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  • Author or Editor: Jonathan D. Kahl x
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Jonathan D. Kahl

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Jonathan D. Kahl and Perry J. Samson

Abstract

Routine and supplemental rawinsonde observations collected during the Preliminary Regional Experiment for Storm-Central (PRE-STORM) were analyzed to assess the uncertainty in boundary-layer trajectory calculations due to imprecise interpolation of the horizontal wind field. This study was designed to complement our earlier analysis of rawinsonde data collected during the Cross Appalachian Tracer Experiment (CAPTEX; Kahl and Samson 1986). The present study is representative of widespread convective conditions, while our previous study was representative of fairly persistent, undisturbed flow.

Spatial autocorrelation analysis revealed significant wind field variability on scales less than 100 km. Evaluation of several spatial and temporal interpolation techniques yielded mean absolute errors in estimation of u and v wind components ranging from 3.3–6.5 m −1. Spatial interpolation accuracy improved only slightly when supplemental measurements were included in the interpolation procedure.

Estimates of trajectory errors were obtained using the “trajectory of errors” model of Kahl and Samson (1986). Mean horizontal errors of 493 km were found after 72 h of travel. Contributions of spatial and temporal interpolation to the overall trajectory error were equivalent. Trajectory errors wore 40% greater than those estimated using CAPTEX interpolation statistics.

The presence of predominant mesoscale circulations during PRE-STORM is responsible for the elevated small-scale wind variability as compared to CAPTEX conditions, thus leading to larger interpolation errors and, in turn, larger trajectory errors. Our results suggest that data resolution finer than that considered in this study is necessary to significantly improve trajectory accuracy during meteorological conditions similar to PRE-STORM.

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Jonathan D. Kahl and Perry J. Samson

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Meteorological observations conducted during the Cross Appalachian Tracer Experiment (CAPTEX) were utilized to quantify the uncertainty in boundary layer trajectory calculations due to low-resolution meteorological data [the current National Weather Service (NWS) rawinsonde network). Evaluation of several spatial and temporal interpolation techniques against high-resolution measurements revealed mean absolute errors of 2–4 m s−1 in estimation of horizontal wind components.

A trajectory of errors procedure is introduced that allows the quantification of probable errors in transport calculation due to imprecise interpolation. Our results, based on the observed distributions of spatial and temporal interpolation errors during CAPTEX, indicate dust boundary layer trajectories calculated using the current NWS network with 12 h resolution contain a 50% chance of exceeding horizontal displacement errors of 350 km after 72 h travel time. An increase in spatial resolution is shown to improve the accuracy of trajectory calculations more than an increase in temporal resolution. These results are representative of relatively undisturbed flow in the northeastern United States and southern Canada and do not include the possible effects of nonindependent trajectory errors.

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Jonathan D. Kahl and Perry J. Samson

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The dependence of wind interpolation accuracy on vertical shear was investigated using routine and supplemental rawinsonde data collected during the Cross Appalachian Tracer Experiment. Spatial interpolation error distributions for horizontal wind components were stratified by the “bulk” shear within the mixed layer. Results indicated that interpolation errors were approximately proportional to vertical wind shear.

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Austin R. Harris and Jonathan D. W. Kahl

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Gust factors in Milwaukee, Wisconsin, are investigated using Automated Surface Observing System (ASOS) wind measurements from 2007 to 2014. Wind and gust observations reported in the standard hourly ASOS dataset are shown to contain substantial bias caused by sampling and reporting protocols that restrict the reporting of gusts to arbitrarily defined “gusty” periods occurring during small subsets of each hour. The hourly ASOS gust reports are found to be inadequate for describing the gust characteristics of the site and ill suited for the study of gust factors. A gust-factor climatology was established for Milwaukee using the higher-resolution, 1-min version of the ASOS dataset. The mean gust factor is 1.74. Stratified climatologies demonstrate that Milwaukee gust factors vary substantially with meteorological factors, with wind speed and wind direction exerting the strongest controls. A variety of modified gust-factor models were evaluated in which the peak wind gust is estimated by multiplying a gust factor by the observed, rather than forecast, wind speed. Errors thus obtained are entirely attributable to utility of the gust factor in forecasting peak gusts, having eliminated any error associated with the wind speed forecast. Results show that gust-factor models demonstrate skill in estimating peak gusts and improve with the use of meteorologically stratified gust factors.

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Wessam Z. Daoud, Jonathan D. W. Kahl, and Jugal K. Ghorai

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A large set of 10-day, quasi-two-dimensional atmospheric trajectory model data is used to compute Lagrangian autocorrelation functions for horizontal velocity components and to determine their integral timescale T L. The objectives of the study are to investigate the seasonal, interannual, and altitudinal behavior of T L and to present the Lagrangian autocorrelation functions corresponding to synoptic-scale flow. Results indicate that the integral timescale T L ranges from 15 to 24 h, with values for the meridional velocity component that are 10%–25% less than values for the zonal velocity component. The Lagrangian autocorrelation functions are modeled using Gaussian and second-order autoregressive autocorrelation models. The model fits to the observed autocorrelation functions were found to be of similar form to those determined for a 1-yr set of three-dimensional trajectory data, suggesting that these functions are robust with respect to synoptic-scale, tropospheric flow.

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