Detection of anthropogenic climate change

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Presentation transcript:

Detection of anthropogenic climate change Gabi Hegerl, Nicholas School for the Environment and Earth Sciences, Duke University

Temperature trend 1901-2000

Fingerprint methods: lin. regression Estimate amplitude of model-derived climate change signals X=(xi),i=1..n from observation y Best Linear Unbiased Estimator u: noise residual (Hasselmann, 79 etc, Allen + Tett, 99) Vector: eg Temperature(space,time), scalar product: Inverse noise covariance Signal pattern from model, amplitude from observation!

June-July-August Greenhouse gas + sulfate aerosol

uncertainty range Estimated from coupled model internal variability Safety checks: Use model with strong variability test consistency with observed noise residual u

Contribution of greenhouse gas and sulfate aerosols to to trend 1949-98 o: Greenhouse gas + sulfate aerosol simulation +: Greenhouse gas only o/+ inconsistent with observation Ellipse: 90% uncertainty range in obs. Signal estimate from: Hegerl and Allen, 2002

The longer perspective reconstruction of NH warm season temperature Forced component Fat: best fit to paleo Thin: 5-95% range *: significant

Conclusions global/NH SAT Significant climate change observed Uncertainty in distinction between forcings, but: “Most of the recent (last 50 yrs) global warming is likely due to greenhouse gases” Significant and consistent climate signals in long temperature records

Towards detection of anthropogenic changes in climate extremes How to compare course-grid model with station data? Can daily data be substituted by monthly/annual and shift in distribution => no Which index to use for early detection (avoid baseball statistics!) that is moderately robust between models? Change in once/few times/yr events robust and strong

Changes in precipitation extremes stronger

Change in rainfall wettest day/yr NAmerica Consensus Observations show overall increase, too

Annual mean precip changes consistent between two models Wettest day/yr Wettest 5 consecutive days

Results: Anthropogenic vs natural signals, time-space Bars show 5-95% uncertainty limits Allen et al, 2002

Annual mean rainfall change NAmerica consensus

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