Using NOAA UAS Assets and OSSE/DA Capabilities to Improve Sampling Strategies and Numerical Prediction of Tropical Cyclone Track, Intensity, and StructurePrincipal Investigators: Project Members:
Lance Bosart (Univ. at Albany-SUNY) Ryan Torn (Univ. at Albany-SUNY) Funding Information:
Objectives: This investigation proposes to utilize a combination of unmanned aircraft systems (UAS), satellite data, numerical modeling and data assimilation to address one of the main objectives identified by NOAA’s Sensing Hazards with Operational Unmanned Technology (SHOUT) program: quantify the significance of unmanned observations to high impact weather prediction through data impact studies using Observing System Experiments (OSE) using unmanned observations collected during prototype operational field missions and Observing System Simulation Experiments (OSSE) based on expected unmanned observing capabilities. Specific emphasis of this effort will include mission design and support for NOAA Global Hawk missions into tropical cyclones (TCs), optimizing Global Hawk aircraft real-time sampling strategies in both the TC inner core and the surrounding environment, using Global Hawk data to investigate various aspects of the TC inner core and surrounding environment (e.g. warm core, boundary layer, and cirrus canopy regions) in the context of TC intensity change, and numerical modeling analyses that will use a combination of high-resolution, multi-scale HWRF, a state-of-the-art, ensemble-based, high-resolution DA system (HEDAS; Aksoy et al. 2012 and 2013, Aksoy 2013), and a comprehensive OSSE platform that combines all of these tools in an end-to-end system with a wide range of diagnostic tools designed to investigate TCs. Accomplishments:
When all available observations were assimilated in these two cases and were compared to when Global Hawk dropsondes were withdrawn from assimilation, the impact of the Global Hawk dropsondes on the analysis fields was very noticeable as can be seen in the following figure: It is clear in the above figure that when Global Hawk dropsondes were the only observations in the inner core, they had a significant impact on the inner-core structure in the analysis. On the other hand, when Global Hawk dropsondes had to compete with a large volume of other data, their impact on the analysis was restricted in the inner core but more pronounced in the near environment. When forecasts were initialized with these analyses, we obtained impacts on track and intensity that were consistent with the impacts on the analyses themselves, as is demonstrated in the following figure: The impact on the analyses is nicely reflected in the forecasts as well. When Global Hawk dropsondes were the only observations in the inner core, they had a significant positive impact on the intensity forecast, whereas when they had to compete with a large volume of other data, their positive impact on the forecast can be mostly observed for track. References:
|
Links of Interest
AOML Tools & Resources
Employee Tools
|