Browsing by Author "Nielsen, Erik R., author"

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Open Access
Insights into extreme short-term precipitation associated with supercells and mesovortices
(Colorado State University. Libraries, 2019) Nielsen, Erik R., author; Schumacher, Russ S., advisor; van den Heever, Susan C., committee member; Bell, Michael M., committee member; Niemann, Jeffrey D., committee member
Overall, this manuscript aims to holistically evaluate the relationship between rotation and extreme precipitation processes, since radar and rain-gauge observations in several flash flooding events have suggested that the heaviest short-term rainfall accumulations were associated with supercells or mesovortices embedded within larger convective systems. A specific subclass of these events, when tornadoes and flash floods are both concurrent and collocated (referred to here at TORFF events), present a unique set of concerns, since the recommended life-saving actions for each threat are contradictory. Given this, Chapter 2 aims to evaluate the climatological and meteorological characteristics associated with TORFF events over the United States. Two separate datasets, one based on overlapping tornado and flash flood warnings and the other based on observations, were used to arrive at estimations of the instances when a TORFF event was deemed imminent and verified to have occurred, respectively. These datasets, combined with field project data, were then used to discern the geographical and meteorological characteristics of recent TORFF events. The results show that TORFF scenarios commonly occur, are not easily distinguishable from tornadic events that fail to produce collocated flash flooding, and present difficult challenges both from the perspective of forecasting and public communication. The research in Chapter 3 strives to identify the influence that rotation has on the storm-scale processes associated with heavy precipitation. Five total idealized simulations of a TORFF event, where the magnitude of the 0-1 km shear was varied, were performed to test the sensitivity of precipitation processes to rotation. In the simulations with greater environmental low-level shear and associated rotation, more precipitation fell, both in a point maximum and area-averaged sense. Intense, rotationally induced low-level vertical accelerations associated with the dynamic nonlinear perturbation vertical pressure gradient force were found to enhance the low-to-mid level updraft strength, total vertical mass flux, and allowed access to otherwise inhibited sources of moisture and CAPE in the higher shear simulations. The dynamical accelerations, which increased with the intensity of the low-level shear, dominated over buoyant accelerations in the low levels and were responsible for inducing more intense, low-level updrafts that were sustained despite a stable boundary layer. Chapter 4 aims to explore how often extreme short-term rain rates in the United States are associated with storm-scale or mesoscale vortices, since significant low-level rotation does not always yield a tornado (i.e., not all extreme rainfall events are TORFFs). Five years of METAR observations and three years of Stage-IV analyses were obtained and filtered for hourly accumulations over 75 and 100 mm, respectively. Local dual-pol radar data was then obtained for the remaining events for the hour leading up to the METAR observation. Nearly 50% of the cases were associated with low-level rotation in high-precipitation supercells and/or mesoscale vortices embedded in more organized storm modes. These results support recent modeling results, presented in Chapter 3, suggesting that rotationally induced dynamic vertical pressure accelerations are important to the precipitation formation mechanisms that lead to extreme short-term rainfall rates. The upper Texas Coast, in and around the Houston, TX area, has experienced many intense TORFF events over the recent years. The research in Chapter 5 focuses on examining the horizontally heterogeneous environmental characteristics associated with one of those events, the Tax Day flood of 2016, which was identified as a "verified" TORFF event in Chapter 2. Radar and local mesonet rain gauge observations were used to examine the storm scale characteristics to identify the locations and structures of extreme rain rate producing cells. To supplement the observational based analysis above, a WRF-ARW simulation of the Tax Day flood in 2016, based upon a real-time forecast from the HRRR, was examined. Convective cells that produced the most intense short-term (i.e., sub-hourly to hourly) accumulations within the MCS were examined for the influence of any attendant rotation on both the dynamics and microphysics of the precipitation processes. Results show that the most intense rainfall accumulations, as in the observations analysis, are associated with rotating convective elements, and the results of this chapter confirm that the processes described in Chapter 3 apply outside of the idealized framework.
Open Access
Using convection-allowing ensembles to understand the predictability of extreme rainfall
(Colorado State University. Libraries, 2016) Nielsen, Erik R., author; Schumacher, Russ, advisor; van den Heever, Susan, committee member; Ramirez, Jorge, committee member
The meteorological community has well established the usefulness of ensemble-based numerical weather prediction for precipitation guidance, since trusting one possible atmospheric solution can lead to, in some cases, particularly bad forecasts for precipitation guidance, owing to inherent uncertainties in precipitation processes that make deterministic prediction impractical. However, continued predictive challenges associated with intense convective rainfall has led to an increasing need to determine the most effective use of these ensemble systems in high impact, extreme precipitation events. Further, it cannot be assumed that ensembles will evolve similarly in both extreme precipitation and more benign events, due to the importance and error growth associated with convective-scale motions. This error growth associated with the chaotic nature of moist convective dynamics can also serve to limit the predictability of an extreme rainfall event (known as intrinsic predictability), in addition to predictability limits imposed by deficiencies in observing systems and numerical models (known as practical predictability). This research will focus on using a recently developed, operationally based ensemble dataset, specifically the National Oceanic and Atmospheric Administration's (NOAA) Second Generation Global Medium-Range Ensemble Reforecast Dataset (Reforecast-2), to create downscaled ensemble reforecasts of the extreme precipitation events. Some events examined during the course of this research are the inland movement of tropical storm Erin in 2007 and flooding associated with mesoscale convective vortices in Arkansas in 2010 and San Antonio, Texas in 2013. The global reforecasts are used to force an ensemble of convection-allowing WRF-ARW numerical simulations for the purpose of evaluating ensemble-based precipitation forecasts associated with specific extreme rainfall events. Using these ensemble forecasts, we address several questions related to the practical versus the intrinsic predictability of the extreme rainfall events examined. Experiments that vary the magnitude of the perturbations to the initial and lateral boundary conditions (ICs and LBCs) reveal a seemingly proportional scaling of ensemble spread early in the simulations associated with the magnitude of the perturbation, but this scaling is not maintained throughout the simulations. Additionally, a diurnal cycle in ensemble spread growth is observed with large growth associated with afternoon convection, but the growth rate then reduced after convection dissipates the next morning rather than continuing to grow. The specific characteristics of the diurnal cycle, however, vary based upon region and flow regime. Lastly, the ensemble spread was found to be influenced by the size of the IC perturbations out to at least 48 hours. These spread evolution characteristics speak to the viability of running convection-allowing ensembles for prediction on multi-day timescales, since no saturation of the ensemble spread is seen despite extreme precipitation within the modeled time period. In addition to the overall ensemble characteristics, terrain-induced precipitation variability associated with the terrain feature known as the Balcones Escarpment, located in central Texas, is analyzed in multiple instances of heavy rainfall in San Antonio and the surrounding area. Simulations in which the Balcones Escarpment is removed reveal that when the synoptic to mesoscale forcing for heavy rainfall are in place over the Balcones Escarpment, the terrain does not directly affect the occurrence or magnitude of precipitation. It does affect the spatial distribution of the precipitation in a small but consistent way. This shift in precipitation associated with removing the Balcones Escarpment, when compared to a WRF-ARW ensemble for the event, is smaller than shifts associated with typical atmospheric variability. The combined results of these experiments demonstrate that downscaled ensemble NWP systems using readily available global ensemble forecasts can faithfully represent previously unresolved mesoscale features, precipitation totals, and depict ensemble-spread characteristics associated with moist convection.