A comparison of WRF simulated composite reflectivity and precipitation to observations in the Central US
| dc.contributor.advisor | Li, Yanping | |
| dc.contributor.committeeMember | Ireson, Andrew | |
| dc.contributor.committeeMember | Guo, Huiqing | |
| dc.contributor.committeeMember | Li, Wenhong | |
| dc.creator | Flemke, Jason Peter 1993- | |
| dc.creator.orcid | 0000-0003-2622-6801 | |
| dc.date.accessioned | 2020-01-06T20:38:27Z | |
| dc.date.available | 2020-01-06T20:38:27Z | |
| dc.date.created | 2019-12 | |
| dc.date.issued | 2020-01-06 | |
| dc.date.submitted | December 2019 | |
| dc.date.updated | 2020-01-06T20:38:27Z | |
| dc.description.abstract | Precipitation from Mesoscale Convective Systems (MCSs) in the central US are not only a large contributor to water resources, but a hazard to society due to hail, wind gusts, tornadoes, lightning, and flash floods. These severe storms can cause damage to houses, vehicles, and trees. Due to this significance, there is a large interest in using Numerical Weather Prediction (NWP) to predict extreme weather and climate. Also, with a changing climate, it is important to understand how weather system characteristics will change in the future. Convection-permitting NWP models simulate convective processes more realistically than coarser grid models due to errors in local-scale processes and convective parameterization not accurately producing convection. The National Center for Atmospheric Research (NCAR) conducted a continental-scale convection-allowing simulation using the regional Advanced Research Weather Research and Forecasting (WRF-ARW) model. The model simulations are made up of two parts: (1) A 13-year (2000–2013) simulation of historical weather and climate patterns, and (2) A pseudo global warming (PGW) simulation to project the weather and climate patterns at the end of the 21st century. This model was designed to have 4-km grid spacing covering the entire continental US and the southern portion of Canada (up to 56 ºN) and downscaled the ERA-Interim reanalysis for the period from October 2000 to September 2013. Downscaling to a higher resolution permits the model to simulate deep convection without parameterization, proving to be more realistic. The primary objective of this study is to evaluate the historical portion of the WRF model’s capabilities in producing the characteristics of observed warm-season convection in the central United States, with an emphasis on radar reflectivity distribution, the diurnal cycle of precipitation and storm propagation. The secondary objective is to evaluate the PGW projection to understand how a future climate will impact radar reflectivity distribution, the diurnal cycle of precipitation, and storm propagation. The first objective is achieved by comparing the simulated composite (column maximum) radar by comparing the Weather Surveillance Radar-1988 Dopplers (WSR-88Ds) national mosaic is an objective of this research. Along with radar, the accumulated modeled precipitation is validated against the Stage IV multisensory gridded observed precipitation product. The comparison focuses on the central plains of the US for March through August. Specifically, the area of interest for this research is between 30 ºN and 45 ºN, and 90 ºW and 105 ºW. Results comparing the historical simulation to observations show that the simulation can produce a similar distribution of heavy extreme reflectivity values, yet is shown to underestimate light and moderate reflectivity and precipitation frequencies. This study also determined that the model can capture the timing of the precipitation diurnal cycle, including the general propagation of thunderstorms across the domain. However, there is a significant underestimation of nocturnal convection in the central US east of the high plains. These model deficiencies are partly due to small (> 4km) scale forcing mechanisms (i.e., cold pool propagation and undular bores) that play a role in nocturnal initiation of convection and the warm/dry bias present in the simulation during JJA. The research presented in this thesis illustrates that this convective permitting high-resolution WRF simulation is beneficial in understanding the precipitation patterns in the central US and possible effects of climate change on precipitation. However, the warm and dry bias present in the central US, lack of simulated small scale forcing mechanisms, and the PGW simulation not including the change in climate storm track dynamics should be considered as model weaknesses. This study concludes that this simulation can be more useful by improving the land surface and radiation schemes, improve the parameterization of small scale mechanisms and use a smaller horizontal grid spacing to simulate shallow convection better. This research should contribute to the climate modeling community since this is a high-resolution climate simulation that has shown to be a large improvement from coarse resolution climate models. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/10388/12513 | |
| dc.subject | Climate change | |
| dc.subject | Convection-Permitting Model | |
| dc.subject | Pseudo Global Warming | |
| dc.subject | Radar | |
| dc.subject | Precipitation Diurnal Cycle | |
| dc.subject | Weather Research and Forecasting | |
| dc.title | A comparison of WRF simulated composite reflectivity and precipitation to observations in the Central US | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | School of Environment and Sustainability | |
| thesis.degree.discipline | Environment and Sustainability | |
| thesis.degree.grantor | University of Saskatchewan | |
| thesis.degree.level | Masters | |
| thesis.degree.name | Master of Environment and Sustainability (M.E.S.) |