A Further Examination of Potential Observation Network Design with Mesoscale Ensemble Sensitivities in Complex Terrain
Abstract
Recent expansion in availability of stand-alone atmospheric observing sensors introduces the question of where placement maximizes gain in forecast accuracy. This study examined how sensitivity analysis and observation targeting can be used to optimize sensor placement. The primary objective of this project was to determine whether a mesoscale Ensemble Sensitivity Analysis (ESA) can be used to identify the sensitivity profile of fog formation in a complex terrain environment. Building on work by Chilcoat (2012), this study utilized several alternate methodologies to conduct ESA, including a more realistic observing network and implementation of a Gaussian filter. The second objective was to determine whether the calculated sensitivities could be used to reduce forecast uncertainty for a forecast metric related to dense fog formation. This was done by introducing a real-world truth observation at the location of greatest sensitivity. The results of this study indicate that ESA provides a cogent mesoscale sensitivity profile which can be used to accurately predict forecast changes in fog using initial condition potential temperature values. This type of information may prove valuable in planning the layout of future observational networks, as well as introduce the potential for performing data-thinning during data assimilation and real-time updates to forecast metrics.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 2013
- Accession Number
- ADA579823
Entities
People
- Sean M. Wile
Organizations
- Naval Postgraduate School