TRENDS IN TOTAL COLUMN WATER VAPOR

Figure number: Figure 3.12 From the IPCC Working Group I Contribution to the Sixth Assessment Report: Chapter 3

Description:

Column water vapor path trends (%/decade) for the period 1988-2019 averaged over the near-global oceans (50°S-50°N). The figure shows satellite data (RSS) and ERA5.1 reanalysis, as well as CMIP5 (sky blue) and CMIP6 (brown) historical simulations. All available ensemble members were used (see Section 3.2. Fits to the model trend probability distributions were performed with kernel density estimation. Figure is updated from Santer et al. (2007).

Author list:

• Santer, S.D.: LLNL, U.S.; santer1@llnl.gov
• Weigel, K.: University of Bremen, Germany
• Kazeroni, R.: DLR, Germany

Publication sources:

Santer, B. D., Mears, C., Wentz, F. J., Taylor, K. E., Glecker, P. J., Wigley, T. M. L., et al. (2007). Identification of human-induced changes in atmospheric moisture content. Proc. Natl. Acad. Sci. 25, https://doi.org/10.1073/pnas.0702872104

Santer, B. D., Po-Chedley, S., Mears, C., Fyfe, J. C., Gillett, N., Fu, Q., Painter, J. F., Solomon, S., Steiner, A. K., Wentz, F. J., Zelinka, M. D., & Zou, C. (2021). Using Climate Model Simulations to Constrain Observations, Journal of Climate, 34(15), 6281-6301, https://doi.org/10.1175/JCLI-D-20-0768.1

ESMValTool Branch:

• ESMValTool-AR6-OriginalCode-FinalFigures: ar6_chapter_3

ESMValCore Branch:

• ESMValCore-AR6-OriginalCode-FinalFigures: fix_cmip6_models_newcore

Recipe & diagnostics:

Recipe used: recipes/ipccwg1ar6ch3/recipe_ipccwg1ar6ch3_santer21jclim.yml

Diagnostic used: diag_scripts/santer21jclim/santer21jclimfig.py

Expected image path:

This is the path of the image relative to the automatically generated ESMValTool output location:

• recipe_ipccwg1ar6ch3_santer21jclim_newextendedv3_YYYYMMDD_HHMMSS/plots/wvtrend/santer20jclim/fig1.png

Ancillary figures and datasets:

There is one optional, additional figure which can be turned on in the recipe displays the pdf for ensemble members of chosen models (instead of all CMIP5 and CMIP6 models) by listing model names under the key word "add_model_dist".

Additional datasets:

RSS data: SOURCE = "ftp://ftp.remss.com/vapor/monthly_1deg/" Remote Sensing Systems. Monthly Mean Total Precipitable Water Data Set on a 1 degree grid made from Remote Sensing Systems Version-7 Microwave Radiometer Data, Date created: 20201110T185551Z accessed on 2020-11-19]. Santa Rosa, CA, USA. Available at www.remss.com

cmorized with esmvaltool/cmorizers/obs/cmorize_obs_rss.ncl (in the ar6_chapter_3 branch, not in the main ESMValTool branch, yet) using the "precipitable_water" variable. The "fixed coverage" mask was produced from the same file, using "precipitable_water_climatology" and "precipitable_water_anomaly" with a tool based on the cmorizer: esmvaltool/cmorizers/obs/cmorize_obs_rssanom.ncl.

Software description:

• ESMValTool environment file: IPCC_environments/ar6_newcore_remi_conda_environment.yml
• pip file: IPCC_environments/ar6_newcore_remi_pip_environment.txt

Hardware description:

Machine used: Mistral