[Seminar] Title: Anthropogenic Climate Change in Tropical and Subtropical Asia, and Its Impacts on Biodiversity

This is a really difficult region for modeling climate. Sea and land are intimately mixed in most of Southeast Asia, the Himalayan mountain range is too tall, too long, and orientated in exactly the wrong direction, the monsoons are really complicated, and the region is strongly influenced on a variety of timescales by a whole suite of climatic acronyms: MJO, ENSO, IOD, PDO, AMO, IPO, etc. To make things even more difficult, humans have massively changed land surface properties by deforestation, growing crops, and urbanization, and continue to add huge amounts of short-lived aerosols in complex, ever-changing, mixtures, to the atmosphere. Not surprisingly, while global climate models agree pretty well on future changes in temperature under particular emission scenarios, projections of future rainfall and other variables are model-dependent, and there is little or no agreement for most of the region. Model agreement can be increased to some extent by eliminating models that don’t reproduce present-day climates accurately, but the error bars are still large.

              We have already had around one degree of global warming and most of the world agreed in Paris two years ago to limit warming below twice this. This target may be optimistic, but even for two to three degrees warming it may sometimes make more sense to extrapolate current trends in climate variables rather than rely on models that do not even agree with each other. Rainfall has been declining in most of S China for the last 40 years, for example, while the CMIP5 model ensemble suggest it should be getting wetter. On the other hand, model projections are based on mechanisms, and should improve as our understanding of climate processes improves, while extrapolations must assume that the underlying processes remain the same. GCMs are also not good at projecting future changes in the frequency and intensity of extreme events. Unfortunately, extrapolation also works poorly with rare events, since we usually have too few records of these to assess past trends reliably. Models and observations agree on an increasing trend for very hot days, but almost everything else is uncertain.

              Impact uncertainties are added to model uncertainties. Under climate change, species can acclimate, adapt, move, or die, but none of these processes are well understood. The paleoecological record suggests movement has been the dominant response to past climate change, but habitat fragmentation makes this difficult for most species now. Moreover, projected rates of change are higher than any currently known from the paleo record, and climates are already warmer than 90% of the Pleistocene.This is a really difficult region for modeling climate. Sea and land are intimately mixed in most of Southeast Asia, the Himalayan mountain range is too tall, too long, and orientated in exactly the wrong direction, the monsoons are really complicated, and the region is strongly influenced on a variety of timescales by a whole suite of climatic acronyms: MJO, ENSO, IOD, PDO, AMO, IPO, etc. To make things even more difficult, humans have massively changed land surface properties by deforestation, growing crops, and urbanization, and continue to add huge amounts of short-lived aerosols in complex, ever-changing, mixtures, to the atmosphere. Not surprisingly, while global climate models agree pretty well on future changes in temperature under particular emission scenarios, projections of future rainfall and other variables are model-dependent, and there is little or no agreement for most of the region. Model agreement can be increased to some extent by eliminating models that don’t reproduce present-day climates accurately, but the error bars are still large.