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An ensemble of bias-adjusted CMIP6 climate simulations based on a high-resolution North American reanalysis.


ABSTRACT: ESPO-G6-R2 v1.0 is a set of statistically downscaled and bias-adjusted climate simulations based on the Coupled Model Intercomparison Project 6 (CMIP6) models. The dataset is composed of daily timeseries of three variables: daily maximum temperature, daily minimum temperature and daily precipitation. Data are available from 1950 to 2100 over North America. The simulation ensemble is comprised of 14 models driven by two emissions scenarios (SSP2-4.5 and SSP3-7.0). In this paper, we describe the workflow used for the bias-adjustment, which relies on the detrended quantile mapping method and the Regional Deterministic Reforecast System (RDRS) v2.1 reference dataset. Using the framework defined in the VALUE project, we show the improvements made by the bias-adjustment on marginal, temporal and multivariate aspects of the data. We also verify that the bias-adjusted climate data have similar climate change signal to the original climate model simulations. Finally, we provide guidance to users on how to use this dataset.

SUBMITTER: Lavoie J 

PROVIDER: S-EPMC10784550 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

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An ensemble of bias-adjusted CMIP6 climate simulations based on a high-resolution North American reanalysis.

Lavoie Juliette J   Bourgault Pascal P   Smith Trevor James TJ   Logan Travis T   Leduc Martin M   Caron Louis-Philippe LP   Gammon Sarah S   Braun Marco M  

Scientific data 20240111 1


ESPO-G6-R2 v1.0 is a set of statistically downscaled and bias-adjusted climate simulations based on the Coupled Model Intercomparison Project 6 (CMIP6) models. The dataset is composed of daily timeseries of three variables: daily maximum temperature, daily minimum temperature and daily precipitation. Data are available from 1950 to 2100 over North America. The simulation ensemble is comprised of 14 models driven by two emissions scenarios (SSP2-4.5 and SSP3-7.0). In this paper, we describe the w  ...[more]

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