Articles | Volume 13, issue 12
https://doi.org/10.5194/amt-13-6445-2020
https://doi.org/10.5194/amt-13-6445-2020
Research article
 | 
01 Dec 2020
Research article |  | 01 Dec 2020

Interpolation uncertainty of atmospheric temperature profiles

Alessandro Fassò, Michael Sommer, and Christoph von Rohden

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Cited articles

Alegria, A., Caro, S., Bevilacqua, M., Porcu, E., and Clarke, J.: Estimating covariance functions of multivariate skew-Gaussian random fields on the sphere, Spat. Stat.-Neth., 22, 388–402, 2017. a
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
Ceccherini, S., Carli, B., Tirelli, C., Zoppetti, N., Del Bianco, S., Cortesi, U., Kujanpää, J., and Dragani, R.: Importance of interpolation and coincidence errors in data fusion, Atmos. Meas. Tech., 11, 1009–1017, https://doi.org/10.5194/amt-11-1009-2018, 2018. a
Cressie, N. and Wikle, C.: Statistics for Spatio-Temporal Data, Wiley, New York, USA, 2011. a, b
Dirksen, R. J., Sommer, M., Immler, F. J., Hurst, D. F., Kivi, R., and Vömel, H.: Reference quality upper-air measurements: GRUAN data processing for the Vaisala RS92 radiosonde, Atmos. Meas. Tech., 7, 4463–4490, https://doi.org/10.5194/amt-7-4463-2014, 2014. a
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Short summary
Modern radiosonde balloons fly from ground level up to the lower stratosphere and take temperature measurements. What is the uncertainty of interpolated values in the resulting atmospheric temperature profiles? To answer this question, we introduce a general statistical–mathematical model for the computation of interpolation uncertainty. Analysing more than 51 million measurements, we provide some understanding of the consequences of filling missing data with interpolated ones.