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- Author or Editor: Robert E. Eskridge x
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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.
Abstract
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.
Abstract
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.
Abstract
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.
Abstract
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.
Abstract
Inhomogeneities in U.S. radiosonde data that used the VIZ and Vaisala RS80 cannot be explained by radiation errors, which can be removed by the heat balance models. WMO intercomparision data, modeling results, temperature time series, and 1200 minus 0000 UTC temperature differences are examined to show that there appears to be an error in the U.S. RS80/RSN93 temperature correction software.
Radiosonde soundings taken at U.S. stations that launch Vaisala RS80 radiosondes, which are integrated within the National Weather Service (NWS) Microcomputer Automatic Radio-Theodolite (Micro-ART) system, should not be used in climate studies since there is a large systematic error of unknown origin in the temperature data. This paper is the first of two and is primarily concerned with the midtroposphere. The second paper discusses the large unexplained 0000 and 1200 UTC differences in the stratosphere.
Abstract
Inhomogeneities in U.S. radiosonde data that used the VIZ and Vaisala RS80 cannot be explained by radiation errors, which can be removed by the heat balance models. WMO intercomparision data, modeling results, temperature time series, and 1200 minus 0000 UTC temperature differences are examined to show that there appears to be an error in the U.S. RS80/RSN93 temperature correction software.
Radiosonde soundings taken at U.S. stations that launch Vaisala RS80 radiosondes, which are integrated within the National Weather Service (NWS) Microcomputer Automatic Radio-Theodolite (Micro-ART) system, should not be used in climate studies since there is a large systematic error of unknown origin in the temperature data. This paper is the first of two and is primarily concerned with the midtroposphere. The second paper discusses the large unexplained 0000 and 1200 UTC differences in the stratosphere.
