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Reassessing the Value of Regional Climate Modeling Using Paleoclimate Simulations
Author(s) -
Armstrong Edward,
Hopcroft Peter O.,
Valdes Paul J.
Publication year - 2019
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2019gl085127
Subject(s) - gcm transcription factors , climatology , climate model , general circulation model , paleoclimatology , proxy (statistics) , environmental science , mesoscale meteorology , climate change , storm , geology , meteorology , atmospheric sciences , geography , computer science , oceanography , machine learning
Regional climate models (RCMs) are often assumed to be more skillful compared to lower‐resolution general circulation models (GCM). However, RCMs are driven by input from coarser resolution GCMs, which may introduce biases. This study employs versions of the HadAMB3 GCM at three resolutions (>50 km) to investigate the added value of higher resolution using identically configured simulations of the preindustrial (PI), mid‐Holocene, and Last Glacial Maximum. The RCM shows improved PI climatology compared to the coarse‐resolution GCM and enhanced paleoanomalies in the jet stream and storm tracks. However, there is no apparent improvement when compared to proxy reconstructions. In the high‐resolution GCM, accuracy in PI climate and atmospheric anomalies are enhanced despite its intermediate resolution. This indicates that synoptic and mesoscale features in a RCM are influenced by its low‐resolution input, which impacts the simulated climatology. This challenges the paradigm that RCMs improve the representation of climate conditions and change.