TCOM-H2O: TOMCAT CTM and Occultation Measurements based daily zonal stratospheric H2O profile dataset

The TOMCAT simulation was conducted at a T64L32 resolution, consistent with previous work by Dhomse and Chipperfield (2023), covering the period from 2000 to 2024. These simulations utilized ERA-5 reanalysis data.

H2O Profile Processing and Bias Correction

Collocated H2O 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, TOMCAT tracers are interpolated on the ACE FTS height (1km to 50km) Separate XGBoost regression models are trained to predict ACE FTS measurements for a given altitude /latitude bin if more than 2000 measurements are available. XGBoost model is then used to estimate H2O volume mixing ratios for all the TOMCAT grids.  Height resolved data are then interpolated on 22-pressure levels. 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 H2O profiles on height (1-50 km) and pressure (300-1 hPa) – 22 levels (9132 days/64 latitudes). Files also include uncertainties estimated using quantile regression and uncertainty = NaN means data is from TOMCAT CTM (scientifically useful range 5 to 25km).

zmh2o_tcom_hlev_2000-2024_V2.0.nc – height level data (1 to 50 km)

zmh2o_tcom_plev_2000-2024_V2.0.nc – pressure level data (300 to 1 hPa)

Daily 3D profiles on height and pressure levels would be made available on request. Xarrays “resample” can be used to get monthly means.

(Attached pdf file gives more details. This data set improves from our previous methodology (Dhomse and Chipperfield, 2023, ESSD) and manuscript describing to those updates is submitted to ESSD as Dhomse and Chipperfield, 2026.

Reference Publications

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

Dhomse, S. S. and Chipperfield, M. P.: TCOM-CFC11 and TCOM-CFC12: A Gap-Free, Observationally Constrained Global Dataset of Stratospheric CFC11 and CFC12 Profiles (V2)., submitted to Earth Syst. Sci. Data, 2026