TCOM-CH4: TOMCAT CTM and Occultation Measurements based daily zonal stratospheric methane profile dataset [1991-2021] constructed using machine-learning

Methodology:  

he 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.

CH4 Profile Processing and Bias Correction

Collocated CH4 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). It is important to note that unlike previous versions that might have used both HALOE and ACE measurements, this version exclusively utilizes ACE-FTS data, which is why the dataset starts from 2000.

Separate XGBoost regression models are then trained for these CH4 differences at each height level within a given latitude bin. These trained models are subsequently used to estimate CH4 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 CH4 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 CH4 profiles:

• zmch4_TCOM_hlev_T2Dz_2000-2024_V1.1.nc: Contains height level data (10,km to 60,km).

• zmch4_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.