Evaluation of historical CMIP6 model simulations of extreme precipitation over contiguous US regions
| Autor: | Richard Grotjahn, Abhishekh Srivastava, Paul A. Ullrich |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Atmospheric Science
Coupled model intercomparison project 010504 meteorology & atmospheric sciences Spatial and temporal variation of precipitation Geography Planning and Development 0207 environmental engineering Dry spell Climate change 02 engineering and technology Management Monitoring Policy and Law lcsh:QC851-999 01 natural sciences CMIP6 precipitation CMIP5 and CMIP6 comparison Climatology Environmental science lcsh:Meteorology. Climatology Precipitation Observational uncertainty 020701 environmental engineering ETCCDI extreme precipitation indices 0105 earth and related environmental sciences |
| Zdroj: | Weather and Climate Extremes, Vol 29, Iss, Pp 100268-(2020) |
| ISSN: | 2212-0947 |
| Popis: | Simulated historical precipitation is evaluated for Coupled Model Intercomparison Project Phase 6 (CMIP6) models using precipitation indices defined by the Expert Team on Climate Change Detection and Indices. The model indices are evaluated against corresponding indices from the CPC unified gauge-based analyses of precipitation over seven geographical regions across the contiguous US (CONUS). The regions assessed match those in recent US National Climate Assessment Reports. To estimate observational uncertainty, precipitation indices for three other observational datasets (HadEx2, Livneh and PRISM) are evaluated against the CPC analyses. Both the moderate and extreme mean precipitation intensities are overestimated over the western CONUS and underestimated in the areas of the Central Great Plains (CGP) in most CMIP6 models tested. Most CMIP6 models overestimate the mean and variability of wet spell durations and underestimate the mean and variability of dry spell durations across the CONUS. Biases in interannual variability of most of the indices have similar patterns to those in corresponding mean biases. The median and interquartile model spreads in CMIP6 model biases are clearly smaller than those in CMIP5 model biases for wet spell durations. Multimodel medians of CMIP6 (CMIP6-MMM) and CMIP5 (CMIP5-MMM) have similar biases in climatology and variability but biases tend to be smaller in CMIP6-MMM. Depending on the index, extreme precipitation is slightly better in parts of the eastern half of the CONUS in CMIP6-MMM, otherwise, the biases in climatology and variability are similar to CMIP5-MMM. CMIP6-MMM performs better than individual models and even observational datasets in some cases. Differences between observational datasets for most indices are comparable to the CMIP6 interquartile model spread. The better-performing observational and model datasets are different in different parts of the CONUS. |
| Databáze: | OpenAIRE |
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