Multi-scale subseasonal forecasts using an unstructured grid global
model - a TC and Heatwave Case Study
Abstract
In traditional practice, weather forecasts typically span up to two
weeks, while climate forecasts begin at the seasonal timescale and
extend further. Consequently, there exists a gap between weather and
climate predictions in the subseasonal to seasonal (S2S) range. There is
a growing demand within operational prediction and application
communities for forecasts that bridge this gap, providing predictions
between daily weather forecasts and seasonal climate outlooks. A global
model with an unstructured grid mesh is utilized for this study to
examine the forecast skill. Additionally, ensemble forecasting is taken
into account, which involves running multiple simulations with slightly
different initial conditions to capture uncertainties in the forecast.
These ensemble forecasts are integrated for a period of 23 to 27 days,
allowing for an extended prediction window beyond the typical forecast
horizon. Results indicate that the model can give reasonable predictions
on the development of a super Typhoon at lead times up to 10 days ahead
of its peak intensity. Signal of a heat wave in southern China
associated with the subsidence heating from TC outflow was also
predicted reasonably well, despite variability among members existed due
to disparity in the predicted TC tracks. Additionally, we carried out
sensitivity tests on the use of radiation schemes on model cloud
fraction. It is also found that the use of Xu and Randall generates more
realistic cloud cover than Sundqvist, and resulting in greatly improving
the evolution of synoptic scale weather systems over the western North
Pacific consequentially.