Mesoscale dryline features and their dependence on network density



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Texas Tech University


The dependence of dryline analyses on the observational mesonetwork density is examined. Surface data obtained by the National Severe Storms Laboratory (NSSL) mesonetwork during dryline events are used to derive representative physical and kinematic parameters. Objective analyses of these parameters determine the mesoscale features for each of four dryline events. For two cases, the sensitivity of dew point temperature, equivalent potential temperature, and moisture divergence patterns to network density is examined. Those features sensitive to station density are identified by comparing the analyses based on the entire data network and analyses employing 60 percent and 75 percent of the observation stations. Sparser networks are comprised of uniformly spaced stations over the original network area.

Results of this investigation show that (for the two cases tested) the NSSL network densities were more than adequate in capturing the essential dryline features. In terms of the physical parameters, these drylines could have been faithfully resolved with a network sampling area of 344 km^ per station (instead of the densest network's sampling area of 100 km^ per station). However, analyses of a kinematic parameter suffer when network sampling areas are less compact than approximately 200 km^ per station.



Fronts (Meteorology), National Severe Storms Laboratory, Meteorological stations, Meteorology -- Observations