Articles | Volume 13, issue 12
Atmos. Meas. Tech., 13, 6445–6458, 2020
Atmos. Meas. Tech., 13, 6445–6458, 2020

Research article 01 Dec 2020

Research article | 01 Dec 2020

Interpolation uncertainty of atmospheric temperature profiles

Alessandro Fassò et al.

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Earth Syst. Sci. Data Discuss.,,, 2020
Revised manuscript not accepted
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Cited articles

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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,, 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,, 2014. a
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.