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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 7, issue 12 | Copyright
Atmos. Meas. Tech., 7, 4463-4490, 2014
https://doi.org/10.5194/amt-7-4463-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 18 Dec 2014

Research article | 18 Dec 2014

Reference quality upper-air measurements: GRUAN data processing for the Vaisala RS92 radiosonde

R. J. Dirksen1, M. Sommer1, F. J. Immler1,*, D. F. Hurst2,3, R. Kivi4, and H. Vömel1 R. J. Dirksen et al.
  • 1Deutscher Wetterdienst, Meteorologisches Observatorium Lindenberg, Richard-Aßmann-Observatorium, Am Observatorium 12, 15848, Lindenberg/Tauche, Germany
  • 2Global Monitoring Division, NOAA Earth System Research Laboratory, Boulder, CO, USA
  • 3Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA
  • 4Finnish Meteorological Institute, Sodankylä, Finland
  • *now at: European Commission, Brussels, Belgium

Abstract. The GCOS (Global Climate Observing System) Reference Upper-Air Network (GRUAN) data processing for the Vaisala RS92 radiosonde was developed to meet the criteria for reference measurements. These criteria stipulate the collection of metadata, the use of well-documented correction algorithms, and estimates of the measurement uncertainty. An important and novel aspect of the GRUAN processing is that the uncertainty estimates are vertically resolved. This paper describes the algorithms that are applied in version 2 of the GRUAN processing to correct for systematic errors in radiosonde measurements of pressure, temperature, humidity, and wind, as well as how the uncertainties related to these error sources are derived. Currently, the RS92 is launched on a regular basis at 13 out of 15 GRUAN sites. An additional GRUAN requirement for performing reference measurements with the RS92 is that the manufacturer-prescribed procedure for the radiosonde's preparation, i.e. heated reconditioning of the sensors and recalibration during ground check, is followed. In the GRUAN processing however, the recalibration of the humidity sensors that is applied during ground check is removed. For the dominant error source, solar radiation, laboratory experiments were performed to investigate and model its effect on the RS92's temperature and humidity measurements. GRUAN uncertainty estimates are 0.15 K for night-time temperature measurements and approximately 0.6 K at 25 km during daytime. The other uncertainty estimates are up to 6% relative humidity for humidity, 10–50 m for geopotential height, 0.6 hPa for pressure, 0.4–1 m s−1 for wind speed, and 1° for wind direction. Daytime temperature profiles for GRUAN and Vaisala processing are comparable and consistent within the estimated uncertainty. GRUAN daytime humidity profiles are up to 15% moister than Vaisala processed profiles, of which two-thirds is due to the radiation dry bias correction and one-third is due to an additional calibration correction. Redundant measurements with frost point hygrometers (CFH and NOAA FPH) show that GRUAN-processed RS92 humidity profiles and frost point data agree within 15% in the troposphere. No systematic biases occur, apart from a 5% dry bias for GRUAN data around −40 °C at night.

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