Impacts of the Upper Level Rossby Wave Packets on Medium-range Forecast Errors and Uncertainties

Upper level Rossby wave packets (RWPs) have frequently been linked to high impact weather events, including being precursors to explosively deepening surface cyclones and heavy precipitation events. Previous studies have suggested RWPs may have some implications to weather forecasting, e.g., short-range (1-3 days) forecast errors disperse and grow like linear RWPs. In addition, both medium- (3-7 days) and short- range forecast uncertainties also can develop and propagate like linear RWPs. However, to date it is still not clear how RWPs affect the development of forecast errors and uncertainties, although there have been suggestions that in some cases, large forecast uncertainties developed simultaneously with the initiations of RWPs.

The first objective of this study is to investigate the impacts of RWPs on the occasional forecast skill busts or “dropout” cases as well as the distribution and growth of medium-range forecast errors for deterministic forecast using the Global Forecast System (GFS) analysis/forecast during 2007-2013 cool seasons. The root-mean-square error (RMSE) of geopotential height at 300 hPa over a verification box over East Coast is firstly used to define the forecast dropout cases. Then, the composited RWPs amplitude (RWPA), which is calculated based on horizontal wind data at 300 hPa using a stream-wise Hilbert transform technique, is calculated conditional on forecast dropout cases. The initial results show that there is a positive RWPA anomaly originating from eastern Asia and propagating across the North Pacific and west coast of North America into the verification box, suggesting that the forecast dropouts over East Coast are associated with the presence of enhanced RWPA upstream. The initial results also show that large absolute errors for dropout cases propagate with positive RWPA anomaly, but the maxima tend to be over the leading regions of RWPA anomaly between day 4 and day 7 forecasts.

Another objective of this study is to examine the growth of forecast uncertainties associated with RWPs within ensemble forecast using the Global Ensemble Forecast System (GEFS) ensemble forecast data. The dates with the most coherent RWPs will be determined by utilizing an object-based tracking method developed by Stony Brook University, during which the RWPs-related forecast uncertainties will be examined. The tracking program has also found the locations, sizes and intensities of the RWPs, which will be related to the distributions of forecast uncertainties within the medium-range ensemble forecast. The implications of this work for the predictability associated with the presence of RWPs will also be discussed.