4.1 Article

Differences between in-situ ozonesonde observations and satellite retrieved ozone vertical profiles across Antarctica

Journal

POLAR SCIENCE
Volume 30, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.polar.2021.100688

Keywords

Ozone depletion; Antarctic ozone; MLS; Ozonesonde

Funding

  1. Ministry of Earth Sciences (MOES), the Government of India

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In-situ ozonesonde observations from nine Antarctic stations were used to validate satellite-based Microwave Limb Sounder (MLS) instrument data from 2004 to 2019. The study found good agreement between MLS and in-situ observations over longer averaging periods, but discrepancies at individual profiles, especially seasonally, were higher and could impact estimations of ozone recovery over Antarctica.
In situ ozonesonde observations across nine Antarctic stations were used to validate the vertical profiles retrieved by the satellite-based Microwave Limb Sounder (MLS) instrument from 2004 to 2019. Intra-annual variations in the ozone concentration, along with the shape of the vertical profiles are well reproduced by the MLS with differences in the range of +/- 20%, although seasonally the differences were as high as 60%. The largest differences were also observed during the spring (September-October-November), when largescale ozone depletion takes place over Antarctica, with MLS overestimating concentrations at almost all the stations, except the northernmost stations of Marambio and Dumont d'Urville. This has implications for the estimations of ozone recovery over Antarctica based on MLS. The under-estimation or over-estimation in the MLS data caused differences up to +/- 1 K day(-1) in the estimated heating rate. For the whole dataset, a good correlation (R-2 > 0.9, p < 0.001) was seen at all the stations except at Maitri, where the correlation coefficient was lower but still significant (R-2 = 0.77, p < 0.001). These results show that although the MLS data match the in-situ observations over longer averaging periods, for individual profiles the discrepancies are much higher and need to be considered when computing the ozone impacts using MLS data.

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