| Summary: | This dataset is used for analysis of recent precipitation change over Taklamakan and Gobi Desert. Please refer to this work for more information: Dong, W., Ming, Y., Deng, Y. et al. Recent wetting trend over Taklamakan and Gobi Desert dominated by internal variability . Nat Commun 15, 4379 (2024). https://doi.org/10.1038/s41467-024-48743-x This dataset contains both daily and monthly variables generated by a nugded simulation using the GFDL AM4. The AM4 model, as described in Zhao et al. (2018a,b), is the atmospheric component of the GFDL coupled physical climate model CM4, GFDL’s contribution to CMIP6 (Held et al. 2019 JAMES). The model is driven by the observed SST and sea ice conditions, greenhouse gases, and natural and anthropogenic aerosol emissions. The model horizontal winds are nudged to the 3-hourly averaged products from the MERRA-2 reanalysis with a nudging time scale of 6 h. The simulation period covers 2000-2019. Daily variables include precipitation, specific humidity (700 hPa), geopotential height (500 hPa), and horizontal winds (700, 500, 200 hPa), while Monthly variables include precipitation. All datasets are in netCDF format. The file naming convention follows this structure: var.EXP.freq.(lev).nc . Here, ' var ' denotes the variable name, ' EXP ' represents the experiment name (in this case, nAMIP), ' freq ' indicates the temporal frequency (daily or monthly), and ' lev ' represents the vertical pressure level. References: 1. Zhao, M. et al. The GFDL global atmosphere and land model AM4. 0/LM4. 0: 1. simulation characteristics with prescribed SSTs. J. Adv. Model. Earth Syst. 10, 691–734 (2018a). 2. Zhao, M. et al. The GFDL global atmosphere and land model AM4. 0/LM4. 0: 2. model description, sensitivity studies, and tuning strategies. J. Adv. Model. Earth Syst. 10, 735–769 (2018b). 3. Held, I. et al. Structure and performance of GFDL’s CM4. 0 climate model. J. Adv. Model. Earth Syst. 11, 3691–3727 (2019).
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