Penny Whetton

Implications of CMIP3 model biases and uncertainties for climate projections in the western tropical Pacific

Regional climate projections in the Pacific region are potentially sensitive to a range of existing model biases. This study examines the implications of coupled model biases on regional climate projections in the tropical western Pacific. Model biases appear in the simulation of the El Niño Southern Oscillation, the location and movement of the South Pacific Convergence Zone, rainfall patterns, and the mean state of the ocean–atmosphere system including the cold tongue bias and erroneous location of the edge of the Western Pacific warm pool. These biases are examined in the CMIP3 20th century climate models and used to provide some context to the uncertainty in interpretations of regional-scale climate projections for the 21st century. To demonstrate, we provide examples for two island nations that are located in different climate zones and so are affected by different biases: Nauru and Palau. We discuss some of the common approaches to analyze climate projections and whether they are effective in reducing the effect of model biases. These approaches include model selection, calculating multi model means, downscaling and bias correcting.

Evaluation of CMIP3 and CMIP5 models over the Australian region to inform confidence in projections

The assessment covers mean climate skill over Australia as well as variability measures and teleconnections from up to 47 CMIP5 models and 23 CMIP3 models (for comparison where appropriate). Additionally, the skill in representing important climate features such as MJO, SAM, blocking and cut-off lows are also reviewed. Selected extremes are evaluated as well as simulations of two different types of downscaling simulations used within the NRM project. Finally, an attempt is made to synthesise this information in order to highlight a small group of CMIP5 models which show consistent deficiencies in representing the Australian climate and its features.

Seasonal and regional signature of the projected southern Australian rainfall reduction

A projected drying of the extra-tropics under enhanced levels of atmospheric greenhouse gases has large implications for natural systems and water security across southern Australia. The drying is driven by well studied changes to the atmospheric circulation and is consistent across climate models, providing a strong basis from which adaptation planners can make decisions. However, the magnitude and seasonal expression of the drying is expected to vary across the region. Here we describe the spatial signature of the projected change from the new CMIP5 climate models and downscaling of those models, and review various lines of evidence about the seasonal expression.

The Potential Impacts of Climate Change

Concern over the potential impacts of future climate change on both natural and human systems drives research into the enhanced greenhouse effect. There are two fundamental questions that need to be addressed by this research: whether atmospheric pollution currently being emitted, and likely to be emitted in the coming decades, will result in dangerous climate-related impacts for future generations, and if so, what action should be taken to limit that danger.

Evaluation of simulated recent climate change in Australia

The ability to reproduce recent observed climate change in climate models is a pertinent prerequisite for trust in climate projections. Also, information on the consistency of simulated and observed recent changes helps users to interpret near-term climate change projections. A comprehensive assessment of simulated regional trends, however, is often not available. Therefore, we evaluate daily maximum and minimum temperature trends and rainfall trends from 1956-2005 in Australia in simulations from the CMIP5 archive. For all variables and all models, we find significant (at the 10% level) differences between simulated and observed trends in some areas. Except for daily minimum temperature in spring and summer, however, the areas where we find significant differences are smaller than what we expect by chance. In a multivariate evaluation, simulated joint temperature and rainfall trends of all but one model, however, are found to be significantly (at the 10% level) different from the observed trends. Hence, multivariate evaluation provides a stricter test. We conclude that CMIP5 models share trend biases and regional projections therefore have to account for the presence of biases shared across models.

Tracking regional temperature projections from the early 1990s in light of variations in regional warming, including ‘warming holes’

The perception of the accuracy of regional climate projections made in the early 1990s about climate change by 2030 may be influenced by how the temperature trend has changed in the 25xa0years since their publication. However, temperature trends over this period were influenced not only by external forcings such as greenhouse gases but also natural variations. The temperature of Southern Australia, the Sahel, South Asia and Southern Europe are currently within the warming estimates from statements in the early 1990s from the IPCC and CSIRO, assuming a linear trend between 1990 and 2030. However, northern Australia and central North America are currently at the lower limit or below these projections, having featured areas of multi-year regional cooling during global warming, sometimes called ‘warming holes’. Recent climate model simulations suggest that cooling can be expected in the recent past and near future in some regions, including in Australia and the US, and that cooling is less likely over 1990–2030 than in 1990–2015, bringing observations closer to the IPCC and CSIRO warming estimates by 2030. Cooling at the 25-year scale in some regions can be associated with cyclic variability such as the Inter-decadal Pacific Oscillation, or low trend such as in the Southern Ocean. Explicitly communicating the variability in regional warming rates in climate projections, including the possibility of regional warming ‘holes’ (or the opposite of ‘surges’ or ‘peaks’) would help to set more reliable expectations by users of those projections.