DOI: 10.5061/dryad.0zpc8675t
title: Data and code from: Long-term climate impacts of large stratospheric water vapor perturbations (Part 1)

description: The amount of water vapor injected into the stratosphere after the
 eruption of Hunga Tonga-Hunga Ha’apai (HTHH) was unprecedented, and it is
 therefore unclear what it might mean for surface climate. We use chemistry
 climate model simulations to assess the long-term surface impacts of
 stratospheric water vapor (SWV) anomalies similar to those caused by HTHH,
 but neglect the relatively minor aerosol loading from the eruption. The
 simulations show that the SWV anomalies lead to strong and persistent
 warming of Northern Hemisphere landmasses in boreal winter, and austral
 winter cooling over Australia, years after eruption, demonstrating that
 large SWV forcing can have surface impacts on a decadal timescale. We also
 emphasize that the surface response to SWV anomalies is more complex than
 simple warming due to greenhouse forcing and is influenced by factors such
 as regional circulation patterns and cloud feedbacks. Further research is
 needed to fully understand the multi-year effects of SWV anomalies and
 their relationship with climate phenomena like El Nino Southern
 Oscillation.
description: This data contains selected variables from WACCM and MiMA
 simulations related to the
 associated article. The relevant figures from
 associated paper can be reproduced using the code at https://https://zenodo.org/doi/10.5281/zenodo.11471857. In addition to the code, the data from WACCM and MiMA will also be needed.
description: # Long-term climate impacts of large stratospheric water vapor
 perturbations
 [https://doi.org/10.5061/dryad.0zpc8675t](https://doi.org/10.5061/dryad.0zpc8675t) This data is used for published article [Jucker et al. Journal of Climate (2024)](https://doi.org/10.1175/jcli-d-23-0437.1). ## Description of the data and file structure This collection contains observational data, all necessary code, plus `hungatonga.yml` which contains information about the conda environment which allows running of all code. The code is also stored on GitHub and Zenodo, and additional links are given below. The dataset is large, and therefore split into two further dryad repositories, also given below. In order to run the code, all data needs to be in the working directory. Then, `plot_paper_figures_published.sh` (contained within `hungatonga-v1.0.zip`) will produce all figures from the paper. Note that there is much more data than what is plotted in the figures, but users are expected to use netCDF metadata to find particular variables. ### Files | File | Purpose | | :--------------------- | :------------------------------------------------------------------------------------------------------ | | `hungatonga-v1.0.zip`  | collection of python code used for the analysis and plotting of all figures | | `hungatonga.yml`  | Contains information on conda environment used to run all diagnostics scripts. | | `MLS_data.nc` | Observational total water mass data as a function of time and latitude. | | `MLS_data_h2o.nc` | Observational water vapor data as a function of time, latitude, and pressure. | | `MLS_data_lev.nc` | Observational total water mass data as a function of time and latitude above different pressure levels. | | `atmos_daily.nc`  | Required to plot MLS data on vertical model grid | ## Sharing/Access information The published article is Jucker, M., C. Lucas, and D. Dutta, 2024: Long-term climate impacts of large stratospheric water vapor perturbations. J. Climate, [doi 10.1175/JCLI-D-23-0437.1](https://doi.org/10.1175/JCLI-D-23-0437.1). Additional data is stored at * [WACCM data](https://doi.org/10.5061/dryad.gxd2547v6) * [MiMA data](https://doi.org/10.5061/dryad.sbcc2frfx) ## Code/Software All code is in python and provided within this dataset (`hungatonga-v1.0.zip`), except the external package `aostools` which can be obtained on [GitHub](https://github.com/mjucker/aostools). The recommended conda environment is stored in `hungatonga.yml`.