SGER: Simple Indices of Climate Variability and Change

五个简单的大范围地表温度变化指数将被用来评估一些气候模型在模拟20世纪气候变化和变化方面的表现。这些指数以温室气候变化的空间指纹为基础，包括面积平均地表温度、陆地-海洋温度对比度、北半球经向温度梯度、陆地上温度的年循环幅度和陆地上的日温差幅度。将根据1880-2003年期间的观测数据计算全球区域和北美区域的指数，并与这一时期的模式模拟数据进行比较。要分析的模型包括所有三个美国模型(科罗拉多州博尔德国家大气研究中心的社区气候系统模型、普林斯顿的地球物理流体动力学实验室模型(GFDL)和纽约市的戈达德空间研究所模型)的模拟，这些模型与其他几个国际模型一起提供给政府间气候变化专门委员会(IPCC)第四次评估报告。将在三个不同的时间尺度上比较观测和模型之间的指数变异性和相关结构：年际变率、年代变率以及50年和百年时间尺度上的趋势。这项评价将为使用这些模型进行气候变化检测和归因研究以及预测未来气候变化提供更大的信心。

Five simple indices of large-scale surface temperature variations will be used to assess the performance of a number of climate models in simulating climate variability and change during the 20th century. These indices are based on the spatial fingerprint of greenhouse climate change and include the area-mean surface temperature, the land-ocean temperature contrast, the meridional temperature gradient in the Northern Hemisphere, the magnitude of the annual cycle in temperature over land, and the magnitude of the diurnal temperature range over land. The indices will be calculated for the global domain and for the North American region from observational data for the period 1880-2003 and compared with data from model simulations for this period. The models to be analyzed include simulations from all three U.S. models (Community Climate System Model, at the National Center for Atmospheric Research at Boulder, Colorado; Geophysical Fluid Dynamics Laboratory model (GFDL) at Princeton; and Goddard Institute for Space Studies model (GISS) at New York City) being made available for the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report, together with several other international models. The variability and correlation structure of the indices will be compared between the observations and the models on three different timescales: interannual variability, decadal variability and trends on 50 year and century timescales. This evaluation will provide greater confidence in using these models for climate change detection and attribution studies and for projection of future climate change.