Sahel Climate Change in the IPCC AR4 models Michela Biasutti in collaboration with : Alessandra Giannini, Adam Sobel, Isaac Held

OUTLINE 20 th Century: Was the Sahel drought internal noise? Forced Signal? Anthropogenic? GHG or Aerosols? 21 st Century: What is the source of model disagreement? Different SST forcing? Different response to the same SST forcing?

Hoerling et al., 2006 Fig. 5. The 1950–99 trends of (left) observed and (middle) atmospheric GCM simulated seasonal African rainfall for JAS. Plotted is the total seasonal rainfall change (mm) over the 50-yr period. (right) The empirical PDFs of JAS 50-yr rainfall trends averaged over the Sahel region. The data given by the red curve are from the 80 individual members of the AGCM simulations forced with the history of global observed SSTs. The data given by the blue curve are from 15 individual members of unforced coupled atmosphere–ocean model simulations. The observed trend value is indicated by the gray bar. SST-forced Sahel drought: natural? AMIP coupled CTL

NASA/GISS IPCC Simulations GCMs 20th Century Simulation (XX) Global Warming Scenario (A1B) Pre-Industrial Control (PI) XXPI A1B

Hoerling et al., 2006 “[The ensamble mean] fails to simulate the pattern or amplitude of the twentieth-century African drying, indicating that the drought conditions were likely of natural origin.” IPCC Simulations

Importance of Internal Variability 60 XX Simulations Trend Trend Trend 1. reduced variability 2. predominance of drying trend

Forced Signal: ( mean) minus (PI mean)

XX-PI Rainfall Change

XX-PI SST Change

OUTLINE 20 th Century: Was the Sahel drought internal noise? Forced? Anthropogenic? GHG or Aerosols? 21 st Century: What is the source of model disagreement? Different SST forcing? Different response to the same SST forcing?

Effect of GHG 4x(yrs50:70)-PI Mean Rainfall Change Robustness of Rainfall Change Surface Temperature 20

NASA/GISS SULFATE AEROSOL FORCINGS ( ) Temp RESPONSE Effect of Reflective Aerosols ROTSTAYN AND LOHMANN ‘02 Precip RESPONSE

20 th Century drying of the Sahel is reproduced by almost all IPCC AR4 models  it is (partly) externally forced. (But natural, internal variability is substantial.) The forcing was anthropogenic, with the most robust signal coming from the sulfate aerosol forcing. The response to GHG increase alone is inconsistent across models, which implies an uncertain outlook for the Sahel. Some Conclusions

GFDL Precipitation Response in the Sahel

Given the role of SST in simulations of the 20th Century, is it SST?:  different SST anomalies?  different sensitivity to same SST anomalies? What are the possible causes of discrepancy?

Relationship of Sahel rainfall & SST (pre-industrial, not forced) Biasutti et al., 2007

Linear Multi-Regressive Model: from SST (Indo-Pacific & Atlantic Gradient) to Sahel Rainfall interannual (=detrended) XX A1B goodness of model PI (training run)

Linear Multi-Regressive Model trained on (detrended) PI: from SST ( Indo-Pacific & Atlantic Gradient ) to Sahel Rainfall interannual  interannual + trend PI XX A1B goodness of model nb: same results if NTA & STA are used (3 predictors) and/or if model is trained on XX.

Held & Lu, 2007 Uniform Warming North Atlantic obs AM2 CM2 miroc CM2 miroc Linear Regression Coefficients Simulated &Predicted Sahel Rainfall

~30%(?) of 20 th Century drying of the Sahel was externally forced. The forcing was anthropogenic, with the most robust signal coming from the sulfate aerosol forcing. In the 21 st Century, when GHG are the dominant forcing, the Sahel response is inconsistent across models. Global SST changes can explain the 20 th Century trend, but, in most models, not the 21 st Century one (at least not through the same mechanisms active in the past). A model’s good representation of the past is no indication of a trustworthy prediction of the future. How can we reduce the uncertainty of our climate outlook? Conclusions