Radiation Dry Bias of the Vaisala RS92 Humidity Sensor

Vömel, H.; Selkirk, Henry B.; Miloshevich, Larry M.; Valverde-Canossa, J.; Valdés, Juan; Kyrö, E.; Kivi, Rigel; Stolz, Werner; Peng, G. S.; Diaz, J. A.

doi:10.1175/jtech2019.1

Cited by 240 publications

(269 citation statements)

References 12 publications

(15 reference statements)

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“…Both widely used radiosonde types RS80 and RS9x suffer from a well-known dry bias in their humidity measurements, caused by different error sources: chemical contamination and sensor ageing for the RS80 (see Sect. 2.3 and Van Malderen and De Backer, 2010, and references therein) and solar radiation for daytime RS9x observations (Vömel et al, 2007). The RS80 humidity measurements at Uccle were corrected by the method developed by Leiterer et al (2005), which is currently the best available correction scheme for this radiosonde type (Suortti et al, 2008).…”

Section: Radiosondesmentioning

confidence: 99%

A multi-site intercomparison of integrated water vapour observations for climate change analysis

et al. 2014

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Abstract. Water vapour plays a dominant role in the climate change debate. However, observing water vapour over a climatological time period in a consistent and homogeneous manner is challenging. On one hand, networks of groundbased instruments able to retrieve homogeneous integrated water vapour (IWV) data sets are being set up. Typical examples are Global Navigation Satellite System (GNSS) observation networks such as the International GNSS Service (IGS), with continuous GPS (Global Positioning System) observations spanning over the last 15+ years, and the AErosol RObotic NETwork (AERONET), providing long-term observations performed with standardized and well-calibrated sun photometers. On the other hand, satellite-based measurements of IWV already have a time span of over 10 years (e.g. AIRS) or are being merged to create long-term time series (e.g. GOME, SCIAMACHY, and GOME-2).This study performs an intercomparison of IWV measurements from satellite devices (in the visible, GOME/SCIAMACHY/GOME-2, and in the thermal infrared, AIRS), in situ measurements (radiosondes) and ground-based instruments (GPS, sun photometer), to assess their use in water vapour trends analysis. To this end, we selected 28 sites world-wide for which GPS observations can directly be compared with coincident satellite IWV observations, together with sun photometer and/or radiosonde measurements. The mean biases of the different techniques compared to the GPS estimates vary only between −0.3 to 0.5 mm of IWV. Nevertheless these small biases are accompanied by large standard deviations (SD), especially for the satellite instruments. In particular, we analysed the impact of clouds on the IWV agreement. The influence of specific issues for each instrument on the intercomparison is also investigated (e.g. the distance between the satellite ground pixel centre and the co-located ground-based station, the satellite scan angle, daytime/nighttime differences). Furthermore, we checked if the properties of the IWV scatter plots between these different instruments are dependent on the geography and/or altitude of the station. For all considered instruments, the only dependency clearly detected is with latitude: the SD of the IWV observations with respect to the GPS IWV retrievals decreases with increasing latitude and decreasing mean IWV.

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Section: Radiosondesmentioning

confidence: 99%

A multi-site intercomparison of integrated water vapour observations for climate change analysis

et al. 2014

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“…Here, the instrument errors of the different radiosonde types are small. Humidity data were rejected above 300 hPa due to a notable dry bias at low temperatures especially with the RS-90 and RS-80 radiosondes (Vömel et al, 2007).…”

Section: Observationsmentioning

confidence: 99%

High‐resolution simulation over central Europe: assimilation experiments during COPS IOP 9c

Schwitalla

Bauer

Wulfmeyer

et al. 2011

Quart J Royal Meteoro Soc

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The impact of assimilating conventional and Global Positioning System (GPS)ZenithA further comparison with the operational high-resolution models of DWD during this COPS IOP reveals a strong dependence on the initial boundary-layer wind field especially as the near-surface wind field is better represented in the ECMWF analysis than in the COSMO analysis.As this is, to our knowledge, the first study applying a convection-permitting configuration of WRF over Europe, it can be used as a guidance for further studies.

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“…Therefore, there is a possibility that both radiosondes have biases with opposing signs. The Vaisala-RS92 relative humidity sensor is known to have a solar radiation dry bias of up to ~50% in the upper troposphere (Vömel et al 2007;Miloshevich et al 2009). The software that we used was version 3.63 of Vaisala's DigiCORA Sounding System.…”

Section: Discussionmentioning

confidence: 99%

Comparison of Meisei RS2-91 Rawinsondes and Vaisala RS92-SGP Radiosondes at Tateno for the Data Continuity for Climatic Data Analysis

Kobayashi

Noto

Wakino

et al. 2012

Journal of the Meteorological Society of Japan

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Radiation Dry Bias of the Vaisala RS92 Humidity Sensor

Cited by 240 publications

References 12 publications

A multi-site intercomparison of integrated water vapour observations for climate change analysis

A multi-site intercomparison of integrated water vapour observations for climate change analysis

High‐resolution simulation over central Europe: assimilation experiments during COPS IOP 9c

Comparison of Meisei RS2-91 Rawinsondes and Vaisala RS92-SGP Radiosondes at Tateno for the Data Continuity for Climatic Data Analysis

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