Explaining the Spatial Pattern of U.S. Extreme Daily Precipitation Change

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  • 1 NOAA/Earth System Research Laboratory, Boulder, Colorado
  • 2 NOAA/Earth System Research Laboratory, Boulder, Colorado, and University of Colorado, Cooperative Institute for Research in Environmental Sciences, Boulder, Colorado
  • 3 University of Hawai’i at Mānoa, Honolulu, Hawai‘i
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Abstract

Observed United States trends in the annual maximum 1-day precipitation (RX1day) over the last century consist of 15% - 25% increases over the East and 10% decreases over the Far West. This heterogeneous trend pattern departs from comparatively uniform observed increases in precipitable water over the contiguous U.S. Here we use an event attribution framework involving parallel sets of global atmospheric model experiments with and without climate change drivers to explain this spatially diverse pattern of extreme daily precipitation trends. We find that RX1day events in our model ensembles respond to observed historical climate change forcing differently across the U.S. with 5%-10% intensity increases over the East but no appreciable change over the West. This spatially diverse forced signal is broadly similar among three models used, and is positively correlated with the observed trend pattern. Our analysis of model and observations indicates the lack of appreciable RX1day signals over the West is likely due to dynamical effects of climate change forcing – via a wintertime atmospheric circulation anomaly that suppresses vertical motion over the West – largely cancelling thermodynamic effects of increased water vapor availability. The large magnitude of eastern U.S. RX1day increases is unlikely a symptom of a regional heightened sensitivity to climate change forcing. Instead, our ensemble simulations reveal considerable variability in RX1day trend magnitudes arising from internal atmospheric processes alone, and we argue that the remarkable observed increases over the East has most likely resulted from a superposition of strong internal variability with a moderate climate change signal. Implications for future changes in U.S. extreme daily precipitation are discussed.

Corresponding Author: Dr Martin Hoerling martin.hoerling@noaa.gov

Abstract

Observed United States trends in the annual maximum 1-day precipitation (RX1day) over the last century consist of 15% - 25% increases over the East and 10% decreases over the Far West. This heterogeneous trend pattern departs from comparatively uniform observed increases in precipitable water over the contiguous U.S. Here we use an event attribution framework involving parallel sets of global atmospheric model experiments with and without climate change drivers to explain this spatially diverse pattern of extreme daily precipitation trends. We find that RX1day events in our model ensembles respond to observed historical climate change forcing differently across the U.S. with 5%-10% intensity increases over the East but no appreciable change over the West. This spatially diverse forced signal is broadly similar among three models used, and is positively correlated with the observed trend pattern. Our analysis of model and observations indicates the lack of appreciable RX1day signals over the West is likely due to dynamical effects of climate change forcing – via a wintertime atmospheric circulation anomaly that suppresses vertical motion over the West – largely cancelling thermodynamic effects of increased water vapor availability. The large magnitude of eastern U.S. RX1day increases is unlikely a symptom of a regional heightened sensitivity to climate change forcing. Instead, our ensemble simulations reveal considerable variability in RX1day trend magnitudes arising from internal atmospheric processes alone, and we argue that the remarkable observed increases over the East has most likely resulted from a superposition of strong internal variability with a moderate climate change signal. Implications for future changes in U.S. extreme daily precipitation are discussed.

Corresponding Author: Dr Martin Hoerling martin.hoerling@noaa.gov
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