Some of the success of the systematic approach to tropical cyclone track forecasting is attributed to the ability to recognize likely errors associated with specific dynamical forecast models. These model error traits were identified after assessing the skill associated with an exhaustive set of dynamical forecast cases. Extension of track forecasts to 120 h would benefit from better identification of the location and timing of tropical cyclone formation. This study is an extension of the systematic approach to forecasts of tropical cyclone formation via identification of model error characteristics associated with forecasts of tropical cyclone formation.

An algorithm has been developed to detect and track in dynamical model fields those circulations that have become, or are forecast to become, tropical cyclones. Additionally, specific environmental conditions in the model analysis and forecast fields are attached to the tracked circulation. Threshold values of important environmental parameters associated with failed and successful model predictions of tropical cyclone formation are identified at each forecast range. Examples of environmental parameters include low-level vorticity, sea-level pressure, convective and total precipitation amounts, vertical wind shear, and mid-tropospheric moisture.

Based on the circulation tracks from the algorithm, an assessment of successful and failed 12-h through 120-h forecasts of tropical cyclone formation can be made. Failed forecasts may be actual formations that were never forecast or forecast formations that never occurred. Classification of environmental parameters associated with successful and failed forecasts will be used to calculate a measure of confidence that a forecast circulation will not develop. Such a confidence measure could be used by operational forecasters to maximize the probability of detection of a tropical cyclone formation or minimize a false alarm.

Results from the 2001 tropical cyclone seasons over the western North Pacific and Atlantic Oceans are presented to define threshold values and assess of the performance of the Navy Operational Global Atmospheric Prediction System (NOGAPS) forecast model.