Calibration of <scp>RS41</scp> humidity sensors by using an upper‐air simulator

Lee, Sangwook; Kim, Sunghun; Choi, Byung Il; Woo, Sang-Bong; Lee, Sung-Jun; Kwon, Suyong; Kim, Yong-Gyoo

doi:10.1002/met.2010

Cited by 4 publications

(2 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Polymeric thin-film humidity sensors are known to exhibit systematic errors at low temperatures when a calibration curve obtained solely at room temperature is used for lower temperature measurements [31,32]. This discrepancy arises because the adsorption capacity of polymer films for water vapour increases as temperature decreases, while the absolute humidity decreases at lower temperatures.…”

Section: Sensor Calibration Atmentioning

confidence: 99%

Relative humidity measurements of a thin-film humidity sensor in condensing conditions in the temperature range from −40 °C to 5 °C

Lee,

Choi

et al. 2024

Meas. Sci. Technol.

Self Cite

View full text Add to dashboard Cite

In condensing conditions, metastable states such as supersaturation of water vapour and supercooling of liquid water are commonly observed in the free atmosphere. This study investigates the response of a polymeric thin-film humidity sensor under condensing conditions at various temperatures (-40 °C, -20 °C, -5 °C, and 5 °C) and different relative humidity (RH) levels. To ensure precise control of RH, a saturator-based humidity generator operating in a two-temperature mode is utilized. The condensing conditions are achieved in two ways: by increasing water vapour pressure (WVP) at a fixed temperature and by decreasing the temperature while maintaining a constant WVP. In general, when measuring RH under condensing conditions, the sensor indicates a temporary supersaturation state with an RH peak exceeding 100% before the onset of condensation. Subsequently, the RH value exhibits a delayed decrease when exposed to a non-condensing RH level. The experiments with a constant WVP demonstrate a lower likelihood of ice condensation compared to those with a constant temperature. This study demonstrates the measurement capability and behaviour of thin-film humidity sensors above 100% RH in the supersaturation states that are commonly observed in the free atmosphere at meteorologically-relevant temperatures.

show abstract

Section: Sensor Calibration Atmentioning

confidence: 99%

Relative humidity measurements of a thin-film humidity sensor in condensing conditions in the temperature range from −40 °C to 5 °C

Lee,

Choi

et al. 2024

Meas. Sci. Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Vaisala RS41 is one of the most used radiosondes for measuring RH profiles. Although it is operational since 2014 (Dirksen et al [9]), calibration of its humidity sensor is still being improved (Lee et al [19]), and GRUAN only recently released the data processing (GDP) of RS41, which extends the GDP of the previous Vaisala RS92 radiosonde (Dirksen et al [10]). For various reasons, data gaps may appear along the profiles of virtually all radiosonde types, including Vaisala RS41.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the interpolation uncertainty of radiosonde humidity profiles

Colombo¹,

Fassò²

2022

Meas. Sci. Technol.

View full text Add to dashboard Cite

The Global climate observing system Reference Upper Air Network (GRUAN) provides reference measurements of the essential climate variables and their measurement uncertainty. An important aspect of the measurement uncertainty is the interpolation uncertainty. This problem arises, for example, when GRUAN processes atmospheric proﬁles collected by Vaisala RS41 radiosondes. For various reasons, the radiosonde sensor may fail to collect some values along the vertical proﬁle in the atmosphere. As a consequence, estimation techniques to ﬁll the data gaps and to provide an evaluation of the related interpolation uncertainty are welcome. This paper aims to understand and quantify the interpolation uncertainty of the relative humidity. In particular, we consider linear and Gaussian process interpolation either unidimensional or multidimensional. We provide results in terms of interpolation distance in seconds, which measures the distance of an interpolated data from the interpolating data. We also consider measurement altitude and launch site. Although the Gaussian interpolation results to be generally better than linear interpolation, the diﬀerence in uncertainty is relatively small. The average column uncertainty diﬀerence is in the order of 0.2% and for large data gaps around 0.4%. The interpolation uncertainty is larger in the lower atmosphere. For example at 2-4 km altitude, the uncertainty is around 2% at 10 s distance, around 5% at 40 s and 10% at 90 s. In the upper atmosphere, the uncertainty (and the relative humidity) decrease. For example, at 14-16 km altitude, it is smaller than 2% at all interpolation distances. The present paper is a signiﬁcant expansion of a relevant abstract presented at the Mathematical and Statistical Methods for Metrology 2021 Virtual Workshop, 31 May – 1 June 2021.

show abstract

A review of dew point sensors: Recent advances and future development

Nie,

Liu

2024

Sensors and Actuators B: Chemical

View full text Add to dashboard Cite

Calibration of RS41 humidity sensors by using an upper‐air simulator

Cited by 4 publications

References 18 publications

Relative humidity measurements of a thin-film humidity sensor in condensing conditions in the temperature range from −40 °C to 5 °C

Relative humidity measurements of a thin-film humidity sensor in condensing conditions in the temperature range from −40 °C to 5 °C

Quantifying the interpolation uncertainty of radiosonde humidity profiles

A review of dew point sensors: Recent advances and future development

Contact Info

Product

Resources

About