Table 2 Details of the 16 GCMs from CMIP5 downscaled and bias-corrected by the MACA project.

From: Basin-informed flood frequency analysis using deep learning exhibits consistent projected regional patterns over CONUS

Model name

Model agency

Realization used

bcc-csm1-1

Beijing Climate Center, China Meteorological Administration

r1i1p1

bcc-csm1-1-m

Beijing Climate Center, China Meteorological Administration

r1i1p1

BNU-ESM

College of Global Change and Earth System Science, Beijing Normal University, China

r1i1p1

CanESM2

Canadian Centre for Climate Modeling and Analysis

r1i1p1

CNRM-CM5

National Centre of Meteorological Research, France

r1i1p1

CSIRO-Mk3_6_0

Commonwealth Scientific and Industrial Research Organization/Queensland Climate Change Centre of Excellence, Australia

r1i1p1

GFDL-ESM2G

Geophysical Fluid Dynamics Laboratory Earth System Model version 2 M

r1i1p1

HadGEM2-ES365

Met Office Hadley Center, UK

r1i1p1

HadGEM2-CC365

Met Office Hadley Center, UK

r1i1p1

inmcm4

Institute for Numerical Mathematics, Russia

r1i1p1

IPSL-CM5A-LR

Institute Pierre Simon Laplace, France

r1i1p1

MIROC-ESM

Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute (The University of Tokyo), and National Institute for Environmental Studies

r1i1p1

MIROC-ESM-CHEM

Japan Agency for Marine-Earth Science and Technology, Atmosphere and Ocean Research Institute (The University of Tokyo), and National Institute for Environmental Studies

r1i1p1

MIROC5

Atmosphere and Ocean Research Institute (The University of Tokyo), National Institute for Environmental Studies, and Japan Agency for Marine-Earth Science and Technology

r1i1p1

MRI-CGCM3

Meteorological Research Institute, Japan

r1i1p1

NorESM1-M

Norwegian Climate Center, Norway

r1i1p1