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Robert E. Eskridge

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Robert E. Eskridge and Phanindramohan Das

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The Physical and dynamical effects of simulated precipitation in a rotating wind field are examined by numerical experiments. The physical-dynamical model consists of the three equations of motion, a thermodynamic equation, a conservation equation for precipitation, a diagnostic pressure equation, and appropriate boundary conditions, that are solved numerically by use of central space and time differences in a 1.84 km by 1.82 km grid. While no moisture and latent-heat exchanges are included in this model, the effect of rain and hail is simulated through differing terminal velocities.

The results of two experiments show that vorticity is concentrated by the precipitation-induced, accelerating downdraft which, descending dry adiabatically, becomes warmer than the air outside of the downdraft because the lapse rate of potential temperature in the environmental air is assumed close to moist adiabatic. Near the surface, the air in the downdraft attains sufficient positive buoyancy to overcome the negative buoyancy of the precipitation and begins to be accelerated upward. In fact, two updrafts form near the surface: one on the axis of symmetry and the other approximately 250 m from the axis. The accelerating updraft is accompanied by horizontal inflow near the surface that acts to concentrate vorticity in the lower part of the region near the axis.

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Panmao Zhai and Robert E. Eskridge

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Twice daily radiosonde data from selected stations in the United States (period 1948 to 1990) and China (period 1958 to 1990) were sorted into time series. These stations have one sounding taken in darkness and the other in sunlight. The analysis shows that the 0000 and 1200 UTC time series are highly correlated. Therefore, the Easterling and Peterson technique was tested on the 0000 and 1200 time series to detect inhomogeneities and to estimate the size of the biases. Discontinuities were detected using the difference series created from the 0000 and 1200 UTC time series. To establish that the detected bias was significant, a t test was performed to confirm that the change occurs in the daytime series but not in the nighttime series.

Both U.S. and Chinese radiosonde temperature and humidity data include inhomogeneities caused by changes in radiosonde sensors and observation times. The U.S. humidity data have inhomogeneities that were caused by instrument changes and the censoring of data. The practice of reporting relative humidity as 19% when it is lower than 20% or the temperature is below −40°C is called censoring. This combination of procedural and instrument changes makes the detection of biases and adjustment of the data very difficult. In the Chinese temperatures, them are inhomogeneities related to a change in the radiation correction procedure.

Test results demonstrate that a modified Easterling and Peterson method is suitable for use in detecting and adjusting time series radiosonde data.

Accurate stations histories are very desirable. Stations histories can confirm that detected inhomogeneities are related to instrument or procedural changes. Adjustments can then he made to the data with some confidence.

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Panmao Zhai and Robert E. Eskridge

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Chinese radiosonde data from 1970 to 1990 are relatively homogeneous in time and are used to examine the climatology, trends, and variability of China’s atmospheric water vapor content. The climatological distribution of precipitable water (PW) is primarily dependent on surface temperature. Influenced by the east Asia monsoon, China’s precipitable water exhibits very large seasonal variations. Station elevation is also a dominant factor affecting water vapor distribution in China.

An increase (decrease) in precipitable water over China is associated with an increase (decrease) of precipitation in most regions. Increases in the percentage of PW relative to climatology are greater in winter and spring than in summer and autumn.

Interannual variation and trends in precipitable water and surface temperature are closely correlated in China, confirming a positive “greenhouse” feedback. Interannual variations between precipitable water and precipitation are also significantly correlated.

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Robert E. Eskridge and P. Das

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Robert E. Eskridge and S. Trivikrama Rao

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The primary objectives of this investigation are to determine the temporal and spacial resolution needed to adequately measure vehicle wake turbulence and the characteristics of turbulence near roadways using the knowledge gained in the General Motors (GM) Sulfate Dispersion Experiment, the Long Island (LI) Expressway Diffusion Experiments and wind tunnel experiments.

Observed wind velocity fluctuations at a fixed point near a roadway are due to three distinct causes: wake turbulence, ambient turbulence and the time variation in the wind velocity as a vehicle's wake passes the observation point, hereafter referred to as wake-passing effect. The wake-passing effect can be separated in the data from the ambient and vehicle wake turbulence because of the special spacing and timing of vehicles used in the GM experiment. The measured wake-passing effect is then compared with vehicle wake model predictions. The wake-passing effect, which is shown to constitute a significant portion of the measurable velocity variance near the roadway, does not diffuse pollutants.

In the Long Island Expressway experiment it was shown that most of the velocity variance associated with the vehicle traffic occurred at frequencies greater than 0.5 Hz. It is shown that the GM velocity data, which were recorded once per second, underestimated the velocity variance in short wavelengths and the magnitude of the wind velocity changes due to the vehicle wake.

Recommendations are made, based on wind tunnel and modeling results, as to the time resolution and vertical spacing that are necessary to resolve vehicle wake turbulence and the role of pseudoturbulence in modeling pollutant diffusion near roadways is discussed.

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Robert E. Eskridge and J. C. R. Hunt

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A theory for the velocity deficit in the wake of a moving vehicle in still air is derived from a perturbation analysis of the equations of motion. By suitable assumptions, expressions are found for the turbulent energy fluctuations in the wake. This theory is then applied to predict the velocity deficit and turbulent energy fluctuations on a difference net in the x-z plane across the roadway for the case of the wind speed being much less than the vehicle speed (i.e., the GM experiment). The predictions are then compared to data from the General Motors Sulfate Dispersion Experiment. Comparison of observations to predictions show that the theory predicts the velocity deficit and turbulent fluctuations accurately.

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Robert E. Eskridge and S. Trivikrama Rao

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Oleg A. Alduchov and Robert E. Eskridge

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Algorithms, based on Magnus's form equations, are described that minimize the difference between several relationships between temperature and water vapor pressure at saturation that are commonly used in archiving data. The work was initiated in connection with the development of a unified upper-air dataset that will use measurements gathered from the late 1930s to the present and archived in several data centers. The conversion of field measurements to archived humidity values within the databases that are being used have not been consistent and in some cases are unknown. A goal of this work was to develop a uniform and accurate method to convert these data to various humidity variables without regard to the equations used in archiving the original data. Archived temperature values are recorded to 0.1°C. This precision creates a temperature dependent range in uncertainty in saturation vapor pressure. A procedure was developed to take this into account when the error minimizing equations were derived.

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James K. Luers and Robert E. Eskridge

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Ten of the most common radiosondes used throughout the world since 1960 have been evaluated concerning potential use of their temperature data for climate studies. The VIZ; Space Data Corp.; Chinese GZZ; Japanese RS2-80; Russian RKZ, MARS, and A-22; and Vaisala RS80, RS 12/15, and RS18/21 radiosondes were evaluated by modeling the temperature of the sensing element relative to the temperature of the air in which it is immersed. The difference, designated as the temperature error, was calculated under various environmental conditions. Validation and sensitivity analysis studies were performed on each radiosonde model as a means of estimating the environmental parameters that influence the temperature error and the resulting accuracy of the day and nighttime temperature profiles. Environmental parameters to which some sondes were sensitive include cloud cover, surface temperature, solar angle, ambient temperature profile, blackbody temperature, and the ventilation velocity. The ventilation velocity was found to depend strongly on the position of the sensor in the balloon wake. It is believed that the results of these analyses provide the best guidelines available to anyone wishing to perform climate studies using radiosonde data.

The research work presented in this paper indicates that climate trends can currently be estimated with a subset of the worldwide upper-air data. Trends can be calculated for monthly averaged, nighttime soundings with some confidence for the Vaisala RS80 (models not using the RSN80 and RSN86 corrections), Vaisala RS 12/15, Vaisala RS 18/21, Chinese GZZ (below 25 km), Russian RKZ, Russian MARS, and Russian A-22 (below 20 km) radiosonde models. The analysis presented in this paper shows that all of the above radiosondes have small errors in individual radiosonde soundings at night (< ±1°C) and the errors of the monthly averaged data are estimated to be less than ±0.5°C, except for the A-22 (±0.8°C). In addition, temperature data from the Japanese RS-2-80, the Russian A-22 above 20 km, Vaisala RS80 (RSN80 and RSN86 corrections applied), and VIZ can be made suitable for climate analysis if the appropriate temperature correction models are used to correct the data.

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