A new measure (the Track Forecast Integral Deviation; TFID) for the verification of tropical cyclone (TC) track forecasts is proposed, based on the mathematical consideration that a “good” forecast has a small distance to the observed track not only at zero-order but also at higher orders. The TFID is the mean of two sub-scores, which are respectively calculated for latitude and longitude and defined to be the average value of the mean absolute error and mean absolute deviation of relative errors from the mean relative error along a track. By definition, the smaller the TFID, the more accurate the forecast track. A perfect forecast has zero TFID. It is suggested that such a measure is superior to the widely-used position error (PE) in terms of reflecting the accuracy of the whole track instead of just one position. In an experimental application, TFID was calculated for the track forecasts from the ECMWF-IFS during 2010–2012. A comparison with PE showed that TFID can work as a good supplement to the PE in discriminating good or bad track forecasts, as there are generally some forecasts with small PE but large TFID, or vice versa. The binned characteristics of TFID and PE of ECMWF-IFS were also analyzed based on several traits of the TC or its environment at the initial time of the forecast. It was found that the model performs better for initially strong and large TCs, or those with weak vertical wind shear at lead times shorter than 48 h.

Some recent studies have utilized flight-level (700 mb) winds to document the maximum wind speeds (V_max) and radius of V_max (R_max) of the original and secondary eyewalls during 24 Atlantic hurricane eyewall replacement cycles (ERC). In this study, Hurricane Wind (H*Wind) analyses of Atlantic hurricanes during 2003-2005 are utilized to document changes in the outer vortex surface wind profile beyond the secondary eyewall, with a focus on the radii of gale-force winds (R₃₄) that are often defined operationally as size changes. In Mode 1, complete and partial ERCs in which the pre-, during-, and post-ERC outer wind profiles have approximately the same shape, the outward displacements of R_max leads to size (R₃₄) increases as much as 100 km. Mode 2 ERCs are characterized by sharpened wind profiles outside the secondary eyewall that offset the larger R_max radii to produce only small R₃₄ increases. While statistically significant results are not obtained, the differences in size changes for Mode 1 and Mode 2 SEF cases suggest practical significance for forecasts and warnings.

The Dvorak technique has been widely used by operational warning centres around the world as a major analysis tool to determine the intensity of a tropical cyclone (TC). However, there exist noticeable differences in the application of the technique among different warning centres. In particular, the weakening rules in the technique that governs the determination of TC intensity during the TC weakening stage constitute one such difference and are the subject of review in this paper. Three options to modify the weakening rules are introduced and evaluated based on verification against the best-track datasets from various centres.

China is frequently affected by tropical cyclones in summer and autumn because its southern and eastern parts border low-latitude oceans. The track forecasting of tropical cyclones is a key issue in weather forecasting. In daily operations, forecasters usually focus on the effects of environmental flow fields on tropical cyclones, such as the subtropical high pressure belt, the basic flow, the troughs and ridges in westerlies, the cross-equatorial flow, the equatorial convergence belt, and the polar front. However, these factors become less significant when the environmental fields are so weak that the steering flow does not play a vital role or we cannot accurately determine the evolution of the environment flow field. Meteorological satellite cloud imagery can fill the data gap of conventional observations and provide important clues for forecasting the status and development of tropical cyclones when they are included in day-to-day weather forecasting operations. In this study, using “Muifa”, "Haikui” and other typhoons as examples, the effects of the cloud pattern and the large-scale environmental vapor fields, on the moving tracks of typhoons were analyzed based on satellite data. The results showed that the change of structures of typhoon spiral cloud bands and the turning of the typhoon path were taking on greater relevance, and at the same time the satellite water vapor images had obvious advantages in terms of indicating the large-scale environmental fields. A combination of satellite cloud imagery, observational data, and weather event analysis remains the most effective approach in the operational forecasting of typhoon moving tracks.

An objective tropical cyclone (TC) intensity estimation model is proposed based on the statistical relationship between TC intensity and its inner-core convection, plus the persistence of TC intensity. In the model, the inner-core convection is described by several parameters retrieved from digital infrared (IR) satellite images, including the number of convective cores (Num), their distance to the TC center, and their blackbody temperature (TBB), among others. The persistence of TC intensity is embodied by the TC intensity six hours previous (V_6h). The model was set up by the stepwise regression technique using a five-year dataset (2006-2010) and was tested using an independent dataset covering 2011-2012, with V_6h from the best-track dataset. Selected factors of the
model included V_6h, Num, Lat (TC center latitude), Lon (TC center longitude), DIS_min (minimum distance between convective cores and TC center), and TBB_dif (difference between the maximum and minimum TBB value of convective cores). Results showed that, for independent samples during 2011-2012, the MAE (mean absolute error) and RMSE (root-mean-square error) of V_max estimation were 1.8 m s^-1 and 2.4 m s^-1, respectively. In order to make the model totally independent from the best-track dataset, the model estimation from six hours previous was used as the V_6h for a second independent test covering 2011-2012. The results showed that the model had an MAE and RMSE of 5.4 m s^-1 and 7.3 m s^-1, respectively. Large errors were found for strong TCs (Severe Typhoon or Super Typhoon). The error statistics of the proposed model are comparable to published statistics on the widely used Dvorak technique or its objective versions, implying its potential to be used as an alternative tool for TC intensity estimation in either real-time operation or post-season best-track analyses.