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Understanding CMIP6 Biases in the Representation of the Greater Horn of Africa Long and Short Rains
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Abstract
The societies of the Greater Horn of Africa (GHA) are vulnerable to variability in two climatologically distinct rainy seasons, the March-May ‘long‘ rains and the October-December ‘short‘ rains. Recent trends in both rainy seasons, possibly related to patterns of low-frequency variability, have increased interest in future climate projections from General Circulation Models (GCMs). However, previous generations of GCMs historically have a poor record in simulating the regional hydroclimate. This study conducts a process-based evaluation of simulations of the GHA long and short rains in CMIP6, the latest generation of GCMs. Key biases in CMIP5 models remain or are worsened, including long rains that are too short and weak and short rains that are too long and strong. Model biases are driven by a complex set of related oceanic and atmospheric factors. A too strong climatological zonal sea surface temperature gradient in the Indian Ocean and convection over the GHA that is too deep in particular are connected with erroneously powerful short rains in models. Model mean state biases in the timing of the western Indian Ocean sea surface temperature seasonal cycle are associated with certain GHA rainfall timing biases; this connection is however not replicated in interannual variability within models, suggesting there may be a common driver of both biases. Ocean biases cannot explain rainfall biases on their own; simulations driven by historical SSTs (AMIP runs) often have larger biases than fully coupled runs. A path towards using biases to better understand uncertainty in projections of GHA rainfall is suggested.
Springer Science and Business Media LLC
Title: Understanding CMIP6 Biases in the Representation of the Greater Horn of Africa Long and Short Rains
Description:
Abstract
The societies of the Greater Horn of Africa (GHA) are vulnerable to variability in two climatologically distinct rainy seasons, the March-May ‘long‘ rains and the October-December ‘short‘ rains.
Recent trends in both rainy seasons, possibly related to patterns of low-frequency variability, have increased interest in future climate projections from General Circulation Models (GCMs).
However, previous generations of GCMs historically have a poor record in simulating the regional hydroclimate.
This study conducts a process-based evaluation of simulations of the GHA long and short rains in CMIP6, the latest generation of GCMs.
Key biases in CMIP5 models remain or are worsened, including long rains that are too short and weak and short rains that are too long and strong.
Model biases are driven by a complex set of related oceanic and atmospheric factors.
A too strong climatological zonal sea surface temperature gradient in the Indian Ocean and convection over the GHA that is too deep in particular are connected with erroneously powerful short rains in models.
Model mean state biases in the timing of the western Indian Ocean sea surface temperature seasonal cycle are associated with certain GHA rainfall timing biases; this connection is however not replicated in interannual variability within models, suggesting there may be a common driver of both biases.
Ocean biases cannot explain rainfall biases on their own; simulations driven by historical SSTs (AMIP runs) often have larger biases than fully coupled runs.
A path towards using biases to better understand uncertainty in projections of GHA rainfall is suggested.
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