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Climate Change Projections for the Tropical Rainforest Region of North Queensland: Final Report on MTSRF Research, 2006-2010

Research Report

R. Suppiah, I. G. Watterson, I. Macadam, M. A. Collier and J. Bathols

CSIRO Climate Adaptation National Research Flagship

ISBN 978-1-921359-69-9
Written December 2010
Published by RRRC August 2011

MTSRF Project 2.5ii.1 - Regional climate change projections for tropical rainforests

Executive Summary (Extract)

This is the final report from a four-year (2006-2010) program funded by the Marine and Tropical Sciences Research Facility (MTSRF) on regional climate change projections for the tropical rainforest region of North Queensland. It gives a descriptive assessment of observed climate variability during the past century, and provides general climate change projections for the region into the future. Recommendations for future research are also included at the end of this summary.

Climate change due to the likely increase in atmospheric greenhouse gas concentrations is now inevitable. Climate change will continue to increase until, and to a lesser known degree beyond, a stabilisation of greenhouse gas concentrations can be reached.  We therefore need the best possible estimates of regional climate changes and of the sensitivity of various sectors to such changes.

During the four-year research period, we used several approaches for determining future changes in northeast Queensland, such as temperature, rainfall and potential evaporation patterns for various decades, the behaviour of the El Niño-Southern Oscillation phenomenon (ENSO), and tropical cyclones. These factors were investigated through simulations from global climate models (GCMs), theoretical considerations and the application of higher resolution regional climate models nested in a number of GCMs. Results of higher resolution simulations are given by Thatcher and others (2007, 2008).

Our climate change assessments are based on coupled-ocean-atmosphere GCMs.  Although these are state-of-the-art models it is acknowledged that they are not fully realistic. In particular, the current generation of GCMs simulates ENSO inadequately. Furthermore, there is no consensus on the simulation of likely changes in ENSO characteristics. A major task in the near future is to refine coupled-ocean-atmosphere models to provide simulations of ENSO changes in which we can have confidence, and to use the models to investigate related effects including possible changes in the behaviour of tropical cyclones.

Model simulations indicate a range of plausible changes in temperature, mean rainfall and increased rainfall intensity, potential evaporation and possible changes in ENSO, and tropical cyclone behaviour. The practical implications of these climate change projections suggest possible widespread impacts across northeast Queensland, particularly in the rainforest and Great Barrier Reef regions. Such impacts can significantly affect coastal zones, ecosystems, agriculture, water resources, tourism, human health, fisheries, pests, diseases, mangroves, coral reefs and low lying islands.

The need for developing better methods to produce improved climate change projections under enhanced greenhouse conditions is widely recognised. Studies of the sensitivity of ecosystems and other sectors using climate change projections by colleagues at James Cook University, CSIRO Sustainable Ecosystems and others suggest that enhanced greenhouse conditions can have significant impacts on ecosystems of the tropical rainforest region, as well as economy and tourism, and human settlements.  Within the next stage of post-MTSRF Australian Government funding, we look forward to a growing interaction and collaboration with research communities and application agencies in the region. Even in the absence of confident local projections of climate change, developing the ability to assess the impacts of climate change on particular activities and sectors is a valuable undertaking. It will enable rapid assessments to be made of potential impacts and adaptation strategies once uncertainties in the climate projections are reduced.

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