An Introduction to the Advanced Regional OSSE Framework for Hurricane Prediction
Abstract
The development of an Observing System Simulation Experiment (OSSE) framework dictates how results can be applied to real-world scenarios. The limitations of such a framework must be well-known and accounted for when interpreting results. This requires both a validated Nature Run and a rigorous calibration of the OSSE system using Observing System Experiments (OSEs). Analysis techniques used for the OSEs will be replicated using synthetic observations obtained from AOML's Basin Scale Nature Run to determine the advanced regional OSSE system's ability to replicate reality. Since results from an OSSE can suggest changes to future observing system designs, a versatile framework is required to assess both current and upcoming numerical weather prediction systems.
NOAA's Atlantic Oceanographic and Meteorological Laboratory (AOML) has developed a new testbed for model and data assimilation development, ensemble forecasting, observing system design, and satellite data assimilation research. This testbed adopts a research-based version of the Hurricane Weather Research and Forecasting (HWRF) model that has been reconfigured with fully-cycled ensemble data assimilation on a fixed domain for tropical cyclone forecasts. This version of HWRF supports uninterrupted assimilation of conventional and satellite observations for entire hurricane seasons. The resulting strategy allows for a systematic season-long evaluation of the HWRF model and data assimilation procedures to guide future developments and applications. Therefore, the framework for advanced regional OSSEs takes advantage of this HWRF testbed. This presentation provides an introduction to AOML's advanced regional OSSE framework for tropical cyclones with an emphasis on OSE results obtained using this system. Many hurricane cases are required to obtain robust error statistics for OSSE system calibration. Thus, the cases selected to perform these experiments encompass a wide range of scenarios from the 2017 Atlantic hurricane season, including several intense, long-lived storms and multiple landfalls.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A13C..07R
- Keywords:
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- 3315 Data assimilation;
- ATMOSPHERIC PROCESSESDE: 3336 Numerical approximations and analyses;
- ATMOSPHERIC PROCESSESDE: 3372 Tropical cyclones;
- ATMOSPHERIC PROCESSESDE: 0520 Data analysis: algorithms and implementation;
- COMPUTATIONAL GEOPHYSICS