Tropical intraseasonal variability (ISV, e.g. Madden-Julian Oscillation) exerts significant influences on global climate and weather systems including tropical cyclones (TCs). This serves as a critical basis of the “Seamless Prediction” concept by bridging the forecasting gap between medium to long-range weather forecast and short-term climate prediction. For extended range forecasts of TC activity on an intraseasonal time scale (10~60 days), most of current approaches are based on statistical models or downscaling techniques. Recently, with the development of high-resolution general circulation models (GCMs) with improved model physics, it has become possible for these GCMs to represent both ISV and hurricanes, leading to a new avenue for intraseasonal TC prediction by using dynamical models.
Our recent analyses (Jiang et al. 2011b; Jiang et al. 2011a) of ISV and TC activity over the eastern North Pacific (ENP) based on simulations by the high resolution NOAA/GFDL HiRAM AGCM illustrate that the observed dominant ISV modes over the ENP are captured well in HiRAM; meanwhile, the observed relationship between ISV and TC activity over the ENP can also be faithfully represented in this model. Motivated by these encouraging results, we propose to use HiRAM, a leading edge model in terms its ISV-TC fidelity, to qualify the predictive skill and estimate the predictability for TCs across the Intra-Americas Sea (IAS) on intraseasonal time scales. The objectives of this proposed study are as follows:
1. Conducting hindcast experiments to fully evaluate the prediction skill of ISV over the IAS by the NOAA/GFDL HiRAM;
2. Analyze the HiRAM hindcast ensembles to estimate the intrinsic predictability of TC activity over the IAS;
3. Evaluate the role of ISV in characterizing the prediction skill of TCs over the IAS on intraseasonal time scales;
4. Explore the physical mechanisms associated with ISV modulation of TC formation over the IAS;
5. Using both HiRAM climate simulations and hindcasts, evaluate how model horizontal resolution and different physical parameterization specifications influence model skill in simulating / predicting ISV and TC activity.
With a focus on the close linkage between TCs, one of the most disastrous extreme events, and ISV, a prominent climate mode with broad impacts over the IAS, this proposal directly addresses MAPP program’s FY2012 goals of “modeling of Intra- Americas Sea climate processes associated with extremes over North America”. Moreover, this proposed study is in great agreement with recommendations by the National Academy of Science’s 2010 report “Assessment of Intraseasonal to Interannual Climate Prediction and Predictability” that “Many sources of predictability remain to be fully exploited by intraseasonal to interannual (ISI) forecast systems. To better understand key processes that are likely to contribute to improved ISI predictions, …, MJO influences on other important components of the climate system, such as tropical cyclone genesis should continue to be explored and exploited for additional predictability.”