Recent wetting trend over Taklamakan and Gobi Desert dominated by internal variability
Creators
Abstract
The Taklamakan and Gobi Desert (TGD) region has experienced a pronounced increase in summer precipitation, including high-impact extreme events, over recent decades. Despite identifying large-scale circulation changes as a key driver of the wetting trend, understanding the relative contributions of internal variability and external forcings remains limited. Here, we approach this problem by using a hierarchy of numerical simulations, complemented by diverse statistical analysis tools. Our results offer strong evidence that the atmospheric internal variations primarily drive this observed trend. Specifically, recent changes in the North Atlantic Oscillation have redirected the storm track, leading to increased extratropical storms entering TGD and subsequently more precipitation. A clustering analysis further demonstrates that these linkages predominantly operate at the synoptic scale, with larger contributions from large precipitation events. Our analysis highlights the crucial role of internal variability, in addition to anthropogenic forcing, when seeking a comprehensive understanding of future precipitation trends in TGD.
Copyright and License
© The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Acknowledgement
The authors would like to thank Ming Zhao and Akshaya Nikumbh for their useful discussion and comments on earlier versions of this paper. This research from the Geophysical Fluid Dynamics Laboratory is supported by NOAA’s Science Collaboration Program and administered by UCAR’s Cooperative Programs for the Advancement of Earth System Science (CPAESS) under awards NA16NWS4620043 (W.D.) and NA18NWS4620043B (W.D.). This work is also support by the U.S. National Science Foundation (NSF) through Grant AGS-2032532 (Y.D.) and by the U.S. National Oceanic and Atmospheric Administration (NOAA) through Grant NA22OAR4310606 (Y.D.) and Grant NA20OAR4310380 (Y.D.).
Contributions
W.D. and Y.M. conceived and designed the study. W.D. performed the analyses, with contributions from Y.M. and Y.D. in interpreting the results. Z.S. conducted the nudged simulation. W.D. and Y.M. wrote the paper, and Y.D. and Z.S. contributed to discussions and improving the manuscript.
Data Availability
The monthly Tropical Rainfall Measuring Mission (TRMM) precipitation data is accessible at https://disc.gsfc.nasa.gov/datasets/TRMM_3B43_7/summary. The station records of the monthly precipitation dataset are available for acquisition at https://www.ncei.noaa.gov/data/ghcnm/v4beta/. The other precipitation datasets utilized in this study, including the CPC Global Unified Gauge-Based Analysis of Daily Precipitation dataset, the monthly GPCP precipitation dataset, the monthly UDel precipitation dataset, and the monthly CPC Merged Analysis of Precipitation (CMAP) precipitation dataset, can be found and downloaded at https://psl.noaa.gov/data/gridded/index.html. The PC-based summer NAO index is obtained from https://climatedataguide.ucar.edu/sites/default/files/2023-04/nao_pc_monthly.txt. For the ERA5 reanalysis datasets, they can be accessed from https://apps.ecmwf.int/data-catalogues/era5/?class=ea. The GFDL AM4 model source code can be obtained from https://data1.gfdl.noaa.gov/nomads/forms/am4.0/. Model outputs from AMIP, CMIP, and piControl experiments can be downloaded from the CMIP6 data portal (https://aims2.llnl.gov/search/cmip6/). Model outputs from iCMIP experiment can be accessed publicly from the GFDL SPEAR Large Ensembles website (https://noaa-gfdl-spear-large-ensembles-pds.s3.amazonaws.com/index.html#SPEAR/GFDL-LARGE-ENSEMBLES/CMIP/NOAA-GFDL/GFDL-SPEAR-MED/historical/). Model outputs from the nAMIP experiment have been deposited in the Zenodo database under accession code (https://doi.org/10.5281/zenodo.11110869). Source data are provided with this paper.
Code Availability
The NCAR Command Language (NCL v6.6.2) is used for plotting. All custom codes are direct implementations of standard methods and techniques, described in detail in Methods.
Conflict of Interest
The authors declare no competing interests.
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Additional details
Identifiers
- PMCID
- PMC11116515
Funding
- National Oceanic and Atmospheric Administration
- NA16NWS4620043
- National Oceanic and Atmospheric Administration
- NA18NWS4620043B
- National Science Foundation
- AGS-2032532
- National Oceanic and Atmospheric Administration
- NA22OAR4310606
- National Oceanic and Atmospheric Administration
- NA20OAR4310380