Team from Nanjing University of Information Science and Technology identify factors that influence the prediction of heatwaves in the Yangtze River basin through data from three operational models.
Increase in the occurrence of heatwaves during summer is the result of the damaging effects of global warming. In China, the Yangtze River basin is one of the most densely populated and economically key regions. It is also well-known for heatwaves to occur especially during the summer time. Heatwaves have disastrous impact on human health, public infrastructure, and can cause tremendous impact on the economy. Forecasting of such heatwaves has to be timely with extended lead times and better gauge for heatwave occurrence in the Yangtze River basin for mitigating any of its damaging effects.
Study recently published in Advances in Atmospheric Science, a team led by Professor Hsu Pang-Chi from the Nanjing University of Information Science and Technology investigated the sub-seasonal predictive factors of heatwaves in the Yangtze River basin and identified important components that affect the prediction still using long-term hindcast data from three operational models.
"We compared three models which were developed respectively by the China Meteorological Administration, the U.S. National Centers for Environmental Prediction, and the European Centre for Medium-Range Weather Forecasts," explains Professor Hsu. "These models all participated in the Sub-seasonal to Seasonal Prediction project."
Through the study, the research team found that these operational models were able to anticipate the occurrence, intensity, and duration of heatwaves. This could be due to the ability of the operational models in encapsulating changes in phases and amplitude of high-pressure anomalies which are associated with the intra-seasonal oscillation as well as the dryness of soil moisture induced by decrease in rainfall.
Additionally, the study team was also able to discover that the models used in predicting heatwave occurrence with a longer lead time – 15 to 20 days in advance. The models could capture the evolution and amplitude of 30 to 90-day intra-seasonal circulation rather than the 10 to 30-day intra-seasonal circulation. The biases of intra-seasonal circulation anomalies further affect precipitation anomalies and thus soil moisture conditions, affecting the prediction skill for heatwave intensity and duration.
"In the future, we will further diagnose the key factors influencing the activity of intra-seasonal oscillation and related land-air interactions to gain a more comprehensive and in-depth understanding of the potential sources of sub-seasonal predictability," says Professor Hsu.
The research team will be continuing to work towards improving the sub-seasonal predictive abilities of high-impact weather events.