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Overlake Wind Events on Lake Erie
This project is no longer current. Please see the Research Programs page for a list of current research projects.
Executive Summary
This project is exploratory research using existing meteorological data to find correlation of wind forcing events on Lake Erie to such factors as cyclone tracks through the region and upper-level flow patterns. Analysis was carried out on cyclone (closed low pressure system) tracks and winds in the Lake Erie region, and their linkages to atmospheric patterns on the hemispheric-to-global scale. An interesting observation that is quite robust is that high numbers of cyclones in the Lake Erie region are associated with a large-scale pattern of pressure that is quite reminiscent of the North Atlantic Oscillation (NAO) pattern
Project Report
Strong wind events that can drive dynamical events on Lake Erie, including transient currents and seiches, can be associated with the passage of an extratropical cyclone. These cyclones have been generalized into types following three main tracks--the Alberta track, the Colorado track, and the Gulf of Mexico track. The prevalence of one of these storm tracks over others can be dependent on the patterns of upper level flow, which are known to have dominant modes of variability. This research looks for correlation between dynamical events on Lake Erie and atmospheric events, differentiating between such things as positive and negative Pacific-North American patterns or North Atlantic Oscillation Index; Alberta, Colorado, and Gulf of Mexico track cyclones; and also breaking down relationships by season.
Figure 1. Storm tracks that reach the Lake Erie basin during December, January, and February of (top) the 5 years with the lowest Southern Oscillation index (El Niņo years) and (bottom) the 5 years with the highest Southern Oscillation index (La Niņa years).
A comparison between El Niņo and La Niņa years for the tracks of cyclones coming into the Lake Erie region (Fig. 1) shows a greater number of cyclone tracks approaching from the northwest during El Niņo winters than La Niņa winters, and more overall, but fewer approaching from the south-southwest. The statistical significance of this is currently unknown.
Although there seems to be some effect from the El Niņo-Southern Oscillation (ENSO) index, a pattern that is well known among the popular press and general public, we tried to look beyond this and find whatever large-scale patterns fit best with prevalence of cyclone passage through the immediate vicinity of Lake Erie. To this end, we made the analysis depicted in Figure 2.
Figure 2.The difference in mean sea level pressure between years with high occurrence of Lake Erie cyclone passage and low occurrence
The pattern that appears over the Atlantic Ocean in this figure is quite similar to the positive phase of the North Atlantic Oscillation (NAO, i.e. larger numbers of cyclone passage occur with positive NAO and smaller numbers with negative NAO) as described in, e.g., Deser and Blackmon 1993, but with the positive sea level pressure anomaly displaced northwestward compared to the standard NAO. The positive phase of NAO is known to be associated with increased precipitation in the eastern part of the United States and southeastern Canada, although the cause and effect relation between the NAO and precipitation in this region is subject to debate.
Comparison of 700 mb heights (not shown, but bearing a similar pattern to the mean sea level pressure shown in Figure 2) shows general agreement with the pattern shown by Rodionov (1994) associated with high wintertime precipitation in the Great Lakes area. However, the interpretation of the pattern is different, in that Rodionov characterized it at a modified Pacific-North American (PNA) pattern, emphasizing the antinodes located over the Pacific Ocean and northwestern North America, along with the one off the east coast of North America, while our interpretation of a modified NAO emphasizes the prominent low anomaly near Iceland.
Project Plans
Analyze for systematic difference in frequency of various storm tracks
based on atmospheric states with high persistency.
Derive correlation of wind events with storm track events. Winds will
be based both on near-shore ground station data and scatterometer data.
Evaluate statistical significance of correlation between wind a storm
track events, and of prevalence of distinct storm tracks as a function
of various teleconnection indices, most likely using a non-parametric
Wilcoxon test.
Accomplishments
We have identified a data source and created a system for charting the trajectory of low pressure centers that approach Lake Erie. Many figures have been created by categorizing the conditions by such criteria as the strength of the low, season, and phase of El Niño-Southern Oscillation. Statistical analysis is planned.
This project had significant activity with the help of summer volunteer Peter Bieniek. Peter, along with Brent Lofgren, worked on algorithms for tracking and mapping the paths of storms into Lake Erie. Of considerable aid in this effort was switching from developing our own algorithm for tracking based on input from 12-hourly data from the NCAR/NCEP reanalysis project to using tracks already available online, using the method of Serreze et al. (1993).
References
Deser, C., and M. L. Blackmon, 1993: Surface climate variations over the North Atlantic Ocean during winter: 1900-1993. Journal of Climate, 6, 1743-1753.
Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetmaa, R. Reynolds, R. Jenne, and D. Joseph, The NCEP/NCAR 40-year reanalysis project, Bull. Amer. Meteorol. Soc., 77, 437-471, 1996.
Rodionov, S. N. 1994. Association between winter precipitation and water level fluctuations in the Great Lakes and atmospheric circulation patterns. J. Climate, 7: 1693-1706.
Serreze, M. C., J. E. Box, R. G. Barry, and J. E. Walsh, 1993: Characteristics of Arctic synoptic activity, 1952-1989. Meteorology and Atmospheric Physics, 51, 147-164.
