REYKJAVÍK, ICELAND AUGUST 11-13, 2008 - Veðurstofa Íslands

CLIMATE CHANGE AND VARIABILITY: HOW CAN WE INFORM
STRATEGIES FOR ADAPTATION
Upmanu Lall
ABSTRACT
Anthropogenic climate change has emerged as a major environmental
concern In the 21st century. There is clear evidence that global warming
has occurred in the 20th century, and its connection to the use of fossil
fuels and greenhouse gas emissions is now widely accepted. The
Intergovernmental Panel on Climate Change (IPCC,
http://www.ipcc.ch/) has developed many scenarios for greenhouse gas
emissions corresponding to different degrees of mitigation of greenhouse
gas emissions. These scenarios have been used with more than 45
simulations of different coupled ocean-atmosphere general circulation
models (GCMs) to develop projections of climate up to the year 2100,
for each of the scenarios. The different simulations are made to account
for uncertainty in the knowledge of climate model parameters and also
because, since the equations governing climate are nonlinear, small
differences in the starting values can potentially translate into large
differences in the resulting climate statistics. Climate change impact
assessment and climate change adaptation work is then informed by the
rainfall and temperature data from these simulations.
The talk will first review some hydrologic aspects of these simulations
And highlight the challenge faced in directly using such "data" for water
resource management and project design. The argument is made that
substantial "processing" of these simulations is needed to correct biases
and such, in the control runs covering the 20th century, suggesting that
as far as hydrology is concerned the model physics is likely to be far
from the real world physics. At one level this argues against the use or
credibility of these models for the future. At another level, the question
becomes whether there are any state variables in these models that could
be used to inform key variables of interest in water management, even in
a probabilistic sense.
This idea is developed through an example of what non-stationarity
means for risk based or probabilistic analysis as typical in our field,
using retrospective analyses constrained perhaps by long term proxy
paleoclimate data that exhibits change over many time scales. The
prospective application for the future is then outlined.
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