Laboratory characterisation of the radiation temperature error of radiosondes and its application to the GRUAN data processing for the Vaisala RS41

Rohden, Christoph von; Sommer, M.; Naebert, T.; Motuz, Vasyl; Dirksen, Ruud

doi:10.5194/amt-2021-187

Cited by 6 publications

(5 citation statements)

References 25 publications

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“…The GDPs for Vaisala RS41 radiosonde (Rohden et al, 2021) and for Meteomodem M10 radiosonde (Dupont et al, 2020) and an upgraded of GDP for RS92 are currently under development. Also, the WMO 2022 Upper-Air Instrument Intercomparison Campaign (CIMO Task Team on Upper-air Intercomparison, 2020) is being planned in 2022.…”

Section: Methods For Verification Of Consistency With Uncertaintiesmentioning

confidence: 99%

“…Since February 2020, regular dual soundings of iMS-100 and Vaisala RS41 (the successor to RS92), have been ongoing. RS41-GDP is under development (Rohden et al, 2021) and the comparison results will be published when sufficient IMS-100-GDP and RS41-GDP data available. In addition, IMS-100-GDP, RS41-GDP and M10-GDP (Dupont et al, 2020) are also candidates of the reference data in the WMO 2022 Upper-Air Instrument Intercomparison Campaign (CIMO Task Team on Upper-air Intercomparison, 2020) which will be conducted in 2022.…”

Section: Windmentioning

confidence: 99%

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Comparison of GRUAN Data Products for Meisei iMS-100 and Vaisala RS92 Radiosondes at Tateno, Japan

Hoshino

Sugidachi²,

Shimizu³

et al. 2022

Preprint

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Abstract. A total of 99 dual soundings with Meisei iMS-100 radiosonde and Vaisala RS92 radiosondes were carried out at Aerological Observatory of the Japan Meteorological Agency, known as Tateno (36.06° N, 140.13° E, 25.2 m; WMO station number 47646), from September 2017 to January 2020. Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) data products (GDP) from both sets of radiosonde data for 57 flights were subsequently created using a documented processing program along with the provision of optimal estimates for measurement uncertainty. Differences in radiosonde performance were then quantified using these GDPs. For daytime observations, the iMS-100 temperature is around 0.5 K lower than RS92-GDP in the stratosphere with significant differences in the upper troposphere and lower stratosphere with RS92-GDP in consideration of combined uncertainties. For nighttime observations, the difference is around −0.1 K and data are mostly in agreement. For relative humidity (RH), iMS-100 is around 1–2 %RH higher in the troposphere and 1 %RH smaller in the stratosphere than RS92, but both GDPs are in agreement for most of the profile. The mean pressure difference is ≤ 0.1 hPa, the wind speed difference is from 0.15 m s−1 to 0.01 m s−1, the wind direction difference ≤ 5°, and the root mean square of vector difference (RMSVD) for wind is ≤ 0.72 m s−1.

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Section: Methods For Verification Of Consistency With Uncertaintiesmentioning

confidence: 99%

Section: Windmentioning

confidence: 99%

Comparison of GRUAN Data Products for Meisei iMS-100 and Vaisala RS92 Radiosondes at Tateno, Japan

Hoshino

Sugidachi²,

Shimizu³

et al. 2022

Preprint

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“…The Global Climate Observing System Reference Upperair Network (GRUAN) (Von Rohden et al [28]) has a special role in this frame. Indeed, it provides reference measurement of temperature, wind, and water vapour throughout the atmospheric column at selected sites around the world.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the interpolation uncertainty of radiosonde humidity profiles

Colombo¹,

Fassò²

2022

Meas. Sci. Technol.

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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.

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“…In the stratosphere, solar radiation causes significant temperature errors during the day. The constantly changing position of the payload due to pendulum motion and rig rotation has been shown to produce quasi-periodic structures in balloon data, particularly in the temperature profile (Philipona et al 2013;von Rohden et al 2016). A HAVOC payload could reduce quasi-periodic errors in temperature data by reducing the rig rotation.…”

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confidence: 99%

A Platform for Active Stabilization of High-Altitude Balloon Payloads

Stark,

McKinney,

Booker

et al. 2023

Bulletin of the American Meteorological Society

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Weather balloon payloads are commonly used by atmospheric researchers and enthusiasts to gain insight about the upper atmosphere. Balloon payloads are often unstable during flight due to high wind speeds that are experienced in both the troposphere and lower stratosphere. High Altitude Visual Orientation Control (HAVOC) is a platform of cold gas thrusters designed to control the azimuth of high-altitude balloon payloads to counteract high wind conditions. HAVOC’s active control scheme uses valves that direct the flow of pressurized gas into two sets of nozzles that can generate torque in either a clockwise or counterclockwise direction. This counteracts the rotation induced by wind and other forces encountered during a high-altitude balloon flight. The HAVOC design is discussed including its methods of measuring and controlling balloon payload rotation. Data from preliminary flights is presented, demonstrating the system’s ability to reduce payload rotation to a user defined ±40 deg s-1 for a duration of 1 hour and 49 minutes, and to maintain a fixed payload azimuth within ±30 deg for 1 hour. In addition, we present possible uses for the HAVOC system tailored to the type of user, including atmospheric researchers, videographers, and students.

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Laboratory characterisation of the radiation temperature error of radiosondes and its application to the GRUAN data processing for the Vaisala RS41

Cited by 6 publications

References 25 publications

Comparison of GRUAN Data Products for Meisei iMS-100 and Vaisala RS92 Radiosondes at Tateno, Japan

Comparison of GRUAN Data Products for Meisei iMS-100 and Vaisala RS92 Radiosondes at Tateno, Japan

Quantifying the interpolation uncertainty of radiosonde humidity profiles

A Platform for Active Stabilization of High-Altitude Balloon Payloads

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