Much of our current risk assessment, especially for extreme events and natural disasters, comes from the assumption that the likelihood of future extreme events can be predicted based on the past. However, as global temperatures rise, established climate ranges may no longer be applicable, as historic records for extremes such as heat waves and floods may no longer accurately predict the changing future climate. To assess extremes (present‐day and future) over the contiguous United States, we used NOAA's Climate Extremes Index (CEI), which evaluates extremes in maximum and minimum temperature, extreme one‐day precipitation, days without precipitation, and the Palmer Drought Severity Index (PDSI). The CEI is a spatially sensitive index that uses percentile‐based thresholds rather than absolute values to determine climate “extremeness” and is thus well‐suited to compare extreme climate across regions. We used regional climate model data from the North American Regional Climate Change Assessment Program (NARCCAP) to compare a late 20th century reference period to a mid‐21st century “business as usual” (SRES A2) greenhouse gas‐forcing scenario. Results show a universal increase in extreme hot temperatures across all models, with annual average maximum and minimum temperatures exceeding 90th percentile thresholds consistently across the continental United States. Results for precipitation indicators have greater spatial variability from model to model, but indicate an overall movement towards less frequent but more extreme precipitation days in the future. Due to this difference in response between temperature and precipitation, the mid‐21st century CEI is primarily an index of temperature extremes, with 90th percentile temperatures contributing disproportionately to the overall increase in climate extremeness. We also examine the efficacy of the PDSI in this context in comparison to other drought indices.
Quantitative simulation of precipitation in current climate has been an ongoing challenge for global climate models. Despite serious biases in correctly simulating probabilities of extreme rainfall events, model simulations under global warming scenarios are routinely used to provide estimates of future changes in these probabilities. To minimize the impact of model biases, past literature tends to evaluate fractional (instead of absolute) changes in probabilities of precipitation extremes under the assumption that fractional changes would be more reliable. However, formal tests for the validity of this assumption have been lacking. Here we evaluate two measures that address properties important to the correct simulation of future fractional probability changes of precipitation extremes, and that can be assessed with current climate data. The first measure tests climate model performance in simulating the characteristic shape of the probability of occurrence of daily precipitation extremes and the second measure tests whether the key parameter governing the scaling of this shape is well reproduced across regions and seasons in current climate. Contrary to concerns regarding the reliability of global models for extreme precipitation assessment, our results show most models lying within the current range of observational uncertainty in these measures. Thus, most models in the Coupled Model Intercomparison Project Phase 6 ensemble pass two key tests in current climate that support the usefulness of fractional measures to evaluate future changes in the probability of precipitation extremes.
more » « less- Award ID(s):
- 1936810
- PAR ID:
- 10362220
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research Letters
- Volume:
- 16
- Issue:
- 2
- ISSN:
- 1748-9326
- Page Range / eLocation ID:
- Article No. 024017
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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