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- Author or Editor: William R. Cotton x
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Abstract
At Colorado State University the Regional Atmospheric Modeling System (RAMS) has been used to produce real-time forecasts of precipitation for the Colorado mountain region since 1991. Originally a so-called dump-bucket scheme was used to generate precipitation, but starting in the fall of 1995 real-time forecasts used the bulk microphysics scheme available with RAMS.
For the month of April 1995, a series of 24-h accumulated precipitation forecasts for the month were generated with both the dump-bucket and microphysics versions of the forecast model. Both sets of output were compared to a set of 167 community-based station reports and another set of 32 snow telemetry (SNOTEL) automatic pillow-sensor stations.
The addition of microphysics improved the forecasting of the areal extent and maximum amount of precipitation, especially when compared to the SNOTEL observational set, which is found at locations more representative of the model topography. Climatological station precipitation forecasts were improved on the average by correcting for the difference between a station’s actual elevation and the cell-averaged topography used by the model. The model had more problems with the precise timing and geographical location of the precipitation features, probably due in part to the influence of other model physics, the failure of the model to resolve adequately wintertime convection events, and inadequate initializations.
Abstract
At Colorado State University the Regional Atmospheric Modeling System (RAMS) has been used to produce real-time forecasts of precipitation for the Colorado mountain region since 1991. Originally a so-called dump-bucket scheme was used to generate precipitation, but starting in the fall of 1995 real-time forecasts used the bulk microphysics scheme available with RAMS.
For the month of April 1995, a series of 24-h accumulated precipitation forecasts for the month were generated with both the dump-bucket and microphysics versions of the forecast model. Both sets of output were compared to a set of 167 community-based station reports and another set of 32 snow telemetry (SNOTEL) automatic pillow-sensor stations.
The addition of microphysics improved the forecasting of the areal extent and maximum amount of precipitation, especially when compared to the SNOTEL observational set, which is found at locations more representative of the model topography. Climatological station precipitation forecasts were improved on the average by correcting for the difference between a station’s actual elevation and the cell-averaged topography used by the model. The model had more problems with the precise timing and geographical location of the precipitation features, probably due in part to the influence of other model physics, the failure of the model to resolve adequately wintertime convection events, and inadequate initializations.
Abstract
Mesoscale convective systems (MCSs) have a large influence on the weather over the central United States during the warm season by generating essential rainfall and severe weather. To gain insight into the predictability of these systems, the precursor environments of several hundred MCSs across the United States were reviewed during the warm seasons of 1996–98. Surface analyses were used to identify initiating mechanisms for each system, and North American Regional Reanalysis (NARR) data were used to examine the environment prior to MCS development. Similarly, environments unable to support organized convective systems were also investigated for comparison with MCS precursor environments. Significant differences were found between environments that support MCS development and those that do not support convective organization. MCSs were most commonly initiated by frontal boundaries; however, features that enhance convective initiation are often not sufficient for MCS development, as the environment needs also to be supportive for the development and organization of long-lived convective systems. Low-level warm air advection, low-level vertical wind shear, and convective instability were found to be the most important parameters in determining whether concentrated convection would undergo upscale growth into an MCS. Based on these results, an index was developed for use in forecasting MCSs. The MCS index assigns a likelihood of MCS development based on three terms: 700-hPa temperature advection, 0–3-km vertical wind shear, and the lifted index. An evaluation of the MCS index revealed that it exhibits features consistent with common MCS characteristics and is reasonably accurate in forecasting MCSs, especially given that convective initiation has occurred, offering the possibility of usefulness in operational forecasting.
Abstract
Mesoscale convective systems (MCSs) have a large influence on the weather over the central United States during the warm season by generating essential rainfall and severe weather. To gain insight into the predictability of these systems, the precursor environments of several hundred MCSs across the United States were reviewed during the warm seasons of 1996–98. Surface analyses were used to identify initiating mechanisms for each system, and North American Regional Reanalysis (NARR) data were used to examine the environment prior to MCS development. Similarly, environments unable to support organized convective systems were also investigated for comparison with MCS precursor environments. Significant differences were found between environments that support MCS development and those that do not support convective organization. MCSs were most commonly initiated by frontal boundaries; however, features that enhance convective initiation are often not sufficient for MCS development, as the environment needs also to be supportive for the development and organization of long-lived convective systems. Low-level warm air advection, low-level vertical wind shear, and convective instability were found to be the most important parameters in determining whether concentrated convection would undergo upscale growth into an MCS. Based on these results, an index was developed for use in forecasting MCSs. The MCS index assigns a likelihood of MCS development based on three terms: 700-hPa temperature advection, 0–3-km vertical wind shear, and the lifted index. An evaluation of the MCS index revealed that it exhibits features consistent with common MCS characteristics and is reasonably accurate in forecasting MCSs, especially given that convective initiation has occurred, offering the possibility of usefulness in operational forecasting.
Abstract
An unseasonal, severe downslope windstorm along the eastern foothills of the Colorado Rocky Mountains is described. The storm, which occurred on 3 July 1993, produced wind guts in Fort Collins, Colorado, over 40 m s−1 and resulted in extensive tree and roof damage. The synoptic pattern preceding the wind event resembled a pattern typical of that for a Front Range late fall or wintertime wind storm, including a strong south–southwest-oriented height gradient at 700 mb and a strong west to east sea level pressure gradient across the Front Range. A particularly interesting facet of the event was that one small geographical area in and near Fort Collins experienced wind gusts nearly 40% stronger than any other location involved in the event.
The mesoscale forecast version of the Regional Atmospheric Modeling System (RAMS) with 16-km grid spacing over Colorado was run for the storm. Consistent severe winds were not predicted by the model in this configuration. Increasing resolution in postanalysis to a 4-km grid spacing along the Front Range resulted in severe downslope winds but of too strong a magnitude. The addition of explicit, bulk microphysics moderated the forecast wind strengths to observed magnitudes. That is, both a grid spacing of ∼4 km and the use of explicit bulk microphysics were required to produce an accurate representation of the downslope winds observed.
Abstract
An unseasonal, severe downslope windstorm along the eastern foothills of the Colorado Rocky Mountains is described. The storm, which occurred on 3 July 1993, produced wind guts in Fort Collins, Colorado, over 40 m s−1 and resulted in extensive tree and roof damage. The synoptic pattern preceding the wind event resembled a pattern typical of that for a Front Range late fall or wintertime wind storm, including a strong south–southwest-oriented height gradient at 700 mb and a strong west to east sea level pressure gradient across the Front Range. A particularly interesting facet of the event was that one small geographical area in and near Fort Collins experienced wind gusts nearly 40% stronger than any other location involved in the event.
The mesoscale forecast version of the Regional Atmospheric Modeling System (RAMS) with 16-km grid spacing over Colorado was run for the storm. Consistent severe winds were not predicted by the model in this configuration. Increasing resolution in postanalysis to a 4-km grid spacing along the Front Range resulted in severe downslope winds but of too strong a magnitude. The addition of explicit, bulk microphysics moderated the forecast wind strengths to observed magnitudes. That is, both a grid spacing of ∼4 km and the use of explicit bulk microphysics were required to produce an accurate representation of the downslope winds observed.
