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Dataset . 2023
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Dataset . 2023
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Dataset . 2023
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ZENODO
Dataset . 2025
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TCOM-O3: TOMCAT CTM and Occultation Measurements based daily zonal stratospheric ozone profile dataset [1991-2021] constructed using machine-learning

Authors: Dhomse Sandip S.;

TCOM-O3: TOMCAT CTM and Occultation Measurements based daily zonal stratospheric ozone profile dataset [1991-2021] constructed using machine-learning

Abstract

Methodology: TOMCAT simulation is performed at T64L32 resolution for the 1991-2021 time period. Collocated ozone profiles are divided in five latitude bins: SH polar (90S-50S), SH mid-lat (70S-20S), tropics (40S-40N), NH mid-lat (20N-70N) and NH polar (50N-90N). Initially, model observational data differences are calculated for each zonal bins for 46 height levels (15km to 60km). Then separate XGBoost regression models are trained for the ozone differences between TOMCAT and measurements at each level for a given latitude bin. Basically, XGBoost assumes all the observation-model bias observations can be linked to TOMCAT setup, hence TOMCAT tracers are used as explanatory variables. TOMCAT output sampled at 1.30 am and 1.30 pm local time at the equator and XGBoost is used to estimate bias corrections for all the model grids that are added to the original TOMCAT ozone profiles. Height resolved data are then interpolated on 28-pressure levels (300 - 0.1hPa). For overlapping latitude bins, we use averages and then calculate daily zonal mean values. For more details see attached presentation. Dataset also includes two files containing daily mean zonal mean ozone profiles on height (15-60 km) and pressure (300-0.1 hPa) levels: A pdf file is included to provide bit more details about the methodology. zmo3_TCOM_hlev_T2Dz_1991_2021.nc – height level data (15 to 60 km) zmo3_TCOM_plev_T2Dz_1991_2021.nc – pressure level data (300 to 0.1 hPa) Daily 3D profiles on height and pressure levels would be made available on request.

This work was supported by the NERC SISLAC (NE/R001782/1) and LSO3 (NE/V0011863/1) projects.

Related Organizations
Keywords

stratosphere, ozone, machine-learning, satellite data, chemical modeling, solar occultation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average