Impact of Anthropogenic Aerosols on Summer Precipitation in the Beijing-Tianjin-Hebei Urban Agglomeration in China: Regional Climate Modeling Using WRF-Chem

The Beijing-Tianjin-Hebei urban agglomeration is located on the North China Plain, and includes several megacities with tens of millions of inhabitants. With its rapid urban expansion and industrial development, large amounts of anthropogenic aerosols and their precursors have been emitted into the atmosphere over the past several decades, causing the area to be one of the most heavily polluted regions in the world (Duan et al., 2004; Chan and Yao, 2008). Many works have reported that urban and industrial air pollution has the potential to change rainfall by modulating solar radiation processes and acting as cloud condensation nuclei in cloud systems in various climate regimes (Rosenfeld, 2000; Ramanathan et al., 2001; Rosenfeld et al., 2007). Within the East Asian monsoon marginal belt, urban flooding and severe water shortages are becoming major environmental disasters for the Beijing-Tianjin-Hebei urban agglomeration. Understanding responses of rainfall to anthropogenic aerosols and related physical processes are particularly critical to sustainable development in this region (e.g., freshwater management and urban design planning).

Rainfall modification over major metropolitan areas has been extensively studied. Most studies have highlighted the effects of urban land-use on rainfall anomalies (Shepherd and Burian, 2003; Shepherd, 2005; Shem and Shepherd, 2009; Niyogi et al., 2011). Besides the effects of urban land-use, urban precipitation patterns can also be modified by anthropogenic aerosols. Anthropogenic aerosols reflect and scatter solar radiation, altering the energy budget and ultimately cooling the climate system (Kaufman et al., 2002; Andreae et al., 2005). Depending on chemical composition (e.g., elemental carbon), they can absorb sunlight, further reducing solar radiation that reaches the land surface and heating the atmosphere. The asymmetry of temperature changes at the surface and in the atmosphere increases atmospheric stability and impedes convective activity, even rainfall. Serving as cloud condensation nuclei (CCN), aerosols increase nuclei number concentrations, modify the cloud drop size spectrum, and inhibit collision/coalescence processes (Rosenfeld, 1999). On the other hand, studies have found that giant CCN over urban areas could increase the cloud droplet effective radius and enhance rain formation (van den Heever and Cotton, 2007). Numerous works have shown evidence that when the convective cloud base is warm and low, aerosols from pollution could delay warm rain formation, prevent the decrease in vertical velocity caused by the falling raindrops, and increase water for conversion into ice hydrometeors (Li et al., 2011). This would release more latent heat and further invigorate convective systems (Khain et al., 2005; Rosenfeld et al., 2008).

As the main source of anthropogenic aerosols, urban areas provide an ideal setting for studies on aerosol-induced rainfall modification. In fact, many recent studies have attempted to examine the connections between variation in aerosol concentrations and changes in cloud properties and precipitation over urban areas. In a study carried out in metropolitan Atlanta, (Lacke et al., 2009) found that instability is greater and mixing layers shallower on days with high aerosol concentrations, resulting in greater precipitation amounts in most parts of the region. Although observational analyses have revealed some evidence of aerosol-induced precipitation changes, the physical mechanisms pertaining to the modification of regional rainfall by aerosols over urban areas remain elusive. Numerical modeling is a useful tool for revealing the physical processes involved in the interactions among aerosols, clouds and rainfall. Through the use of a cloud-resolving RAMS, (van den Heever and Cotton, 2007) found that urban-forced convergence downwind of a city was influenced by the presence of greater aerosol concentrations. (Wang et al., 2011) employed the cloud-resolving WRF model with a two-moment bulk microphysical scheme to simulate a mesoscale convective system in the Guangzhou megacity area, and found that precipitation and a lightning potential index increased by 16% and 50%, respectively, under the polluted aerosol conditions. Through numerical experiments, (Qian et al., 2014) investigated the local radiative forcing of black carbon in snow over Northern China. Using the WRF model coupled with a chemistry component, and a snow/ice/aerosol radiative model, (Zhao et al., 2014) simulated the radiative forcing of black carbon and dust in seasonal snow over North China. Using the WRF model coupled with spectral-bin microphysics, (Fan et al., 2012) examined the aerosol indirect effects on clouds and precipitation of the warm and cold seasons in Southeast China. A comprehensive review of modeling studies on the effects of aerosols on precipitation was presented by (Khain, 2009). However, most previous studies used only a single rainfall event to investigate the responses of precipitation to aerosols, limiting the universality of their conclusions. Therefore, further understanding of the physical processes controlling the impacts of anthropogenic aerosols on urban precipitation with numerous rainfall events is critical.

The objective of the present work is to investigate the responses of urban summer precipitation to anthropogenic aerosols over the Beijing-Tianjin-Hebei urban agglomeration and understand the related dominant mechanisms. The paper is organized as follows: The model, experimental design, and emission data are described in section 2. The main results are presented and discussed in section 3, followed by conclusion and implications of the findings in section 4.

The model used in this study is the WRF model coupled with chemistry (WRF-Chem), version 3.5.1 (Grell et al., 2005; Fast et al., 2006). WRF-Chem treats emissions, transport, horizontal and vertical mixing, transformation of trace gases and particulates, and dry and wet deposition simultaneously with meteorology. It parameterizes the interactions among aerosols, radiation processes, and cloud microphysics, considering direct, semi-direct and indirect effects of aerosols, as described in (Fast et al., 2006). WRF-Chem has been widely applied in weather and air quality forecasting, and regional climate studies, and has shown satisfying simulation skill (McKeen et al., 2007; Fast et al., 2009; Qian et al., 2009a; Zhang et al., 2009b; Zhang et al., 2009a; Wang et al., 2010; Tuccella et al., 2012).

The WRF-Chem physical packages used in the present study included the new version of the RRTM (Iacono et al., 2008), Lin cloud microphysics scheme (Lin et al., 1983; Chen and Sun, 2002), new Grell cumulus scheme (Grell and Dèvènyi, 2002), Mellor-Yamada-Janjić PBL scheme (Mellor and Yamada, 1982; Janjić, 1994), and Noah land surface scheme (Chen and Dudhia, 2001) coupled with a single-layer urban canopy model (Kusaka et al., 2001). In WRF-Chem, the Lin cloud microphysics scheme was added with a prognostic treatment of cloud droplet number based on aerosol number concentration, which enabled WRF-Chem to simulate aerosol indirect effects. The parameterizations of (Liu et al., 2005) were introduced to enable the auto-conversion from cloud droplets to rain droplets based on droplet number concentrations. By turning on the option of prognostic number density, we enabled the Lin scheme to be a two-moment cloud microphysics scheme, containing ice, snow and graupel processes, which may be suitable for the high-resolution simulations of precipitation produced by stratiform clouds and convective clouds.

Figure 1.  (a) WRF-Chem configuration for the three nested domains. Shadings represent terrain heights (units: m) and the innermost domain encompasses the Beijing-Tianjin-Hebei urban agglomeration. (b) Default MODIS-based land-use classification contained in WRF-Chem for the innermost domain (D3). Red patches denote urbanized areas.

The chemistry schemes used in the present study included the second generation Regional Acid Deposition Model gas phase chemical mechanism (Stockwell et al., 1990) and the Modal Aerosol Dynamics model for Europe (MADE) aerosol dynamic module (Ackermann et al., 1998; Schell et al., 2001). The MADE aerosol module uses a modal approach with three modes (Aitken, accumulation, and coarse modes, with assumption of a log-normal size distribution within each mode) to describe particulate size distributions. This aerosol module requires less computational resource than the sectional approach that discretizes the aerosol size distribution into many bins. Cloud chemistry and aerosol wet scavenging were enabled during the simulations. All these meteorology and chemistry options were identical for all domains.

To elucidate the effects of anthropogenic aerosols on urban summer rainfall, we conducted two sensitivity experiments with different emission scenarios: an absolutely clean case (C-case) and recently polluted case (P-case). In C-case, anthropogenic gases and aerosol emissions were turned off. In P-case, the anthropogenic emissions of all the domains were updated using the corresponding resolution inventory dataset. For the innermost domain, a high-resolution emissions inventory dataset was used, which will be discussed in detail in the next section. To refine the temporal resolution of the emissions inventory, WRF-Chem is designed to create two emissions files that contain hourly emissions from 0000 LST (local standard time) to 1100 LST, and 1200 LST to 2300 LST. This emissions inventory was refined to be representative of a typical summer polluted day in the Beijing-Tianjin-Hebei urban agglomeration, and provided the regional aerosol emissions on each day during the simulations.

Three one-way nested domains were configured. As shown in Fig. 1a, the outer domain (D1) covered most of eastern China (21^°-50^°N, 101^°-129^°E), the finer domain (D2) provided full coverage over North China, and the innermost domain (D3) centered over the Beijing-Tianjin-Hebei urban agglomeration. The horizontal grids of the three domains were 97× 112, 136× 163, and 148× 151, with horizontal grid spacing of 30 km, 10 km, and 3.3 km, respectively. The default MODIS-based land-use classification contained in WRF-Chem for the innermost domain (D3) is denoted in Fig. 1b. The model had 30 vertical levels, with an uppermost pressure of 50 hPa. As this study focuses on the impact of anthropogenic aerosols on large-scale precipitation, not the boundary layer processes, the setting of the vertical levels should have little influence on the main results. Since we investigated the impacts of anthropogenic aerosols on summer precipitation, concentrating on July, numerical simulations for the July of 2008 were conducted. Simulations began from 29 June and ended on 1 August, and the first two days in June were used for model spin-up, which could largely eliminate the bias caused by uncertainties in the initial conditions. Initial and boundary meteorological conditions were provided by the six-hourly NCEP-FNL dataset with 1.0^°× 1.0^° grids. Sea surface and deep soil temperatures were updated with the reanalysis data during the simulations.

A high-quality emissions inventory is fundamental for aerosol modeling studies. To accurately describe spatiotemporal distributions of aerosol particulates in urban areas, an anthropogenic emissions inventory dataset with very high spatiotemporal resolution is required. A number of representative global and regional inventory datasets have been developed. However, the spatiotemporal resolutions of these datasets are too coarse to meet the requirements of research on the effects of aerosols at the urban scale.

Owing to the Beijing 2008 Summer Olympic Games, a more comprehensive environmental measurement network was established to monitor the air quality continuously. Researchers surveyed the emissions intensity for all types of atmospheric pollution in Beijing and the surrounding provinces, including Tianjin and Hebei, and developed an emissions inventory of sources such as power plants, transportation, and industrial energy consumption. Two categories of datasets were considered for the establishment of the emissions inventory. One was the regional emissions inventory from TRACE_P (Streets et al., 2003) for the year 2002 and INTEX-B (Zhang et al., 2009a) for the year 2006. Another was the local emissions dataset covering Beijing and its surrounding provinces, which integrated the power plant emissions inventory in North China, the major industrial emissions in Tianjin and Hebei, and detailed local emissions (domestic, transportation and industry) in Beijing. This emissions dataset has been used in (Wu et al., 2011) and (Wu et al., 2014) for air quality studies and operational forecasting in Beijing. The investigators further refined the size distributions and compositions of all aerosol species. Wu et al. (2012, 2014) indicated that model performance in simulating PM₁₀ was improved significantly after emissions processes were updated by this emissions inventory. We applied this database as an anthropogenic emissions inventory to represent pollution sources over the Beijing-Tianjin-Hebei metropolis. Spatial distributions of daily mean emissions intensities of the major anthropogenic pollutants (gases: SO₂, NO₂, NO, CO and NH₃; aerosols: elemental carbon, sulfate, nitrates, PM_2.5 and PM₁₀) are displayed in Fig. 2. It can be seen that the gases and aerosols concentrated over the major urban areas and main roads. Specifically, the concentrations of PM_2.5 and PM₁₀ were extremely high over the metropolitan areas, like Beijing.

Station-observed rainfall data from the China Meteorological Administration were used to validate model performance (Fig. 3a). Precipitation data from the chosen meteorological stations had no missing values and passed strict quality control. As shown in Fig. 3b, WRF-Chem generally captured the regional-scale characteristics of precipitation in July 2008. However, the model tended to overestimate the amount of precipitation, and the simulation skill in C-case was better than that in P-case. The spatial correlation between C-case (P-case) simulated and observed monthly mean precipitation was 0.53 (0.68). Model biases of rainfall may have resulted from inaccurate initial and boundary conditions and the performance of certain parameterization schemes (e.g., cumulus and cloud microphysics). Given that we computed differences of simulation results in sensitivity experiments, the model systematic bias should have been cancelled out, having little effect on the applicability of our conclusion.

Figure 4a displays the difference in mean precipitation patterns simulated by C-case and P-case in the Beijing-Tianjin-Hebei urban agglomeration. Anthropogenic aerosols enhanced rainfall over most parts of the urban agglomeration (D3). Figure 4b depicts the diurnal variation of the domain-averaged hourly rainfall rate over D3 from the simulation results of the two cases. Due to the effects of anthropogenic aerosols, hourly precipitation declined slightly around noon but noticeably increased in the afternoon and at nighttime. The most pronounced change was at 0000 LST, reaching nearly 50% of the simulated precipitation in C-case.

Figure 2.  Daily mean emissions of chemical gases(SO₂, NO₂, NO, CO, and NH₃) and aerosols (particulate elemental carbon: PEC;PSO₄nitrates: PNO₃, PM_2.5 and PM₁₀). Units for the gases are mole km^-2h^-1, and for the aerosols μg m$^-2$s$^-1$

Figure 3.  (a) Geographical distribution of meteorological stations over the Beijing-Tianjin-Hebei urban agglomeration. (b) Quantile-quantile plot: blue (red) dots indicate comparison between C-case (P-case) simulated and observed monthly mean precipitation in July 2008. The three lines indicate $y=0.5x$, $y=x$, and $y=2x$, respectively.

Figure 4.  (a) Change (P-case minus C-case) of mean daily precipitation pattern caused by anthropogenic aerosols (mm d$^-1$). (b) Diurnal variation of rainfall simulated by C-case (blue line) and P-case (red line). (c) Percentages of grid areas in five precipitation categories over the entire domain simulated by C-case (blue bars) and P-case (red bars). (d) Percentages of rainfall amount in five precipitation categories simulated by C-case (blue bars) and P-case (red bars).

Figure 5.  Averaged all-sky shortwave (SW, left), longwave (LW, middle) and total (right) radiative forcing induced by anthropogenic aerosols over the Beijing-Tianjin-Hebei urban agglomeration. "TOA" represents aerosol radiative forcing at the top of the atmosphere, with upward direction indicated by positive values; "ATM" represents aerosol radiative forcing in the atmosphere, with warming indicated by positive values; "LAND" represents aerosol radiative forcing at the surface with positive values signifying more radiation received at the land surface; and "Total" represents the sum of aerosol SW and LW radiative forcing. Units are W m$^-2$.

To further examine the responses of different types of summer precipitation to the anthropogenic aerosols, we classified the model grids into five categories based on monthly averaged daily rainfall amount (extreme rain: >10 mm d^-1; heavy rain: 5-10 mm d^-1; moderate rain: 2-5 mm d^-1; light rain: 1-2 mm d^-1; and drizzle rain: <1 mm d^-1). Given that the mean rainfall amount for each grid is calculated for the entire simulation period, including many no-rain days, our classification scheme is reasonable and comparable with other studies (Qian et al., 2007; Wang et al., 2011). Figure 4c shows the percentages of grid areas at the five precipitation levels simulated in the two cases. The results reveal that the anthropogenic aerosols tended to cause light or moderate rain to fall on smaller geographic areas. Figure 4d displays the ratios of precipitation amount under different categories over the total precipitation amount simulated by the two cases. The results show that the light and moderate rain decreased in P-case, but rainfall magnitudes increased for the extreme rain. This change implies that the anthropogenic aerosols tended to shift precipitation from lower to higher amounts. Based on observational analysis and numerical simulation results, (Qian et al., 2009b) also suggested that significantly increased aerosol concentrations caused by air pollution were likely to have decreased light rain events in China over the past 50 years. This finding is highly consistent with the simulated responses of summer precipitation to anthropogenic aerosols in the present study.

Since the climate system, including the hydrological cycle, is primarily fueled by radiative energy, investigation of aerosol-induced radiative forcing is essential. Figure 5 shows the spatial distributions of differences between the two cases in simulated shortwave (SW), longwave (LW) and net radiation (SW+LW) at the TOA, in the atmospheric column (ATM), and at the land surface (LAND). Because of the higher albedo of the earth and increased cloud fraction caused by aerosols, more SW radiation was reflected back to space and the domain-averaged SW radiative forcing was negative at the TOA (-9.1 W m^-2). The LW radiative forcing at the TOA was positive or close to zero (+2.5 W m^-2). The net radiative forcing by anthropogenic aerosols at the TOA was negative (-6.6 W m^-2). In the ATM, a portion of SW radiation was absorbed by certain types of anthropogenic aerosols (e.g., elemental carbon), producing a positive SW radiative forcing (+9.0 W m^-2) and warming of the atmosphere. A less pronounced SW radiative forcing in the ATM was found in the northern mountain area, owing to a weaker aerosol emissions intensity there (Fig. 2). The aerosols increased atmospheric outgoing LW radiation in excess of that which they absorbed, resulting in a negative LW radiation forcing in the ATM (-2.9 W m^-2). Note that the direct effect of aerosols on LW radiation should be negligible and the "radiative forcing" referred to here is actually the radiative response to aerosol effects. Since the absolute value of aerosol SW radiation forcing was higher than LW in the ATM, the atmospheric column was warmed by the net radiative forcing of aerosols, with an area-average value of +6.1 W m^-2. As for LAND, downward SW radiation was reduced by the absorption and scattering of anthropogenic aerosols, and the increased cloud amount (the cloud fraction and cloud liquid water path) (-18.1 W m^-2). LW radiation emitted by the land surface was trapped and returned by clouds and aerosols (+5.4 W m^-2). The net radiative forcing of anthropogenic aerosols at LAND was negative (-12.7 W m^-2), resulting in cooling of that surface.

The thermodynamic effects of surface sensible heat flux and direct moisture supply from surface latent heat flux are critical for the initiation and development of convection (Orville et al., 1981). We calculated the changes of surface sensible and latent heat fluxes induced by anthropogenic aerosols (figure not shown). It was found that there was a substantial decrease in sensible heat flux over the urban areas. In the suburban and rural areas, sensible heat flux was also inhibited but with smaller magnitudes. The decrease in sensible heat flux can be attributed to the decreased surface temperature (figure not shown). Surface latent heat flux also greatly decreased, particularly over the southern plain. A small increase in latent heat flux in central urban areas may be caused by the increase in precipitation.

By analyzing the simulation results for the physical mechanisms affecting precipitation in Beijing, (Miao et al., 2011) highlighted the role of thermal transport (including surface sensible and latent heat) in changes of urban rainfall amount, which is more critical than momentum transport. However, in this study, aerosol-induced changes in thermal heating of the surface appear to contradict the simulated pattern of the rainfall response. Therefore, we cautiously infer that the physical mechanisms dominating the summer precipitation modification may not be closely or directly associated with radiative forcing and thermal heating changes caused by anthropogenic aerosols.

Since convective rainfall dominates summer precipitation in this metropolitan region, other related thermodynamic variables require further investigation to unravel potential causes for the precipitation change. Vertical profiles of vertical velocity, PV and equivalent potential temperature (EPT) simulated by the two cases are shown in Fig. 6. As shown in Fig. 6a, vertical motions are enhanced due to the effects of anthropogenic aerosols. In P-case, anthropogenic aerosols generated more positive PV in the lower and middle atmosphere, also implying stronger upward motions, which tended to enhance precipitation. The domain-averaged EPT increased in the lower atmosphere but decreased above, which is indicative of a more unstable atmosphere.

Figure 6.  Profiles of (a) vertical velocity, (b) potential vorticity, and (c) equivalent potential temperature averaged over the entire area simulated by C-case (blue line) and P-case (red line). Units for vertical velocity are mm s$^-1$, for potential vorticity PVU (PV units, 10$^-6$ m$^-2$ s$^-1$ K kg$^-1$), and for equivalent potential temperature K.

Figure 7.  Changes (P-case minus C-case) of (a) convective available potential energy and (b) convective inhibition energy. Units are J s$^-1$.

Figure 8.  Changes in circulation and water vapor mixing ratio on the level of (a) 2 m, (b) 850 hPa, (c) 700 hPa, and (d) 500 hPa. Units for wind speed are m s$^-1$, and for water mixing ratio are g kg$^-1$.

Figure 9.  Vertical profiles of domain-averaged (a) cloud droplet number mixing ratio, and mass mixing ratios of (b) cloud water, (c) rain water, (d) ice, snow and graupel simulated in C-case (blue line) and P-case (red line).

To validate this argument and further reveal the responses of atmospheric thermodynamic conditions to the anthropogenic aerosols, the changes in CAPE (the amount of energy obtained by a parcel of air if lifted a certain distance vertically through the atmosphere) and convective inhibition energy (CIN, the amount of the energy that prevents an air parcel from rising from a certain altitude to the level of free convection) caused by anthropogenic aerosols are shown in Figs. 7a and b. CAPE increased over most areas of rainfall increase (Tianjin and southern Hebei Province) due to the effects of aerosols. CIN over these areas decreased, with less magnitude than CAPE. As CAPE is an effective indicator of atmospheric instability and is often used to predict convection, this suggested that convective strength over the urban areas was likely enhanced by the aerosols.

Changes in convective strength due to anthropogenic aerosols reflect pronounced variation in regional circulations and water vapor. Figures 8a and b show changes in lower atmosphere (10 m and 850 hPa levels) circulation and water vapor mixing ratio, induced by the anthropogenic aerosols. The simulation results indicated that wind convergence was greatly enhanced over the southern part of Beijing. Water vapor was increased in the urban areas but declined slightly in other areas, a pattern coincident with the precipitation change. This water vapor change may be caused by the convergent flow and aerosol indirect effects, which are discussed in detail below. Figures 8c and d portray circulation changes in the mid-troposphere (700 hPa and 500 hPa levels) produced by the anthropogenic aerosols. Cyclone-like wind shear was located over the urban areas. Therefore, the anthropogenic aerosols tended to strengthen the convergence zone in the region of rainfall enhancement. The redistribution of water vapor and various responses of atmospheric circulation to anthropogenic aerosols explain the pattern of rainfall change very well, but the primary reasons for the change of summer precipitation over the Beijing-Tianjin-Hebei urban agglomeration need further exploration.

To gain further insight into aerosol effects on convection, clouds and rainfall, we investigated simulated microphysical properties under the clean and polluted aerosol conditions. Additional aerosol particulates can be activated to act as condensation nuclei, which tend to increase cloud droplets under certain water vapor conditions. Figure 9a shows the vertical profiles of domain-averaged droplet number concentration simulated in the two cases. In P-case, the simulated cloud droplet number concentration was much higher than in C-case. More cloud droplets increased the cloud water mixing ratio (Fig. 9b) and slowed auto-conversion from cloud droplets to raindrops. The smaller water droplets could be lifted to higher altitudes by strong convective airflow and became frozen above the 0^°C isotherm level. As shown in Fig. 9d, the mixing ratios of cloud hydrometeors such as ice, snow and graupel were all increased, indicating that more water droplets were elevated to the freezing level. The simulation results conform to the analyses of in situ, satellite and aircraft observations (Rosenfeld and Woodley, 2003; Andreae et al., 2004). As cloud droplets were converted to ice-phase hydrometeors, greater amounts of latent heat were released and remained in the atmosphere, which caused many changes that invigorated convective systems, and rainfall rates were finally enhanced (Fig. 9c).

Figures 10a and b illustrate the temporal evolution of simulated microphysical latent heating profiles under different pollution conditions. Microphysical latent heat release related to cloud water phase transition mainly appeared at nighttime and in the afternoon, consistent with the time of the precipitation maximum during the daytime. Figure 10c shows that the difference in microphysical latent heating above the level of 700 hPa between P-case and C-case was positive, indicating that the increased condensation from water drops due to anthropogenic aerosols enhanced the latent heat release. The increase in microphysical latent heating was mainly observed at late night and in the early morning, coinciding well with the periods of rainfall enhancement (Fig. 4b). The stronger negative microphysical latent heating from the level of 900 hPa to 700 hPa may be related to the enhanced ice melt and rain evaporation. Changes in microphysical latent heating induced by aerosol indirect effects may be the leading cause of the changes in convective strength, atmospheric instability, horizontal circulation, water vapor, and ultimately summer precipitation over the Beijing-Tianjin-Hebei urban agglomeration.

Figure 10.  Temporal evolution of the microphysical latent heating profile for (a) C-case, (b) P-case, and (c) P-case minus C-case. Units are K s$^-1$.

We investigated the effects of anthropogenic aerosols on summer precipitation over the Beijing-Tianjin-Hebei urban agglomeration, based on numerical simulations with two distinct pollutant emissions scenarios. The results of sensitivity experiments revealed that anthropogenic aerosols enhanced summer rainfall in the urban areas. The domain-averaged rainfall amount increased in most of the time because of anthropogenic aerosols. Around noon, however, precipitation decreased slightly. Aerosol effects tended to shift the precipitation from light and moderate categories to extreme ones. Because of the impacts of anthropogenic aerosols, the light and moderate rainfall events were distributed over a smaller area, and the extreme rainfall events were distributed over a greater area.

Analysis of radiative forcing revealed that the aerosol effects reduced downward SW radiation, but increased downward LW radiation at the land surface. Overall, net aerosol effects on radiation forcing at the surface were negative. In the atmosphere, domain-averaged SW radiative forcing was positive, but that of LW radiation was negative. The net radiative forcing of aerosols warmed the atmosphere. Regarding the surface energy balance, the negative radiation forcing at the surface should be compensated by the decrease in surface heat fluxes. Simulation results showed that anthropogenic aerosols resulted in reduced sensible heat and latent heat fluxes at the surface. This suggests that heat and moisture fluxes from the land surface, which provide energy for the initiation and development of convection, were inhibited. All these changes enhanced atmospheric stability, and suppressed precipitation. Therefore, it was inferred that the domain-averaged rainfall increase may not be primarily caused by the changes in radiation processes and surface heat fluxes across the entire region.

To further explore the physical processes governing aerosol-related precipitation change and redistribution over the Beijing-Tianjin-Hebei urban agglomeration, we explored atmospheric variables related to convection and cloud microphysical properties. It was found that aerosol effects strongly enhanced CAPE in the areas of rainfall increase. CIN decreased over these areas, with an order of magnitude less than CAPE. This suggests that the enhancement of convective precipitation may make a greater contribution to the rainfall increase. Analysis of changes of the water vapor mixing ratio revealed that water vapor in the lower atmosphere increased over the areas of precipitation enhancement, which supported the development of convective activity. A change in mesoscale circulation in the mid-troposphere revealed strong cyclonic wind shear over the southern part of Beijing. This change was consistent with the analysis of modifications in atmospheric potential vorticity. Aerosols also enhanced ascending motion, triggering more cloud formation and convective systems. Anthropogenic aerosols modified the equivalent potential temperature, warming the lower atmosphere and cooling the upper atmosphere. Analysis of cloud microphysical properties showed that additional anthropogenic aerosols generated a larger number of smaller cloud droplets and narrower droplet spectrum width, thereby inhibiting rain formation processes. With stronger updraft strength in convection, more cloud droplets ascended above the freezing level and were transformed into ice hydrometeors. The extra latent heat released from phase transition further invigorated convection, leading to the rainfall increase over the urban areas. Under the polluted air conditions, microphysical latent heating increased, consistent with aerosols' invigoration effects. Therefore, we tentatively suggest that the aerosol indirect effect on cloud microphysical properties may well be the major driver of the simulated summer rainfall modification over the Beijing-Tianjin-Hebei region.

(Wu et al., 2013) used WRF-Chem to examine aerosol impacts on precipitation over China during the East Asian summer monsoon. Results showed that the aerosol microphysical effect induced ascent to the north (high aerosol areas) and descent to the south, leading to a precipitation shift from south to north. Their study also revealed that the aerosol-induced anomalies of precipitation were mainly contributed by the changes in vertical velocity associated with convection, while the horizontal advection of moisture played a significant role. In our study, numerical simulations also revealed aerosol-induced enhancements in vertical motion, local advection of water vapor, and convective energy, which are highly consistent with the results of (Wu et al., 2013) in northern China. It should be noted that (Wu et al., 2013) focused on the aerosol effects on summer monsoon precipitation produced by stratiform clouds and convective clouds on large scales. Our study examined the responses of summer precipitation to anthropogenic aerosols over a representative metropolis, which has important implications with respect to the verification of observational analysis on the relationship between aerosols and urban precipitation modification. (Ntelekos et al., 2009) performed numerical experiments for three intense convective storm days and for two representative aerosol conditions. They found that increasing aerosol concentrations can lead to either enhancement or suppression of precipitation. Storms developing in areas of relatively high (low) concentrations of aerosols tended to enhance (suppress) the rainfall. (Guo et al., 2014) conducted a case study of aerosol impacts on summer convective precipitation over northern China and found that the maximum rainfall rate above 30 mm h^-1 was enhanced, but that below 30 mm h^-1 was suppressed. Results from these case studies suggest that the impacts of aerosols on summer precipitation depend on the aerosol concentrations and atmospheric conditions. Our month-long simulation results with numerous rainfall events indicate the overall rainfall enhancement due to the impacts of anthropogenic aerosols. Future studies still need to employ more long-term and higher-resolution simulations to uncover the complex processes dominating the climatic impacts of anthropogenic aerosols on summer rainfall over urban areas.