Accuracy assessment and correction of Vaisala RS92 radiosonde water vapor measurements

• Published in: Journal of Geophysical Research: Atmospheres 2009-06, Vol.114 (D11), p.n/a
• Main Authors: Miloshevich, Larry M., Vömel, Holger, Whiteman, David N., Leblanc, Thierry
• Format: Article
• Language: English
• Subjects: Earth sciences; Earth, ocean, space; Exact sciences and technology; humidity; radiosonde; RS92
• ISSN: 0148-0227; 2156-2202
• DOI: 10.1029/2008JD011565

Relative humidity (RH) measurements from Vaisala RS92 radiosondes are widely used in research and operational applications, but their accuracy is not well characterized as a function of height, RH, and time of day (or solar altitude angle). This study compares RS92 RH measurements to simultaneous water vapor measurements from three reference instruments of known accuracy. Cryogenic frost point hygrometer measurements are used to characterize the RS92 accuracy above the 700‐mbar level, microwave radiometer measurements characterize the RS92 accuracy averaged over essentially the lower troposphere, and the RS92 accuracy at the surface is characterized by a system of 6 RH probes with National Institute of Standards and Technology–traceable calibrations. The three RS92 accuracy assessments are combined to yield a detailed estimate of RS92 accuracy for all RH conditions from the surface to the lowermost stratosphere. An empirical correction is derived to remove the mean bias error, yielding corrected RS92 measurements whose bias uncertainty is independent of height or RH and is estimated to be ±4% of the measured RH value for nighttime soundings and ±5% for daytime soundings, plus an RH offset uncertainty of ±0.5% RH that is significant for dry conditions. The accuracy of an individual RS92 sounding is further characterized by the 1‐σ “random production variability,” estimated to be ±1.5% of the measured RH value. The daytime bias correction must be used with caution, as it is only accurate for clear‐sky or near‐clear conditions owing to the complicated effect of clouds on the solar radiation error.