Comparison of GRUAN data products for Meisei iMS-100 and Vaisala RS92 radiosondes at Tateno, Japan
-
Published:2022-10-19
Issue:20
Volume:15
Page:5917-5948
-
ISSN:1867-8548
-
Container-title:Atmospheric Measurement Techniques
-
language:en
-
Short-container-title:Atmos. Meas. Tech.
Author:
Hoshino ShunsukeORCID, Sugidachi Takuji, Shimizu Kensaku, Kobayashi Eriko, Fujiwara MasatomoORCID, Iwabuchi Masami
Abstract
Abstract. A total of 99 dual soundings with Meisei iMS-100 radiosonde and Vaisala RS92 radiosondes were carried out at the Aerological Observatory of the Japan Meteorological Agency, known as Tateno (36.06∘ N, 140.13∘ E, 25.2 m; the World Meteorological Organization, WMO, station number 47646), from September 2017 to January 2020. Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) data products (GDPs) from both sets of radiosonde data for 59 flights were subsequently created using a documented processing programme 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 cooler than RS92-GDP in the stratosphere, with significant differences in the upper troposphere and lower stratosphere 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 % RH–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 −0.04 to +0.14 m s−1, the wind direction difference is ≤6.4∘, and the root mean square vector difference (RMSVD) for wind is ≤1.04 m s−1.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference38 articles.
1. Bodeker, G. E., Bojinski, S., Cimini, D., Dirksen, R. J., Haeffelin, M.,
Hannigan, J. W., Hurst, D. F., Leblanc, T., Madonna, F., Maturilli, M.,
Mikalsen, A. C., Philipona, R., Reale, T., Seidel, D. J., Tan, D. G. H.,
Thorne, P. W., Vömel, H., and Wang, J.: Reference Upper-Air Observations
for Climate: From Concept to Reality, B. Am. Meteorol. Soc., 97, 123–135,
https://doi.org/10.1175/bams-d-14-00072.1, 2016. a 2. Carreño, C. R., Suárez, A., Torrecilla, J. L., Berrocal, M. C., Manchón, P. M., Manso, P. P., Bernabé, A. H., Fernández, D. G., and Hong, Y.: GAA-UAM/scikit-fda: Version 0.4 (0.4), Zenodo [code], https://doi.org/10.5281/zenodo.3957915, 2020. a, b 3. CGMS: Consolidated report of CGMS activities (10th edition, V10), The Coordination Group for Meteorological Satellites (CGMS), Tech.
rep., http://www.cgms-info.org/documents/consolidated-report-of-cgms-activities-%282003%29.pdf (last access: 3 December 2020),
2003. a 4. CIMO Task Team on Upper-air Intercomparison: Project Plan for the WMO
Upper-Air Instrument Intercomparison, https://community.wmo.int/activity-areas/imop/intercomparisons, (last access: June 2021) 2020. a 5. Colombo, P. and Fassò, A.: Quantifying the interpolation uncertainty of
radiosonde humidity profiles, Meas. Sci. Technol., 33, 074001,
https://doi.org/10.1088/1361-6501/ac5bff, 2022. a
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|