The atmospheric–ocean mixed-layer coupled model Met Office Unified Model (MetUM)-Global Ocean Mixed Layer coupled configuration version 1 (GOML1) (Hirons et al., 2015) was used to assess the contribution of changes in GHG emissions and AA together or individually to the decadal variations in precipitation in China through a set of numerical experiments. MetUM-GOML1 is a near-globally-coupled atmosphere–ocean-mixed-layer model. The coupled model comprises the MetUM Global Atmosphere, version 3 (Hewitt et al., 2011; Walters et al., 2011) coupled to the multi-column K-profile parameterization (MC-KPP) mixed layer ocean model. The resolution in the current study is 1.875° longitude and 1.25° latitude with 85 vertical layers; the model lid is at 850 km. Details about the MetUM-GOML1 model and the numerical experiments (Table 1) have been reported previously by Su and Dong (2019). First, we perform a relaxation experiment (R0) for 12 yr, in which the PD (1994–2011) GHG and AA forcings are used and the ocean temperature and salinity were relaxed to a PD climatology, which is derived from the Met Office ocean analysis (Smith and Murphy, 2007). Using different forcings, four other time-sliced experiments are performed, that is, the CEP experiment conducted by using mean GHG concentrations and AA emissions from 1964 to 1981 (EP), the CPD experiment similar to CEP but from 1994 to 2011, the CPDGHG experiment forced by the mean GHG concentrations during the period 1994–2011 (PD) and the appropriate EP mean AA emissions, and the CPDAA experiment forced by the PD mean AA emissions and the EP mean GHG concentrations. All experiments are run for 50 yr and use the climatological PD sea ice extent from the Met Office Hadley Centre’s sea ice and sea surface temperature (HadISST; Rayner et al., 2003). The last 45 years of each experiment are used for analysis. The same set of experiments was used to study the forcing changes of summer precipitation in East Asia by Tian et al. (2018), the decadal changes in temperature extremes over China by Chen and Dong (2019), and the decadal changes in heatwaves by Su and Dong (2019). We used the same model and numerical experiments to study the decadal changes in precipitation over China.
Abbreviation Experiment Ocean Radiative forcing R0 Relaxation run Relax to PD mean three-dimensional (3D) ocean temperature and salinity to diagnose climatological temperature and salinity tendencies Relax to PD GHG over PD and AA emissions over 1994–2010 with GHG and AA after 2006 from RCP4.5 scenario CEP Early period Climatological temperature and salinity flux tendencies from relaxation run EP mean GHG and EP mean AA emissions CPD PD with GHG and AA forcing PD mean GHG and PD mean AA emissions CPDGHG PD with GHG forcing PD mean GHG and EP mean AA emissions CPDAA PD with AA forcing EP mean GHG and PD mean AA emissions
Table 1. Summary of numerical experiments
The heavy, moderate, and light rainfall in the experiments were defined in the same way as in the observational dataset and the relative thresholds were calculated as the daily 90th and 60th percentiles of precipitation based on the last 45 years of the CEP experiment. A pair of experiments contains and excludes a specific forcing, and the difference between the two experiments represents the response to the compulsion. The difference between the CPD and CEP experiments shows the combined influence of changes in both GHG concentrations and the emission of AA (hereafter referred to as ALL forcing). The influence of GHG concentration change (hereinafter referred to as GHG forcing) is the difference between CPDGHG and CEP experiments, while the impact of AA emission change (hereinafter referred to as AA forcing) is the difference between CPDAA and CEP experiments.
Figures 1b, d, f, and h show the simulated summer precipitation and the contributions of the three types of precipitation to the summer seasonal mean values in the PD simulation. The main feature of the summer precipitation simulated by the model is that there is more precipitation over southern China and less precipitation over northwestern China (Fig. 1b), with heavy rainfall accounting for 30%–40% of summer precipitation over large areas of eastern China and accounting for about 10%–30% of summer precipitation over western China (Fig. 1d). Moderate rainfall explains about 50%–60% of summer precipitation. This contribution is about 10% higher than in the observational dataset and 10% higher than the contribution from heavy precipitation in the model simulation (Figs. 1c–f). The contribution from light precipitation shows the form of west more and east less that accounts for < 20% of summer precipitation in eastern China and 20%–30% over western China, which is similar to the observational dataset. These results show that the main characteristics of summer precipitation and the contributions of the three types of precipitation to summer precipitation in the observational dataset are well reproduced by the MetUM-GOML1 model.