous studies show uncertainty in the extreme precipitation‐temperature relationship (scaling) due to various thermodynamic/dynamic factors. Here, we show that uncertainty may arise from the choice of data and methods. Using hourly precipitation (PPT) and daily dewpoint temperature (DPT) across 2, 905 locations over the United States, we found higher scaling for quality‐controlled data, all locations showing positive (median 6.2%/K) scaling, as compared to raw data showing positive (median 5.3%/K) scaling over 97.5% of locations. We found higher scaling for higher measurement precision of PPT (0.25 mm: median 7.8%/K; 2.54 mm: median 6.6%/K). The method that removes seasonality in PPT and DPT gives higher (with seasonality: median 6.2%/K; without seasonality: median 7.2%/K) scaling. Our results demonstrate the importance of quality‐controlled, high‐precision observations and robust methods in estimating accurate scaling for a better understanding of PE change with warming. Plain Language Summary: Studies based on precipitation observations and climate models provide evidence of an increase in short‐duration precipitation extremes both over recent decades and into the future. To understand how precipitation extremes relate to warming, the common practice is to establish the statistical relationship between extreme precipitation and temperature referred to as scaling. Theory and observations suggest that extreme precipitation increases with a rate of around 7% per one‐degree rise in temperature. However, variations in the scaling rate can be observed using different sources of data, data quality, and different scaling calculation methods. Here, we demonstrate the importance of improving the quality of the data, using fine precision precipitation measurements, and robust scaling methods to estimate accurate scaling rates. Our results have implications for understanding the changes in the occurrence of extreme precipitation with warming and therefore potential changes in the risk of flash floods. Key Points: We estimated scaling rates from hourly observed precipitation and daily dewpoint temperature over the conterminous continental United States We highlight the importance of quality‐controlled, high precision observations and robust statistical methods in estimating accurate scaling Our results have implications for a better understanding of change in extreme precipitation and flash floods with warming