Search Results
You are looking at 1 - 10 of 20 items for
- Author or Editor: Robert E. Eskridge x
- Refine by Access: All Content x
Abstract
No abstract available.
Abstract
No abstract available.
Abstract
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.
Abstract
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.
Abstract
The National Weather Service VIZ radiosonde and the Vaisala RS-80 radiosondes are used worldwide to obtain upper-air measurements of atmospheric temperature and moisture. The temperature measured by each sensor is not equal to the atmospheric temperature due to solar and infrared irradiation of the sensor, heat conduction to the sensor from its attachment points, and radiation emitted by the sensor. Presently, only the RS-80 radiosonde applies corrections to the sensor temperature to compensate for these heating sources, and this correction is only considered to be a function of solar angle and pressure.
Temperature correction models VIZCOR (VIZ sonde) and VAICOR (Vaisala RS-80 sonde) have been developed that derive the atmospheric temperature from the sensor temperature, taking into account all significant environmental processes that influence the beat transfer to the sensor. These models have been validated by comparing their corrected profiles with atmospheric temperature profiles derived from the NASA multithermistor radiosonde. All three radiosondes were flown on the same balloon during the potential reference radiosonde intercomparison. Excellent agreement has been found between all profiles up to an altitude of 30 km. Since the significant error sources in the VIZCOR, VAICOR, and multithermistor techniques are largely independent, agreement between all profiles implies that the corrected sensor profiles are providing an unbiased estimate of the true atmospheric temperature.
Abstract
The National Weather Service VIZ radiosonde and the Vaisala RS-80 radiosondes are used worldwide to obtain upper-air measurements of atmospheric temperature and moisture. The temperature measured by each sensor is not equal to the atmospheric temperature due to solar and infrared irradiation of the sensor, heat conduction to the sensor from its attachment points, and radiation emitted by the sensor. Presently, only the RS-80 radiosonde applies corrections to the sensor temperature to compensate for these heating sources, and this correction is only considered to be a function of solar angle and pressure.
Temperature correction models VIZCOR (VIZ sonde) and VAICOR (Vaisala RS-80 sonde) have been developed that derive the atmospheric temperature from the sensor temperature, taking into account all significant environmental processes that influence the beat transfer to the sensor. These models have been validated by comparing their corrected profiles with atmospheric temperature profiles derived from the NASA multithermistor radiosonde. All three radiosondes were flown on the same balloon during the potential reference radiosonde intercomparison. Excellent agreement has been found between all profiles up to an altitude of 30 km. Since the significant error sources in the VIZCOR, VAICOR, and multithermistor techniques are largely independent, agreement between all profiles implies that the corrected sensor profiles are providing an unbiased estimate of the true atmospheric temperature.
Abstract
A method developed in the former Soviet Union for predicting cloud amounts is supplemented with a new method of determining the base and tops of clouds. Criteria for predicting a cloud layer are 0 ≤ T″(z) and R″(z) ≤ 0, where T″ is the second derivative of the vertical profile of temperature and R″ is the second derivative of the relative humidity. This test was found from an analyses of United States radiosonde data.
Cloud amount (sky cover) is predicted from a relationship between cloud amount and dewpoint depression within the predicted cloud layer and the temperature at that level. This relationship is based on data from the former Soviet Union and data from the Indian 0cean and divides cloud amount into four categories: 0%–20%, 20%–60%, 60%–80%, and 80%–100% coverage.
The new composite method is evaluated using data from several United States radiosonde stations within different climates. Evaluation data was selected to include only situations in which the observer (providing the “truth”) could me only one cloud layer. Consequently, the evaluation is biased toward stratified cloud conditions. The method will provide cloud information that can be used in models of radiosonde sensors to adjusted temperature data.
Abstract
A method developed in the former Soviet Union for predicting cloud amounts is supplemented with a new method of determining the base and tops of clouds. Criteria for predicting a cloud layer are 0 ≤ T″(z) and R″(z) ≤ 0, where T″ is the second derivative of the vertical profile of temperature and R″ is the second derivative of the relative humidity. This test was found from an analyses of United States radiosonde data.
Cloud amount (sky cover) is predicted from a relationship between cloud amount and dewpoint depression within the predicted cloud layer and the temperature at that level. This relationship is based on data from the former Soviet Union and data from the Indian 0cean and divides cloud amount into four categories: 0%–20%, 20%–60%, 60%–80%, and 80%–100% coverage.
The new composite method is evaluated using data from several United States radiosonde stations within different climates. Evaluation data was selected to include only situations in which the observer (providing the “truth”) could me only one cloud layer. Consequently, the evaluation is biased toward stratified cloud conditions. The method will provide cloud information that can be used in models of radiosonde sensors to adjusted temperature data.
Abstract
No abstract available
Abstract
No abstract available
Abstract
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.
Abstract
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.
Abstract
Correct radiosonde station elevation (balloon release height) is important in quality control of radiosonde soundings. Incorrect heights introduce errors in calculated temperature trends and numerical forecasts. Radiosonde metadata frequently contain erroneous information regarding station elevations. Soundings are produced at the station using the correct station elevation and the hydrostatic equation to determine the height of each pressure level in the sounding. It is easy to do a reverse calculation using the soundings to calculate the station elevation (release point). From a time series of calculated station elevations, the change dates and station elevations can be determined for individual stations. A method was developed to calculate station elevation and change dates automatically from time series of calculated station elevations.
Abstract
Correct radiosonde station elevation (balloon release height) is important in quality control of radiosonde soundings. Incorrect heights introduce errors in calculated temperature trends and numerical forecasts. Radiosonde metadata frequently contain erroneous information regarding station elevations. Soundings are produced at the station using the correct station elevation and the hydrostatic equation to determine the height of each pressure level in the sounding. It is easy to do a reverse calculation using the soundings to calculate the station elevation (release point). From a time series of calculated station elevations, the change dates and station elevations can be determined for individual stations. A method was developed to calculate station elevation and change dates automatically from time series of calculated station elevations.
Abstract
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.
Abstract
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.
Abstract
No abstract available.
Abstract
No abstract available.
Abstract
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.
Abstract
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.
