Lagrangian trajectories were computed for three extreme summer rainfall events (with rainfall exceeding 100 mm) over the southern Mackenzie River basin to test the hypothesis that the low-level moisture feeding these rainstorms can be traced back to the Gulf of Mexico. The three-dimensional trajectories were computed using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT).
For all three events, parcel trajectories were identified that originated near the Gulf of Mexico and terminated over the southern Mackenzie River basin. Specifically, the transport of low-level moisture was found to occur along either quasi-continuous or stepwise trajectories. The time required to complete the journey varied between 6 and 10 days.
Closer examination of the data suggests that, for the three cases in question, the transport of modified Gulf of Mexico moisture to high latitudes was realized when the northward extension of the Great Plains low-level jet to the Dakotas occurred in synch with rapid cyclogenesis over Alberta, Canada. In this way, modified low-level moisture from the Gulf of Mexico arrived over the northern Great Plains at the same time as a strong southerly flow developed over the Dakotas and Saskatchewan, Canada, in advance of the deepening cutoff low over Alberta. This moist air was then transported northward over Saskatchewan and finally westward over the southern Mackenzie River basin, where strong ascent occurred.
This study examines simulations of two flooding events in Alberta, Canada, during June 2005, made using the Weather Research and Forecasting Model (WRF). The model was used in a manner readily accessible to nonmeteorologists (e.g., accepting default choices and parameters) and with a relatively large spatial resolution for rapid model runs. The simulations were skillful: strong storms were developed having the correct timing and location, generating precipitation rates close to observations, and with precipitation amounts near that observed. The model was then used to examine the sensitivity of the two storms to the topography of the Rocky Mountains. Comparing model results using the actual topographic grid with those of a reduced-mountain grid, it is concluded that a reduction in mountain elevation decreases maximum precipitation by roughly 50% over the mountains and foothills. There was little sensitivity to topography in the precipitation outside the mountains.
Abstract:In order to evaluate cumulus parameterization (CP) schemes for hydrological applications, the Pennsylvania State University-National Center for Atmospheric Research's fifth-generation mesoscale model (MM5) was used to simulate a summer monsoon in east China. The performances of five CP schemes (Anthes-Kuo, Betts-Miller, Fritsch-Chappell, Kain-Fritsch, and Grell) were evaluated in terms of their ability to simulate amount of rainfall during the heavy, moderate, and light phases of the event. The Grell scheme was found to be the most robust, performing well at all rainfall intensity and spatial scales. The Betts-Miller scheme also performed well, particularly at larger scales, but its assumptions may make it inapplicable to non-tropical environments and at smaller scales. The Kain-Fritsch scheme was the best at simulating moderate rainfall rates, and was found to be superior to the Fritsch-Chappell scheme on which it was based. The Anthes-Kuo scheme was found to underpredict precipitation consistently at the mesoscale. Simulation performance was found to improve when schemes that included downdrafts were used in conjunction with schemes that did not include downdrafts.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.