Abstract: An automated trigger device and a corresponding method for dynamic triggering of developing and/or imminent tropical storms for integrated monitoring devices and/or control devices and/or early warning systems. The trigger device includes a trigger module, and measurement devices arranged in cellular, geographically and/or topologically definable units or zones. Geophysical measurement parameters can be transmitted from the measurement devices to the trigger module. By a Monte Carlo module—and based on the measurement parameters—data records can be dynamically generated for definable future time intervals. By an extrapolation module track distribution parameters of a track distribution integrable over the plurality of data records are generated for each of the definable future time intervals. By an activating device—and based on the generated track distribution parameters and/or the trigger parameters—a corresponding control signal is transmitted to the monitoring device.

Abstract: A method for automated location dependent probabilistic tropical cyclone forecast. A plurality of new data records representative of alternative tracks are generated based on historical tracks by a first MonteCarlo-module. Points of the new data records are generated from points along the historical track by a dependent sampling process, whereas an intensity climatology is generated, based upon intensity data associated with at least some of the plurality of points along the historical tracks located within a certain grid cell. New intensity data are generated by a second MonteCarlo-module, from the intensity data associated with at least some of the plurality of points along the historical tracks by a MonteCarlo sampling process.

Abstract: A computer method of generating a probabilistic dataset relating to a weather event includes inputting data representative of an historical weather event, and generating data representative of a plurality of alternative events. The data for the alternative events are generated, in certain embodiments, by a dependent sampling process. In particular embodiments, the dependent sampling process is a directed random walk process. Data for the alternative events may include data relating to the geographical positions or “tracks” of the event, data relating to atmospheric pressures, or both.

Abstract: A method for automated location dependent probabilistic tropical cyclone forecast. A plurality of new data records representative of alternative tracks are generated based on historical tracks by a first MonteCarlo-module. Points of the new data records are generated from points along the historical track by a dependent sampling process, whereas an intensity climatology is generated, based upon intensity data associated with at least some of the plurality of points along the historical tracks located within a certain grid cell. New intensity data are generated by a second MonteCarlo-module, from the intensity data associated with at least some of the plurality of points along the historical tracks by a MonteCarlo sampling process.

Abstract: A computer method of generating a probabilistic dataset relating to a weather event includes inputting data representative of an historical weather event, and generating data representative of a plurality of alternative events. The data for the alternative events are generated, in certain embodiments, by a dependent sampling process. In particular embodiments, the dependent sampling process is a directed random walk process. Data for the alternative events may include data relating to the geographical positions or “tracks” of the event, data relating to atmospheric pressures, or both.

Abstract: A computer method of generating a probabilistic dataset relating to a weather event includes inputting data representative of an historical weather event, and generating data representative of a plurality of alternative events. The data for the alternative events are generated, in certain embodiments, by a dependent sampling process. In particular embodiments, the dependent sampling process is a directed random walk process. Data for the alternative events may include data relating to the geographical positions or “tracks” of the event, data relating to atmospheric pressures, or both.

Abstract: A computer method of generating a probabilistic dataset relating to a weather event includes inputting data representative of an historical weather event, and generating data representative of a plurality of alternative events. The data for the alternative events are generated, in certain embodiments, by a dependent sampling process. In particular embodiments, the dependent sampling process is a directed random walk process. Data for the alternative events may include data relating to the geographical positions or “tracks” of the event, data relating to atmospheric pressures, or both.