Nested MPI-CWRF dynamical downscaling and future projections of summer extreme precipitation changes in China

Abstract

This study develops a nested MPI-CWRF dynamical downscaling system by using the regional Climate-Weather Research and Forecasting Model (CWRF, ~30 km) driven by the MPI-ESM1-2-HR global climate model (GCM, ~100 km), aiming to improve the future projections of summer extreme precipitation over China. This system is implemented for both present climate simulations (1980−2014) and future projections (2016−2050) under the highest emission scenario of SSP5-8.5. Comparative analyses with high-resolution MPI-ESM1-2-XR (~50 km) demonstrate that dynamical downscaling achieves superior improvements in simulating summer precipitation extremes than mere GCM resolution enhancement. Future projections indicate divergent trends and interannual variability across eastern China: summer precipitation averages (PRA), daily precipitation extremes (P95), and intensity of persistent precipitation events (Rx5day) are projected to have greater increases and enhanced interannual variability under MPI-CWRF compared to GCM, while the number of rainy days (NRD) is projected to decline with reduced interannual variability in south-eastern regions. Specifically, Central China exemplifies this pattern with NRD decreasing by 4.0%, but PRA, P95, and Rx5day increasing by 4.9%, 8.9%, and 11.8%, respectively. These projected changes correlate with key atmospheric shifts: the south-eastward expansion of the South Asian High, the southward-displaced East Asian jet, and anomalous low-level cyclonic circulations over the Yellow-Bohai Seas, as well as strengthened moisture convergence and convective available potential energy through intensified southerly monsoon flows. The physical coherence among these key circulation changes ensures the reliability of extreme precipitation projections made by the MPI-CWRF dynamical downscaling system.

Graphical abstract

Keywords

regional climate model / dynamical downscaling / summer extreme precipitation / future projection

References

[1] Choi H I, Kumar P, Liang X Z (2007). Three-dimensional volume-averaged soil moisture transport model with a scalable parameterization of subgrid topographic variability.Water Resour Res, 43(4): w04414

[2] ChouMD, SuarezM J (1999). A Solar Radiation Parameterization for Atmospheric Studies. NASA/TM-1999–104606/VOL15

[3] ChouMD, SuarezM J, LiangXZ, Yan M MH (2001). A Thermal Infrared Radiation Parameterization for Atmospheric Studies. NASA/TM-2001–104606/VOL19

[4] Gleckler P J, Taylor K E, Doutriaux C (2008). Performance metrics for climate models.J Geophys Res D Atmospheres, 113: D06104

[5] Gutjahr O, Putrasahan D, Lohmann K, Jungclaus J H, von Storch J S, Brüggemann N, Haak H, Stössel A (2019). Max Planck Institute Earth System Model (MPI-ESM1.2) for the High-Resolution Model Intercomparison Project (HighResMIP).Geosci Model Dev, 12(7): 3241–3281

[6] Haarsma R J, Roberts M J, Vidale P L, Senior C A, Bellucci A, Bao Q, Chang P, Corti S, Fuckar N S, Guemas V, von Hardenberg J, Hazeleger W, Kodama C, Koenigk T, Leung L R, Lu J, Luo J J, Mao J F, Mizielinski M S, Mizuta R, Nobre P, Satoh M, Scoccimarro E, Semmler T, Small J, von Storch J S (2016). High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6.Geosci Model Dev, 9(11): 4185–4208

[7] He B R, Zhai P M (2018). Changes in persistent and non-persistent extreme precipitation in China from 1961 to 2016.Adv Clim Chang Res, 9(3): 177–184

[8] Hersbach H, Bell B, Berrisford P, Hirahara S, Horányi A, Muñoz-Sabater J, Nicolas J, Peubey C, Radu R, Schepers D, Simmons A, Soci C, Abdalla S, Abellan X, Balsamo G, Bechtold P, Biavati G, Bidlot J, Bonavita M, De Chiara G, Dahlgren P, Dee D, Diamantakis M, Dragani R, Flemming J, Forbes R, Fuentes M, Geer A, Haimberger L, Healy S, Hogan R J, Hólm E, Janisková M, Keeley S, Laloyaux P, Lopez P, Lupu C, Radnoti G, de Rosnay P, Rozum I, Vamborg F, Villaume S, Thépaut J N (2020). The ERA5 global reanalysis.Q J R Meteorol Soc, 146(730): 1999–2049

[9] Holtslag A A M, Boville B A (1993). Local versus nonlocal boundary-layer diffusion in a global climate model.J Clim, 6(10): 1825–1842

[10] Huang X, Wang Y H, Ma X F (2024). Simulation of extreme precipitation changes in Central Asia using CMIP6 under different climate scenarios.Theor Appl Climatol, 155(4): 3203–3219

[11] Jiang R S, Sun L, Sun C, Liang X Z (2021). CWRF downscaling and understanding of China precipitation projections.Clim Dyn, 57(3−4): 1079–1096

[12] Jiang X W, Li Y Q, Yang S, Wu R G (2011). Interannual and interdecadal variations of the South Asian and western Pacific subtropical highs and their relationships with Asian-Pacific summer climate.Meteorol Atmos Phys, 113: 171–180

[13] Karl T R, Nicholls N, Ghazi A (1999). CLIVAR/GCOS/WMO Workshop on indices and indicators for climate extremes - Workshop summary.Clim Change, 42(1): 3–7

[14] Kong X H, Wang A H, Bi X Q, Wang D (2019). Assessment of temperature extremes in China using RegCM4 and WRF.Adv Atmos Sci, 36(4): 363–377

[15] Li Q Q, Wang T, Wang F, Liang X Z, Zhao C B, Dong L L, Zhao C Y, Xie B (2021). Dynamical downscaling simulation of the East Asian summer monsoon in a regional climate-weather research and forecasting model.Int J Climatol, 41(S1): E1700–E1716

[16] Liang X Z, Sun C, Zheng X H, Dai Y J, Xu M, Choi H I, Ling T J, Qiao F X, Kong X H, Bi X Q, Song L C, Wang F (2019). CWRF performance at downscaling China climate characteristics.Clim Dyn, 52(3−4): 2159–2184

[17] Liang X Z, Wang W C (1998). Associations between China monsoon rainfall and tropospheric jets.Q J R Meteorol Soc, 124(552): 2597–2623

[18] Liang X Z, Xu M, Yuan X, Ling T J, Choi H I, Zhang F, Chen L G, Liu S Y, Su S J, Qiao F X, He Y X, Wang J X L, Kunkel K E, Gao W, Joseph E E, Morris V, Yu T W, Dudhia J, Michalakes J (2012). Regional climate-weather research and forecasting model.Bull Am Meteorol Soc, 93(9): 1363–1387

[19] Liu G, Liang X (2017). Progress of the climate extension of weather research and forecast (CWRF) model application in China.Adv Earth Sci, 32: 781–787

[20] Liu J, Yang K, Wang J, Zhou X, Jiang Y, Shao C, Lu H, Yao X, Sun J, Shi J (2024). Impacts of a shallow convection scheme on kilometer-scale atmospheric simulations over the Tibetan Plateau.Clim Dyn, 62(8): 8019–8034

[21] Liu Q, Qiao F, Zhu Y, Liang X, Liu Y, Zhang H, Wang R (2021). Evaluation of the spatio-temporal variations of extreme temperature simulations in China based on the regional climate-weather research and forecasting model.Climat Environ Res, 26: 333–350

[22] Liu S Y, Liang X Z, Gao W, Zhang H (2008). Application of climate - weather research and forecasting model (CWRF) in China: domain optimization.Chin J Atmos Sci, 32: 457–468

[23] Lu S, Hu Z, Wang B, Qin P, Wang L (2020). Spatio-temporal patterns of extreme precipitation events over China in recent 56 Years.Plateau Meteorol, 39: 683–693

[24] Müller W A, Jungclaus J H, Mauritsen T, Baehr J, Bittner M, Budich R, Bunzel F, Esch M, Ghosh R, Haak H, Ilyina T, Kleine T, Kornblueh L, Li H, Modali K, Notz D, Pohlmann H, Roeckner E, Stemmler I, Tian F, Marotzke J (2018). A higher-resolution version of the Max Planck Institute Earth System Model (MPI-ESM1.2-HR).J Adv Model Earth Syst, 10(7): 1383–1413

[25] Park S, Bretherton C S (2009). The University of Washington shallow convection and moist turbulence schemes and their impact on climate simulations with the community atmosphere model.J Clim, 22(12): 3449–3469

[26] Qiao F X, Liang X Z (2016). Effects of cumulus parameterization closures on simulations of summer precipitation over the United States coastal oceans.J Adv Model Earth Syst, 8(2): 764–785

[27] Qiao F X, Liang X Z (2017). Effects of cumulus parameterization closures on simulations of summer precipitation over the continental United States.Clim Dyn, 49(1−2): 225–247

[28] Scherrer S C (2011). Present-day interannual variability of surface climate in CMIP3 models and its relation to future warming.Int J Climatol, 31(10): 1518–1529

[29] Sun J, Zhang F (2017). Daily extreme precipitation and trends over China.Sci China Earth Sci, 60(12): 2190–2203

[30] Tao W K, Starr D, Hou A, Newman P, Sud Y (2003). A cumulus parameterization workshop.Bull Am Meteorol Soc, 84: 1055–1062

[31] Wang X Y, Tang J P, Niu X R, Wang S Y (2016). An assessment of precipitation and surface air temperature over China by regional climate models.Front Earth Sci, 10(4): 644–661

[32] Wang X, Gu H, Dai B, Zhang H, Yu Z (2024). Simulation of climate characteristics in the Qinghai-Tibet Plateau by regional climate models at different horizontal resolutions.Arid Zone Res, 41: 363–374

[33] Wang Y, Li H, Wang H, Sun B, Chen H (2021). Evaluation of CMIP6 model simulations of extreme precipitation in China and comparison with CMIP5.Acta Meteorol Sin, 79: 369–386

[34] Wei P, Dong G, Shi J, Zhang B (2019). Dynamical downscaling simulation and projection of extreme precipitation over East China.Climat Environ Res, 24: 86–104

[35] Wei W, Zhang R H, Wen M, Kim B J, Nam J C (2015). Interannual variation of the South Asian High and its relation with Indian and East Asian summer monsoon rainfall.J Clim, 28(7): 2623–2634

[36] Wu J, Gao X J (2013). A gridded daily observation dataset over China region and comparison with the other datasets.Chin J Geophys, 56: 1102–1111

[37] Xu H R, Liang X Z, Xue Y K (2024). Regional climate modeling to understand Tibetan heating remote impacts on East China precipitation.Clim Dyn, 62(4): 2683–2701

[38] Yang L, Zhao J, Mao M, Li Y, Liu G (2024). Evaluation of the simulation capability of CMIP6 model for summer precipitation in the northern monsoon region of China.Climat Environ Res, 29: 549–562

[39] Yang X L, Zhou B T, Xu Y, Han Z Y (2021). CMIP6 evaluation and projection of temperature and precipitation over China.Adv Atmos Sci, 38(5): 817–830

[40] Yuan X, Liang X Z (2011). Improving cold season precipitation prediction by the nested CWRF-CFS system.Geophys Res Lett, 38(2): L02706

[41] Zhang H, Liang X Z, Dai Y J, Song L C, Li Q Q, Wang F, Zhang S L (2024). CWRF downscaling with improved land surface initialization enhances spring-summer seasonal climate prediction skill in China.J Clim, 37(17): 4437–4459

[42] Zhang L, Chen X, Xin X (2019). Short commentary on CMIP6 scenario model intercomparison project (ScenarioMIP).Climat Change Res, 15: 519–525

[43] Zhang S Y, Wang M H, Wang L N, Liang X Z, Sun C, Li Q Q (2023). Sensitivity of the simulation of extreme precipitation events in China to different cumulus parameterization schemes and the underlying mechanisms.Atmos Res, 285: 106636

[44] Zhao Y, Qiao F X, Liang X Z, Yu J H (2024). Understanding and improving Yangtze River Basin summer precipitation prediction using an optimal multi-Physics ensemble.Front Earth Sci, 18(1): 256–277

[45] Zhou T, Chen Z, Chen X, Zuo M, Jiang J, Hu S (2021). Interpreting IPCC AR6: future global climate based on projection under scenarios and on near-term information.Climat Change Res, 17: 652–663

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