
Methodology: The TOMCAT simulation was conducted at a T64L32 resolution, consistent with previous work by Dhomse et al. (2021, 2022), covering the period from 2000 to 2024. These simulations utilized ERA-5 reanalysis data. HCl Profile Processing and Bias Correction Collocated HCl profiles are organized into five distinct latitude bins: NH polar: 90∘N - 50∘N NH mid-lat: 20∘N - 70∘N Tropics: 40∘S - 40∘N SH mid-lat: 70∘S - 20∘S SH polar: 90∘S - 50∘S Initially, differences between TOMCAT and satellite measurements (primarily ACE-FTS data) are calculated for each zonal bin across 51 height levels (ranging from 10,km to 60,km). Separate XGBoost regression models are then trained for these HCl differences at each height level within a given latitude bin. These trained models are subsequently used to estimate HCl bias corrections for all daytime TOMCAT grids (9132 days), specifically sampled at 1:30 PM local time at the equator. This yields grid-specific bias corrections that are applied to the original TOMCAT profiles. Height-resolved HCl profile data are then interpolated onto 28 standard pressure levels (from 300,hPa to 0.1,hPa), using pressure levels directly from the TOMCAT grids. For overlapping latitude bins, values are averaged to ensure smoother fields near boundary regions. Data Files The dataset includes two files containing daily mean zonal mean HCl profiles: zmhcl_TCOM_hlev_T2Dz_2000-2024_V1.1.nc: Contains height level data (10,km to 60,km). zmhcl_TCOM_plev_T2Dz_2000-2024_V1.1.nc: Contains pressure level data (300,hPa to 0.1,hPa). Reference Publication This methodology, incorporating only ACE-FTS data and various minor algorithmic developments, is based on the following publication: Dhomse, S. S. and Chipperfield, M. P.: Using machine learning to construct TOMCAT model and occultation measurement-based stratospheric methane (TCOM-CH4) and nitrous oxide (TCOM-N2O) profile data sets, Earth Syst. Sci. Data, 15, 5105–5120, https://doi.org/10.5194/essd-15-5105-2023, 2023
This work was supported by the NERC SISLAC (NE/R001782/1) and LSO3 (NE/V0011863/1) projects.
stratosphere, hydrogen chloride profiles, machine-learning, satellite data, chemical modeling
stratosphere, hydrogen chloride profiles, machine-learning, satellite data, chemical modeling
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