Probabilistic distributions of regional climate change and their application in risk analysis of wheat production

Climate Research

Brett Bryan¹  Martin Williams¹  Qunying Luo¹  Roger N. Jones¹  William Bellotti¹ 

关键词: Probability distribution functions;    Monte Carlo random sampling;    Uncertainty management;    Climate change;    APSIM-Wheat model;    Risk analysis;    Wheat production;   

DOI  :  10.3354/cr029041

来源: Inter-Research Science Publishing

【 摘 要 】

ABSTRACT: Downscaled outputs from 9 climate models and information from the 2000 Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) were used to construct probability distributions of regional climate change for Roseworthy, South Australia. The construction of probability distribution for regional climate change involved the identification, quantification and treatment of uncertainties from greenhouse gas (GHG) emission scenarios, climate sensitivity and local climate change. Monte Carlo random sampling techniques were applied to component ranges of uncertainty defined by quantified upper and lower limits, assuming uniform probability over each range. Construction of resulting probability distributions of regional climate provided a framework for risk analysis. These probabilities were applied to the Agricultural Production System sIMulator (APSIM)-Wheat model to evaluate potential wheat production at Roseworthy for the year 2080 through the identification of critical yield thresholds. The conditional probability of not meeting the critical yield threshold increased from 27% under baseline conditions to 45% under the median probability for the year 2080, indicating less profitable wheat production in the study area.

【 授权许可】

Unknown