期刊
INTERNATIONAL JOURNAL OF CLIMATOLOGY
卷 28, 期 8, 页码 1097-1112出版社
WILEY
DOI: 10.1002/joc.1612
关键词
climate models; AR4; model skill; probability density function; Murray-Darling Basin
We assess the capacity of models submitted for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), to simulate the maximum and minimum temperatures and precipitation over the Murray-Darling Basin (Australia). We use daily data from the AR4 to calculate the mean of these three quantities, but we also derive probability density functions (PDFs) for each variable. We quantify the skill of each climate model to simulate the probability density function as a basis of assessing those models with significant capacity over the basin. We show that Commonwealth Scientific and Industrial Research Organization (CSIRO), Insitut Pierre Simon Laplace (IPSL), and MIROC-m capture the observed PDFs of maximum and minimum temperature and precipitation relatively well. Other models capture one or two of these variables well but show limitations, or could not be assessed, in a third. We, therefore, recommend these three models to users of model results, but note that this recommendation is limited to this basin. However, our methodology provides quite a straightforward and quantitatively based means to choose climate models for impact assessment in any data-rich region. Specifically, we note that to demonstrate skill in simulating the daily derived PDFs is far more challenging than just simulating the mean (as a model can simulate the mean well by averaging large biases of opposite sign). Our method therefore provides a more robust foundation for using a model in impacts assessment. Copyright (C) 2007 Royal Meteorological Society.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据