Uncertainties in regional climate change prediction: a regional analysis of ensemble simulations with the HADCM2 coupled AOGCM

Abstract

We analyze ensembles (four realizations) of historical and future climate transient experiments carried out with the coupled atmosphere-ocean general circulation model (AOGCM) of the Hadley Centre for Climate Prediction and Research, version HADCM2, with four scenarios of greenhouse gas (GHG) and sulfate forcing. The analysis focuses on the regional scale, and in particular on 21 regions covering all land areas in the World (except Antarctica). We examine seasonally averaged surface air temperature and precipitation for the historical period of 1961±1990 and the future climate period of 2046±2075. Compared to previous AOGCM simulations, the HADCM2 model shows a good performance in reproducing observed regional averages of summer and winter temperature and precipitation. The model, however, does not reproduce well observed interannual variability. We ®nd that the uncertainty in regional climate change predictions associated with the spread of dierent realizations in an ensemble (i.e. the uncertainty related to the internal model variability) is relatively low for all scenarios and regions. In particular, this uncertainty is lower than the uncertainty due to inter-scenario variability and (by comparison with previous regional analyses of AOGCMs) with inter-model variability. The climate biases and sensitivities found for dierent realizations of the same ensemble were similar to the corresponding ensemble averages and the averages associated with individual realizations of the same ensemble did not dier from each other at the 5% con®dence level in the vast majority of cases. These results indicate that a relatively small number of realizations (3 or 4) is sucient to characterize an AOGCM transient climate change prediction at the regional scale.

Changes in Temperature-based Extremes Indices Due to Global Warming Projected by a Global 20-km-mesh Atmospheric Model

“…1. The area averages for 23 regions are shown in Table 2, following the classification of Giorgi and Francisco (2000 cance of change is calculated using the t-test. Table 2 indicates that most indices change significantly due to global warming, but changes in ETR are significant only in the high latitudes, the east coast of continents in the midlatitudes (east Asia and eastern North America), and the Amazon.…”

“…It increases more in the low latitudes and less in the high latitudes and 70 Table 2. Extremes indices and a basic index in the present (upper) climate and changes due to global warming (lower) in each area as defined by Giorgi and Francisco (2000). The value in italics is not significant at the 95% confidence level.…”

Climate change in Central America and Mexico: regional climate model validation and climate change projections

“…Regional projections were obtained from the compilation of general circulation model (GCM) simulations (known as the multi-model data set; MMD) by dividing the world into a number regions as defined in Giorgi and Francisco (2000). One of these regions is Central America and Mexico spanning latitudes from 10°to 30°N and longitudes from 83°to 116°W.…”

Assessment of representations of model uncertainty in monthly and seasonal forecast ensembles

“…Overall, it can be seen that the level of skill in the ENSEMBLES system is comparable with that (d) wet November between the ENSEMBLES multi-model ensemble (MME), perturbed physics ensemble (PPE), stochastic physics ensemble (SPE) and the control simulation for the stochastic physics ensemble (CTRL) on forecast lead time 1 month. Definition of the regions after Giorgi and Francisco [2000].…”