The application of a single‐model ensemble system to the seasonal prediction of winter temperatures for Islamabad and Lahore using coupled general circulation models

Abstract

The purpose of this study is the selection of an appropriate coupled general circulation model (CGCM) for seasonal weather prediction of winter temperatures in two cities of Pakistan: Islamabad and Lahore. The data used in the study comprises 32 years (1969–2000) of real‐time observations from the Pakistan Meteorological Department (PMD) and simulation data from CGCMs, including the European Centre for Medium Range Weather Forecasts (ECMWF) and the UK Met Office (UKMO). This study attempts to establish accurate average seasonal weather predictions using a single‐model Ensemble Prediction System (EPS). Accurate seasonal prediction is important for developing an early warning system. The probabilistic forecast is calculated for the lower tercile (i.e. [0, 0.33]) keeping in view the trend of winter temperature for both cities. The initial conditions (ICs) obtained from the CGCMs have been alternatively processed for better results. The probabilistic forecast obtained from the EPS has been further verified against PMD observations and European Reanalysis Data (ERA‐40) using two different measures of probabilistic skill: the Brier Skill Score (BSS) and the Relative Operating Characteristic Skill Score (ROCSS). The ECMWF and UKMO models were used for both of the cities under study. The results demonstrate that the ECMWF model is more suitable for Islamabad, whereas the UKMO model is more suitable for Lahore. The results from these models might be generalised for other areas at the same latitudes with similar topographic and climatic conditions.