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The evolution of climate modeling Kevin Hennessy on behalf of CSIRO & the Bureau of Meteorology Tuesday 30 th September 2003 Canberra Short course & Climate.

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Presentation on theme: "The evolution of climate modeling Kevin Hennessy on behalf of CSIRO & the Bureau of Meteorology Tuesday 30 th September 2003 Canberra Short course & Climate."— Presentation transcript:

1 The evolution of climate modeling Kevin Hennessy on behalf of CSIRO & the Bureau of Meteorology Tuesday 30 th September 2003 Canberra Short course & Climate Science Workshop 10 September 2003

2 Outline Need for climate models What is a climate model? Model evolution Model hierarchy The future

3 Need for climate models The complexity of climate system means we can’t simply extrapolate observed trends to predict the future Climate models are the best tools we have for forecasting daily weather, seasonal climate (over the next 3-12 months) and climate change over the coming decades Models provide insight to causes of past climate change and exploration of future scenarios, such as different greenhouse gas or aerosol emissions

4 Global warming scenarios Range of uncertainty is due to the range of future greenhouse gas and aerosol emissions and the range of global warming responses from 7 different climate models

5 Need for climate models Climate model output is used for regional impact assessments, e.g. climate change impact studies for industry, government and the IPCC The credibility of forecasts depends critically on the quality of output from climate models, so demonstrating and improving the reliability of climate models is important Australia has the only substantial modeling program in the Southern Hemisphere. We place more scrutiny on processes and ecosystems that are unique to our region, compared with other modeling groups that have northern hemisphere priorities

6 What is a climate model? A simplified mathematical representation of the Earth’s climate system Four main components: the atmosphere, the land surface and biosphere, the oceans and polar ice Ability to simulate the climate system depends on our understanding of physical, chemical and biological processes, e.g. clouds, currents, radiation This understanding has improved over time, along with computer power and our ability to represent the processes in computer models

7 Model evolution 1956: Phillips’ model 2-dimensional grid of points in a 2-level slice of the atmosphere uniform land surface, no ocean or sea-ice 1965: Smagorinsky’s model 3-dimensional atmospheric model with moisture and clouds for the northern hemisphere 9 levels in the vertical direction 500 km between points in the horizontal direction uniform land surface, no ocean or sea-ice a 300-day simulation 1969: Manabe and Bryan’s model 3-dimensional global model with moisture and clouds 9 levels in the atmosphere uniform land surface with 5 levels in the ocean but no sea-ice 500 km between grid-points and simplified geography a one-year simulation took 50 days of computer time

8 New components developed and tested separately, then coupled in the model and tested again Land surface Ocean IPCC 2001

9 Model evolution 2003: CSIRO Mark 3 model 3-dimensional global model 18 levels in atmosphere 31 levels in ocean including sea-ice 6 soil levels, 9 soil types, 13 vegetation types 3 snow levels 180 km between grid-points (100 km in tropics to better simulate El Nino) Data for 100 climate variables computed in 30-minute time- steps for a series of months, years decades or centuries Models adequately simulate observed daily weather and average climate patterns A one-year simulation takes 1 day of computer time

10 CSIRO Mark 3 climate model Temperature ( o C)

11 CSIRO climate model grids Mark 3 grid Mark 2 grid Facilitated by improved computing power and optimised programming

12 Improved simulation of El Nino Southern Oscillation Observed sea surface temperature anomaly CSIRO Mark 2 model CSIRO Mark 3 model

13 Model hierarchy Global climate model (grid: 180 km by 180 km) Regional climate model (grid: e.g. 70 km by 70 km) Regional climate model (grid: e.g. 14 km by 14 km) Statistical downscaling (local sites: e.g. Perth) PC software, e.g. MAGICC, OzClim ComplexSimple

14 CSIRO’s stretched grid model (CCAM) Effective resolution of 70 km over Australia

15 Observed Rainfall over Australia CSIRO Mark 3 climate model ~ 180 km grid CSIRO CCAM ~ 70 km grid Summer Autumn Lots of room for improvement!

16 The future Need enhanced super-computer resources to facilitate ongoing model development and evaluation Further improvement of model components: –interactive terrestrial biosphere –oceanic biogeochemical & carbon cycle –sea level rise –surface hydrology, aerosols and clouds –variability, predictability, extreme events, e.g. El Nino and tropical cyclones Perform a range of policy-relevant climate change simulations, e.g. effect of stabilizing CO 2 concentrations in 100 years

17 The future 20 th century climate simulations with different forcing factors (e.g. solar variations, volcanic eruptions, ozone depletion, greenhouse gases, aerosols) required for detection & attribution of observed climate change Further development of CSIRO’s stretched grid model, including a coupled ocean, for improved regional input to downscaling techniques Further development of fine resolution models for better simulating extreme events like cyclones and hail Complementary development of statistical downscaling techniques for site-specific data Further development of OzClim PC software

18 OzClim PC software Database includes: Observed and simulated monthly-average data on 25 km grid 10 climate models 6 IPCC emission scenarios 3 climate sensitivities 9 climate variables Functions: Plot maps and global warming curves Save regional average data Run simple impact models


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