Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida
Abstract
Abstract The present work evaluates historical precipitation and its indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) in suites of dynamically and statistically downscaled regional climate models (RCMs) against NOAA’s Global Historical Climatology Network Daily (GHCN-Daily) dataset over Florida. The models examined here are: (1) nested RCMs involved in the North American CORDEX (NA-CORDEX) program, (2) variable resolution Community Earth System Models (VR-CESM), (3) Coupled Model Intercomparison Project phase 5 (CMIP5) models statistically downscaled using localized constructed analogs (LOCA) technique. To quantify observational uncertainty, three in situ-based (PRISM, Livneh, CPC) and three reanalysis (ERA5, MERRA2, NARR) datasets are also evaluated against the station data. The reanalyses and dynamically downscaled RCMs generally underestimate the magnitude of the monthly precipitation and the frequency of the extreme rainfall in summer. The models forced with CanESM2 miss the phase of the seasonality of extreme precipitation. All models and reanalyses severely underestimate both the mean and interannual variability of mean wet-day precipitation (SDII), consecutive dry days (CDD), and overestimate consecutive wet days (CWD). Metric analysis suggests large uncertainty across NA-CORDEX models. Both the LOCA and VR-CESM models perform better than the majority of models. Overall, RegCM4 and WRF models performmore »
- Publication Date:
- Research Org.:
- Univ. of California, Davis, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC); USDA
- OSTI Identifier:
- 1827222
- Alternate Identifier(s):
- OSTI ID: 1976623
- Grant/Contract Number:
- SC0016605
- Resource Type:
- Published Article
- Journal Name:
- Climate Dynamics
- Additional Journal Information:
- Journal Name: Climate Dynamics Journal Volume: 58 Journal Issue: 5-6; Journal ID: ISSN 0930-7575
- Publisher:
- Springer Science + Business Media
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; ETCCDI precipitation indices; regional climate models precipitation assessment; ERA5; NARR; MERRA2; NA-CORDEX; LOCA; Florida extreme precipitation
Citation Formats
Srivastava, Abhishekh Kumar, Grotjahn, Richard, Ullrich, Paul Aaron, and Zarzycki, Colin. Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida. United States: N. p., 2021.
Web. doi:10.1007/s00382-021-05980-w.
Srivastava, Abhishekh Kumar, Grotjahn, Richard, Ullrich, Paul Aaron, & Zarzycki, Colin. Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida. United States. https://doi.org/10.1007/s00382-021-05980-w
Srivastava, Abhishekh Kumar, Grotjahn, Richard, Ullrich, Paul Aaron, and Zarzycki, Colin. Fri .
"Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida". United States. https://doi.org/10.1007/s00382-021-05980-w.
@article{osti_1827222,
title = {Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida},
author = {Srivastava, Abhishekh Kumar and Grotjahn, Richard and Ullrich, Paul Aaron and Zarzycki, Colin},
abstractNote = {Abstract The present work evaluates historical precipitation and its indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) in suites of dynamically and statistically downscaled regional climate models (RCMs) against NOAA’s Global Historical Climatology Network Daily (GHCN-Daily) dataset over Florida. The models examined here are: (1) nested RCMs involved in the North American CORDEX (NA-CORDEX) program, (2) variable resolution Community Earth System Models (VR-CESM), (3) Coupled Model Intercomparison Project phase 5 (CMIP5) models statistically downscaled using localized constructed analogs (LOCA) technique. To quantify observational uncertainty, three in situ-based (PRISM, Livneh, CPC) and three reanalysis (ERA5, MERRA2, NARR) datasets are also evaluated against the station data. The reanalyses and dynamically downscaled RCMs generally underestimate the magnitude of the monthly precipitation and the frequency of the extreme rainfall in summer. The models forced with CanESM2 miss the phase of the seasonality of extreme precipitation. All models and reanalyses severely underestimate both the mean and interannual variability of mean wet-day precipitation (SDII), consecutive dry days (CDD), and overestimate consecutive wet days (CWD). Metric analysis suggests large uncertainty across NA-CORDEX models. Both the LOCA and VR-CESM models perform better than the majority of models. Overall, RegCM4 and WRF models perform poorer than the median model performance. The performance uncertainty across models is comparable to that in the reanalyses. Specifically, NARR performs poorer than the median model performance in simulating the mean indices and MERRA2 performs worse than the majority of models in capturing the interannual variability of the indices.},
doi = {10.1007/s00382-021-05980-w},
journal = {Climate Dynamics},
number = 5-6,
volume = 58,
place = {United States},
year = {Fri Oct 22 00:00:00 EDT 2021},
month = {Fri Oct 22 00:00:00 EDT 2021}
}
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