Use of a Real-Time Computer Graphics System in Analysis and Forecasting

Cahir, John J.; Lowry, Dale A.

doi:10.1175/1520-0493(1981)109<0485:uoartc>2.0.co;2

Cited by 14 publications

(5 citation statements)

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“…Snowfall data was obtained from cooperative observers and snow spotters from the NWS, and official NWS observations. Station plots and buoy data were obtained from the NWS in State College, Pennsylvania, and from The Pennsylvania State University meteorological system (Cahir et al 1981). Buoy data was available for two of the three cases.…”

Section: Methodsmentioning

confidence: 99%

Mesoscale Band Formation in Three Major Northeastern United States Snowstorms

Nicosia¹,

Grumm²

1999

Wea. Forecasting

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The National Centers for Environmental Prediction's 29-km version Meso Eta Model and Weather Surveillance Radar-1988 Doppler base reflectivity data were used to diagnose intense mesoscale snowbands in three northeastern United States snowstorms. Snowfall rates within these snowbands were extreme and, in one case, were close to 15 cm (6 in.) per hour. The heaviest total snowfall with each snowstorm was largely associated with the positioning of these mesoscale snowbands. Each snowstorm exhibited strong midlevel frontogenesis in conjunction with a deep layer of negative equivalent potential vorticity (EPV). The frontogenesis and negative EPV were found in the deformation zone, north of the developing midlevel cyclone. Cross-sectional analyses (oriented perpendicular to the isotherms) indicated that the mesoscale snowbands formed in close correlation to the intense midlevel frontogenesis and deep layer of negative EPV. It was found that the EPV was significantly reduced on the warm side of the midlevel frontogenetic region as midlevel dry air, associated with a midlevel dry tongue jet, overlaid a low-level moisture-laden easterly jet, north of each low-level cyclone. The continual reduction of EPV on the warm side of the frontogenetic region is postulated to have created the deep layer of negative EPV in the warm advection zone of each cyclone. The negative EPV was mainly associated with conditional symmetric instability (CSI). Each case exhibited a much smaller region of conditional instability (CI) on the warm side of the frontogenesis maximum for a short period of time. The CSI and, to a lesser extent, CI are postulated to have been released as air parcels ascended the moist isentropes, north of the warm front, upon reaching saturation. This likely was a major factor in the mesoscale band formation and heavy snowfall with each snowstorm. The results indicate that model frontogenesis and EPV fields can be used to predict the potential development of mesoscale snowbands. When a deep layer of negative EPV and strong midlevel frontogenesis are forecast by the models, forecasters can anticipate the regions where mesoscale snowbands may form. Inspection of saturation equivalent potential temperature in conjunction with EPV is suggested to determine whether CI is present in a negative EPV region. If CI is present in addition to CSI, then upright convection may dominate over slantwise convection leading to heavier snowfall rates. The region where the frontogenesis and negative EPV are forecast to persist the longest (usually left of the 700-hPa low track) is where the heaviest storm total snowfall will occur. Once mesoscale bands are detected on radar, accurate short-term forecasts of areas that will receive heavy snowfall can be made.

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Section: Methodsmentioning

confidence: 99%

Mesoscale Band Formation in Three Major Northeastern United States Snowstorms

Nicosia¹,

Grumm²

1999

Wea. Forecasting

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“…All data were analyzed subjectively with the exception of the 500-mb vorticity and the 200mb divergence fields. These fields were analyzed using the objective analysis system described by Cahir et al (1981) and smoothed using the Barnes analysis technique (Barnes 1964). All radiosonde data and corresponding indices were analyzed using the RAOB PRO software package (Environmental Research Services, Matamoras, PA).…”

Section: Methodsmentioning

confidence: 99%

The Madison County, Virginia, Flash Flood of 27 June 1995

1999

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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 highe 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.

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“…Fankhauser justified allocating equal weight to the lowest layer despite its smaller depth by noting that most of the air entering a thunderstorm originates at low levels. Estimates of the winds in the vicinity of the MCCs were obtained using the objective analysis system documented in Cahir et al (1981).…”

Section: Methodsmentioning

confidence: 99%

Predicting the Movement of Mesoscale Convective Complexes

1996

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A procedure for operationally predicting the movement of the mesobeta-scale convective elements responsible for the heavy rain in mesoscale 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 01 and 17Њ. 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.

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Use of a Real-Time Computer Graphics System in Analysis and Forecasting

Cited by 14 publications

References 0 publications

Mesoscale Band Formation in Three Major Northeastern United States Snowstorms

Mesoscale Band Formation in Three Major Northeastern United States Snowstorms

The Madison County, Virginia, Flash Flood of 27 June 1995

Predicting the Movement of Mesoscale Convective Complexes

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