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Early Warning of Simulated Amazon Dieback

Early Warning of Simulated Amazon Dieback. Chris Boulton. C.A.Boulton@ex.ac.uk. HadCM3-ESE. Defined an Amazon region to test the methods on and pulled out time series for the forest (BL fraction etc) and drivers (temperature, CO2, ...).

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Early Warning of Simulated Amazon Dieback

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  1. Early Warning of Simulated Amazon Dieback Chris Boulton C.A.Boulton@ex.ac.uk

  2. HadCM3-ESE Defined an Amazon region to test the methods on and pulled out time series for the forest (BL fraction etc) and drivers (temperature, CO2, ...). Consists of 57 members with perturbed parameters under 3 emissions scenarios. There are a range of behaviours to test methods and see how they work. Slight worry that models which don’t show dieback by 2100 (transient change) do eventually dieback (committed change) and indicators should pick this up too.

  3. Testing Variance - aknaa

  4. Testing Variance - aknab

  5. Dry-Season Resilience

  6. Dry-Season Resilience

  7. Dry-Season Resilience

  8. (Moving) Cross Mapping Method adapted from CCM but uses a sliding window length to test ‘causality of a driver over time’. Create shadow manifolds as seen in diagram (M_x etc). Attempt to map the alternative time series onto this manifold (i.e. Map y onto M_x Correlation between Y and Y|M_x gives a measure of causality. Shadow Manifolds – Sugihara et al. 2012

  9. Simple Example y = 1/4*x^4 - 1/2*x^2 – m*x m increased from 0 to 2*sqrt(3)/9

  10. Using MCM in the Amazon models Model shows dieback by 2100 and looks similar to tipping model. This one shows no dieback but has same pattern. Suggests a tipping post 2100?

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