Forced Decadal Changes in Summer Precipitation Characteristics over China: The Roles of Greenhouse Gases and Anthropogenic Aerosols

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  • Corresponding author: Bo ZHANG, zhangb81@yeah.net
  • Funds:

    Supported by the National Natural Science Foundation of China (41905091), Support Plan of the National Science and Technology (2015BAC03B04), and Fund Project of the National Meteorological Center Forecaster (Y201904). Buwen DONG is supported by the UK National Centre for Atmospheric Science-Climate (NCAS-Climate) at the University of Reading

  • doi: 10.1007/s13351-020-0060-4

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  • We investigated the decadal changes in the different types of summer mean precipitation over China across the mid-1990s based on observational datasets. The spatial variations in the observed decadal changes were estimated by comparing the present day (PD) time period of 1994–2011 with an earlier period of 1964–1981. The summer total precipitation increased in southern China and decreased in northern China from the early period to the PD. The increases of precipitation in southern China were due to increases in the frequency of heavy and moderate rainfall, whereas the decreases over northern China were mainly due to decreases in the frequency of moderate and light rainfall. Based on a set of numerical experiments using an atmospheric general circulation model coupled with a multilevel mixed-layer ocean model, we found that the increase of precipitation frequency forced by greenhouse gases is the main reason of increasing precipitation over southern and northeastern China, while the decrease of frequency caused by anthropogenic aerosol (AA) induces the decreasing precipitation over northern China. The water vapor flux convergence and water vapor flux strengthen in southern China and northeastern China by anthropogenic greenhouse gases. This distribution is also conducive to precipitation in most of southern China and northeastern China. Under the control of weakened southwesterly winds and 850-hPa divergence, precipitation decreases over northern and southwestern China by AA.
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  • Fig. 1.  Summer [June, July, and August (JJA)] seasonal mean precipitation (mm day−1) in the (a) observations and (b) model simulations for the present day (PD; 1994–2011). Percentage contribution of (c, d) heavy, (e, f) moderate, and (g, h) light rainfall to the seasonal mean precipitation in the (c, e, g) observations and (d, f, h) model simulations.

    Fig. 2.  (a) Distribution of stations in the observational dataset. The green, red, black, and blue dots represent the sub-regions of western, northern, northeastern, and southern China, respectively. Time series of the area-averaged total summer precipitation (mm) based on observations over (b) southern and (c) northern China. The black line is total rainfall (left-hand y axis), the red line is heavy rainfall (left-hand y axis), the blue line is moderate rainfall (left-hand y axis), and the orange line is light rainfall (right-hand y axis). The two black horizontal bars indicate the PD (1994–2011) and early period (1964–1981) rainfall.

    Fig. 3.  Spatial patterns of the differences in precipitation between the PD (1994–2011) and the early period (1964–1981) in summer. (a) Total precipitation (mm), (b) number of dry days (day), and contributions (mm) of (c) heavy, (d) moderate, and (e) light rainfall in the observational dataset. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Fig. 4.  Spatial patterns of the differences in summer precipitation between the PD (1994–2011) and the early period (1964–1981) in the observational dataset. Frequency (number of days) of (a) heavy, (c) moderate, and (e) light rainfall and intensity (mm day−1) of (b) heavy, (d) moderate, and (f) light rainfall. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Fig. 5.  The changes of the total summer precipitation (mm) in response to (a) ALL forcing, (b) GHG forcing, and (c) AA forcing. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Fig. 6.  Model simulated changes in (a) heavy rainfall, (b) moderate rainfall, and (c) light rainfall (mm) in response to ALL forcing (CPD − CEP). The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Fig. 7.  Model simulated changes in (a) frequency (number of days) and (b) intensity (mm day−1) of heavy rainfall in response to changes in ALL forcing. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Fig. 8.  Model simulated changes in frequency (number of days) of heavy rainfall in response to changes in (a) GHG forcing and (b) AA forcing. Model simulated changes in intensity (mm day−1) of heavy rainfall in response to changes in (c) GHG forcing and (d) AA forcing. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Fig. 9.  Area-averaged changes in frequency (event yr−1) of (a) heavy rainfall, (b) moderate rainfall, and (c) light rainfall over southern (SC), northern (NC), northeastern (NEC), and western China (WC) in the observational dataset (orange bars) and the simulations forced by ALL forcing (dark blue bars), GHG forcing (blue bars), and AA forcing (light blue bars).

    Fig. 10.  As in Fig. 9, but for intensity (mm day−1).

    Fig. 11.  The difference of 850-hPa water vapor flux divergence (× 10−9 kg cm−2 s−1 hPa−1) and water vapor flux (kg cm−1 s−1 hPa−1) between CPD and CEP experiments in JJA in response to (a) ALL forcing, (b) GHG forcing, and (c) AA forcing. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Fig. 12.  Vertical velocity (shading; 10−3 hPa s−1) and surface air temperature (contour; K) difference between CPD and CEP experiments in JJA in response to (a) ALL forcing, (b) GHG forcing, and (c) AA forcing.

    Table 1.  Summary of numerical experiments

    AbbreviationExperimentOceanRadiative forcing
    R0Relaxation runRelax to PD mean three-dimensional (3D) ocean temperature and salinity to diagnose climatological temperature and salinity tendenciesRelax to PD GHG over PD and AA emissions over 1994–2010 with GHG and AA after 2006 from RCP4.5 scenario
    CEPEarly periodClimatological temperature and salinity flux tendencies from relaxation runEP mean GHG and EP mean AA emissions
    CPDPD with GHG and AA forcingPD mean GHG and PD mean AA emissions
    CPDGHGPD with GHG forcingPD mean GHG and EP mean AA emissions
    CPDAAPD with AA forcingEP mean GHG and PD mean AA emissions
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Forced Decadal Changes in Summer Precipitation Characteristics over China: The Roles of Greenhouse Gases and Anthropogenic Aerosols

    Corresponding author: Bo ZHANG, zhangb81@yeah.net
  • 1. National Meteorological Center, China Meteorological Administration, Beijing 100081, China
  • 2. National Centre for Atmospheric Science-Climate, Department of Meteorology, University of Reading, Reading RG6 6UR, UK
Funds: Supported by the National Natural Science Foundation of China (41905091), Support Plan of the National Science and Technology (2015BAC03B04), and Fund Project of the National Meteorological Center Forecaster (Y201904). Buwen DONG is supported by the UK National Centre for Atmospheric Science-Climate (NCAS-Climate) at the University of Reading

Abstract: We investigated the decadal changes in the different types of summer mean precipitation over China across the mid-1990s based on observational datasets. The spatial variations in the observed decadal changes were estimated by comparing the present day (PD) time period of 1994–2011 with an earlier period of 1964–1981. The summer total precipitation increased in southern China and decreased in northern China from the early period to the PD. The increases of precipitation in southern China were due to increases in the frequency of heavy and moderate rainfall, whereas the decreases over northern China were mainly due to decreases in the frequency of moderate and light rainfall. Based on a set of numerical experiments using an atmospheric general circulation model coupled with a multilevel mixed-layer ocean model, we found that the increase of precipitation frequency forced by greenhouse gases is the main reason of increasing precipitation over southern and northeastern China, while the decrease of frequency caused by anthropogenic aerosol (AA) induces the decreasing precipitation over northern China. The water vapor flux convergence and water vapor flux strengthen in southern China and northeastern China by anthropogenic greenhouse gases. This distribution is also conducive to precipitation in most of southern China and northeastern China. Under the control of weakened southwesterly winds and 850-hPa divergence, precipitation decreases over northern and southwestern China by AA.

1.   Introduction
  • China is located in the Asian monsoon region and precipitation in summer is mainly controlled by the East Asian summer monsoon. A decadal shift occurred in East China in the late 1970s, with more precipitation in the Yangtze River valley and less precipitation in northern China (Wu and Chen, 1998; Gong and Ho, 2002; Yu et al., 2004; Zhai et al., 2005; Ding et al., 2008; Qian and Qin, 2008; Zhao et al., 2010). Summer precipitation over southern China then increased after 1992/1993 (Yao et al., 2008; Ding et al., 2009; Wu et al., 2010; Fan et al., 2014; Xu et al., 2015). There have been many studies of the decadal variations in different types of precipitation (Qian and Qin, 2008; Wang et al., 2011; Yang and Li, 2014; He and Zhai, 2018). Under the current conditions of global climate change, the amount of heavy precipitation in eastern China has increased (Wang et al., 2011; Yang and Li, 2014) and the contribution of extreme precipitation to the total amount of precipitation in summer has also increased in most parts of China (Min and Qian, 2008; He and Zhai, 2018), although precipitation has decreased in central Inner Mongolia and the Sichuan basin (He and Zhai, 2018). The frequency and amount of light rainfall in eastern China have shown decreasing trends since the 1950s (Qian et al., 2009; Rajah et al., 2014).

    Many researchers have investigated the possible causes of changes in precipitation in China (Yu et al., 2004; Yu and Zhou, 2007; Zhou et al., 2009). The impact of human activity on changes in precipitation has been studied in some regions, including land at high latitudes in the Northern Hemisphere (Min and Qian, 2008; Wan et al., 2015), South Asia (Bollasina et al., 2011), and East Asia (Ma et al., 2017). Because variations of the East Asian summer monsoon and related rainfall can be caused by both changes in anthropogenic forcing and natural variability, many previous studies have analysed the relative importance of these variations (Shen et al., 2008; Wang et al., 2012, 2013; Song et al., 2014). Some studies have shown that changes in greenhouse gas (GHG) concentrations and anthropogenic aerosol (AA) emissions are the most important factors for the Southern-Flood–Northern-Drought (SFND) pattern (Wang et al., 2013; Dong et al., 2016; Xie et al., 2016; Chen and Sun, 2017; Ma et al., 2017; Zhang et al., 2017; Tian et al., 2018). The amount of precipitation in southern China increases with an increase in GHG concentrations, whereas changes in AA dominate the drought conditions in northern China. Forcing by AA weakens the East Asian summer monsoon, which leads to divergent wind anomalies and reduced precipitation in northern China (Tian et al., 2018). The decrease in light rainfall in recent decades is mainly due to dramatic increases in AA (Rosenfeld et al., 2007; Qian et al., 2009; Wang et al., 2016). A study by Liu et al. (2015) showed that global climate change rather than aerosol effects is the main reason for the change in the intensity of precipitation in eastern China.

    A large number of global climate models have projected that climate extremes (such as extreme precipitation and the number of consecutive dry days and extremely hot days) will increase with increases in the concentrations of GHG and decreases in aerosol emissions (Caesar and Lowe, 2012; Kharin et al., 2013; Sillmann et al., 2013; Zhou et al., 2014). The response of precipitation to global climate change takes two forms: an increase in the total amount of rainfall and an increase in the rain rates of the heaviest events. Trenberth (1999) explained that this difference means that precipitation changes toward more heavy rains and a decrease of rainfall frequency. Based on Phase 5 of the Coupled Model Intercomparison Project (CMIP5), Pendergrass and Hartmann (2014) found that rain rates are increasing with global climate change. Using Community Atmospheric Model version 5 (CAM5) model experiments, Wang et al. (2016) found that dramatic increases in AA are the main reason for the observed decrease in light rainfall in eastern China since the 1950s.

    Most published studies have focused on the decadal variations in extreme and light precipitation and how these are affected by human activity. By contrast, the variations in different magnitudes of precipitation, especially the changes in the frequency and intensity of rainfall in recent decades, are still unclear. The individual contributions of changes in GHG concentrations and emissions of AA to the recent decadal changes in precipitation have not yet been assessed. Therefore, the main aims of this work were: (1) to investigate recent decadal changes in the characteristics of summer precipitation (light, moderate, and heavy rainfall), their spatial variation, and their contributions to the summer mean precipitation over China; and (2) to quantify the relative roles of changes in GHG concentrations and the emission of AA in shaping these changes.

    The rest of this paper is organized as follows: Section 2 revisits the observed decadal changes of the mean summer precipitation and the characteristics of precipitation over China. Section 3 describes the model and experiments and Section 4 reports the simulated changes in response to different changes in anthropogenic forcing. Section 5 describes the initial physical processes of simulating precipitation changes through different anthropogenic forcings, such as GHG concentrations and AA emissions. Finally, a summary and discussion are given in Section 6.

2.   Observed decadal changes in precipitation characteristics over China
  • The daily rainfall data used in this study were selected from the daily rainfall datasets of 2474 stations in China from 1960 to 2013 provided by the National Meteorological Information Center, China Meteorological Administration (Ren et al., 2012). As a result of the construction and removal of individual stations during this time period, 1361 stations were finally included in this study. The summer mean precipitation refers to the mean precipitation from June to August.

  • Because there are many different types of climate in China, the absolute precipitation threshold cannot be used to distinguish the type of precipitation. A percentile value was therefore used to determine the threshold of different types of precipitation. The two relative thresholds of three different types of precipitation on each calendar day for each station were calculated during the baseline period of 1964–1981. The first threshold was the 90th percentile and the second was the 60th percentile of precipitation.

    Daily precipitation in China was divided into three types: (1) heavy precipitation (i.e., precipitation above the 90th percentile); (2) moderate precipitation (i.e., precipitation between the 90th and 60th percentiles); and (3) light precipitation (i.e., precipitation below the 60th percentile).

    Summer precipitation and its characteristics were studied based on the frequency, intensity, and number of dry days. A dry day was defined as a day with daily precipitation < 1 mm. The frequency was defined as the cumulative number of days in a certain category of precipitation in the summer of one year. The corresponding intensity was calculated from the average intensity of all events.

  • Figures 1a, c, e, and g show the spatial distribution of the annual average summer precipitation and the contributions of heavy, moderate, and light rainfall, respectively, to the observations during the period 1994–2011. Influenced by the East Asian summer monsoon, summer precipitation in China is mainly concentrated in southeastern China, while the precipitation in northwestern China is less than that in southeastern China. Heavy rainfall accounts for about 40%–50% of summer precipitation in eastern China and about 20%–40% in western China (Fig. 1c). Moderate rainfall accounts for about 40%–50% of summer precipitation (Fig. 1e), whereas the contribution of light rainfall is in the form of west more and east less and accounts for < 20% of precipitation in eastern China and 20%–30% in western China.

    Figure 1.  Summer [June, July, and August (JJA)] seasonal mean precipitation (mm day−1) in the (a) observations and (b) model simulations for the present day (PD; 1994–2011). Percentage contribution of (c, d) heavy, (e, f) moderate, and (g, h) light rainfall to the seasonal mean precipitation in the (c, e, g) observations and (d, f, h) model simulations.

    To show the temporal and decadal variation in summer precipitation, we defined summer precipitation indexes for northern (35°–45°N, 105°–120°E) and southern (20°–35°N, 105°–120°E) China as the same two regions reported by Tian et al. (2018). Figure 2a shows the station distribution in China. The total summer precipitation over southern China was about 548.6 mm during the early period (EP) and increased to 612.4 mm during the present day (PD) period (Fig. 2b). The decadal increase in the total summer precipitation over southern China is a result of contributions from increases in both heavy and moderate precipitation, whereas there is a decrease in the contribution from light precipitation. The total summer precipitation over northern China (Fig. 2c) in the early period is about 268.2 mm, which reduces to 254.1 mm during the PD period. The decadal decrease in precipitation in northern China is mainly a result of the decrease in light rainfall; the change in moderate and heavy rainfall is not significant in this area (Fig. 2c).

    Figure 2.  (a) Distribution of stations in the observational dataset. The green, red, black, and blue dots represent the sub-regions of western, northern, northeastern, and southern China, respectively. Time series of the area-averaged total summer precipitation (mm) based on observations over (b) southern and (c) northern China. The black line is total rainfall (left-hand y axis), the red line is heavy rainfall (left-hand y axis), the blue line is moderate rainfall (left-hand y axis), and the orange line is light rainfall (right-hand y axis). The two black horizontal bars indicate the PD (1994–2011) and early period (1964–1981) rainfall.

    Figure 3 shows the spatial distribution of the decadal changes in total summer precipitation, the number of dry days, and the contributions of heavy, moderate, and light rainfall in China across the mid-1990s in the observational dataset. Precipitation increased in southern China and decreased in northern China. This pattern is named as SFND pattern across the mid-1990s (Fig. 3a). The spatial distribution of the number of dry days over northern and southwestern China in Fig. 3b is opposite to that of total precipitation in Fig. 3a. The change in the number of dry days over southern China contributes to the change in the total summer precipitation in the mid-1990s (Fig. 3b).

    Figure 3.  Spatial patterns of the differences in precipitation between the PD (1994–2011) and the early period (1964–1981) in summer. (a) Total precipitation (mm), (b) number of dry days (day), and contributions (mm) of (c) heavy, (d) moderate, and (e) light rainfall in the observational dataset. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    According to the spatial distribution of the decadal variations in the three types of precipitation, heavy rainfall in China increases except for some regions of northern and western China, and heavy rainfall in southern China increases greatly, similar to the spatial distribution of the total precipitation (Fig. 3c). The changes in moderate rainfall show a decrease in most of China, with a weak increase over the mid to lower reaches of the Yangtze River, the eastern part of southern China (south of 25°N and east of 108°E), the southern flank of the Tibetan Plateau, and the western part of Xinjiang (Fig. 3d). A significant decrease in light rainfall is seen in most of China, especially in northeastern China and the region between the Yangtze River and Yellow River (Fig. 3e). These results show that the decadal increase in summer precipitation over southern China is caused by the increase in heavy and moderate rainfall, whereas the decadal decrease in precipitation over northern China in the mid-1990s is caused by the decrease in moderate and light rainfall.

    Figure 4 shows the spatial pattern of the decadal variations in the frequency and intensity of three types of precipitation over China in the mid-1990s in the observational dataset. The main characteristics are that the frequency of heavy rainfall increases and the frequency of light rainfall decreases over most of China (Figs. 4a, e). The frequency of moderate rainfall increases in southern China, the western part of Xinjiang, and most part of Tibetan Plateau, whereas it decreases in northern, northeastern China, and the region between 100° and 110°E (Fig. 4c). The intensity of heavy rainfall increases in the southern part of southern China and the eastern part of Yellow–Huai River and northeastern China, and decreases in most other areas (Fig. 4b). The intensity of moderate rainfall shows little change except in the central part of eastern China (Fig. 4d). The variation in the intensity of light rainfall in China is very weak (Fig. 4f).

    Figure 4.  Spatial patterns of the differences in summer precipitation between the PD (1994–2011) and the early period (1964–1981) in the observational dataset. Frequency (number of days) of (a) heavy, (c) moderate, and (e) light rainfall and intensity (mm day−1) of (b) heavy, (d) moderate, and (f) light rainfall. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    These results show that the frequency and intensity of the three types of precipitation vary in different regions of China. The similarity between the frequency distribution of the three types of precipitation and the contribution of different kinds of precipitation to summer precipitation shows that the changes in frequency of the three types of precipitation dominate the overall change in summer precipitation. The increase of total rainfall is mainly due to the frequency increase of heavy and moderate rainfall over southern China. By contrast, the main reason for the decrease of summer rainfall over northern China is the decrease in the frequency of moderate and light rainfall.

    These observational analyses show the changes in the three types of precipitation over China with respect to their frequency, intensity, and their contributions to the change in the summer seasonal mean precipitation over different regions of China across the mid-1990s. The increasing frequency of heavy and moderate rainfall is the main reason for the increase of precipitation over southern China. The main reason for the decrease of precipitation in northern China is the decrease of the frequency of moderate and light rainfall. To determine the driving factors for these decadal changes in precipitation over China, we carried out a series of numerical experiments to solve this question.

3.   Model, experimental design, and model climatology
  • 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.

    AbbreviationExperimentOceanRadiative forcing
    R0Relaxation runRelax to PD mean three-dimensional (3D) ocean temperature and salinity to diagnose climatological temperature and salinity tendenciesRelax to PD GHG over PD and AA emissions over 1994–2010 with GHG and AA after 2006 from RCP4.5 scenario
    CEPEarly periodClimatological temperature and salinity flux tendencies from relaxation runEP mean GHG and EP mean AA emissions
    CPDPD with GHG and AA forcingPD mean GHG and PD mean AA emissions
    CPDGHGPD with GHG forcingPD mean GHG and EP mean AA emissions
    CPDAAPD with AA forcingEP 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. 1cf). 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.

4.   Model simulated responses to different anthropogenic forcings
  • Figure 5 shows the spatial patterns of changes in the total summer precipitation in response to ALL forcing, GHG forcing, and AA forcing. By ALL forcing, the total precipitation shows a + − + pattern from north to south over China east of 100°E. Precipitation increases over southern and northeastern China, but decreases over northern and most parts of southwestern and northwestern China, which is similar to the variability of precipitation calculated by the observational dataset. Through comparison, it is found that the increase of precipitation in southern and northeastern China is mainly caused by greenhouse gas emissions, while the decrease of precipitation in northern China and most parts of southwestern and northwestern China is mainly caused by AA.

    Figure 5.  The changes of the total summer precipitation (mm) in response to (a) ALL forcing, (b) GHG forcing, and (c) AA forcing. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Figure 6 shows the spatial patterns of changes in the contributions from heavy, moderate, and light rainfall in response to ALL forcing. The increase in heavy rainfall is the main reason for the increase in summer total precipitation in southern China in the ALL forcing experiment (Fig. 6a), which is consistent with the observational dataset (Fig. 3c). However, the region in which precipitation and the contribution of heavy rainfall increase simulated by the model is located over southeastern China and there is no clear northward expansion. The decrease in heavy, moderate, and light rainfall over northern China leads to the decrease in the total summer precipitation, consistent with the observational dataset.

    Figure 6.  Model simulated changes in (a) heavy rainfall, (b) moderate rainfall, and (c) light rainfall (mm) in response to ALL forcing (CPD − CEP). The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Because the variation in heavy rainfall is the main contributor to the change in total precipitation in summer, Fig. 7 shows the changes in the frequency and intensity of heavy rainfall in the ALL forcing experiment. In the ALL forcing experiment, the principal features of the changes in heavy precipitation are that the frequency increases significantly over southern and northeastern China, and most of the area west of 100°E, but decreases over northern China (Fig. 7a). These main features have some spatial similarities with the observed changes (Fig. 4a), although the spatial extent of the decrease in frequency of heavy rainfall over northern China is larger than in the observational dataset. The change of intensity of heavy precipitation in response to changes in ALL forcing (Fig. 7b) shows a + − + pattern from northern China to southern China, which is consistent with the observational datasets (Fig. 4b). The changes of heavy precipitation are more similar to the spatial variations in the changes in frequency than in the changes in intensity, indicating a dominant role of the changes in frequency, consistent with the observational dataset.

    Figure 7.  Model simulated changes in (a) frequency (number of days) and (b) intensity (mm day−1) of heavy rainfall in response to changes in ALL forcing. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Separate forcing experiments suggested that changes in the concentration of GHG emissions increase the frequency of heavy rainfall over almost all regions of China, especially over southern and northeastern China, whereas changes in AA play a dominant part in reducing the frequency of heavy rainfall over northern China (Figs. 8a, b). The variation in intensity of heavy rainfall in response to GHG forcing (Fig. 8c) is similar to that in the ALL forcing experiment (Fig. 7b), especially the increased intensity over the eastern part of northern and northeastern China and the decreased intensity over southern China. The results indicate that the dominant contribution of anthropogenic changes to changes in summer precipitation is mainly realized by the changes in the frequency of heavy rainfall. The increase in the concentration of GHG plays an important part in the increase in summer precipitation over southern and northeastern China, which is mainly caused by the increase in the frequency of heavy rainfall. The changes in AA are important in the decrease in precipitation over northern China, which is mainly due to the decrease in the frequency of heavy rainfall (Fig. 8).

    Figure 8.  Model simulated changes in frequency (number of days) of heavy rainfall in response to changes in (a) GHG forcing and (b) AA forcing. Model simulated changes in intensity (mm day−1) of heavy rainfall in response to changes in (c) GHG forcing and (d) AA forcing. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

  • Based on the unique characteristics of the climate in China, we studied the decadal changes in precipitation in four sub-regions of China: northern China (35°–45°N, 105°–120°E), northeastern China (north of 40°N and east of 120°E), southern China (20°–35°N, 105°–120°E), and western China (west of 105°E). Figure 2a shows the distribution of the stations over the four sub-regions. Figure 9 shows the area-averaged changes in the frequency of the three types of precipitation over the four sub-regions for both the observational dataset and the model experiments. Besides, the change in frequency of heavy rainfall in northern China, moderate rainfall in southern China, and light rainfall in northeastern China, the changes in the three types of precipitation in response to the changes in ALL forcing simulated by the model are consistent with the observational dataset. The simulated increases in the frequency of heavy precipitation by ALL forcing averaged over southern, northeastern, and western China are similar to the observed changes, but the increases in frequency over southern and western China are weaker than the observed changes (Fig. 9a). Changes in GHG emissions play a leading part in the changes in frequency averaged over southern, northeastern, and western China. The changes in the frequency of moderate rainfall averaged over northern, northeastern, and western China in the ALL forcing experiment are close to those in the observations (Fig. 9b). Changes in AA play a key part in the changes in the frequency of moderate rainfall over northern and northeastern China. The simulated changes in the frequency of light rainfall averaged over northern, southern, and western China in the ALL forcing experiment are close to those in the observational dataset (Fig. 9c). The variations in light rainfall over southern, northern, and western China are clearly influenced by the changes in GHG emissions.

    Figure 9.  Area-averaged changes in frequency (event yr−1) of (a) heavy rainfall, (b) moderate rainfall, and (c) light rainfall over southern (SC), northern (NC), northeastern (NEC), and western China (WC) in the observational dataset (orange bars) and the simulations forced by ALL forcing (dark blue bars), GHG forcing (blue bars), and AA forcing (light blue bars).

    Figure 10 shows the area-averaged changes in intensity of the three types of precipitation over the four sub-regions for both the observational dataset and the model experiments. For heavy rainfall, as presented in Fig. 10a, the observed decreases in the intensity of precipitation averaged over southern China are simulated by the ALL forcing, but the change is underestimated. The changes in the concentration of GHGs explain the response in the simulated changes of heavy precipitation over southern and northeastern China, indicating the predominant role of changes in GHG emissions in influencing the intensity of heavy rainfall. For moderate rainfall, the changes in intensity averaged over northern, southern, and western China in the ALL forcing experiment are close to those in the observational dataset (Fig. 10b). Changes in AA play a key part in causing the changes in the intensity of moderate rainfall over southern, northern, and western China. For light rainfall, the simulated changes in intensity averaged over western China in the ALL forcing experiment are close to those in the observational dataset, although the simulated changes in intensity over western China are clearly overestimated. The changes in light rainfall over western China are significantly influenced by the changes in GHG concentrations, indicating the predominant role of GHG emissions in affecting the intensity of light rainfall (Fig. 10c).

    Figure 10.  As in Fig. 9, but for intensity (mm day−1).

    The simulated changes in the frequency of different types of precipitation are more consistent with those in the observational dataset than the simulated changes in intensity. The model simulations also show that changes in the frequency of different types of precipitation affect the contribution of the different types of precipitation to the changes in the total summer precipitation, in agreement with the observational database.

5.   Physical processes responsible for the simulated decadal changes of precipitation
  • First, we present the difference of the 850-hPa water vapor flux divergence and water vapor flux between CPD and CEP experiments in summer by the different forcings. During summer, the water vapor flux convergence in response to ALL forcing appears in most areas to the east of 110°E and to the south of the Yangtze River, as well as northeastern China. The warm and southwesterly flow transports moisture to the above two regions and it is beneficial to the occurrence of precipitation in the above two areas. Over northern and southwestern China, water vapor flux divergence and the implicit water vapor flux transport are not conductive to the occurrence of precipitation (Fig. 11a). From the pattern by GHG forcing, we can see that the water vapor flux convergence appears in southern and northeastern China. The water vapor flux in the above regions is significantly higher than that in ALL forcing. This distribution is also conductive to precipitation in southern and northeastern China (Fig. 11b). As far as the result of AA forcing is concerned (Fig. 11c), the obvious water vapor flux convergence appears in the southeastern China only and the southwesterly water vapor transport is also significantly weakened. In addition, the weak water vapor flux divergence is located in southwestern China, eastern part of northern China, and Yellow–Huai River. Under the control of weakened southwesterly winds and 850-hPa divergence, precipitation decreases over northern and southwestern China (Fig. 5c).

    Figure 11.  The difference of 850-hPa water vapor flux divergence (× 10−9 kg cm−2 s−1 hPa−1) and water vapor flux (kg cm−1 s−1 hPa−1) between CPD and CEP experiments in JJA in response to (a) ALL forcing, (b) GHG forcing, and (c) AA forcing. The grids highlight regions where the differences are statistically significant at the 90% confidence level using a two-tailed Student’s t test.

    Figure 12 shows the difference of the vertical velocity and air temperature between CPD and CEP experiments in JJA in response to ALL forcing, GHG forcing, and AA forcing. In response to ALL forcing (Fig. 12a), the air temperature warms over troposphere between 0° and 50°N, corresponding to ascent between 20° and 30°N and descent between 30° and 40°N. In response to GHG forcing (Fig. 12b), the rise of the air temperature between 0° and 40°N is especially evident. The ascending movement decreases between 20° and 30°N and increases between 30° and 40°N. In response to AA forcing (Fig. 12c), the tropospheric temperature decreases obviously, and the pattern of vertical velocity is similar to that by ALL forcing.

    Figure 12.  Vertical velocity (shading; 10−3 hPa s−1) and surface air temperature (contour; K) difference between CPD and CEP experiments in JJA in response to (a) ALL forcing, (b) GHG forcing, and (c) AA forcing.

6.   Conclusions
  • We determined the decadal changes in the frequency and intensity of three types of summer precipitation (heavy, moderate, and light rainfall) across the mid-1990s based on an observational dataset. A set of numerical time-slice experiments was carried out using an atmosphere–ocean-mixed-layer coupled model to assess the impact of human activities, including changes in GHG concentrations and AA emissions, on the decadal changes of heavy rainfall. Our main conclusions are as follows.

    The analyses of the observed precipitation show increases over southern China, but decreases over northern and southwestern China from the early period of 1964–1981 to the PD period of 1994–2011. The decadal increase in summer precipitation over southern China is caused by the increase in heavy and moderate rainfall, whereas the decadal decrease in precipitation over northern China in the mid-1990s is caused by the decrease in moderate and light rainfall. The main reason for the decrease in summer precipitation over northern China is the decrease in the frequency of moderate and light rainfall. The increases in frequency of heavy and moderate rainfall over southern China are the main causes of the increases in total precipitation.

    Numerical model experiments show that the changes in AA emissions have a dominant role in the frequency of heavy rainfall over northern China and that the response to GHG forcing is more significant for the frequency of heavy precipitation over southern and northeastern China. The increase of precipitation frequency forced by greenhouse gases is the main reason of increasing precipitation over southern and northeastern China, while the decrease of frequency caused by AA induces the decreasing precipitation over northern China.

    By the analysis of preliminary physical mechanism, we found that the water vapor flux convergence strengthens in southern and northeastern China by GHG forcing, and the water vapor flux in the above regions enhances too. This distribution is also conducive to precipitation in southern and northeastern China. From the atmospheric circulation of AA forcing, we can find that the obvious water vapor flux convergence appears over southeastern China only and the southwesterly water vapor transport is also significantly weakened. In addition, the weak water vapor flux divergence is located in southwestern China, eastern part of northern China, and Yellow–Huai River. Under the control of weakened southwesterly winds and 850-hPa divergence, precipitation decreases over northern and southwestern China.

    This paper mainly studies the individual roles of GHG concentrations and AA emissions in the decadal changes of the three types of summer precipitation over China. Based on the change of total precipitation, a preliminary physical mechanism analysis has been performed. How-ever, the causes for the changes in precipitation frequency and intensity still need a further investigation in future.

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