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Filtering of GCM simulated Sahel precipitation
Author(s) -
Tippett Michael K.
Publication year - 2006
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 - 10.1029/2005gl024923
Subject(s) - gcm transcription factors , climatology , environmental science , sea surface temperature , precipitation , general circulation model , coherence (philosophical gambling strategy) , filter (signal processing) , atmosphere (unit) , geology , meteorology , climate change , mathematics , oceanography , geography , computer science , statistics , computer vision
Atmospheric general circulation models (GCMs) forced with observed sea surface temperature (SST) reproduce some aspects of observed Sahel rainfall variability, particularly decadal variability. Here a filter based on signal‐to‐noise (S/N) EOFs is applied to seven GCM simulations of Sahel precipitation to extract SST‐forced variability. Using filter coefficients based on GCM estimates of internal variability has limited, though positive, impact on simulation skill. Additional removal of empirically identified model error improves the representation of both decadal and interannual variability. The model error shows some coherence across the seven GCMs and correlates with local Atlantic SST. We hypothesize that the model error is related to the representation of ocean‐atmosphere interactions in the SST‐forced GCM simulations.