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Assimilation of surface weather observations in complex terrain

University of British Columbia

Present computing power allows fine-resolution numerical weather prediction models to resolve meso-gamma flows within individual valleys. Such resolution is critical for mountainous British Columbia, because the valleys contain most of the population centers, industries, and transportation routes. Accurate high-resolution forecasts depend on accurate initial fields from which to start. To this end, dense local surface weather observations should be utilized to supplement the existing coarse-resolution Eta model analysis, while keeping computational costs of data assimilation reasonable for local mesoscale modeling. This dissertation develops a technique that allows the creation of a new anisotropic background-error correlation model for complex terrain, which horizontally spreads surface weather observations along circuitous valleys. The technique, called the mother-daughter approach, is based on first-order boundary-layer characteristics in mountainous terrain. The approach is further refined to account for land-sea anisotropy, and to treat mountaintop observations differently from valley observations. The resulting improved analysis from combining the detailed surface analysis with pseudo upper-air data from the Eta model analysis is used to initialize a high-resolution forecast model. The mother-daughter approaches are tested and compared with two existing methods, using virtual and real observations over different domains in mountainous British Columbia. It is found that the mother-daughter approaches outperform the other methods. The coastline refinement adds value to the original mother-daughter approach in maintaining thermal contrast across coastlines. Numerical experiments are performed to assess the impacts of assimilating surface observations in complex terrain on subsequent forecasts of near-surface parameters. Better skill in predicting near-surface potential temperature is found when surface information is spread upward throughout the whole boundary layer instead of at only one model level. Experimental results show improvement on subsequent near-surface forecasts of the variables (e.g., temperature and humidity) that are directly assimilated into the model. However, the assimilation forecast run tends to worsen the forecasts of near-surface winds, which were not assimilated. These findings are confirmed by operational runs, and only minor differences are found. In summary, a method is devised to bring local surface weather observations in complex terrain into a high-resolution forecast model. Suggestions are made to also assimilate surface-wind data.

Text

2009-12-23

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http://hdl.handle.net/2429/17090

Atmospheric Science

University of British Columbia

UBCV

DSpace