Abstract:Monsoons are a crucial component of the atmospheric circulation system, playing a vital role in affecting the human's living environment and social economies worldwide. The East Asian monsoon, an important part of the global monsoon system, consists of tropical and subtropical monsoons (
“…According to the MMM, the linear trends of the 400 mm isohyet are 0.26°−1.21° (uncertainty due to different scenarios), 0.24°−1.26°, and 1.05°−2.29° of latitude, those of the P summer boundary are 0.31°−1.14°, 0.26°−0.83° and 0.61°−1.38° of latitude, and those of the GM metric are 0.17°−1.01°, 0.38°−0.75° and 0.61°−1.29° of latitude in the western, middle, and eastern parts of the boundary during 2015–2099, respectively. There are larger change trends and model spreads in the east for three metrics (Table S4), which is probably due to the regional difference in the precipitation gradient (Wu et al, 2021). The 400 mm isohyet generally exhibits the largest migration trend in the three parts, especially in the east (Figure 4d).…”
Section: Resultsmentioning
confidence: 96%
“…As the movement magnitudes of the EASM northern boundary are spatially uneven, we divide the boundary into three segments, as in previous studies (Chen et al, 2018; Wu et al, 2021). The fluctuations are mild with a range of 1.37°−2.45° of latitude for the MMM in the western part of the boundary (105° E−110° E), while in the east (115° E−120° E), there are larger fluctuations ranging from 3.50° to 4.70° of latitude under the three scenarios (Figure S4).…”
Section: Resultsmentioning
confidence: 99%
“…This metric has important climatic, ecological and geographical implications, which separates the sub‐humid from the semi‐arid zones, forest from grassland vegetation, and monsoonal from non‐monsoonal regions. Moreover, this index can reflect the annual range of the total monsoonal precipitation, which is closely associated with the monsoon intensity (Liu et al, 2009; Wang et al, 2012; Wu et al, 2021). Second, the 2 mm day −1 isohyet in May–September (MJJAS) (hereafter P summer ) is utilized to indicate the climatological EASM northern boundary (Chen et al, 2018; Wang et al, 2022).…”
Section: Methodsmentioning
confidence: 99%
“…Specifically, the simulated ratios of monthly precipitation in 2015–2099 at each grid in each model over the 1981–2010 precipitation climatology are calculated, and then the ratios are multiplied by the observed climatological precipitation during 1981–2010. This correction method has been widely used when calculating indicators that are sensitive to threshold values in previous studies (e.g., Belda et al, 2016; Déqué, 2007; Wu et al, 2021). The statistical significance of the linear trends of the EASM northern boundary migration in 2015–2099 is measured by Student's t test, and the linear trends are multiplied by 85 years for convenience.…”
The East Asian summer monsoon (EASM) projection has attracted much attention, whereas there are few investigations on the future changes of the EASM northern boundary. The boundary migration would influence the distribution of precipitation and the related vegetation, and its projection is important for policy development of climate change adaptation. In this study, based on the median of 22 selected Coupled Model Intercomparison Project Phase 6 (CMIP6) models, the linear trends of meridional movement of the EASM northern boundary are found to be 0.45−1.39° of latitude during 2015–2099 based on the three precipitation‐based metrics under three shared socioeconomic pathway scenarios. Spatially, the multimetric climatological EASM northern boundary displays a 70–170 km northwestward advance during 2080–2099 compared to 1981–2010. Such an advance also holds true for most individual models, but the migration magnitudes vary with metrics, scenarios and models. The strengthened EASM in association with the intensified land–sea thermal contrast and the enhanced atmospheric water vapour content in response to global warming account for the northwestward advance of the EASM northern boundary, which is related to the increased possibility of the negative phase of the Pacific decadal oscillation in the future. Additionally, the thermodynamic component due to the increased moisture content contributes more than the dynamic term arising from the reinforced EASM circulations to the intensified precipitation and northwestward migration of the EASM northern boundary. The future advance of the EASM northern boundary favours a “northern flood and southern drought” precipitation pattern over eastern China, which would partly mitigate drought conditions in northern arid regions.
“…According to the MMM, the linear trends of the 400 mm isohyet are 0.26°−1.21° (uncertainty due to different scenarios), 0.24°−1.26°, and 1.05°−2.29° of latitude, those of the P summer boundary are 0.31°−1.14°, 0.26°−0.83° and 0.61°−1.38° of latitude, and those of the GM metric are 0.17°−1.01°, 0.38°−0.75° and 0.61°−1.29° of latitude in the western, middle, and eastern parts of the boundary during 2015–2099, respectively. There are larger change trends and model spreads in the east for three metrics (Table S4), which is probably due to the regional difference in the precipitation gradient (Wu et al, 2021). The 400 mm isohyet generally exhibits the largest migration trend in the three parts, especially in the east (Figure 4d).…”
Section: Resultsmentioning
confidence: 96%
“…As the movement magnitudes of the EASM northern boundary are spatially uneven, we divide the boundary into three segments, as in previous studies (Chen et al, 2018; Wu et al, 2021). The fluctuations are mild with a range of 1.37°−2.45° of latitude for the MMM in the western part of the boundary (105° E−110° E), while in the east (115° E−120° E), there are larger fluctuations ranging from 3.50° to 4.70° of latitude under the three scenarios (Figure S4).…”
Section: Resultsmentioning
confidence: 99%
“…This metric has important climatic, ecological and geographical implications, which separates the sub‐humid from the semi‐arid zones, forest from grassland vegetation, and monsoonal from non‐monsoonal regions. Moreover, this index can reflect the annual range of the total monsoonal precipitation, which is closely associated with the monsoon intensity (Liu et al, 2009; Wang et al, 2012; Wu et al, 2021). Second, the 2 mm day −1 isohyet in May–September (MJJAS) (hereafter P summer ) is utilized to indicate the climatological EASM northern boundary (Chen et al, 2018; Wang et al, 2022).…”
Section: Methodsmentioning
confidence: 99%
“…Specifically, the simulated ratios of monthly precipitation in 2015–2099 at each grid in each model over the 1981–2010 precipitation climatology are calculated, and then the ratios are multiplied by the observed climatological precipitation during 1981–2010. This correction method has been widely used when calculating indicators that are sensitive to threshold values in previous studies (e.g., Belda et al, 2016; Déqué, 2007; Wu et al, 2021). The statistical significance of the linear trends of the EASM northern boundary migration in 2015–2099 is measured by Student's t test, and the linear trends are multiplied by 85 years for convenience.…”
The East Asian summer monsoon (EASM) projection has attracted much attention, whereas there are few investigations on the future changes of the EASM northern boundary. The boundary migration would influence the distribution of precipitation and the related vegetation, and its projection is important for policy development of climate change adaptation. In this study, based on the median of 22 selected Coupled Model Intercomparison Project Phase 6 (CMIP6) models, the linear trends of meridional movement of the EASM northern boundary are found to be 0.45−1.39° of latitude during 2015–2099 based on the three precipitation‐based metrics under three shared socioeconomic pathway scenarios. Spatially, the multimetric climatological EASM northern boundary displays a 70–170 km northwestward advance during 2080–2099 compared to 1981–2010. Such an advance also holds true for most individual models, but the migration magnitudes vary with metrics, scenarios and models. The strengthened EASM in association with the intensified land–sea thermal contrast and the enhanced atmospheric water vapour content in response to global warming account for the northwestward advance of the EASM northern boundary, which is related to the increased possibility of the negative phase of the Pacific decadal oscillation in the future. Additionally, the thermodynamic component due to the increased moisture content contributes more than the dynamic term arising from the reinforced EASM circulations to the intensified precipitation and northwestward migration of the EASM northern boundary. The future advance of the EASM northern boundary favours a “northern flood and southern drought” precipitation pattern over eastern China, which would partly mitigate drought conditions in northern arid regions.
“…The possible reason is that the decreasing surface wind speed in China is related to the weakening trend of the monsoon in East Asia and South Asia [42,43]. Besides, some related studies [44][45][46] predict that the Asian summer monsoon index will increase significantly, and the winter monsoon index will weaken significantly in the future. However, the ARNC is deeply inland and weakly affected by the monsoon, so the variation trends of the surface wind speed in summer and winter are different from those in China.…”
Near surface wind speed has significant impacts on ecological environment change and climate change. Based on the CN05.1 observation data (a gridded monthly dataset with the resolution of 0.25 latitude by 0.25 longitude over China), this study evaluated the ability of 25 Global Climate Models (GCMs) from Coupled Model Intercomparison Project phase 6 (CMIP6) in simulating the wind speed in the Arid Region of Northwest China (ARNC) during 1971–2014. Then, the temporal and spatial variations in the surface wind speed of ARNC in the 21st century were projected under four Shared Socioeconomic Pathways (SSPs), SSP1-2.6, SSP2-4.5, SSP3-7.0, and SP5-8.5. The results reveal that the preferred-model ensemble (PME) can fairly evaluate the temporal and spatial distribution of surface wind speed with the temporal and spatial correlation coefficients exceeding 0.5 at the significance level of p = 0.05 when compared to the 25 single models and their ensemble mean. After deviation correction, the PME can reproduce the distribution characteristics of high wind speed in the east and low in the west, high in mountainous areas, and low in basins. Unfortunately, no models or model ensemble can accurately reproduce the decreasing magnitude of observed wind speed. In the 21st century, the surface wind speed in the ARNC is projected to increase under SSP1-2.6 scenario but will decrease remarkably under the other three scenarios. Moreover, the higher the emission scenarios, the more significant the surface wind speed decreases. Spatially, the wind speed will increase significantly in the west and southeast of Xinjiang, decrease in the north of Xinjiang and the south of Tarim Basin. What’s more, under the four scenarios, the surface wind speed will decrease in spring, summer and autumn, especially in summer, and increase in winter. The wind speed will decrease significantly in the north of Tianshan Mountains in summer, decrease significantly in the north of Xinjiang and the southern edge of Tarim Basin in spring and autumn, and increase in fluctuation with high values in Tianshan Mountains in winter.
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