Case-Base Devaluation of a Physical Initialization Technique for Assimilating Precipitation in NWP
A novel method for assimilating precipitation observations into a numerical weather prediction model is presented and evaluated for a case study of a monsoon rainfall event over the Asian subcontinent. The method, known as physical initialization (Krishnamurti et al. 1991), involves the iterative ad...
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| Format: | Others |
| Language: | English English |
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Florida State University
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| Online Access: | http://purl.flvc.org/fsu/fd/FSU_SUMMER2017_Chaney_fsu_0071N_14094 |
| Summary: | A novel method for assimilating precipitation observations into a numerical weather prediction model is presented and evaluated for a case study of a monsoon rainfall event over the Asian subcontinent. The method, known as physical initialization (Krishnamurti et al. 1991), involves the iterative adjustment of the vertical moisture profile towards a configuration that would permit simulated precipitation where there is observed precipitation. The physical initialization procedure was incorporated into the Weather Research and Forecasting (WRF) model. Evaluation of the technique was accomplished through the comparison of two simulations: one with the physical initialization and one without. Both simulations were evaluated against TRMM rainfall. The impact of physical initialization was shown to be beneficial to the two-day typical Indian Summer Monsoon case study with respect to the rainfall forecast skill as well as the mesoscale circulation and vertical redistribution of moisture. Specifically, the correlation between simulated and observed 3-hour accumulated precipitation is higher throughout the two-day forecast period in the run with physical initialization. The probability distribution of rainfall amounts in the run with physical initialization was also more similar to the observations, whereas the control WRF run exhibited a large bias of widespread light to moderate rain. Additionally, the run with physical initialization improves the forecast location of mesoscale precipitation features and removes regions of spurious rain from the forecast. Simulations were conducted and evaluated for this case only. === A Thesis submitted to the Department of Earth, Ocean and Atmospheric Science in partial fulfillment of the requirements for the degree of Master of Science. === Summer Semester 2017. === July 7, 2017. === Includes bibliographical references. === Jeffrey Chagnon, Professor Directing Thesis; Robert Hart, Committee Member; Vasu Misra, Committee Member; Robert Ross, Committee Member. |
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