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Andrew Turner

UKCDS Bangladesh Delegation Visit Wednesday 3 March 2010. Key modes of climate variability over South Asia and uncertainties in future climate projections. Andrew Turner. Introduction.

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Andrew Turner

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  1. UKCDS Bangladesh Delegation Visit Wednesday 3 March 2010 Key modes of climate variability over South Asia and uncertainties in future climate projections Andrew Turner

  2. Introduction • Climate of Bangladesh is particularly influenced by the South Asian summer monsoon, in addition to tropical cyclones and other low-pressure systems. • This talk particularly focuses on: • the skill with which monsoon processes on various timescales are modelled; • the uncertainty in future projections of the regional climate, particularly in the IPCC AR4 / CMIP3 database.

  3. Outline • Introduction • How is the mean monsoon and its seasonal cycle simulated in models? • How certain are projections of change to seasonal mean rainfall? • What about modes of monsoon variability and their teleconnections? • Can we say anything about changes to short-timescale variability? • Summary

  4. The mean monsoon... Few models can simulate the major precipitation centers and their interannual variation. from Annamalai et al. (2007) J. Climate

  5. ...and its seasonal cycle Only 6 CMIP3 models can reasonably simulate both the spatial distribution and seasonal cycle of rainfall over South Asia! from Annamalai et al. (2007) J. Climate

  6. Uncertainties in late 21st century IPCC AR4 A1B mean projections • In this scenario, reasonable agreement between coupled climate models on surface temperature changes in the South Asia region: 3–4˚C • Inter-model spread of precipitation projections is large for all the monsoon systems, including South Asia. from Meehl et al. (2007) Global Climate Projections in the IPCC AR4

  7. Uncertainties in late 21st century IPCC AR4 A1B mean projections Large uncertainty in mean JJA rainfall change over Bangladesh? From Turner & Slingo (2009b) Atmos. Sci. Lett. 10

  8. Interannual variability and relationship with ENSO • Flooding in Bangladesh linked to the Southern Oscillation. El Niño events also influence upstream precipitation (e.g., Chowdhury, 2003, Theor. Appl. Climatol.)  need institutional collaboration. • Climate models have difficulty with these teleconnections, thus inhibiting accurate seasonal prediction. from Turner et al. (2005), Q. J. R. Meteorol. Soc. 131

  9. Interannual variability and relationship with ENSO The ENSO-monsoon correlation waxes and wanes, and is currently in a weakened phase. Is this related to warming? Variation in teleconnections on decadal timescales needs to be considered when designing seasonal forecasts.

  10. Boreal summer intraseasonal variability • EOF reconstruction of OLR during the active-break cycle of the monsoon. • Based on finding the patterns that explain the most variance of OLR in a 20-100 day period during the monsoon season • Note the distinct NW-SE tilt of the bands of active and suppressed convection • Taken from Annamalai & Sperber (2005) J. Atmos. Sci.

  11. ‘MJO’ strongly implicated in 2009 summer: April to August Daily OLR anomalies + ‘MJO’ modal projection (Matt Wheeler) Symmetric Anti-symmetric ‘MJO’ mode by filtering in the zonal wavenumber / frequency domain, Wheeler & Weickmann (2001)

  12. Model capability at simulating BSISV OBS Northward propagation latitude time From Sperber & Annamalai (2008) Clim. Dyn.

  13. Model capability at simulating BSISV OBS eastward propagation time longitude

  14. Model capability at simulating BSISV • Very few coupled climate models are able to simulate the northward and eastward propagation inherent to intraseasonal variability during boreal summer. • More needs to be understood about the physical processes involved before we can be sure how their climate responses can be assessed.

  15. A possible projection of BSISV at 2xCO2? • This example uses the Hadley Centre model HadCM3, which is able to well capture the seasonal cycle of rainfall in the region and northward propagation of BSISV. • Active and break modes of BSISV potentially intensified? Active convection Break convection 2xCO2 minus control from Turner & Slingo (2009a), Q. J. R. Meteorol. Soc. 135

  16. Spatial change in HadCM3: mean & subseasonal extremes Changes in response to 2xCO2 in simulations with HadCM3: percentile extremes calculated for each JJA season then meaned. Mean precipitation change 99th subseasonal percentile change • Response of subseasonal extreme is closely tied to signal of seasonal mean change. from Turner & Slingo (2009a), Q. J. R. Meteorol. Soc. 135

  17. Uncertainty in spatial pattern of change to subseasonal rainfall extremes • Considerable uncertainty in mean and extreme projections. • Predominantly positive in sign. • Qualitative similarity, although extreme changes are of larger magnitude.

  18. Maximum increase of around 13%, as predicted by atmospheric warming at 2xCO2 and Clausius-Clapeyron. Predictability in changes to the heaviest rainfall • Allen & Ingram (2002) suggested changes to the heaviest rainfall events could be predicted based on the climate sensitivity and increases in atmospheric moisture suggested by Clausius-Clapeyron. • Turner & Slingo (2009a) showed that this could also apply locally for the South Asia region in HadCM3. 2xCO2 1xCO2 ratio

  19. Predictability in changes to the heaviest events: 3 case studies • Some models suggest remarkable predictability of changes to maximum precipitation intensity based on thermodynamic arguments. • Allen & Ingram (2002) argued that monsoons could undergo larger increases due to feedbacks between latent heat release and moisture convergence. • We examine 3 model case studies of different behaviour in predictions vs. measured changes: 1) Changes above those predicted: gfdl_cm2_1 and 5 others (6/15). 3) Changes inline with predictions: cnrm_cm3 and 5 others (6/15), as well as HadCM3. 2) Changes below predictions: ipsl_cm4 and 2 others (3/15).

  20. Rainfall statistics CMIP3 models overestimate drizzle at the expense of heavy precipitation. Can we trust projections of extremes? observations

  21. Summary • State-of-the-art coupled models have some skill in simulating the monsoon and its seasonal cycle of rainfall in South Asia. • Short timescale variability and teleconnections could be improved. • Further research is required to narrow the range of uncertainty in climate projections.

  22. Thank You Email: a.g.turner@reading.ac.uk Web: www.met.rdg.ac.uk/~sws05agt

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