Application of Ensemble-based Sensitivity in Operational Observation Collection During Extreme Weather Events
Abstract
Although the most popular application of ensemble forecasts is the mean and forecast standard deviation, there is substantial information within the higher moment statistics of these datasets that can be used to evaluate the dynamics, sensitivity, and predictability of dynamical systems. In addition, ensemble-based sensitivity methods can be used to identify locations where additional observations could change and/or reduce the variance in a forecast metric of interest, such as tropical cyclone (TC) position or rainfall. One of the advantages of this approach is that it is flexible and computationally inexpensive post-processing application that can be quickly evaluated from operational or experimental ensemble forecast output. The goal of this talk is to provide examples of how ensemble-based sensitivity, applied to ECMWF ensemble forecasts, is currently being used as guidance for operational observation deployment. Since 2017, the National Hurricane Center has used experimental ensemble-based sensitivity output to guide aircraft dropwindsonde locations that are meant to improve TC track forecasts. In addition, this technique has been used within the AR Recon program to evaluate the forecast uncertainty and target locations for precipitation forecasts during landfalling atmospheric rivers along the west coast of North America. The goal of this talk is to summarize the ensemble-based sensitivity technique, lessons learned, and examples of how this guidance has influenced operations.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMA196...02T
- Keywords:
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- 3314 Convective processes;
- ATMOSPHERIC PROCESSES;
- 3355 Regional modeling;
- ATMOSPHERIC PROCESSES;
- 1817 Extreme events;
- HYDROLOGY;
- 4313 Extreme events;
- NATURAL HAZARDS