The Predictability of Extratropical Storm Tracks and the Sensitivity of Their Prediction to the Observing System

Abstract

A new method for assessing forecast skill and predictability that involves the identification and tracking of extratropical cyclones has been developed and implemented to obtain detailed information about the prediction of cyclones that cannot be obtained from more conventional analysis methodologies. The cyclones were identified and tracked along the forecast trajectories, and statistics were generated to determine the rate at which the position and intensity of the forecasted storms diverge from the analyzed tracks as a function of forecast lead time. The results show a higher level of skill in predicting the position of extratropical cyclones than the intensity. They also show that there is potential to improve the skill in predicting the position by 1–1.5 days and the intensity by 2–3 days, via improvements to the forecast model. Further analysis shows that forecasted storms move at a slower speed than analyzed storms on average and that there is a larger error in the predicted amplitudes of intense storms than the weaker storms. The results also show that some storms can be predicted up to 3 days before they are identified as an 850-hPa vorticity center in the analyses. In general, the results show a higher level of skill in the Northern Hemisphere (NH) than the Southern Hemisphere (SH); however, the rapid growth of NH winter storms is not very well predicted. The impact that observations of different types have on the prediction of the extratropical cyclones has also been explored, using forecasts integrated from analyses that were constructed from reduced observing systems. A terrestrial, satellite, and surface-based system were investigated and the results showed that the predictive skill of the terrestrial system was superior to the satellite system in the NH. Further analysis showed that the satellite system was not very good at predicting the growth of the storms. In the SH the terrestrial system has significantly less skill than the satellite system, highlighting the dominance of satellite observations in this hemisphere. The surface system has very poor predictive skill in both hemispheres.

Assessment of an ensemble of ocean–atmosphere coupled and uncoupled regional climate models to reproduce the climatology of Mediterranean cyclones

“…Note that in each dataset the same cyclone may be detected by more than one method. We remove these multiples by considering that two cyclones are the same if their centers are located within no more than 3° in longitude and latitude, and if both cyclones occur within a time difference of no more than 12 h. This methodology to diagnose "identical" cyclone tracks is simpler than the one applied by Blender and Schubert (2000) or Froude et al (2007), who used a criterion based on the whole cyclone tracks. However, here we treat a complex dataset with tracks reproduced from different methods and hence of different track characteristics (e.g., track lengths of the same cyclones might be considerably different; Fig.…”

Objective determination of the extratropical transition of tropical cyclones in the Northern Hemisphere

“…Froude, 2010Froude, , 2011Grise et al, 2013;Strachan et al, 2013;Zappa et al, 2013). There is extensive description of this in the existing literature, for example Froude et al (2007aFroude et al ( , 2007b. The particular configuration of the methodology is described in Hodges and Emerton (2014).…”

Extra-tropical cyclones in the present and future climate: a review

“…Information on the characteristics and paths of cyclones are important both in terms of understanding variations of local weather and for a characterization of climate. Such an approach was recently used for the assessment of (ensemble) forecasts and estimates of predictability (Froude et al 2007a(Froude et al , 2007b. The current paper reviews the actual knowledge on the broader scale cyclone occurrence, including its identification and tracking from global data sets with "state-of-the-art" methods.…”