1. Introduction
As the “Roof of the World” and the “Asian Water Tower,” the Tibetan Plateau (TP), which is highly sensitive and vulnerable to climate changes (Qiu 2008; Immerzeel et al. 2010, 2020; Bibi et al. 2018), has experienced significant wetting under a warming climate (Wang et al. 2018; C. Y. Zhou et al. 2019). The precipitable water (Lu et al. 2015), precipitation (Sun et al. 2020), and lake area (Zhang et al. 2019) over the TP have obviously increased since the mid–late 1990s, resulting in an acceleration of its water cycle. Primarily due to the increased precipitation, surface soil moisture on the plateau has been proved to increase significantly in early summer since the 1980s (W. Zhang et al. 2017). Meanwhile, the TP evaporation (including soil evaporation, canopy evaporation, and plant transpiration) shows a remarkable increase trend, especially in the late 1990s, which is mainly attributed to wetting, followed by warming (Ma and Zhang 2022). Evaporation is a crucial water cycle component related to the energy and carbon exchanges on Earth (Trenberth et al. 2009; Jung et al. 2010; Friedlingstein et al. 2014; Green et al. 2019; Ma et al. 2021; Liu et al. 2022). The increase in latent heat flux (proportional to evaporation) is accompanied by a decrease in sensible heat flux, which is determined by the surface energy balance.
Since the TP is one of the regions with the strongest land–atmosphere interactions (Xue et al. 2010, 2021), much research has investigated the impact of climate change on its land surface (Yang et al. 2014; G. Zhang et al. 2017; Ma and Zhang 2022), but relatively little is known about the response of climate to land surface changes. Among these land–atmosphere interactions, soil moisture–evaporation–precipitation feedbacks are of wide interest (Yang et al. 2018; Hu et al. 2021; Zhou et al. 2021). There are uncertainties as to the effect of evaporation on precipitation, while the other processes among soil moisture, evaporation, and precipitation are deterministic (Seneviratne et al. 2010). For the TP, the influence of evaporation on precipitation is more complex. This is because the plateau is also known as a “heat pump” (Wu and Zhang 1998), which can affect regional and even global climate through strong thermal forcing. Changes in evaporation accompanying changes in surface sensible heating thus may have important implications for the Asian monsoon circulation (Wu et al. 2015; He et al. 2019; Liu et al. 2020). Given the significant increase in evaporation on the TP, revealing the evaporation impact on the plateau land–atmosphere system can help deepen our understanding of local and surrounding climate change in the Asian monsoon region. However, the strong atmospheric forcings on the land surface make it difficult to detect the individual impacts of land surface processes on the atmosphere from observations, and numerical modeling may help to elucidate these complex processes (Notaro et al. 2017; Yue et al. 2021; Sun et al. 2022).
Despite the significant increase in total precipitation over the TP, the amount and frequency of that precipitation have been found to vary with its intensity (Ayantobo et al. 2022). Identifying these individual variations in light-to-heavy-precipitation events helps to assess the risk of drought, soil erosion (Gu et al. 2020), and debris flow (Ma et al. 2022). Land–atmosphere feedbacks can affect both precipitation amount and frequency. Some studies found that dry soil could result in less precipitation and then exacerbate drought (e.g., S. Zhou et al. 2019; Alessi et al. 2022). By contrast, Taylor et al. (2012) have demonstrated that precipitation is more likely to occur over drier soils due to negative land–atmosphere feedbacks. Given these complex feedbacks, it is thus of great importance to reveal the impact of land–atmosphere interactions on precipitation amount and frequency over the TP. Moreover, Mueller and Seneviratne (2014) showed systematic biases in evaporation as simulated by global climate models; however, the impact of these biases on climate simulations was unclear. Therefore, investigating the influence of evaporation on climate cannot only reveal its role in past, present, and future climate, but also help us understand the impact of simulated evaporation errors on model capabilities.
In addition, there is an obvious east–west contrast in the distribution of precipitation amount over the TP, causing wet conditions in its eastern part and dry in its west. This east–west contrast has decreased since the mid-1990s (Sun et al. 2020) and is expected to narrow further in the future due to greater precipitation increasing the ratio over the western TP (Kitoh and Arakawa 2016). Furthermore, land–atmosphere feedbacks may depend on aridity. For example, Tuttle and Salvucci (2016) found contrasting soil moisture–precipitation feedbacks across the United States, which were positive in its arid west while negative in the humid east. On the TP, however, it is not clear whether there is an east–west contrast in land–atmosphere feedbacks similar to that in the United States, and the impact of these feedbacks on the spatial pattern of the plateau precipitation has not been explored.
In this context, the current study aims to answer the following questions: Do surface energy changes (including increased evaporation) on the TP exert positive or negative feedbacks on precipitation? Or do they mitigate or reinforce the interdecadal increase in precipitation over the past four decades? How does the altered surface energy budget affect the plateau east–west contrast pattern in precipitation amount? Do the responses of precipitation amount and frequency vary with intensity? The remainder of this paper is arranged as follows. Section 2 introduces the data, analysis methods, regional climate model, and experiment design. Section 3 analyzes the interdecadal changes in surface energy budget and precipitation on the TP and further explores the feedbacks of the altered surface energy budget on the plateau climate through numerical experiments. Section 4 discusses the responses of precipitation at various intensities. Finally, a summary of this study is presented in section 5.
2. Materials and methods
a. Data and analysis methods
The ERA5 reanalysis data (Hersbach et al. 2020), including surface latent and sensible heat fluxes and precipitation, are used in this study to reveal their interdecadal variations. Although ERA5 overestimates precipitation over the TP, it performs best in capturing interdecadal variability in precipitation among high-resolution data; furthermore, it can accurately capture precipitation events (Yuan et al. 2021). The data span the period from 1959 to the present, with temporal and spatial resolutions of 1 h and 0.25°, respectively. The hourly data are aggregated into monthly and daily means to analyze magnitude and frequency, respectively. In this study, when the daily precipitation amount does not exceed 0.1 mm day−1, it is considered a nonprecipitation day; otherwise, it is a precipitation day with three intensity classes: 0.1–1.5 mm day−1 (light), 1.5–6.0 mm day−1 (moderate) and >6.0 mm day−1 (heavy). The interdecadal variation is obtained based on a 9-yr running average.
b. Model and experiment design
The widely used Weather Research and Forecasting (WRF) Model (version 4.0; Skamarock et al. 2019) is applied and coupled with the Noah LSM with multiparameterization options (Noah-MP; Niu et al. 2011), which provides great flexibility to adjust the scheme configuration. Two numerical experiments are designed to investigate the effects of increased evaporation in the monsoon season (May–August) on the TP. Figure 1a presents the simulation region with horizontal and vertical resolutions of 0.09° and 37 layers between the surface and 50 hPa, respectively. The WRF Model is initialized and driven by ERA5 reanalysis data. The Noah-MP model provides the surface resistance scheme proposed by Sakaguchi and Zeng (2009, hereafter SZ09) and an adjusted soil resistance scheme of Sellers et al. (1992; hereafter AS92). When the surface soil liquid water is the same, the estimated surface resistances of the SZ09 scheme are generally greater than those of the AS92 scheme, and the magnitudes of the estimated surface resistance differences between the two schemes are appropriate (Fig. S1 in the online supplemental material). The first experiment (WRF-CTL) is conducted with the SZ09 scheme. The second experiment (WRF-SEN) replaces the SZ09 scheme with the AS92 scheme on the TP (i.e., areas with altitudes ≥ 2500 m); otherwise, the same as the WRF-CTL. To better describe the TP soil characteristics, a new soil hydrothermal parameterization considering soil organic matter (Sun et al. 2021) is used with layered soil input obtained from a global high-resolution soil dataset (Dai et al. 2019a,b). The other model configurations selected in this study are listed in Table 1.
(a) Distribution of terrain height within the WRF simulation domain (65°–110°E, 15°–45°N). The plateau area (altitude ≥ 2500 m) enclosed by the black solid line is the study domain of this study. (b),(c) Climatology (1979–2021) of monsoon-season (May–August) latent heat flux and precipitation over the TP based on the ERA5 reanalysis data.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
Physical parameterization schemes adopted for the WRF simulations in this study.
The simulation period is 24 April–31 August for the years 2015 and 2018, with 24–30 April used for spinup and the remainder for analysis. The two years are selected because they are typically dry and wet years for the TP, respectively, with quite different climate conditions. This helps us to analyze the sensitivity of land–atmosphere interactions, and it is demonstrated that our results are not sensitive to climate conditions because the results are essentially the same in both years. The results for the dry year 2015 are presented below, with those for the wet year 2018 shown in the supplemental material. The plateau area (altitude ≥ 2500 m) enclosed by the black solid line in Fig. 1a is the focus of this study, and the TP averages all refer to the averages of this plateau region. Most of the TP is sparsely vegetated and thus its evaporation is dominated by soil evaporation (Wang et al. 2020; Ma and Zhang 2022). Under the same forcing conditions, evaporation in the WRF-SEN experiment should be greater than that in the WRF-CTL due to differences in surface resistance; thus, comparing the two experiments provides an opportunity to reveal the effects of the altered land surface energy budget (including increased evaporation) on the coupled land–atmosphere system.
3. Results
a. Interdecadal changes in surface energy budget and precipitation from ERA5
Previous studies have demonstrated that climate warming is expected to change the TP water and energy cycle. In terms of climatic regimes, latent heat flux and precipitation present obvious east–west and north–south contrast patterns on the TP (Figs. 1b,c). Figure 2 shows the time series of monsoon-season latent heat flux, sensible heat flux, and precipitation averaged over the TP. Clearly, the TP-averaged latent heat flux and precipitation have increased since the mid-1990s (Figs. 2a,c). This agrees well with previous studies (Ma et al. 2019; Lin et al. 2021; Ma and Zhang 2022; Wang et al. 2022). The increase in latent heat flux is accompanied by a decrease in sensible heat flux (Fig. 2b). Besides, it is well known that more precipitation can increase latent heat flux by humidifying the soil, but the effect of the altered surface energy budget on precipitation is less clear.
Time series of monsoon-season latent heat flux, sensible heat flux, and precipitation averaged over the TP based on the ERA5 reanalysis data. The horizontal line indicates the 1979–2021 climatology, and the blue line is the 9-yr running mean.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
Based on daily precipitation amount, we further analyze the precipitation frequency at various intensities in the monsoon season. Figure 3 exhibits the variations of TP-averaged nonprecipitation and intensity-classified precipitation frequency, all of which exhibit evident interannual fluctuations. The frequency of nonprecipitation and light precipitation (≤1.5 mm day−1) has decreased, whereas that of moderate and heavy precipitation (>1.5 mm day−1) has increased since the mid-1990s, consistent with Ayantobo et al. (2022). Compared with the period 1979–95, the TP-averaged frequencies of nonprecipitation and light precipitation decrease by 3.23 and 1.71 days, whereas those of moderate and heavy precipitation increasing by 2.68 and 2.26 days in the period 1996–2021, respectively. These results imply that the land–atmosphere conditions for precipitation formation at different intensities may be divergent. Therefore, the effects of the altered surface energy budget (i.e., increased latent heat flux and decreased sensible heat flux) on precipitation within various intensity classes deserve to be explored in depth.
Time series of monsoon-season nonprecipitation and classified precipitation frequency averaged over the TP based on the ERA5 reanalysis data. The horizontal line indicates the 1979–2021 climatology, and the blue line is the 9-yr running mean.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
b. Atmospheric response to altered surface energy budget
In this section, we analyze the above altered surface energy budget feedbacks on the TP atmosphere by numerical simulations. By selecting two different surface resistance schemes in numerical experiments, the interdecadal changes in the TP land surface energy since the mid-1990s (Fig. 2) are qualitatively reproduced. Compared with the WRF-CTL, surface resistance is lower on the TP in the WRF-SEN, which favors soil evaporation and thus results in an increase in latent heat flux (Fig. 4a), a decrease in sensible heat flux and ground temperature (Figs. 4b,c), and a negligible decrease in ground heat flux (not shown). The insets in Figs. 4a–c show that compared with latent heat flux, there are obvious zonal differences in sensible heat flux and ground temperature, with the most pronounced decrease on the Inner TP (80°–90°E) in the WRF-SEN. Figures 4d–f present the histograms of the number of grids with these differences; most grids show differences with the same sign for each variable, with TP-averaged values of 6.99 W m−2, −10.93 W m−2, and −2.74°C for latent heat flux, sensible heat flux, and ground temperature, respectively. These indicate that the differences in surface energy budget generally vary in the same direction (either positive or negative) over the TP. Note that the increased magnitude of TP-averaged latent heat flux in the simulations is comparable to that which has occurred since the mid-1990s.
(a)–(c) Spatial distributions and meridional averages (insets) of differences in monsoon-season latent heat flux, sensible heat flux, and ground temperature between the two experiments (WRF-SEN minus WRF-CTL). The black line denotes the 2500-m isoline of terrain height. (d)–(f) The histograms of these differences for all grids. The mean value is specified in each panel.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
Figure 5 presents the atmospheric response to the altered surface energy budget. The decrease in sensible heat flux favors a decrease in 2-m air temperature (Fig. 5a). As shown in Fig. 5b, 2-m specific humidity appears to increase over the Inner TP and Qaidam Basin and decrease in other plateau regions. Figure 5c shows an overall increase in 2-m relative humidity, which is basically consistent with 2-m air temperature and thus indicates that air temperature is the main factor affecting relative humidity in this study. In contrast, there are apparent discrepancies in the patterns of specific humidity and relative humidity differences, with the former caused by changes in both local evaporation and external water vapor transport. The air temperature and humidity show clear zonal differences, again with the most noticeable differences over the Inner TP (the inset in Figs. 5a–c). Figure 5d shows that there occurs less precipitation on the TP, especially east of about 88°E. This suggests that the altered surface energy budget (including increased latent heat flux and decreased sensible heat flux) can also help to narrow the east–west contrast in precipitation amount on the TP, consistent with the results of Kitoh and Arakawa (2016). The enhanced TP evaporation is found to be driven predominantly by precipitation (Ma and Zhang 2022); in the meantime, our results suggest that the enhanced evaporation and its concomitants exert negative feedbacks on precipitation, which implies that land–atmosphere interactions can slow the rate of precipitation increase over the TP through land surface energy changes. As shown in Figs. 5e–h, for 2-m air temperature and 2-m relative humidity, almost all grids present sign-consistent differences, but for 2-m specific humidity and precipitation, the grids show an increased likelihood of sign-inconsistent differences, suggesting the complexity of water cycle mechanisms.
(a)–(d) Spatial distributions and meridional averages (insets) of differences in monsoon-season 2-m air temperature, 2-m specific humidity, 2-m relative humidity, and precipitation between the two experiments (WRF-SEN minus WRF-CTL). The black line denotes the 2500-m isoline of terrain height. (e)–(h) The histograms of these differences for all grids. The mean value is specified in each panel.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
As mentioned above, the altered surface energy budget not only affects local water vapor, but also may alter external water vapor transport by influencing atmospheric circulation. On the seasonal time scale, precipitation is equal to the sum of evaporation and moisture flux convergence due to the negligible precipitable water tendency term (Li et al. 2013; Wang et al. 2017). Figure 6 displays the differences in monsoon-season moisture flux convergence and evaporation between the two experiments. Compared with the WRF-CTL, the decreased precipitation over the TP is mainly caused by the weakened convergence of moisture flux in the WRF-SEN (Fig. 6a). This implies that the weakened surface sensible heating on the plateau can affect the atmospheric circulation and reduce the transport of external water vapor, whereas the enhanced evaporation is much smaller in comparison (Fig. 6b). As shown in Figs. 6c and 6d, the histogram of the number of grids with differences in moisture flux convergence is similar to that for precipitation, but the mean magnitude of the former (−0.57 mm day−1) is greater than that of the latter (−0.34 mm day−1) due to the offset caused by enhanced evaporation (with a mean value of 0.23 mm day−1). This suggests that the weakened thermal forcing of the TP is dominant in the land surface energy–precipitation feedback in our study.
(a),(b) Spatial distributions and meridional averages (insets) of differences in monsoon-season moisture flux convergence and evaporation between the two experiments (WRF-SEN minus WRF-CTL). The black line denotes the 2500-m isoline of terrain height. (c),(d) The histograms of these differences for all grids. The mean value is specified in each panel.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
c. How does precipitation respond to surface energy changes?
As a key region of land–atmosphere interactions, the land surface energy changes on the TP can profoundly affect its weather and climate as well as the evolution of the Asian monsoon system. The South Asia high centered over the plateau is the most dominant circulation in the upper part of the subtropical troposphere in the monsoon season. Spatial distributions of differences in monsoon-season geopotential height between the two experiments are shown in Figs. 7a and 7b. The weakened surface sensible heating on the TP leads to geopotential height increasing in the lower troposphere while decreasing in the upper troposphere, thus weakening the South Asia high.
Spatial distributions of differences in monsoon-season (a),(b) geopotential height (gpm) at 500 and 200 hPa, (c) specific humidity (g kg−1; shaded) and wind (m s−1; vectors) at 500 hPa, and (d) vertical integral of water vapor flux (kg m−1 s−1) between the two experiments (WRF-SEN minus WRF-CTL). The black line denotes the 2500-m isoline of terrain height.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
To discover the reasons for the decrease in precipitation, the wind and water vapor flux are further analyzed. Figures 7c and 7d present spatial distributions of differences in specific humidity and wind at 500 hPa and vertical integral of water vapor flux between the two experiments. Due to the anticyclonic anomaly over the TP, less water vapor from the Bay of Bengal enters the plateau from its southeastern boundary. Moreover, the stronger westerlies north of 33°N sweep more water vapor out from the eastern boundary of the plateau. The cyclonic anomaly in the Indian plain favors more water vapor entering the plateau from its southwestern boundary. These factors lead to less precipitation over the TP, especially in its east.
4. Discussion
Although the above results indicate that the land surface energy changes can inhibit precipitation over the TP through dynamical processes, the responses of precipitation at different intensities are unclear. As the ERA5 reanalysis data show, the changes in precipitation frequency vary with intensity and therefore require further analyses. Here, we divide daily precipitation into three intensity classes, which is the same as was done in section 3a.
a. Intensity-classified precipitation responses
Figure 8 shows the differences in precipitation amount and frequency at different intensities between the two experiments. It is evident that the decrease of total precipitation amount during the monsoon season over the TP (mean value of −41.97 mm; Fig. 8a) is mainly caused by the decrease of heavy-precipitation amount (mean value of −45.40 mm; Fig. 8b), and the changes of light- and moderate-precipitation amount have little influence on the total precipitation amount changes (not shown). The differences in precipitation frequency are also analyzed. As shown in Fig. 8c, compared with the WRF-CTL, in the WRF-SEN there is a decrease in nonprecipitation frequency and thus an increase in precipitation frequency over the Inner TP and Qaidam Basin (positive feedback), whereas it is the opposite over other regions (negative feedback). Further classification analyses of these differences according to precipitation intensity indicate that the increase in precipitation frequency over the TP is mainly reflected in the light precipitation (positive feedback; Fig. 8d), whereas its decrease is present in the heavy precipitation (negative feedback; Fig. 8f). By contrast, the frequency of moderate precipitation changes slightly (Fig. 8e). On the regional scale, the TP-averaged differences in nonprecipitation and heavy-precipitation frequency between the WRF-SEN and WRF-CTL experiments are −0.17 and −2.22 days, respectively, whereas those in light and moderate-precipitation frequency are 1.49 and 0.90 days, respectively. As mentioned above, there has been a decrease in the light-precipitation frequency but an increase in the heavy-precipitation frequency on the TP since the mid-1990s (Fig. 2), so these land surface energy changes have the potential to mitigate the changes in both the light and heavy-precipitation frequency.
Spatial distributions of differences in monsoon-season precipitation (a),(b) amount and (c)–(f) frequency between the two experiments (WRF-SEN minus WRF-CTL). The black line denotes the 2500-m isoline of terrain height. The mean value is specified in each panel.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
b. Why do precipitation responses vary with intensity?
A question then arises as to why these precipitation amounts and frequency responses vary with intensity, which is further analyzed from the perspective of the atmospheric moisture budget.
Figure 9 presents the boxplots of simulated moisture budget components on the TP in the two experiments, accumulated on nonprecipitation and intensity-classified precipitation days. It is clear that on nonprecipitation days and light–moderate-precipitation days, the differences in moisture flux convergence and evaporation between the WRF-SEN and WRF-CTL experiments contribute mainly to the precipitable water tendency term, thus causing little change in the precipitation amount. On heavy-precipitation days, however, the moisture flux convergences in the WRF-SEN are much less than those in the WRF-CTL, which then results in an obvious decrease in the heavy-precipitation amount. Therefore, the decrease of heavy-precipitation amount dominates the decrease of total precipitation amount during the monsoon season over the TP.
Boxplots of moisture budget components (mm) over the TP during the monsoon season in the WRF-CTL and WRF-SEN experiments, accumulated on nonprecipitation and intensity-classified precipitation days. The horizontal line inside the shaded box indicates the median value, the upper and lower boundaries of the gray shaded box indicate the 25th and 75th percentiles, respectively, and the black stars indicate the mean value. The differences in mean values are specified in each panel.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
To explore the reasons for differences in precipitation frequency responses, simulated moisture budget components on the TP in the two experiments are binned into WRF-CTL nonprecipitation and intensity-classified precipitation days, as shown in Fig. 10. Although moisture flux convergence decreases on the seasonal time scale on the TP (Fig. 6a), the magnitude and sign of these differences are not the same when distinguishing into WRF-CTL nonprecipitation and intensity-classified precipitation days (Fig. 10a). Compared with the WRF-CTL, the moisture flux convergence in the WRF-SEN exhibits a decrease on WRF-CTL heavy-precipitation days but an increase on WRF-CTL nonprecipitation and light-precipitation days, with a slight decrease on WRF-CTL moderate-precipitation days. In contrast, the evaporation differences are almost indistinguishable among WRF-CTL nonprecipitation and intensity-classified precipitation days with small magnitudes (Fig. 10b). Changes in moisture flux convergence and evaporation (dominated by the former) not only affect precipitation, but also affect the precipitable water tendency term. As shown in Figs. 10c and 10d, the signs of differences in precipitable water tendency term and precipitation are generally determined by those of moisture flux convergence differences. Therefore, even on precipitation days with different intensities, the moisture flux convergence change still plays a dominant role in precipitation change. In short, the enhanced moisture flux convergences on WRF-CTL nonprecipitation and light-precipitation days and the weakened moisture flux convergences on WRF-CTL heavy-precipitation days result in increased light-precipitation frequency and decreased heavy-precipitation frequency in the WRF-SEN, when compared with the WRF-CTL.
Boxplots of moisture budget components (mm day−1) over the TP during the monsoon season in the WRF-CTL and WRF-SEN experiments, binned into WRF-CTL nonprecipitation and intensity-classified precipitation days. The horizontal line inside the shaded box indicates the median value, the upper and lower boundaries of the gray shaded box indicate the 25th and 75th percentiles, respectively, and the black stars indicate the mean value. The differences in mean values are specified in each panel.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
5. Conclusions
In this study, the interdecadal variations of monsoon-season latent heat flux, sensible heat flux, and precipitation on the TP from 1979 to 2021 are analyzed, and based on this, the impact of the plateau land surface energy changes on the coupled land–atmosphere system is investigated using numerical simulations.
The ERA5 reanalysis data show that since the mid-1990s, latent heat flux and precipitation have increased significantly, whereas sensible heat flux has decreased over the TP. There are divergences in the changes of ERA5 precipitation frequency at different intensities, with the frequency of light precipitation (0.1–1.5 mm day−1) decreasing, with that of moderate and heavy precipitation (>1.5 mm day−1) increasing. Based on regional climate simulations, we find that increased evaporation and decreased sensible heat flux result in decreased 2-m air temperature and increased 2-m relative humidity. The altered surface energy budget–induced changes in atmospheric water vapor are more complex, with greater spatial heterogeneity (an increase over the Inner TP and Qaidam Basin, but a decrease in other regions). Under global warming, the TP becomes wetter due to enhanced moisture flux convergence (C. Y. Zhou et al. 2019; Sun et al. 2020). However, the changes in the plateau land surface energy budget can weaken the South Asian monsoon through thermal effects, thus causing a reduction in moisture flux convergence in this region and ultimately, its precipitation. The decrease in precipitation is more pronounced over the eastern TP, due to its greater exposure to the South Asian monsoon. Given that these results are essentially the same in dry and wet years, we conclude that the land surface energy changes over the TP can attenuate the precipitation increase rate and mitigate the east–west contrast in precipitation amount, through dynamical processes. These processes are schematized in Fig. 11.
The processes of interdecadal changes in surface energy budget over the TP affecting the atmosphere. The light-red ring labeled A and the light-blue ring labeled C indicate anomalous anticyclonic and cyclonic induced by the altered surface energy budget, respectively. The interdecadal changes in the TP land surface energy budget (including enhanced surface latent heat and weakened surface sensible heat) can lead to low-level anomalous anticyclonic and upper-level anomalous cyclonic, and thus weaken the South Asian monsoon, causing a reduction in moisture flux from the Bay of Bengal entering the TP and ultimately less precipitation over the plateau, especially in its east.
Citation: Journal of Climate 36, 11; 10.1175/JCLI-D-22-0686.1
Further specific analyses show that the enhanced evaporation and weakened sensible heating contribute to precipitation frequency increasing over the Inner TP and Qaidam Basin, while decreasing over other regions. The precipitation frequency responses also vary with intensity: the increase of precipitation frequency mainly occurs in light precipitation (0.1–1.5 mm day−1), whereas its decrease is present in heavy precipitation (>6.0 mm day−1). The changes in water vapor flux convergence are divergent under different precipitation intensities, which is the main cause of these different precipitation responses. These results suggest that the altered land surface energy budget can mitigate the changes in precipitation frequency at various intensities observed from the reanalysis data.
In other words, although TP wetting and warming lead to increased evaporation accompanied by decreased surface sensible heating, the latter, in turn, buffers the acceleration of the plateau water cycle under global climate change.
Acknowledgments.
This work was supported by the Second Tibetan Plateau Scientific Expedition and Research Program (STEP, Grant 2019QZKK0206), the National Science Foundation of China (Grant 41975125), the Basic Science Center for Tibetan Plateau Earth System (BCTPES, NSFC Project 41988101), and the 13th Five-year Informatization Plan of Chinese Academy of Sciences (Grant XXH13505-06). The simulations were performed at the CASEarth Cloud (http://portal.casearth.cn) from the Computer Network Information Center, Chinese Academy of Sciences.
Data availability statement.
The ERA5 reanalysis data are available at ECMWF (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5). The global high-resolution soil dataset is obtained from http://globalchange.bnu.edu.cn/research/soil5.jsp.
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