Will a warmer world change Queensland s rainfall? Nicholas P. Klingaman National Centre for Atmospheric Science-Climate Walker Institute for Climate System Research University of Reading
The Walker-QCCCE Collaboration Investigate the key drivers of rainfall variability in Queensland Assess the ability of a high-resolution global model to reproduce those drivers Understand how those drivers may change in a warmer world Rainfall Observed rainfall (historical data) Rainfall drivers Project timeline Observed rainfall Meteorological reanalyses (best estimates of historical weather) Climate variability and change Observed rainfall Reanalyses High-resolution climate models (best predictions of future climate)
Queensland rainfall variability Climatological annual-total rainfall in Australia (100s of mm) Percentage anomalies in area-averaged Queensland rainfall during the wet half of the year (November April)
Key drivers of Queensland rainfall
Key drivers of Queensland rainfall
The El Niño-Southern Oscillation La Niña and El Niño are naturally occurring phenomena, in which ocean temperatures in the equatorial Pacific cool and warm, respectively. The atmospheric component of ENSO alters the overturning Walker Circulation and induces positive (winds) and negative (convection) feedbacks on the SST anomalies. Events often develop in June-September, peak in November- January, then decay in March-May. La Niña and El Niño are episodic. El Niño does not necessary follow La Niña; neutral conditions can prevail for years.
Impacts of El Nino and La Nina La Nina and El Nino affect Queensland rainfall most strongly in winter (June- August) and spring (September-November). Effects in summer and autumn are generally smaller. Red colours indicate that El Nino causes drought and that La Nina causes abnormally wet conditions. Autumn Spring Winter Summer
Climate change projections The percentage change in annual mean rainfall per degree of global warming from 22 CMIP3 models. Models exhibit a wide variety of responses of Australian rainfall to increased greenhouse gases. Identifying models with good mean states (ticks) only slightly decreases the spread among models. Models with accurate mean states may have poor variability, or may not generate rainfall over Australia for the right reasons. Changes in the mean versus changes in year-to-year variability.
The HiGEM climate model HiGEM is a computer-based climate model, based on the physical laws of the atmosphere and ocean. All models represent the atmosphere, land surface and ocean as a grid of rectangles; the spacing between the squares is the model s resolution. HiGEM has a finer resolution than nearly all of the models used for the last IPCC report, which may allow it to better represent regional climate. Resolution: 90 km in atmosphere, 30 km in ocean. Comparing the resolution of HiGEM (right) to an earlier version of the Hadley Centre climate model (HadCM3; left).
The HiGEM climate model We have analysed two simulations of HiGEM: Control simulation: 150 years Climate-change simulation: 50 years The control simulation uses present-day (1980s) values for atmospheric carbon dioxide, ozone, methane, sulfate aerosols and other gases. The climate-change simulation doubles the amount of carbon dioxide in the atmosphere. This is equivalent to 2090 under the IPCC medium emissions A1B scenario. Projected changes in global-average surface temperatures under various IPCC SRES scenarios.
The HiGEM climate model We have confidence in HiGEM s projections of rainfall change in Queensland because HiGEM simulates most of the key climate drivers of Queensland s rainfall. The drivers of rainfall were identified from an earlier analysis, using observations and meteorological reanalyses (best estimates of historical weather and climate). HiGEM simulates all three key drivers for summer rainfall, which is critical as much of Queensland s rainfall occurs in December-February.
The HiGEM climate model HiGEM SSTs for DJF EOT 1 DJF EOT 1 HiGEM HiGEM MSLP and 850 hpa winds DJF EOT 1 SILO HadISST SSTs for DJF EOT 1 20CR MSLP and 850 hpa winds
Caveats (Health warning) The following results about climate change come from only one model. An identical analysis on another model would likely yield different conclusions. These results should not be treated as a concrete prediction of definite changes in Queensland climate. Rather, they represent one possibility of change with increased atmospheric carbon dioxide. These results are the effect of increasing atmospheric carbon dioxide only. There will be other effects from changes in methane, ozone and aerosols (e.g., sulphate emissions, black carbon from biomass burning). These changes are not considered. Further research is needed to evaluate a range of climate models, to separate them into those that perform well for drivers of Queensland rainfall and those that perform poorly.
Projected temperature changes Summer Autumn Winter Spring Temperatures rise by about 2 C on average. Increases are largest in autumn and winter.
Projected circulation changes The monsoon circulation strengthens in summer, but weakens in the autumn at the end of the wet season. Summer Autumn The Southern Ocean storm track shifts toward the pole, away from southern Australia. Winter Spring
Projected rainfall changes Summer Autumn Winter Spring Change in annual-total rainfall from HiGEM 2xCO2 minus HiGEM control
Projected rainfall changes Summer Autumn Winter Spring
Projected rainfall changes Are the rainfall changes found in the HiGEM 2xCO2 simulation outside the range of natural variability from the control simulation? Deep red = 99% confidence in rainfall decrease Deep blue = 99% confidence in rainfall increase
Compression of the wet season Control 2xCO2 minus control Start of wet season 15% of Sep-Apr total Wet season begins 6-10 days later on average, particularly in coastal Queensland. Shift from early December to mid- December End of wet season 85% of Sep-Apr total Wet season ends 10-20 days earlier on average, particularly in southern Queensland. Shift from early-mid March to late February
Compression of the wet season Nov. Dec. Jan. HiGEM Control Nov. Dec. Jan. The intensity of the colours shows the contribution of each month toward the wet-season total rainfall. HiGEM 2xCO2
Compression of the wet season Feb. Mar. Apr. HiGEM Control Feb. Mar. Apr. The intensity of the colours shows the contribution of each month toward the wet-season total rainfall. HiGEM 2xCO2
Rainfall frequency and intensity Frequency Intensity 1 mm threshold For summer rainfall 5 mm threshold Summers become wetter because the intensity of rainfall increases.
Rainfall frequency and intensity Frequency Intensity 1 mm threshold For autumn rainfall 5 mm threshold Autumns become drier because the number of rainy days decreases.
Extreme daily rainfall For the tropics as a whole, the frequency of extreme rainfall is expected to increase with warming temperatures. Clausius-Clapeyron: the atmosphere can contain more water vapour at higher temperatures, before it begins to condense into liquid droplets. This does not mean that global warming will make every rainfall event stronger, or that total rainfall will increase everywhere. Changes in frequency of extreme rainfall in the tropics with warming ocean temperatures Figure from Allan et al. (2010, Env. Res. Lett.)
Extreme daily rainfall HiGEM projects a 40% increase in the number of days with 100 mm of rain in summer under 2xCO2. For summer rainfall (December-February) In the control simulation, an 80 mm rainfall occurs once every 420 days. In the 2xCO2 simulation, an 80 mm rainfall occurs once every 330 days. The 1-in-200 day rainfall intensifies by 13% (55 to 62 mm). The return period (in days) for daily rain accumulations between 1 and 100 mm in summer (December-February)
Extreme daily rainfall The number of light and moderate rainfall accumulations decreases in autumn. For autumn rainfall (March-May) This is consistent with the overall decrease in autumn rainfall. The number of heavy rain days (above 50 mm) increases, however. The frequency of a 100 mm accumulation increases by 20%. The return period (in days) for daily rain accumulations between 1 and 100 mm in autumn (March-May)
Extreme daily rainfall Estimated size of daily rain events Black line: Control Red line: 2xCO2 Estimated duration of rain events Black line: Control Red line: 2xCO2 Increasing size of event Increasing intensity of rainfall Increasing length of event Increasing intensity of rainfall HiGEM projects that heavy rain events will cover a wider area. HiGEM simulates an increased probability of consecutive days of heavy rainfall. These results have important consequences for flooding.
Tropical cyclones Number of tropical cyclones passing through Control Number of tropical cyclones forming Control 2xCO2 minus control 2xCO2 minus control HiGEM simulates slightly fewer tropical cyclones near Australia in a warmer world, consistent with many other climate models.
El Nino and La Nina Summer Autumn Winter Spring Summer Autumn Winter Spring HiGEM projects that the relationship between El Nino/La Nina and Queensland rainfall weakens in a warmer world. There is low confidence in these results, however, due to having only 50 years of the 2xCO2 simulation.
Summary and conclusions The HiGEM model has been shown to reliably reproduce the key climate drivers of Queensland s rainfall. This gives us greater confidence in its ability to project future changes with global warming. A 50-year HiGEM simulation with 690 ppm of CO2 (approximately 2090 under moderate future emissions) shows that for Queensland: The annual-total rainfall remains similar to present-day levels. The wet season becomes compressed, with more rain falling in summer and less in late spring and throughout autumn. Rainfall intensity increases by 10-25% in summer, while the number of wet days does not change much. Extreme rainfall becomes more frequent and more intense, with a 40% increase in the number of days with a 100 mm accumulation in summer. HiGEM projects that Queensland will rely more strongly upon heavy, mid-summer rains. It would therefore be important to capture and store the water from these rains to provide adequate water supplies for a growing population.