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- Author or Editor: Henry Liu x
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Abstract
Wind generated Pressure inside buildings, normally referred to as “internal pressure” in engineering literature, has a profound effect on the atmospheric pressure measured with indoor barometers during severe storms. The magnitude of the internal pressure is proportional to the dynamic pressure (stagnation pressure) which in turn increases with the square of the wind speed. Normally, this pressure is negative, and it has a magnitude in the neighborhood of 50% of the stagnation pressure. Its value changes drastically when an opening such as a door or window is opened or broken in high winds. The internal pressure also fluctuates readily with the fluctuations of the external pressure when a large opening exists. Surface pressure measurements taken in severe storms may contain serious errors if this internal pressure effect is not corrected. The paper summarizes latest research findings on internal pressure reported in the literature, and explores their implications to meteorology—especially to the study of severe storms such as hurricanes and tornadoes. Measures to correct or reduce the error generated by internal pressure are also discussed.
Abstract
Wind generated Pressure inside buildings, normally referred to as “internal pressure” in engineering literature, has a profound effect on the atmospheric pressure measured with indoor barometers during severe storms. The magnitude of the internal pressure is proportional to the dynamic pressure (stagnation pressure) which in turn increases with the square of the wind speed. Normally, this pressure is negative, and it has a magnitude in the neighborhood of 50% of the stagnation pressure. Its value changes drastically when an opening such as a door or window is opened or broken in high winds. The internal pressure also fluctuates readily with the fluctuations of the external pressure when a large opening exists. Surface pressure measurements taken in severe storms may contain serious errors if this internal pressure effect is not corrected. The paper summarizes latest research findings on internal pressure reported in the literature, and explores their implications to meteorology—especially to the study of severe storms such as hurricanes and tornadoes. Measures to correct or reduce the error generated by internal pressure are also discussed.
Abstract
The Portable Automated Mesonet II (PAM II) is a network of automated remote weather stations developed by the National Center for Atmospheric Research (NCAR) for measuring wind speed and direction, atmospheric pressure, temperature, humidity, and precipitation. The atmospheric pressure is measured with a pressure transducer connected to the central opening of a round disk—the pressure port. Wind tunnel tests were conducted to determine wind effects an the atmospheric pressure measured with this port. Three port designs were tested in the wind tunnel and their performances were compared. It was found that the two with symmetric edges performed the best at high wind speeds. The expected pressure errors were evaluated for normal PAM II operation and were generally found to be less than the rms error in the pressure transducers. For special circumstances where these pressure errors cannot be neglected, the wind tunnel data and the procedures discussed here can be used to make appropriate corrections if the horizontal and vertical components of the wind velocity at the height of the pressure port are measured. Results of this study should be of value to those who intend to use PAM II or other systems to make measurements in severe storms such as tornadoes, hurricanes, downbursts, or mountain downslope winds.
Abstract
The Portable Automated Mesonet II (PAM II) is a network of automated remote weather stations developed by the National Center for Atmospheric Research (NCAR) for measuring wind speed and direction, atmospheric pressure, temperature, humidity, and precipitation. The atmospheric pressure is measured with a pressure transducer connected to the central opening of a round disk—the pressure port. Wind tunnel tests were conducted to determine wind effects an the atmospheric pressure measured with this port. Three port designs were tested in the wind tunnel and their performances were compared. It was found that the two with symmetric edges performed the best at high wind speeds. The expected pressure errors were evaluated for normal PAM II operation and were generally found to be less than the rms error in the pressure transducers. For special circumstances where these pressure errors cannot be neglected, the wind tunnel data and the procedures discussed here can be used to make appropriate corrections if the horizontal and vertical components of the wind velocity at the height of the pressure port are measured. Results of this study should be of value to those who intend to use PAM II or other systems to make measurements in severe storms such as tornadoes, hurricanes, downbursts, or mountain downslope winds.
Abstract
Since 2007, meteorologists of the U.S. Army Test and Evaluation Command (ATEC) at Dugway Proving Ground (DPG), Utah, have relied on a mesoscale ensemble prediction system (EPS) known as the Ensemble Four-Dimensional Weather System (E-4DWX). This article describes E-4DWX and the innovative way in which it is calibrated, how it performs, why it was developed, and how meteorologists at DPG use it. E-4DWX has 30 operational members, each configured to produce forecasts of 48 h every 6 h on a 272-processor high performance computer (HPC) at DPG. The ensemble’s members differ from one another in initial-, lateral-, and lower-boundary conditions; in methods of data assimilation; and in physical parameterizations. The predictive core of all members is the Advanced Research core of the Weather Research and Forecasting (WRF) Model. Numerical predictions of the most useful near-surface variables are dynamically calibrated through algorithms that combine logistic regression and quantile regression, generating statistically realistic probabilistic depictions of the atmosphere’s future state at DPG’s observing sites. Army meteorologists view E-4DWX’s output via customized figures posted to a restricted website. Some of these figures summarize collective results—for example, through means, standard deviations, or fractions of the ensemble exceeding thresholds. Other figures show each forecast, individually or grouped—for example, through spaghetti diagrams and time series. This article presents examples of each type of figure.
Abstract
Since 2007, meteorologists of the U.S. Army Test and Evaluation Command (ATEC) at Dugway Proving Ground (DPG), Utah, have relied on a mesoscale ensemble prediction system (EPS) known as the Ensemble Four-Dimensional Weather System (E-4DWX). This article describes E-4DWX and the innovative way in which it is calibrated, how it performs, why it was developed, and how meteorologists at DPG use it. E-4DWX has 30 operational members, each configured to produce forecasts of 48 h every 6 h on a 272-processor high performance computer (HPC) at DPG. The ensemble’s members differ from one another in initial-, lateral-, and lower-boundary conditions; in methods of data assimilation; and in physical parameterizations. The predictive core of all members is the Advanced Research core of the Weather Research and Forecasting (WRF) Model. Numerical predictions of the most useful near-surface variables are dynamically calibrated through algorithms that combine logistic regression and quantile regression, generating statistically realistic probabilistic depictions of the atmosphere’s future state at DPG’s observing sites. Army meteorologists view E-4DWX’s output via customized figures posted to a restricted website. Some of these figures summarize collective results—for example, through means, standard deviations, or fractions of the ensemble exceeding thresholds. Other figures show each forecast, individually or grouped—for example, through spaghetti diagrams and time series. This article presents examples of each type of figure.
