As the Earth's mean temperature has increased, more extreme events happened, changing the total and season peak value of streamflow in rivers, making it more easily to cause droughts and floods. CMIP6 is based on the Representative Concentration Pathways (RCPs) of CMIP5 and proposes the Shared Socioeconomic Pathways (SSPs), which reflect newer and more diverse greenhouse gas concentration changes under social development, and has improved the simulation of temperature and precipitation in the China region compared with CMIP5. However, the spatial resolution of GCMs is coarse, and reference China station observation data is limited in existing downscaled CMIP6 GCMs, leading to some inaccuracy in Chinese hydrological applications.
To address this issue, Associate Professor Lu Hui's group at Department of Earth System Science, Tsinghua University, used the equidistant cumulative distribution
function method (EDCDFm), with reference to the high-resolution China meteorological forcing dataset (CMFD) historical gridded data, to downscale and bias-correct six CMIP6 GCMs (CanESM5, FGOALS-g3, GFDL-CM4, IPSL-CM6A-LR, MPI-ESM1-2-HR and MRI-ESM2-0) for daily precipitation, maximum and minimum temperatures, and using wind speed and corrected precipitation and temperature variables to drive the variable infiltration capacity (VIC) hydrological model, the results indicate that under the SSP2-4.5 and SSP5-8.5 scenarios, which represents middle and high both challenges for adaptation and mitigation and radiation forcing respectively, the multi-GCM arithmetic means Ensemble projections for the Chinese mainland annual precipitation, evapotranspiration and runoff increase in volatility during the 21st century (Fig. 1), with more dramatic increases for the SSP5-8.5 scenario. Multiyear average annual precipitation, evapotranspiration, and total annual runoff depth for the Chinese mainland and each basin increase relative to the historical period in the near future (2020–2049) and far future (2070–2099) under the SSP2-4.5 and SSP5-8.5 scenarios (Fig. 2).
The CMIP6 GCMs, which are statistical downscaled with more measured sites data reference in CMFD in China, showing larger difference in annual precipitation variation with CMIP5 GCMs, which may be the main reason for differences that increase (in this study) and decrease (in previous researches) annual runoff depth projections over the Chinese mainland and major basins (Fig. 3). The conclusions of this study may provide a strong scientific reference for future water resource management studies in China under climate change.
See the article:
Zhou J, Lu H, Yang K, Jiang R, Yang Y, Wang W, Zhang X. 2023. Projection of China's future runoff based on the CMIP6 mid-high warming scenarios. Science China Earth Sciences, 66(3): 528-546, https://doi.org/10.1007/s11430-022-1055-5
