Abstract
Abstract. The operational medium-range weather forecasting based on numerical weather prediction (NWP) models are complemented by the forecast products based on ensemble prediction systems (EPSs). This change has been recognised as an essentially useful tool for medium-range forecasting and is now finding its place in forecasting the extreme events. Here we investigate extreme events (heatwaves) using a high-resolution NWP model and its ensemble models in union with the classical statistical scores to serve verification purposes. With the advent of climate-change-related studies in the recent past, the rising number of extreme events and their plausible socio-economic effects have encouraged the need for forecasting and verification of extremes. Applying the traditional verification scores and associated methods to both the deterministic and the ensemble forecast, we attempted to examine the performance of the ensemble-based approach in comparison to the traditional deterministic method. The results indicate an appreciable competence of the ensemble forecast at detecting extreme events compared to the deterministic forecast. Locations of the events are also better captured by the ensemble forecast. Further, it is found that the EPS smoothes down the unexpectedly increasing signals, thereby reducing the false alarms and thus proving to be more reliable than the deterministic forecast.
Highlights
Reliable weather forecasting plays a pivotal role in our everyday activities
We investigate the utility of the ensemble prediction system over the deterministic forecast in studying extreme events like heatwaves
We have used India Meteorological Department (IMD)’s real-time daily gridded (Shepard, 1968; Piper and Stewart, 1996; New et al, 2000; Kiktev et al, 2003; Rajeevan et al, 2005; Caesar et al, 2006; Srivastava et al, 2009) temperature data to verify the real-time forecasts based on NCMRWF unified model (NCUM; deterministic) and NCMRWF ensemble prediction system (NEPS) ensemble mean forecast temperatures
Summary
Reliable weather forecasting plays a pivotal role in our everyday activities. Over the years numerical weather prediction (NWP) systems have been employed to serve this purpose. This study uses two cases to demonstrate the strengths and weaknesses of the EPS approach in predicting such extreme events With these factors in mind, we can say that temperature (minimum and maximum) forms a vital component of weather and climatic studies, which are becoming increasingly important and challenging. We have used IMD’s real-time daily gridded (Shepard, 1968; Piper and Stewart, 1996; New et al, 2000; Kiktev et al, 2003; Rajeevan et al, 2005; Caesar et al, 2006; Srivastava et al, 2009) temperature (maximum and minimum) data to verify the real-time forecasts based on NCMRWF unified model (NCUM; deterministic) and NCMRWF ensemble prediction system (NEPS) ensemble mean forecast temperatures. Uncertainty in the forecasting model is taken into account by making small random variations to the model and using a stochastic kinetic energy backscatter scheme (Tennant et al, 2010)
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