Near-global summer circulation response to the spring surface temperature anomaly in Tibetan Plateau –– the GEWEX/LS4P first phase experiment

Journal Article · 28 March 2024 · Climate Dynamics

DOI: https://doi.org/10.1007/s00382-024-07210-5 · OSTI ID:2338042

Zhang, Yang  ^[1]; Pan, Yan ^[2]; Xue, Yongkang ^[3]; Diallo, Ismaila ^[4]; Zeng, Xubin ^[5]; Li, Shuting ^[1]; Neelin, J. David ^[3]; Lau, William M. ^[6]; Boone, Aaron A. ^[7]; Vitart, Frederic ^[8]; Yao, Tandong ^[9]; Tang, Qi ^[10]; Sato, Tomonori ^[11]; Koo, Myung-Seo ^[12]; Ardilouze, Constantin ^[7]; Saha, Subodh K. ^[13]; Yang, Jing ^[14]; Materia, Stefano ^[15]; Lin, Zhaohui ^[9]; Qi, Xin ^[14] ; Qin, Yi ^[16]; Nakamura, Tetsu ^[11]; Nobre, Paulo ^[17]; Peano, Daniele ^[18]; Senan, Retish ^[8]; Takaya, Yuhei ^[19]; Wang, Hailan ^[20]; Zhang, Hongliang ^[21]; Zhan, Yanling ^[9]; Zhao, Mei ^[22]; Mechoso, Carlos R. ^[3]; Bao, Qing ^[9]; Bottino, Marcus Jorge ^[17]; Hong, Songyou ^[23]; Lin, Yanluan ^[24]; Xie, Shaocheng ^[10]; Pan, Xiaoduo ^[9]; Nayak, Hara Prasad ^[3]; Chou, Sin Chan ^[17]; Guo, Weidong ^[1]

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1. Nanjing University (China)
2. Nanjing University (China); Duke University, Durham, NC (United States)
3. University of California, Los Angeles, CA (United States)
4. Pennsylvania State University, University Park, PA (United States)
5. University of Arizona, Tucson, AZ (United States)
6. University of Maryland, College Park, MD (United States)
7. University of Toulouse (France)
8. European Centre for Medium-Range Weather Forecasts, Reading (United Kingdom)
9. Chinese Academy of Sciences (CAS), Beijing (China)
10. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
11. Hokkaido University, Sapporo (Japan)
12. Korea Institute of Atmospheric Prediction Systems, Seoul (South Korea)
13. Indian Institute of Tropical Meteorology, Pune (India)
14. Beijing Normal University, Beijing (China)
15. Barcelona Supercomputing Centre, Barcelona (Spain)
16. Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
17. National Institute for Space Research (INPE), São José dos Campos (Brazil)
18. Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Bologna (Italy)
19. Japan Meteorological Agency, Tsukuba (Japan)
20. National Center for Environmental Prediction, College Park, MD (United States)
21. Center for Earth System Modeling and Prediction, CMA, Beijing (China)
22. Bureau of Meteorology, Melbourne (Australia)
23. Hokkaido University, Sapporo (Japan); National Oceanic and Atmospheric Administration (NOAA), Boulder, CO (United States)
24. Tsinghua University, Beijing (China)

Subseasonal to seasonal (S2S) prediction of droughts and floods is one of the major challenges of weather and climate prediction. Recent studies suggest that the springtime land surface temperature/subsurface temperature (LST/SUBT) over the Tibetan Plateau (TP) can be a new source of S2S predictability. The project “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction (LS4P)” was initiated to study the impact of springtime LST/SUBT anomalies over high mountain areas on summertime precipitation predictions. The present work explores the simulated global scale response of the atmospheric circulation to the springtime TP land surface cooling by 16 current state-of-the-art Earth System Models (ESMs) participating in the LS4P Phase I (LS4P-I) experiment. The LS4P-I results show, for the first time, that springtime TP surface anomalies can modulate a persistent quasi-barotropic Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train from the TP via the northeast Asia and Bering Strait to the western part of the North America, along with the springtime westerly jet from TP across the whole North Pacific basin. The TRC wave train modulated by the TP thermal anomaly play a critical role on the early summer surface air temperature and precipitation anomalies in the regions along the wave train, especially over the northwest North America and the southern Great Plains. The participant models that fail in capturing the TRC wave train greatly under-predict climate anomalies in reference to observations and the successful models. These results suggest that the TP LST/SUBT anomaly via the TRC wave train is the first order source of the S2S variability in the regions mentioned. Furthermore, the TP surface temperature anomaly can influence the Southern Hemispheric circulation by generating cross-equator wave trains. However, the simulated propagation pathways from the TP into the Southern Hemisphere show large inter-model differences. More dynamical understanding of the TRC wave train as well as its cross-equator propagation into the Southern Hemisphere will be explored in the newly launched LS4P phase II experiment.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA); Chinese Academy of Sciences; National Science Foundation (NSF)
• Grant/Contract Number: AC52-07NA27344
• OSTI ID: 2338042
• Report Number(s): LLNL-JRNL-852223; 1079297
• Journal Information: Climate Dynamics, Journal Name: Climate Dynamics Vol. 62; ISSN 0930-7575
• Publisher: Springer-VerlagCopyright Statement
• Country of Publication: United States
• Language: English