1. Introduction
Anthropogenic forcings, including anthropogenic greenhouse gases (GHG) and anthropogenic aerosols (AA), play an important role in regulating the long-term trends of regional and global climate (Lau et al. 2006; Ye et al. 2013; Seo et al. 2013; Song et al. 2014; Lau and Kim 2017; Tian et al. 2018; Lin et al. 2020). GHG can warm the surface and atmosphere globally, and AA is an important driver of regional cooling (Charlson et al. 1992; Penner et al. 2001; Ramanathan et al. 2001; Ueda et al. 2006; Dong et al. 2009; Li and Ting 2017). As a result, GHG and AA change surface or atmospheric temperature on various spatial scales (Dong et al. 2009; Christidis et al. 2012; Song et al. 2014; Wang et al. 2015, 2016). To date, the effect of anthropogenic forcings on the mean temperature at seasonal or longer time scales has been extensively studied.
Thermal contrast is an essential issue in the regional climate in response to human activities. The spatial distribution of radiation forcing induced by human activities can affect the thermal contrast between mountains, land, or sea (Myhre et al. 2013). GHG concentration usually has little horizontal asymmetric, but its warming effect differs over continent and ocean, leading to the change of land–sea or mountain–plain thermal contrast (Dong et al. 2009; Liu et al. 2011). The GHG has strengthened the thermal contrast between continental East Asia and the western Pacific in past decades, which led to the enhanced intensity of the East Asia summer monsoon (EASM) (Dong et al. 2009; Bao and Zhang 2013). On the other hand, as the AA concentration is distributed more regionally than GHG, the horizontal thermal contrast caused by AA cooling can be more localized (Myhre et al. 2013). The AA emissions increased rapidly over East Asia in past decades, which may lead to a more substantial cooling effect in East Asia than in adjacent oceans (Ming and Ramaswamy 2009, 2011; Zheng et al. 2016; Tian et al. 2018; Lin et al. 2020).
The diurnal cycle of temperature, which is a key feature of regional climate, can also be changed by anthropogenic forcings. Recent detections reveal that the global mean diurnal temperature range (DTR), which is denoted by daily Tmax − Tmin, declines in past decades (Dai et al. 1999; Wei et al. 2021; Liu et al. 2022). Studies have been carried out to separate the effect of natural forcings and anthropogenic forcings such as GHG and AA. Natural forcing contributes slightly to the DTR in long-term changes (Zhou et al. 2010; Liu et al. 2022). For anthropogenic forcings, the declined annual-mean DTR due to GHG is evident in the high-latitude regions of Eurasia and North America, and regional and seasonal variations are also seen in the GHG-induced DTR trends (Dai et al. 1999; Stjern et al. 2020; Liu et al. 2022). The AA effect on DTR is much more complicated. The direct effect and indirect effect of AA can absorb or reflect solar radiation in the daytime and reduce surface DTR (Chung et al. 2005; Kinne 2019; Khatri et al. 2022), while AA emissions can also affect longwave radiation (Panicker et al. 2008; Zhou and Savijärvi 2014). Besides, the DTR trends depend on many aspects of the anthropogenic forcings, such as type of aerosols (black carbon, sulfate and sea salt; Kinne 2019; Stjern et al. 2020), aerosol emission concentration (Kinne 2019), and nonradiative feedback (e.g., surface albedo, Bowen ratio, and land cover change; González and Calbó 2013; Marvel et al. 2016; Bright et al. 2017; Chakraborty and Lee 2019; Kinne 2019; Park et al. 2020; Wei et al. 2021). Further studies on how the thermal contrast at a diurnal time scale evolves in a warming climate are critical. Detailed evaluations on the regional radiation effect of GHG and AA are key issues for understanding the response of regional climate to anthropogenic forcings.
The diurnal cycle of surface temperature is vital for driving the diurnally varying local circulations and regional climate. The heated surface in the daytime strengthens turbulent mixing in the atmospheric boundary layer (ABL), which induces a friction effect on low-level winds (Blackadar 1957). The low-level winds accelerate after the sunset when the friction effect of turbulent mixing declines. The diurnal deviation of low-level winds undergoes a clockwise rotation due to the Coriolis force (Fig. 1). It reaches a maximum southerly wind at around 0200 LST, which is regarded as the boundary layer inertial oscillation (BLO). Previous studies noted that the BLO is a key process showing the response of regional circulations over East Asia to the vertical thermal contrast between the land surface and the atmosphere in boreal summer (Du et al. 2015; Xue et al. 2018; Chen 2020). To date, it calls for further studies on how the BLO changes with the regional heating induced by human activities and affects low-level winds over East Asia.
Topography of East China (shaded; units: m) and the climatology of diurnal component of 925-hPa wind (vectors; units: m s−1) in July and August during 1960–2017 based on JRA-55. Daily mean of 925-hPa wind is removed to present the diurnal component. The diurnal variation of winds at 0200, 0800, 1400, and 2000 LST are denoted by the vectors in green, blue, yellow, and red, respectively. The solid black line represents the height of 700 m and only vectors over low-lying plains (lower than 700 m) are shown. The red box represents the region of North China and the plains are the North China plains (NCP) in this study.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
The horizontal thermal contrast over inhomogeneous underlying surfaces is another key factor regulating the diurnal variation of local circulations (Holton 1967; Bao et al. 2011; Du and Rotunno 2014, 2018). On a regional scale in North China, the mountains are heated (cooled) more than the low-lying plains at noon (midnight), leading to upslope (downslope) flows (He and Zhang 2010; Yuan et al. 2014; Pan and Chen 2019). This thermally driven circulation, also called mountain–plain solenoids (MPS), results in low-level ascent over mountains (plains) in the daytime (nighttime). The North China plains (NCP) are located between the Taihang Mountains and the Yellow Sea, with an altitude difference of more than 1000 m (Fig. 1). The MPS induces a pronounced nighttime upward motion over NCP during summertime (He and Zhang 2010; Pan and Chen 2019). On a larger scale than MPS, the heating difference between continents and adjacent oceans can induce the diurnal variation of circulation, such as land–sea breeze (LSB). The thermal contrast between continental eastern China and western North Pacific can drive a continental-scale LSB (Huang et al. 2010). The well-developed LSB at 2000 LST is featured by the anomalous southeasterly winds over NCP from June to August. Therefore, both MPS and large-scale LSB express a key response of regional circulation to the horizontal thermal contrast, but the large-scale LSB reaches its maximum intensity few hours later than regional-scale MPS, which is contributed by the delayed peak of large-scale pressure gradient and the geostrophic adjustment processes (Huang et al. 2010; Du and Rotunno 2014; Yu and Jou 2005; Yu and Lin 2017; Pan and Chen 2019). Some studies found that the horizontal thermal contrast over East Asia has been strengthened on both local and large scales (Makowski et al. 2008; Yao et al. 2019; Stjern et al. 2020). However, it is less discussed how the thermal contrast induced by anthropogenic forcings regulates the MPS and LSB in a warming climate.
Thermally driven local circulations have direct impacts on precipitation. The southerlies and rainfall over the plains usually maximize near midnight or morning, though the MPS/LSB-related peak hours are slightly earlier than the BLO-related ones. The MPS-related local circulation can intensify the upward motion over plains at 0200 LST and contributes to the eastward-moving convection systems and the late-night precipitation over eastern China during mei-yu periods (Bao et al. 2011; Bao and Zhang 2013). The LSB-related local circulation also strengthens the southeasterly flows and transports moisture into NCP at 2000 LST (Huang et al. 2010). The BLO-related nocturnal low-level southeasterlies can bring abundant warm and moist air and low-level ascents at their northern terminus, leading to an early-morning peak of precipitation (Yu et al. 2007; Yuan et al. 2010, 2013; Chen et al. 2012; Pan and Chen 2019; Zhang et al. 2019; Chen 2020). Such an enhanced southerly wind after midnight when overlying with active monsoon flows and colliding with the mei-yu front can lead to extremely heavy rainfall events (Zeng et al. 2019; Fu et al. 2019; Guan et al. 2020). The morning-peak rainfall related to MPS and LSB is strongest during summer and marches northward along with the progress of EASM rainband (Chen et al. 2021). In particular, both diurnal deviation and daily average of southerlies become most pronounced over the NCP in July and August, which is focused on in this study. At the interdecadal time scale, the EASM and related diurnal variation have declined in the late twentieth century, contributing to a reduction in precipitation amount over East Asia (G. Chen et al. 2014, 2021; Tian et al. 2018). Observations over NCP found that the precipitation increased in the evening (around 2000 LST) but reduced after midnight in past decades (Yuan et al. 2013). This paradox implies that the effects of MPS/LSB and BLO on the increased nighttime proportion of precipitations might be complicated due to their different peak hours. We should note that the diurnally varying local circulations also affect the extreme events of nighttime rainfall (M. Zhang et al. 2019; Dong and Dong 2021; Zhang et al. 2020). Further studies on how the regional circulations respond to anthropogenic forcings may improve our understanding of the possible change of extreme rainfall in the future.
Previous studies of climate change focus on a seasonal-mean time scale, and this study aims to clarify how human activities affect the diurnal variations of regional climate over NCP in past decades, focusing on: 1) How do anthropogenic forcings affect the surface temperature at diurnal time scale? 2) How do thermal contrasts regulate the long-term trend in diurnal variations of regional circulations and precipitation? The rest of this paper is presented as follows. Section 2 introduces the data used in this study. Section 3 analyzes how anthropogenic forcings induce the long-term trend in the diurnal variation of surface temperature. Section 4 reveals the physical processes of how thermal contrast regulates the long-term trend of regional circulations. Section 5 discusses the long-term trend of precipitation diurnal variation in response to regional circulations. Finally, conclusions are drawn in section 6.
2. Data and methods
In this study, we use Japanese 55-yr Reanalysis (JRA-55) data to examine the long-term trend of atmospheric circulation and surface temperature (Kobayashi et al. 2015). The JRA-55 dataset starts in 1958, which is long enough to describe the long-term circulation trend. The JRA-55 at 6-hourly intervals can capture well the diurnal cycles of winds, temperature, and humidity over East Asia (G. Chen et al. 2014, 2021). The JRA-55 data also describe the diurnal variations of precipitation relating to the regional circulations better than other reanalysis, and in good agreement with satellite observations (G. Chen et al. 2014). In particular, as JRA-55 assimilates land observation, the trends of 2-m temperature are in a good agreement with surface observation data (Morice et al. 2012; Harada et al. 2016). This study uses the atmospheric variables assimilated at the four synoptic hours (0200, 0800, 1400, and 2000 LST) on the surface or pressure levels. Their diurnal variations at given hours are obtained by removing their daily mean. Then, the diurnal variations are averaged from July to August each year, and their long-term trends are calculated by linear regression. An F test is adopted to present the statistical significance of long-term trends in this study.
We evaluate the radiation effects of human-induced GHG and AA emissions using the International Satellite Cloud Climatology Project (ISCCP) data (Jakob and Tselioudis 2003; McDonald et al. 2016). ISCCP 6-hourly data help us capture the diurnal cycle of shortwave or longwave radiation and their thermal effects on surface temperature (Wu and Chen 2021). Cloud and AOD data in ISCCP are used to explain the radiation trends. ISCCP data started in 1980, which is shorter than the atmospheric reanalysis and observation data used in this study (JRA-55). As GHG and AA concentrations have increased linearly in past decades over China (Meinshausen et al. 2011; Myhre et al. 2013; Hoesly et al. 2018), their trends in the past four decades are still reliable for analyzing the radiation effects of human activities. We estimate the trend of the diurnal variation of radiation data in ISCCP using the same method as in JRA-55 data. The radiation budget estimated in this study is the net radiation on the surface, including net surface longwave (LW) and shortwave (SW) radiation. LW and SW radiations can be divided into two components, i.e., clear-sky radiation and cloud radiative effect (CRE, total radiation minus clear-sky radiation). We also use the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), which provide radiation data in assuming clear-sky and/or no-aerosol condition, to separate the effects of AA and GHG (Gelaro et al. 2017; Randles et al. 2017). Based on MERRA-2 radiation data, the GHG radiative effect is evaluated by the trend of radiation in clear-sky no-aerosol condition. The direct radiative effect (DRE) of AA is estimated as the difference between clear-sky radiation and clear-sky no-aerosol radiation. The CRE can be evaluated by the no-aerosol radiation minus clear-sky and no-aerosol radiation, which is a more precise estimation than that in ISCCP. Note that the radiative effect of AA in this study only refers to the DRE, as this method cannot separate the indirect AA effect on cloud property and droplets.
In section 5, we estimate the diurnal cycle of precipitation using 12-h accumulated rain gauge data from 1960 to 2018 provided by the China Meteorological Data Service Center and National Meteorological Information Center (Yuan et al. 2010, 2013). Daytime precipitation is 12-h accumulated rainfall from 0800 to 2000 LST, and nighttime precipitation from 2000 to 0800 LST the next day. We use 309 rain gauges with few data missing in eastern China, and 66 of them are in the NCP (32°–40°N, 110°–120°E, with an altitude lower than 700 m). The long-term trend is defined by the linear trend from 1960 to 2018. Extreme rainfall days are the highest 5% of daily precipitation days at given sites in July to August from 1960 to 2018.
3. Thermal contrast caused by anthropogenic forcings
As the anthropogenic forcings directly change surface temperature, we first show the long-term trend of 2-m temperature in past decades (Fig. 2). NCP is featured by a cooling trend at 1400 and 2000 LST at a rate of −0.06° and −0.03°C decade−1, respectively (Figs. 2a,b). In contrast, it becomes a warming trend of 0.02°C decade−1 at 0200 and 0800 LST (Figs. 2c,d). Such a cooler day–warmer night temperature trend is thought to reduce the diurnal temperature amplitude by 0.07°C decade−1 over NCP (Fig. 2e). The spatial asymmetry of temperature trends might also lead to the changes in regional thermal contrast at different hours. Over the west highlands in China (west of the red line in Fig. 2), warming trends greater than 0.2°C decade−1 are observed at all four synoptic hours. Over North China (black box in Fig. 2a), the difference in temperature trend between the Taihang Mountains (highlands in the black box in Fig. 2a) and NCP (lowlands in the black box in Fig. 2a) is about 0.08°C decade−1 at 1400 LST (Fig. 2a), while the difference declines to 0.02°C decade−1 at 0200 LST (Fig. 2c). The local effects in warming background may lead to a relatively small temperature trend over the NCP. When the daily mean of temperature trend is removed, the DTR over the NCP (Fig. 2e) and mountain–plain thermal contrast are both statistically significant. Thus, the trends of thermal contrasts that drive diurnal variation of regional circulation are still robust.
The linear trend of diurnal 2-m temperature (units: °C decade−1) in July and August (JA) from 1960 to 2018. (a) 1400; (b) 2000; (c) 0200; (d) 0800 LST. Stippled regions are statistically significant at the 10% level using an F test. The red line denotes the altitude of 700 m. (e) Seasonal average of diurnal temperature range (DTR; solid lines; units: °C) over NCP in JA based on JRA-55 (red lines) and MERRA-2 (blue lines). Dashed lines are the linear trend of DTR in JA. The JRA-55 starts from 1960 and MERRA-2 starts from 1980.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
To clarify the physical processes responsible for temperature change, we examine the long-term changes in cloud fraction and AA emission and estimate the regional radiation budgets. Note that the trends of AA emission, cloud fraction, and radiation budget are estimated from 1980 to 2020 when the ISCCP data are available. The AOD has increased considerably in China since 1980, and the maximum is seen over NCP (Fig. 3a). The increasing AOD blocks the solar radiation to the surface and leads to a notable reduction of the clear-sky shortwave radiation on the surface (clear-sky SW) at a cooling rate of 10 W m−2 (Fig. 3b). This feature agrees with previous studies in that the AA’s direct effect might affect the surface temperature more regionally (Dong et al. 2009; Liu et al. 2011; Stjern et al. 2020).
Linear trends of daily-mean aerosol optical depth (units: 0.1 decade−1) and total cloud friction (units: 0.1 decade−1) in July and August from 1980 to 2020. Stippled regions are statistically significant at the 10% level using an F test.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
The cloud fraction increases slightly over East China plains, and the statistical significance is only seen in a confined area over NCP (Fig. 3b). The increased cloud fraction results in the cloud radiation effect of shortwave radiation (CRE-SW) with a cooling rate of about 1 W m−2 over NCP (Fig. 4c). The cloud-related CRE-SW is smaller than the AOD-related clear-sky SW, and they are combined to induce a large SW cooling rate over NCP (Fig. 4a). In contrast, the reduced cloud fraction is mainly seen in adjacent regions, including northeast China, western China, and the western North Pacific (Fig. 3b). It leads to the increased CRE-SW (Fig. 4c) that offsets the reduction of clear-sky SW (Fig. 4b). As a result, the decreasing total shortwave radiation (ALL-SW) is evident in East China plains, especially NCP, more than in the adjacent regions (Fig. 4a).
The linear trend of daily-mean surface net radiation to the surface (units: 0.1 W m−2 decade−1) in July and August from 1980 to 2020 based on ISCCP data. (a) Surface net shortwave radiation, (b) surface clear-sky net shortwave radiation, (c) surface cloud radiative effect of shortwave radiation, (d) surface net longwave radiation, (e) surface clear-sky net longwave radiation, (f) surface cloud radiative effect of longwave radiation. Stippled regions are statistically significant at the 10% level using an F test.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
The GHG emission leads to direct warming by increasing clear-sky longwave radiation (clear-sky LW) at the large rate of 5–8 W m−2 on the land of East China (Fig. 4e), and its distribution shows fewer regional differences south of 40°N. The cloud radiation effect of longwave radiation (CRE-LW) has a smaller contribution, and it slightly warms the surface north of 32°N and cools the surface south of 32°N by 1–2 W m−2 (Fig. 4f). So, the GHG-induced clear-sky LW is primarily responsible for the increasing total longwave radiation (ALL-LW), shown by the highly similar spatial distributions in Figs. 4d and 4e. The long-term changes of SW and LW explain well the spatial patterns of temperature trends in Fig. 2. The SW cooling is stronger than LW warming in East China plains, while the SW cooling is weaker than the LW warming in the western highlands of China. So, the differences lead to an increasing trend in the thermal contrast between the plains and the western highlands (Figs. 2a,b).
As the AA blocks solar radiation only in the daytime, it may lead to different trends of temperature at different hours (Fig. 2). Figure 5 quantifies the contribution of SW cooling and LW warming to the surface radiation budget in the NCP at four synoptic hours. The SW effect (red bars in Fig. 5) acts to cool in the NCP at 0800 and 1400 LST with the trends of about −10 and −20 W m−2 decade−1, respectively, while the LW (orange bars in Fig. 5a) warms the surface by 4 W m−2 decade−1 at 0800 LST and 9 W m−2 at 1400 LST. The SW cooling is much stronger than LW in the daytime, leading to the cooling trend in the total radiation (yellow bars in Fig. 5a) at the rates of −6 W m−2 decade−1 at 0800 LST and −11 W m−2 decade−1 at 1400 LST. At 2000 and 0200 LST, when there is no solar radiation on the surface, the increased LW warms the surface at the rate of 5 W m−2 decade−1. Therefore, these differences in the trend of total radiation between daytime and nighttime lead to a cooler day–warmer night trend over the NCP (Fig. 2). At all four synoptic hours, the contributions of clear-sky components (gray bars in SW and LW bars) to SW and LW trends are much greater than the CREs (blue bars in SW and LW bars), which is similar to the daily-mean trends of radiation (Figs. 4b,c,e,f).
The linear trend of diurnal net radiation variation (units: 0.1 W m−2 decade−1) in July and August from 1980 to 2020 over NCP (32°–40°N, 110°–120°E; grids lower than 700 m) based on (a) ISCCP and (b) MERRA-2. Grouped bars from left to right in each panel are at 0800, 1400, 2000, and 0200 LST (daily mean not removed). Red, orange, and yellow bars are surface shortwave radiation, surface longwave radiation, and total surface radiation. Blue and green bars denote cloud radiation effect (CRE) and aerosol direct radiation effect (DRE). Gray bars are clear-sky radiation in (a) and are clear-sky no-aerosol radiation in (b). MERRA-2 does not provide no-aerosol LW, so the DRE of LW is not shown.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
The clear-sky radiation trends in ISCCP include the DRE of AA and the clear-sky no-aerosol radiation due to GHG. Their individual contributions can be separated using MERRA-2 data as noted in section 2. The trends of diurnal total radiation in MERRA-2 have the same signs but half values compared to ISCCP (red, orange, and yellow bars in Fig. 5). The relatively large climatology in ISCCP may lead to such differences in trends, indicating that the radiation response to cloud and aerosols vary somewhat in datasets (Chen and Wang 2016; Delgado-Bonal et al. 2020; X. Zhang et al. 2020; Tang et al. 2022). The DREs to SW are about −5 W m−2 decade−1 at 0800 LST and −7 W m−2 decade−1 at 1400 LST (Fig. 5b), while the CRE to SW and clear-sky no-aerosol SW decrease less than −2 W m−2 decade−1. These suggest that the DRE of AA dominates the decreased SW and results in anomalous daytime cooling. The clear-sky no-aerosol LW (gray bars in LW bars) have almost the same trend to the total LW, indicating that LW warming is induced by GHG, while neither clouds nor aerosols have notable impact. Overall, the DRE of aerosols reduces surface net SW and leads to the daytime cooling, while the GHG increases LW individually and warms the surface during the whole day.
The results above suggest that anthropogenic forcings play an important role in causing the temperature trends at different synoptic hours. Individual roles of AA and GHG are separated based on ISCCP and MERRA-2. The AA reduces the clear-sky SW through the direct effect, and GHG increase the LW in clear-sky no-aerosol condition. Although the GHG warms the mountains and plains in both daytime and nighttime, the AA emission locally cools NCP only in the daytime. As a result, the temperature trend shows a cooler day–warmer night trend over the NCP, leading to a reduced diurnal temperature range (DTR). It also explained the increased thermal contrast between NCP and western highlands in past decades. Note that the nonradiative processes, such as the surface albedo and land cover changes due to GHG and AA, are not considered in this section. These processes might enhance or weaken the temperature response of same radiation perturbations (Bright et al. 2017; Chakraborty and Lee 2019; Chakraborty et al. 2021; Park et al. 2020).
4. Regional circulations in response to the trends of thermal contrast
a. Long-term trends of moisture transport
In this section, we examine how the long-term trends of thermal contrast regulate the diurnal variations of low-level winds and related moisture transports so that the impact of anthropogenic forcings on regional circulations is clarified. In this section, the moisture transport is vertical integrated from the surface to 300 hPa [
Linear trends of diurnal moisture transport [units: 0.1 kg (m s)−1 decade−1; vectors] and convergence [units: 10−6 kg (m2 s)−1 decade−1; contours] in July and August from 1960 to 2018 based on 6-hourly JRA55 at (a) 1400, (b) 2000, (c) 0200, and (d) 0800 LST. Moisture transports are vertically integrated from the surface to 300 hPa. Moisture convergence is the divergence of moisture transports multiply by −1. The daily mean (an average from 1400 to 0800 LST of the next day) is removed. Changes in moisture convergence in dot regions are statistically significant at the 10% level using an F test. The red line denotes the altitude of 700 m. Red, blue, and yellow arrows in (a)–(c) denote anticyclonic, cyclonic, and southerlies trends of moisture transport. The yellow line in (a) is for the vertical section in Fig. 10.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
At 2000 LST, an anomalous southerly over East China plains leads to the increased moisture convergence over NCP (Fig. 6b). This southerly anomaly has a spatial scale larger than the changes at 1400 and 0200 LST, which might be associated with the extensive temperature changes over the plains. As the turbulent mixing due to daytime heating tends to slow the background southerlies at 2000 LST climatologically, this trend of southerly anomaly is also related to the weakened BLO. Moisture convergence reduces at 0800 LST with a northerly anomaly, but it is much weaker than at other synoptic hours.
We use the 7-yr running mean of the NCP-averaged moisture convergence to estimate the long-term changes in moisture conditions (Fig. 7a). In the 1960s to 1970s, the moisture convergence is greater than the daily mean at 0200 and 0800 LST at a value of about 1.0 × 10−5 kg (m2 s)−1. The moisture convergence at 1400 and 2000 LST is about −1.0 × 10−5 kg (m2 s)−1 (negative indicates the divergence anomaly relative to the daily mean). The moisture divergence at 1400 LST experiences a long-term enhancement from the 1960s to the end of the twentieth century [−2.1 × 10−5 kg (m2 s)−1], with a fast rate in the 1980s and 1990s. The MPS intensity increases in the twentieth century (Fig. 7b), which corresponds well to the enhanced moisture divergence at 1400 LST (Fig. 7a).
(a) The 7-yr moving means of the moisture convergence [units: 10−5 kg (m2 s)−1, divergence of vertically integrated moisture transports multiplied by −1] in July and August from 1960 to 2018 over NCP (32°–40°N, 110°–120°E; grids lower than 700 m). Orange, red, green, and blue lines are at 0800, 1400, 2000, and 0200 LST, respectively. Daily means are removed. (b) The 7-yr moving means of standardized boundary layer inertial oscillation (BLO) and mountain–plain solenoid (MPS) index in July and August from 1960 to 2018. BLO index is defined by the southerly wind at 0200 LST minus the daily mean (28°–32°N, 110°–125°E). MPS index is defined as ωplain-night + ωmount-day − ωplain-day − ωmount-night (ω is omega at 800 hPa). Mountain (plain) grids are over 32°–40°N, 110°–120°E higher (lower) than 700-m altitude.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
An increasing trend of moisture convergence is found at 0200 LST (as a reversal to 1400 LST), which also corresponds to strengthened MPS. Note that the increase of moisture convergence at 0200 LST is estimated at 0.6 × 10−5 kg (m2 s)−1 between 1960–80 and 2000–18, which is smaller than the reduction at 1400 LST [1.1 × 10−5 kg (m2 s)−1]. This difference might be related to the weakened BLO (yellow line in Fig. 7b), which reduces the moisture convergence at 0200 LST in the twentieth century and partly offsets the trend of MPS-induced convergence. Moreover, the moisture convergence at 0200 LST decreases slightly in the first decade of the twenty-first century and increase in recent years (Fig. 6a), which corresponds well to the rebound of BLO strength (Fig. 7b). At 2000 LST, the moisture convergence undergoes a rapid increase from the 1960s to the 1990s and a slight decrease in the early twenty-first century (Fig. 7a). This long-term variation might also be correlated to the weakened BLO with a rapid decrease before the mid-1990s and a slight increase thereafter. The moisture convergence at 0800 LST does not show an obvious long-term trend.
In general, the moisture convergence increases at 2000 and 0200 LST and decreases at 1400 LST over NCP, which may result in a larger nighttime proportion of precipitation. The MPS increases rapidly in the twentieth century, while the BLO undergoes a weakened trend that in part offsets the MPS-induced trend at 0200 LST. Therefore, the local circulations driven by the thermal contrast due to anthropogenic forcings play a key role in the long-term trends in the diurnal variations of moisture convergence.
b. Physical processes responsible for the trends of diurnal wind variations
In the climatology of diurnal cycles, the local change term is positive over the East China plains at 2000 and 0200 LST, as the diurnally varying low-level winds rotate from northerlies at 1400 LST to southerlies at 0200 LST (Du and Rotunno 2014; Chen 2020). In past decades, the local change term shows a positive trend (contributes to anomalous southerlies) at 2000 LST over most regions of East China plains (Fig. 8a), but it turns to a negative trend (contributes to anomalous northerlies) at 0200 LST (Fig. 9a). These features correspond to the increasing (decreasing) trend of southerly moisture transports at 2000 LST (0200 LST) over the plains (Figs. 6b,c and 7b).
The linear trend of the local change and forcing terms of 925-hPa meridional wind at 2000 LST in July and August from 1960 to 2018. Stippled regions are statistically significant at the 10% level using an F test. Surface pressure lower than 925 hPa is masked. (a) Local change term of the meridional wind (units: 10−4 m s−2 decade−1), (b) Coriolis force, (c) pressure gradient force, and (d) vertical diffusion and residual term.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
As in Fig. 8, but for 0200 LST.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
The PGF terms have negative trends extensively over the East China plains at both 2000 and 0200 LST (Figs. 8c and 9c). These decreasing PGF terms are partly offset by the CF terms due to the geostrophic balance (Figs. 8b,c and 9b,c). As the change of the PGF terms is more significant than the CF terms, the geostrophic components contribute to the decreasing trends of southerly wind. This effect has less diurnal change and is expected to result from a long-term reduction of the northward pressure gradient at the daily-mean or seasonal-mean time scale (figure not shown). Previous studies suggest that the high pressure trend in North China is much greater than in South China (reduced northward pressure gradient), which has been a key driver of the weakening EASM in past decades (Song et al. 2014).
The nongeostrophic term shows an increasing trend of southerly wind at 2000 LST over the East China plains (Fig. 8d). It exceeds the effect of the geostrophic component (PGF + CF) and leads to the increasing trend of local change term at 2000 LST (Fig. 8a). As the nongeostrophic term in climatology is negative due to the frictional effect of turbulent mixing, this increasing trend of the nongeostrophic term indicates that turbulent mixing has been getting weaker in past decades. The reduction of turbulent mixing corresponds to the weakening trend of BLO (Fig. 7b), which is theoretically related to the change of vertical temperature gradient in the boundary layer (Blackadar 1957). Such a temperature gradient can be seen in the zonal-mean vertical section over NCP, in which the cooling trend near the surface is larger than in the lower troposphere (Fig. 10b). As shown in section 3, the AA forcing is the major cause of the daytime cooling trend near the surface of the plains (Figs. 2b and 5). Therefore, it suggests that the AA-induced cooling leads to the less friction effect of turbulent mixing (weakened BLO), which explains the increasing southerlies at 2000 LST.
(a) The linear trend of sea level pressure (units: 0.01 hPa decade−1) at 2000 LST minus daily mean in July and August from 1960 to 2018. Stippled regions are statistically significant at the 10% level using an F test. Red lines denote an altitude of 700 m. (b) The linear trend of the zonal-mean (112°–122°E) vertical section of geopotential height (contours; units: 0.1 gpm decade−1) and temperature (shaded; units: °C decade−1) at 2000 LST minus daily mean in July and August from 1960 to 2018. The terrain is masked by white. Units of meridional wind are 0.1 m s−1 decade−1; units of vertical velocity are 0.1 hPa s−1 decade−1.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
The nongeostrophic term turns to a decreasing trend at 0200 LST (Fig. 9d), implying that the turbulent mixing is intensified to suppress the background southerlies. It is contributed by the warming trend in the nighttime due to the GHG forcing (Figs. 2c and 5). The diurnally varying trends of turbulent mixing (decreasing at 2000 LST and increasing at 0200 LST) are opposite to those of the climatological BLO (G. Chen et al. 2014; Chen 2020). This weakened amplitude of BLO is thus responsible for the trends of anomalous southerlies at 2000 LST and northerlies at 0200 LST (Figs. 6b,c). The weakened BLO can be related to both the weakened background flow and the reduced DTR (Blackadar 1957; Huang and Chen 2015; Chen et al. 2021). Here, we highlight that the weakened southerly background flow of EASM is associated with the daily-mean geostrophic components. The reduced DTR (cooler day–warmer night) induced by human activities is strongly related to the diurnally varying nongeostrophic components. The nongeostrophic component increases the southerly at 2000 LST by offsetting the effect of the geostrophic component, but it decreases the southerly at 0200 LST by overlying the geostrophic component. Therefore, the weakened southerlies of EASM are more evident at 0200 LST than at 2000 LST due to the anthropogenic forcing’s effect on regional circulations.
We also note that the PGF term has a southerly trend at the east slope of the Taihang Mountains at 2000 LST (Fig. 8c) but not at 0200 LST. In this region, the SLP shows an increasing trend over plains and a decreasing trend over mountains (Fig. 10a), which corresponds to the daytime mountain–plain pressure gradient and the PGF term. The different trend of pressure is also seen in the zonal-mean vertical section in Fig. 10b, and the largest pressure gradient is found at the lower troposphere near 40°N. The change of southerlies and horizontal pressure gradients near the slopping terrains can be related to the late-afternoon maximum of thermal contrast (Holton 1967; Huang et al. 2010). Here, the high-pressure trend over plains and the low-pressure trend over mountains can be explained by the horizontal thermal contrast (the warming trend in the mountains and the cooling trend in plains), which is attributed to human activities, as noted in section 3. However, the nongeostrophic term near the Taihang Mountains shows a decreasing trend (Fig. 8d), probably because of orographic lifting. This decreasing nongeostrophic term is comparable to the increasing PGF term at the east slope of the Taihang Mountains, thereby resulting in a minor change in local change term (Fig. 8a).
In summary, human activities can lead to an evident change in the diurnally varying regional circulations, with the increasing trend of low-level southerlies both over the plains and near the terrains in the early evening. Over NCP, the major factor is the vertical thermal contrast due to the cooler day–warmer night trend that explains the weakened turbulent mixing in the daytime. As it is related to the BLO process, we suggest the response of low-level winds to anthropogenic forcings can be expressed through the Blackadar mechanism (Blackadar 1957). Near the slope of terrains, the impact of human activities is characterized by the horizontal thermal contrast between NCP and its west highlands that regulates the strength of southerlies. So, this process is another response of the regional circulations to anthropogenic forcings through the Holton mechanism (Holton 1967). These results highlight that the different components of human-induced thermal forcings can contribute to different responses in the thermally driven regional circulations at a diurnal time scale, which is important for understanding the long-term trends of regional climate.
c. Physical processes responsible for the strengthened MPS
We further discuss the physical process related to the convergence over the NCP at 0200 LST (Fig. 6c). Figure 10a shows the vertical section at 0200 LST, with an ascending trend over the NCP (east of 110°E) and a descending trend over the Taihang Mountains (around 105°E). The surface temperature trend over the NCP is about 0.05°C decade−1 warmer than the Taihang Mountains, while the air temperature at 800 hPa above the NCP is warmer than the Taihang Mountains by 0.06°C decade−1 (Fig. 11a). The patterns of mountain–plain-varying vertical motion and temperature are nearly opposite at 1400 LST compared to those at 0200 LST. In climatology, the thermal contrast between mountains and plains leads to the ascending motion that is shifted from the mountains at 1400 LST to the plains at 0200 LST (Pan and Chen 2019). In past decades, the trend of daytime warming over mountains stronger than NCP has increased the mountain–plain thermal contrast (Fig. 11). As a result, the enhanced thermal contrast tends to intensify the climatological upward motion over NCP at 0200 LST but suppresses it at 1400 LST, as also shown by the increasing trend of the MPS index (Fig. 7b). As discussed in section 3, the increasing trend of mountain–plain thermal contrast is mainly induced by the asymmetric GHG warming and AA cooling, suggesting that the anthropogenic forcings are responsible for the trends of enhanced MPS and convergence over the NCP at 0200 LST.
Vertical section of linear trend of temperature (contours; units: 0.01°C decade−1) and vertical velocity (omega; shaded; units: 0.01 hPa s−1 decade−1) at 0200 and 1400 LST (daily mean removed) in July and August from 1960 to 2018. The vertical section is made from 40°N, 95°E to 30°N, 120°E (yellow line in Fig. 2a).
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
5. Diurnal difference of precipitation associated with anthropogenic forcings
It is well known that the daily precipitation over East China shows a south flood–north drought trend (Fig. 12a). Previous studies have shown that it is related to the human-induced weakened EASM that results in less moisture transport to NCP but strengthens precipitation over South China (Seo et al. 2013; Song et al. 2014; Tian et al. 2018). In sections 3 and 4, we find that the anthropogenic forcings can regulate the diurnal variations of low-level winds and moisture convergence by changing surface temperature. The moisture convergence is enhanced over NCP in the nighttime (2000 and 0200 LST) than in the daytime (0800 and 1400 LST). In this section, we estimate the diurnal differences in precipitation trends to clarify how human-induced regional circulations regulate precipitation.
The linear trend of (a) daily-mean precipitation (mm day−1 decade−1), (b) nighttime proportion of precipitation (% decade−1), and (c) nighttime proportion of precipitation in extreme precipitation day (% decade−1) in July–August from 1960 to 2018. Extreme precipitation day is defined as the 95th percentile of daily precipitation of each station. Each dot represents an observation station. Red (blue) dot is negative (positive) trend. Larger dots have greater absolute value than smaller dots. The red line denotes the altitude of 700 m.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
Figure 12b shows the trend of the nighttime proportion of precipitation, which is defined by the ratio of accumulated precipitation at 2000–0800 LST to the daily precipitation. The increases in the nighttime proportion of precipitation in past decades are seen in most stations in East China, with the largest increase (∼0.8% decade−1) in the southeast part of NCP. We also see a similar spatial pattern of the nighttime proportion on extreme precipitation days that increases (Fig. 12c). The increase rate on extreme days in the southeast part of NCP is ∼1.5% decade−1 (Fig. 12c), which is even more significant than that in the July–August mean (Fig. 12b). This increased nighttime proportion of precipitation might be led by the moisture convergence change in the nighttime larger than the daytime (Figs. 6b,c), which is thought to be caused by anthropogenic forcings in section 4.
Figure 13 shows the diurnal variations of atmospheric variables averaged over NCP to clarify the dynamic and thermodynamic processes that produce precipitation trends. The daily-mean moisture convergence experienced a decreased trend (red dashed lines), but the decrease is more evident at 0800–1400 LST than that at 2000–0200 LST (Fig. 12a). It corresponds to the decreased daily precipitation but the increased proportion of nighttime precipitation (Figs. 12b,c). The meridional moisture transport at 2000 LST is much larger than the daily mean and the other synoptic hours (Fig. 13b), which is related to the weakened BLO (Fig. 7b). The daily-mean vertical velocity in the lower troposphere decreased (Fig. 13c). But the decrease at 1400/2000 LST is more evident than that at 0200/0800 LST in association with the strengthened MPS (Figs. 6b and 10). So, the MPS-induced vertical motion is mainly responsible for the precipitation at 0200 LST, and the BLO-induced meridional moisture transports primarily explain that at 2000 LST. The observed precipitable water also shows a decreased trend for all four synoptic hours (Fig. 13d), though its diurnal variation is small and contributes less to the diurnal cycle of precipitation. Therefore, the dynamic processes associated with the weakened BLO and strengthened MPS play more important roles in the moisture convergence trends affecting nighttime precipitation. We suggest that the anthropogenic forcings strongly regulate the diurnal cycle of precipitation through the regional circulations, regardless of the weakened EASM and reduced daily precipitation.
The linear trend of (a) moisture convergence [units: 10−6 kg (m2 s)−1 decade−1], (b) meridional moisture transports [units: kg (m s)−1 decade−1], (c) vertical velocity on 850 hPa (omega; units: −0.1 hPa s−1 decade−1), and (d) precipitable water (units: kg decade−1) over NCP (32°–40°N, 110°–120°E; only grid points lower than 700 m are included) in July–August from 1960 to 2018. Red lines are the linear trend of the daily mean. Bars are trends at 0800, 1400, 2000, and 0200 LST from left to right, respectively. The brown (green) bars represent contributions to the drying (wetting) trend more than the daily mean at each synoptic hour.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
6. Conclusions
The anthropogenic forcings have been shown to regulate the monsoon climate, including the temperature, atmospheric circulation, and precipitation at seasonal and longer time scales. Based on JRA-55 and MERRA-2 datasets, rain gauge data, and ISCCP satellite observation, this study examines the impacts of anthropogenic forcings on the regional climate over NCP in July and August from a diurnal-cycle perspective. We clarify the day–night differences in GHG and AA radiation forcings and their influence on the regional surface temperature. We further discuss the physical processes of regional circulations and precipitation in response to human-induced thermal conditions. The results are shown in the schematic model of Fig. 14 and summarized below.
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In past decades, a cooler day–warmer night trend (reduced DTR) has been observed over East China plains, while a warming trend is evident over the west highlands. These regional differences in temperature trends at the diurnal cycle lead to a weakened vertical thermal contrast in the boundary layer over NCP but an enhanced horizontal thermal contrast between NCP and west highlands. The trends of both vertical and horizontal thermal contrasts are strongly regulated by the radiation effects of anthropogenic forcings. The AA emission that reduces net shortwave radiation to the surface is more dominant over the plains, which is crucial for daytime cooling over the NCP (Fig. 14a). The GHG effect that increases net longwave radiation to the surface may explain the warming trends over the highlands for all hours and over the plains in the nighttime (Fig. 14b). The direct effects of anthropogenic forcings denoted by clear-sky radiation are mainly responsible for the temperature trends, and the cloud radiative effect due to a slight change of cloud fraction contributes less to temperature.
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The human-induced thermal contrasts are found to induce the pronounced trends in the diurnal variations of moisture transports over the NCP, with the anomalous southerlies at 2000 LST and northerlies at 0200 LST. The weakened vertical thermal contrast due to the daytime cooling suppresses the boundary layer turbulent mixing and reduces the friction effects to low-level winds over the plains (Fig. 14a). Momentum budget analysis shows that the reduced friction effect leads to an increasing nongeostrophic component of southerly wind at 2000 LST, which can offset the decreasing daily-mean geostrophic component of weakened EASM. In contrast, the nighttime warming over the NCP enhances the friction effects, and the decreasing nongeostrophic component overlies the decreasing geostrophic component to produce the northerlies trend at 0200 LST (Fig. 14b). As a result, the human-induced vertical thermal contrast leads to a weakened BLO during nighttime (anomalous southerlies at 2000 LST and northerlies at 0200 LST). On the other hand, the enhanced horizontal thermal contrast between the NCP and its west highlands has led to the increasing trend of MPS in past decades. The trend of strengthened MPS is related to the enhanced diurnal variations of vertical motions over the NCP, with descending at 1400 LST and ascending at 0200 LST.
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The daily precipitation undergoes a decreased trend over the NCP because of the weakened EASM, while the nighttime proportion of summer precipitation and extreme rainfall days exhibits an increasing trend. These trends are closely related to the moisture convergence, in which its daily mean decreases, and its diurnal variation shows an increasing trend at 2000 and 0200 LST over the NCP. The trend of diurnally varying moisture convergence is mainly regulated by the dynamic processes due to the strengthened MPS and weakened BLO, while the precipitable water shows little diurnal variations. It is concluded that the human-induced changes in regional circulations are thus responsible for the increased nighttime proportion of precipitation over the NCP.
Schematics of long-term trends of circulation related to diurnal variation of the regional climate over the NCP.
Citation: Journal of Climate 36, 13; 10.1175/JCLI-D-22-0498.1
Although the nonradiative process is beyond the scope of this study, the cause of nonradiative process and its impact on the DTR changes over the NCP require further investigation. Several studies suggest that local surface temperature responds to energy budget can be different when the land cover is changed (Bright et al. 2017; Chakraborty and Lee 2019; Chakraborty et al. 2021). We find that the daily maximum and minimum 2-m temperature anomaly in response to net surface radiation anomaly have opposite long-term variation during summertime. This might contribute rather positively or negatively to the AA cooling and GHG warming. On the other hand, in this study we separate the GHG and AA effects on the surface temperature based on reanalysis and satellite observations. However, this method cannot separate their effects on the diurnal variation of circulation and precipitation. Model simulations are helpful to separate the circulation and precipitation changes in response to individual forcing. Based on the Detection and Attribution Model Intercomparison Project (DAMIP; Gillett et al. 2016), we notice that DTR reduces in aerosol-only experiments but DTR trends in GHG-only and natural-only forcing are negligible. These results are in an agreement with this study. However, the trends of diurnal variation of circulation are uncertain in model experiments due to poor ability in reproducing the thermal-driven circulation such as MPS and BLO. How the diurnal variation of regional climate changes as a response to individual forcing remains further studies.
We should also note that the responses of atmospheric circulations to anthropogenic forcings are complicated. The decadal decrease of the daily or seasonal southerly wind of EASM has been attributed to human activities (Seo et al. 2013; Song et al. 2014; Tian et al. 2018). The diurnal amplitude of low-level winds can be regulated by both the daily strength of monsoon southerlies and the DTR (Blackadar 1957; Chen et al. 2021), so its response to anthropogenic forcings needs to be estimated at both daily and diurnal time scales. In this study, we also note that weakened EASM and reduced DTR are offset at 2000 LST and in the phrase at 0200 LST. Numerical experiments may help clarify the relative contribution of weakened monsoon background and reduced DTR to the nighttime proportion of precipitation. On the other hand, the vertical and horizontal components of thermal contrasts can lead to different responses in regional circulations over the NCP. It requires further studies on the anthropogenic forcings that can explicitly resolve these two components at diurnal time scale. It helps us understand the possible trends in diurnal precipitation cycles and even extreme rainfall events more than the mean precipitation amount. Finally, the changing climate might contribute to the movement and initiation of organized convection (Tao and Li 2016; Nishant et al. 2019), while the latter is strongly related to the diurnal variations (Bao and Zhang 2013; M. Chen et al. 2014). An interesting issue is the impacts of anthropogenic forcings on convection systems and their diurnal variations. Further studies of this issue help to clarify whether the frequency and strength of convection systems (or extreme rainfall events) can be changed by human activities.
Acknowledgments.
The authors wish to acknowledge the help of three anonymous reviewers and the data providers JMA, NASA, and CMA for providing the reanalysis datasets JRA-55, ISCCP, MERRA-2, and rain-gauge observation. This work is supported by the Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004), National Key Research and Development Program of China (Grant 2016YFA0600704) and National Natural Science Foundation of China (Grant 41575068).
Data availability statement.
The JRA-55 data from JMA are available at https://jra.kishou.go.jp/JRA-55/index_en.html. The ISCCP radiation flux data from NASA are available at https://isccp.giss.nasa.gov/projects/flux.html. The MERRA-2 data from NASA can be accessed at https://disc.gsfc.nasa.gov/datasets?project=MERRA-2. The variable in MERRA-2 used in this study are from the diurnal mean files including instU_2d_asm_Nx, tavgU_2d_aer_Nx, tavgU_2d_csp_Nx, tavgU_2d_slv_Nx, and tavgU_2d_rad_Nx. The rain-gauge data from China Meteorological Data Service Center and National Meteorological Information Center is available at http://data.cma.cn/en.
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