On July 9 I attended a workshop "Integrated Assessment of International Climate Change Policies" organized by Ifo in Munich.
I presented for the first time my work on climate change scenarios. Still very preliminary, but in progress.
The presentation is available here.
In brief:
GCMs incorporate deterministic
chaos to reflect real-world chaotic dynamics of weather. This implies that
small changes in external forcing can generate very different weather patterns,
especially at local level. By using the Coupled Model Intercomparison Project
phase 3 (CMIP3) multi-model dataset I show that small variations in Greenhouse
Gas Emissions (GHG) and other forcing agents across the SRES scenarios generate
substantial different climate scenarios in the US. By using a Ricardian model
of climate change impacts on agriculture I show that the “noise” in the climate
scenarios generates a “noisy” relationship between global GHG concentrations
and local impacts. This implies that climate change scenarios from the CMIP3
dataset - used for the IPCC AR4 - should be used with caution. This problem
might be limited by providing model ensemble runs that use same initial
conditions but introduce small perturbations around the central exogenous
forcing scenario.