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Probabilistic simulations of the impact of increasing leaf-level atmospheric carbon dioxide on the global land surface
Authors:F T Cruz  A J Pitman  J L McGregor
Institution:1. Climate Change Research Centre, Faculty of Science, University of New South Wales, Sydney, NSW, 2052, Australia
2. Centre for Australian Weather and Climate Research, Australian Bureau of Meteorology and CSIRO, PB1, Aspendale, VIC, 3195, Australia
Abstract:Using a climate model with a sophisticated land surface scheme, simulations were conducted to explore the impact of increases in leaf-level carbon dioxide (CO2) on evaporation, temperature and other land surface quantities. Fifty-one realizations were run, for each of four Januarys and four Julys for CO2 concentrations at leaf-level of 280, 375, 500, 650, 840 and 1,000 ppmv. Atmospheric CO2 concentration was held constant at 375 ppmv in all experiments. Statistically significant decreases in evaporation and increases in temperature occur in specific regions as leaf-level CO2 is increased from 280 to 375 ppmv. These same areas expand geographically, and the magnitude of the changes increase as leaf-level CO2 is increased further suggesting that changes are caused by the increase in leaf-level CO2 and are not internal model variability. As leaf-level CO2 is increased further, larger areas of the continental surface are affected by increasing amounts and a statistically significant change in precipitation is seen. The increase in leaf-level CO2 from 280 ppmv to 375 ppmv causes statistically significant changes in the evaporation over 12% of continental surfaces in July. This increases to 25% at 500 ppmv, 35% at 650 ppmv, 41% at 840 ppmv and 47% at 1,000 ppmv. This affects temperature and rainfall by similar amounts, generally in coincident regions. An analysis of these results over key regions shows that the probability density functions of the latent heat flux and temperature are affected non-uniformly. There is a shift in the latent heat flux probability density function to lower values, mainly through the reduction in the upper tail of the distribution. The temperature probability density function shifts to higher values, mainly through an increase in the upper tail of the distribution indicating that the impact is focussed on extremes. Given that there are a suite of well evaluated land surface models that include the biogeochemical effects of increasing CO2 we suggest that the inclusion of such a model should be a recommended component of climate models used in future assessment reports by the Intergovernmental Panel on Climate Change.
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