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- Author or Editor: J. M. Fritsch x
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Abstract
An automated statistical system that utilizes regional high-density surface observations to forecast low ceiling and visibility events in the upper Midwest is presented. The system is based solely upon surface observations as predictors, featuring forecast lead times of 1, 3, and 6 h.
A test of the forecast system on a 5-yr independent sample of events shows that for a 1-h lead time, an additional 2%–4% reduction in the mean squared error (MSE) is obtained by the high-density forecasting system compared to that for a system utilizing only the standard synoptic observations. Meanwhile, tests on a 3-h lead time reveal an additional 0%–1.5% reduction in MSE by the high-density system over the synoptic system. Little improvement is gained by the high-density system at a 6-h lead time.
The results indicate that current observations-based forecasting techniques can be improved simply by utilizing a higher density of surface weather observations. With this enhanced guidance, it is likely that decisions impacted by the arrival and duration of low ceiling and visibility can be improved.
Abstract
An automated statistical system that utilizes regional high-density surface observations to forecast low ceiling and visibility events in the upper Midwest is presented. The system is based solely upon surface observations as predictors, featuring forecast lead times of 1, 3, and 6 h.
A test of the forecast system on a 5-yr independent sample of events shows that for a 1-h lead time, an additional 2%–4% reduction in the mean squared error (MSE) is obtained by the high-density forecasting system compared to that for a system utilizing only the standard synoptic observations. Meanwhile, tests on a 3-h lead time reveal an additional 0%–1.5% reduction in MSE by the high-density system over the synoptic system. Little improvement is gained by the high-density system at a 6-h lead time.
The results indicate that current observations-based forecasting techniques can be improved simply by utilizing a higher density of surface weather observations. With this enhanced guidance, it is likely that decisions impacted by the arrival and duration of low ceiling and visibility can be improved.
Abstract
Consensus forecasts from the control runs of several operational numerical models are compared to 1) the control-run forecasts of the individual models that compose the consensus and to 2) other consensus forecasts generated by varying the initial conditions of the various individual models. It is found that the multimodel consensus is superior to the individual control runs and to the consensus forecasts constructed from ensembles of runs generated by varying model initial conditions. The source of the forecast improvement by model consensus is not the result of a simple cancellation of errors as a result of an overall positive bias in one model and an overall negative bias in another. Rather the main improvement stems from overlapping differences in the sign of the errors associated with forecasts of individual traveling disturbances. The results suggest that variations in model physics and numerics play a substantial role in generating the full spectrum of possible solutions that can arise in a given numerical forecast.
Abstract
Consensus forecasts from the control runs of several operational numerical models are compared to 1) the control-run forecasts of the individual models that compose the consensus and to 2) other consensus forecasts generated by varying the initial conditions of the various individual models. It is found that the multimodel consensus is superior to the individual control runs and to the consensus forecasts constructed from ensembles of runs generated by varying model initial conditions. The source of the forecast improvement by model consensus is not the result of a simple cancellation of errors as a result of an overall positive bias in one model and an overall negative bias in another. Rather the main improvement stems from overlapping differences in the sign of the errors associated with forecasts of individual traveling disturbances. The results suggest that variations in model physics and numerics play a substantial role in generating the full spectrum of possible solutions that can arise in a given numerical forecast.
Abstract
A procedure for operationally predicting the movement of the mesobeta-scale convective elements responsible for the heavy rain in mesocale convective complexes is presented. The procedure is based on the well-known concepts that the motion of convective systems can be considered the sum of an advective component, given by the mean motion of the cells composing the system, and a propagation component, defined by the rate and location of new cell formation relative to existing cells. These concepts and the forecast procedure are examined using 103 mesoscale convective systems, 99 of which are mesoscale convective complexes.
It is found that the advective component of the convective systems is well correlated to the mean flow in the cloud layer. Similarly, the propagation component is shown to be directly proportional (but opposite in sign) and well correlated to the speed and direction of the low-level jet. Correlation coefficients between forecast and observed values for the speed and direction of the mesobeta-scale convective elements are 0.80 and 0.78, respectively. Mean absolute errors of the speed and direction are 2.0 m s−1 and 17°. These errors are sufficiently small so that the forecast path of the centroid of the mesobeta-scale elements would be well within the heavy rain swath of the typical mesoscale convective complex.
Abstract
A procedure for operationally predicting the movement of the mesobeta-scale convective elements responsible for the heavy rain in mesocale convective complexes is presented. The procedure is based on the well-known concepts that the motion of convective systems can be considered the sum of an advective component, given by the mean motion of the cells composing the system, and a propagation component, defined by the rate and location of new cell formation relative to existing cells. These concepts and the forecast procedure are examined using 103 mesoscale convective systems, 99 of which are mesoscale convective complexes.
It is found that the advective component of the convective systems is well correlated to the mean flow in the cloud layer. Similarly, the propagation component is shown to be directly proportional (but opposite in sign) and well correlated to the speed and direction of the low-level jet. Correlation coefficients between forecast and observed values for the speed and direction of the mesobeta-scale convective elements are 0.80 and 0.78, respectively. Mean absolute errors of the speed and direction are 2.0 m s−1 and 17°. These errors are sufficiently small so that the forecast path of the centroid of the mesobeta-scale elements would be well within the heavy rain swath of the typical mesoscale convective complex.
Abstract
Between 25 and 27 June 1995, excessive rainfall and associated flash flooding across portions of western Virginia resulted in three fatalities and millions of dollars in damage. Although many convective storms occurred over this region during this period, two particular mesoscale convective systems that occurred on 27 June were primarily responsible for the severe event. The first system (the Piedmont storm) developed over Madison County, Virginia (eastern slopes of the Blue Ridge Mountains), and propagated slowly southward producing 100–300 mm of rain over a narrow swath of the Virginia foothills and Piedmont. The second system (the Madison storm) developed over the same area but remained quasi-stationary along the eastern slopes of the Blue Ridge for nearly 8 h producing more than 600 mm of rain.
Analysis of this event indicates that the synoptic conditions responsible for initiating and maintaining the Madison storm were very similar to the Big Thompson and Fort Collins floods along the Front Range of the Rocky Mountains, as well as the Rapid City flood along the east slopes of the Black Hills of South Dakota. In all four events, an approaching shortwave aloft coupled with high-level difluence/divergence signaled the presence of local ascent and convective destabilization. A postfrontal ribbon of relatively fast-moving high-θ e air, oriented nearly perpendicular to the mountain range, provided a copious moisture supply and helped focus the convection over a relatively small area. Weak middle- and upper-tropospheric steering currents favored slow-moving storms that further contributed to locally excessive rainfall.
A conceptual model for the Madison–Piedmont convective systems and their synoptic environment is presented, and the similarities and differences between the Madison County flood and the Big Thompson, Fort Collins, and Rapid City floods are highlighted.
Abstract
Between 25 and 27 June 1995, excessive rainfall and associated flash flooding across portions of western Virginia resulted in three fatalities and millions of dollars in damage. Although many convective storms occurred over this region during this period, two particular mesoscale convective systems that occurred on 27 June were primarily responsible for the severe event. The first system (the Piedmont storm) developed over Madison County, Virginia (eastern slopes of the Blue Ridge Mountains), and propagated slowly southward producing 100–300 mm of rain over a narrow swath of the Virginia foothills and Piedmont. The second system (the Madison storm) developed over the same area but remained quasi-stationary along the eastern slopes of the Blue Ridge for nearly 8 h producing more than 600 mm of rain.
Analysis of this event indicates that the synoptic conditions responsible for initiating and maintaining the Madison storm were very similar to the Big Thompson and Fort Collins floods along the Front Range of the Rocky Mountains, as well as the Rapid City flood along the east slopes of the Black Hills of South Dakota. In all four events, an approaching shortwave aloft coupled with high-level difluence/divergence signaled the presence of local ascent and convective destabilization. A postfrontal ribbon of relatively fast-moving high-θ e air, oriented nearly perpendicular to the mountain range, provided a copious moisture supply and helped focus the convection over a relatively small area. Weak middle- and upper-tropospheric steering currents favored slow-moving storms that further contributed to locally excessive rainfall.
A conceptual model for the Madison–Piedmont convective systems and their synoptic environment is presented, and the similarities and differences between the Madison County flood and the Big Thompson, Fort Collins, and Rapid City floods are highlighted.
Abstract
An analysis of a flash flood caused by a lake-enhanced rainband is presented. The flood took place near Erie, Pennsylvania, on 17 September 1996. It was found that the flood resulted from a complex interplay of several scales of forcing that converged over the Erie region. In particular, the flood occurred during a period when 1) a lake-enhanced convective rainband pivoted over the city of Erie with the pivot point remaining quasi-stationary for about 5 h; 2) a deep, surface-based no-shear layer, favorable for the development of strong lake-induced precipitation bands, passed over the eastern portion of Lake Erie; 3) the direction of flow in the no-shear layer shifted from shore parallel to onshore at an angle that maximized frictional convergence; 4) an upper-level short-wave trough contributed to low-level convergence, lifting, and regional destabilization; and 5) a strong land–lake diurnal temperature difference produced a lake-scale disturbance that locally enhanced the low-level convergence.
Analysis of the Weather Surveillance Radar-1988 Doppler radar data from Buffalo, New York, and Cleveland, Ohio, revealed that most of the radar-derived precipitation estimates for the region were overdone except for the region affected by the quasi-stationary rainband, which was underestimated. Reconstruction of the conditions in the vicinity of the band indicate that cloud bases were considerably lower and equivalent potential temperatures higher than for the areas of precipitation farther east over northwestern Pennsylvania and southwestern New York State. It is postulated that, due to the long distance from the radar sites to the Erie area, the radar was unable to observe large amounts of cloud condensate produced by warm-rain processes below 4 km. Estimates of precipitation rates from a simple cloud model support this interpretation.
Abstract
An analysis of a flash flood caused by a lake-enhanced rainband is presented. The flood took place near Erie, Pennsylvania, on 17 September 1996. It was found that the flood resulted from a complex interplay of several scales of forcing that converged over the Erie region. In particular, the flood occurred during a period when 1) a lake-enhanced convective rainband pivoted over the city of Erie with the pivot point remaining quasi-stationary for about 5 h; 2) a deep, surface-based no-shear layer, favorable for the development of strong lake-induced precipitation bands, passed over the eastern portion of Lake Erie; 3) the direction of flow in the no-shear layer shifted from shore parallel to onshore at an angle that maximized frictional convergence; 4) an upper-level short-wave trough contributed to low-level convergence, lifting, and regional destabilization; and 5) a strong land–lake diurnal temperature difference produced a lake-scale disturbance that locally enhanced the low-level convergence.
Analysis of the Weather Surveillance Radar-1988 Doppler radar data from Buffalo, New York, and Cleveland, Ohio, revealed that most of the radar-derived precipitation estimates for the region were overdone except for the region affected by the quasi-stationary rainband, which was underestimated. Reconstruction of the conditions in the vicinity of the band indicate that cloud bases were considerably lower and equivalent potential temperatures higher than for the areas of precipitation farther east over northwestern Pennsylvania and southwestern New York State. It is postulated that, due to the long distance from the radar sites to the Erie area, the radar was unable to observe large amounts of cloud condensate produced by warm-rain processes below 4 km. Estimates of precipitation rates from a simple cloud model support this interpretation.
