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Climate Change Research ›› 2024, Vol. 20 ›› Issue (4): 403-415.doi: 10.12006/j.issn.1673-1719.2024.021
• Changes in Climate System • Previous Articles Next Articles
ZHOU Tian-Yi(), JIANG Zhi-Hong(), LI Wei, SUN Cen-Xiao
Received:
2024-01-29
Revised:
2024-04-16
Online:
2024-07-30
Published:
2024-07-19
Contact:
JIANG Zhi-Hong
E-mail:ztybryce@foxmail.com;zhjiang@nuist.edu.cn
ZHOU Tian-Yi, JIANG Zhi-Hong, LI Wei, SUN Cen-Xiao. A comparative study of future summer precipitation projections in Northwest China under different physical constraint schemes[J]. Climate Change Research, 2024, 20(4): 403-415.
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URL: http://www.climatechange.cn/EN/10.12006/j.issn.1673-1719.2024.021
Fig. 1 Spatial distribution of the relative change in summer precipitation over the Northwestern China predicted by CMIP6 models for the end of 21st century (2081-2100) compared to the historical period (1995-2014). (The data on the map represent the regional average changes, the bold black solid line in the figure represents the zero line of relative change in precipitation)
Fig. 2 The first empirical orthogonal function (EOF) of the inter-model decomposition of relative changes in summer precipitation over Northwestern China. (a) The first mode, (b) the corresponding contribution sequences of each model and the regional average sequences of each model
Fig. 3 Regression distribution of summer average precipitation over Northwestern China with contemporaneous sea surface temperatures in the tropical Indian Ocean (a) and the 700 hPa wind field (b), respectively. (The coloring area represent the 95% confidence level, the boxed area in (a) indicates the key factor region. The bold black lines represent areas passing the 95% confidence test, the boxed area in (b) indicates Northwestern China)
Fig. 4 Regression of summer average precipitation over Northwestern China with the East Asian subtropical 200 hPa zonal wind (a), and the zonal wind and meridional circulation along the Northwestern China region (74°-105°E) (b), respectively. (The dots represent areas passing the 95% confidence test, the boxed area indicates the key factor region. The red shading indicates west wind anomalies, while the blue shading indicates east wind anomalies)
Fig. 5 Scatter plot of the tropical Indian Ocean sea surface temperature (a) and the East Asian subtropical 200 hPa zonal wind (b) simulated by 25 CMIP6 models and the estimated changes in summer average precipitation over Northwestern China. (The red line represents the observed region mean sea surface temperature over the tropical Indian Ocean)
Fig. 6 Scatter plot of the summer average precipitation over Northwestern China, constrained by the tropical Indian Ocean sea surface temperature (a) and East Asian subtropical 200 hPa zonal wind (b), showing the estimates after constraints versus unconstrained estimates
Fig. 7 Optimal models obtained from the Pareto-optimal ensemble schemes. (a) The Pareto-optimal ensemble of summer precipitation in the Northwest region and tropical Indian Ocean sea surface temperature, (b) the Pareto-optimal ensemble of summer precipitation in the Northwest region and East Asian subtropical 200 hPa zonal wind, (c) the Pareto-optimal ensemble based on three variables, namely, summer precipitation in the Northwest region, tropical Indian Ocean sea surface temperature, and East Asian subtropical 200 hPa zonal wind. (Each point in the graph represents a model, with filled legends indicating the optimal models)
Fig. 8 Boxplots of future summer precipitation estimates for the Northwest region at the end of the 21st century based on different schemes. (The upper and lower boundaries of the box represent the 75th and 25th percentiles of the estimated results, while the upper and lower limits of the box represent the 90th and 10th percentiles, the black line inside the box represents the median)
Fig. 9 Relative change in summer precipitation in the Northwest region at the end of the 21st century (2081-2100) compared to the historical period (1995-2014) based on the three-variable Pareto optimal ensemble scheme (a), along with the difference from the unconstrained estimate (b)
[1] | 施雅风, 沈永平, 胡汝骥. 西北气候由暖干向暖湿转型的信号、影响和前景初步探讨[J]. 冰川冻土, 2002, 24 (3): 219-226. |
Shi Y F, Shen Y P, Hu R J. Preliminary study on signal, impact and foreground of climatic shift from warm-dry to warm-humid in Northwest China[J]. Journal of Glaciology and Geocryology, 2002, 24 (3): 219-226 (in Chinese) | |
[2] | 李栋梁, 魏丽, 蔡英, 等. 中国西北现代气候变化事实与未来趋势展望[J]. 冰川冻土, 2003, 25 (2): 135-142. |
Li D L, Wei L, Cai Y, et al. The present facts and the future tendency of the climate change in Northwest China[J]. Journal of Glaciology and Geocryology, 2003, 25 (2): 135-142 (in Chinese) | |
[3] | 杨晓丹, 翟盘茂. 我国西北地区降水强度、频率和总量变化[J]. 科技导报, 2005, 23 (6): 24-26. |
Yang X D, Zhai P M. Changes in precipitation intensity, frequency and total in Northwest China[J]. Science &Technology Review, 2005, 23 (6): 24-26 (in Chinese) | |
[4] | 王鹏翔, 何金海, 郑有飞, 等. 近 44 年来我国西北地区干湿特征分析[J]. 应用气象学报, 2007, 18 (6): 769-775. |
Wang P X, He J H, Zheng Y F, et al. Aridity-wetness characteristics over Northwest China in recent 44 years[J]. Journal of Applied Meteorological Science, 2007, 18 (6): 769-775 (in Chinese) | |
[5] | Yang J, Zhang Q, Yue P, et al. Characteristics of warming and humidification in the Yellow River’s upper reaches and their impact on surface water resources[J]. International Journal of Climatology, 2023, 43 (16): 7667-7681 |
[6] | Zhang Q, Yang J H, Duan X Y, et al. The eastward expansion of the climate humidification trend in Northwest China since the start of this century and the synergistic influences on the circulation mechanism[J]. Climate Dynamics, 2022, 59: 2481-2497 |
[7] | 张强, 朱飙, 杨金虎, 等. 西北地区气候湿化趋势的新特征[J]. 科学通报, 2021, 66 (28-29): 3757-3771. |
Zhang Q, Zhu B, Yang J H, et al. New characteristics about the climate humidification trend in Northwest China[J]. Chinese Science Bulletin-Chinese, 2021, 66 (28-29): 3757-3771 (in Chinese) | |
[8] | Zhang Q, Yang J H, Wang W, et al. Climate warming and humidification in the arid regions of Northwest China: process, multi-scale characteristics and its effect on the ecological vegetation[J]. Journal of Meteorological Research, 2021, 35 (1): 113-127 |
[9] |
丁一汇, 柳艳菊, 徐影, 等. 全球气候变化的区域响应: 中国西北地区气候“暖湿化”趋势、成因及预估研究进展与展望[J]. 地球科学进展, 2023, 38 (6): 551-562.
doi: 10.11867/j.issn.1001-8166.2023.027 |
Ding Y H, Liu Y J, Xu Y, et al. Regional responses to global climate change: progress and prospects for trend, causes, and projection of climatic warming-wetting in Northwest China[J]. Advances in Earth Science, 2023, 38 (6): 551-562 (in Chinese)
doi: 10.11867/j.issn.1001-8166.2023.027 |
|
[10] | 张诗妍, 胡永云, 李智博. 我国西北降水变化趋势和预估[J]. 气候变化研究进展, 2022, 18 (6): 683-694. |
Zhang S Y, Hu Y Y, Li Z B. Recent changes and future projection of precipitation in Northwest China[J]. Climate Change Research, 2022, 18 (6): 683-694 (in Chinese) | |
[11] | Chen H P, Sun J Q. How the “best” models project the future precipitation change in China[J]. Advances in Atmospheric Sciences, 2009, 26 (4): 773-782 |
[12] | IPCC. Climate change 2014: synthesis report[M]. Cambridge: Cambridge University Press, 2014: 151 |
[13] | Wang Y J, Zhou B T, Qin D H, et al. Changes in mean and extreme temperature and precipitation over the arid region of northwestern China: observation and projection[J]. Advances in Atmospheric Sciences, 2017, 34 (3): 289-305 |
[14] | 周天军, 邹立维, 陈晓龙. 第六次国际耦合模式比较计划(CMIP6)评述[J]. 气候变化研究进展, 2019, 15 (5): 445-456. |
Zhou T J, Zou L W, Chen X L. Commentary on the Coupled Model Intercomparison Project Phase 6 (CMIP6)[J]. Climate Change Research, 2019, 15 (5): 445-456 (in Chinese) | |
[15] | Wu T W, Lu Y X, Fang Y J, et al. The Beijing Climate Center Climate System Model (BCC-CSM): the main progress from CMIP5 to CMIP6[J]. Geoscientific Model Development, 2019, 12 (4): 1573-1600 |
[16] | Jiang J, Zhou T J, Chen X L, et al. Central Asian precipitation shaped by the tropical Pacific decadal variability and the Atlantic multidecadal variability[J]. Journal of Climate, 2021, 34 (18): 7541-7553 |
[17] | Zhu H, Jiang Z, Li J, et al. Does CMIP 6 inspire more confidence in simulating climate extremes over China?[J]. Advances in Atmospheric Sciences, 2020, 37: 1119-1132 |
[18] | 周天军, 陈梓明, 邹立维, 等. 中国地球气候系统模式的发展及其模拟和预估[J]. 气象学报, 2020, 78 (3): 332-350. |
Zhou T J, Chen Z M, Zou L W, et al. Development of climate and Earth system models in China: past achievements and new CMIP6 fesults[J]. Acta Meteorologica Sinica, 2020, 78 (3): 332-350 (in Chinese) | |
[19] | 王予, 李惠心, 王会军, 等. CMIP6全球气候模式对中国极端降水模拟能力的评估及其与CMIP5的比较[J]. 气象学报, 2021, 79 (3): 369-386. |
Wang Y, Li H X, Wang H J, et al. Evaluation of CMIP6 model simulations of extreme precipitation in China and comparison with CMIP5[J]. Acta Meteorologica Sinica, 2021, 79 (3): 369-386 (in Chinese) | |
[20] | 张强, 杨金虎, 王朋岭, 等. 西北地区气候暖湿化的研究进展与展望[J]. 科学通报, 2023, 68: 1814-1828. |
Zhang Q, Yang J H, Wang P L, et al. Progress and prospect on climate warming and humidification in Northwest China[J]. Chinese Science Bulletin, 2023, 68: 1814-1828 (in Chinese) | |
[21] | Zhu H, Jiang Z, Li L, et al. Intercomparison of multi-model ensemble-processing strategies within a consistent framework for climate projection in China[J]. Science China: Earth Science, 2023, 66: 2125-2141 |
[22] | Boé J, Hall A, Qu X. September sea-ice cover in the Arctic Ocean projected to vanish by 2100[J]. Nature Geoscience, 2009, 2: 341-343 |
[23] | Lian X, Piao S, Huntingford C, et al. Partitioning global land evapotranspiration using CMIP5 models constrained by observations[J]. Nature Climate Change, 2018, 8: 640-646 |
[24] | Li G, Xie S P, He C, et al. Western Pacific emergent constraint lowers projected increase in Indian summer monsoon rainfall[J]. Nature Climate Change, 2017 (7) : 708-712 |
[25] | Chen X, Zhou T, Wu P, et al. Emergent constraints on future projections of the western North Pacific Subtropical High[J]. Nature Communication, 2020, 11: 2802 |
[26] | Langenbunner B, Neelin J. Pareto-optimal estimates of California precipitation change[J]. Geophysical Research Letters, 2017, 44: 12436-12446 |
[27] | Brient F. Reducing uncertainties in climate projections with emergent constraints: concepts, examples and prospects[J]. Advances in Atmospheric Sciences, 2020, 37: 1-15 |
[28] | Langenbunner B, Neelin J. Multiobjective constraints for climate model parameter choices: Pragmatic Pareto fronts in CESM1[J]. Journal of Advances in Modeling Earth Systems, 2017, 9: 2008-2026 |
[29] | Herger N, Abramowtz G, Sherwood S, et al. Ensemble optimisation multiple constraints and overconfidence: a case study with future Australian precipitation change[J]. Nature, 2019, 53: 1581-1596 |
[30] | Sun C, Jiang Z, Tang Z, et al. Multi-objective ensemble-processing strategies to optimize the simulation of the western North Pacific Subtropical High in boreal summer[J]. Geophysical Research Letters, 2023, 50: e2023GL107040 |
[31] | 吴佳, 高学杰. 一套格点化的中国区域逐日观测资料及与其它资料的对比[J]. 地球物理学报, 2013, 56 (4): 1102-1111. |
Wu J, Gao X J. A gridded daily observation dataset over China region and comparison with the other datasets China[J]. Chinese Journal of Geophysics, 2013, 56 (4): 1102-1111 (in Chinese) | |
[32] | Chen Z, Zhou T, Chen X, et al. Observationally constrained projection of Afro-Asian monsoon precipitation[J]. Nature Communication, 2022, 13: 2552 |
[33] |
杨建玲, 郑广芬, 王素艳, 等. 印度洋海盆模影响西北东部降水的大气环流分析[J]. 高原气象, 2015, 34 (3): 700-705.
doi: 10.7522/j.issn.1000-0534.2014.00011 |
Yang J L, Zheng G F, Wang S Y, et al. Analyses of atmospheric circulation of tropical Indian Ocean basin mode influencing precipitation in East of Northwest China[J]. Plateau Meteorology, 2015, 34 (3): 700-705 (in Chinese)
doi: 10.7522/j.issn.1000-0534.2014.00011 |
|
[34] | Wu P, Liu Y, Ding Y, et al. Modulation of sea surface temperature over the North Atlantic and Indian-Pacific warm pool on interdecadal change of summer precipitation over Northwest China[J]. International Journal of Climatology, 2022, 42 (16): 8526-8538 |
[35] | Zhao Y, Wang M, Huang A, et al. Relationships between the West Asian subtropical westerly jet and summer precipitation in northern Xinjiang[J]. Theoretical and Applied Climatology, 2014, 116: 403-411 |
[36] | Peng D D, Zhou T J. Why was the arid and semiarid Northwest China getting wetter in the recent decades?[J]. Journal of Geophysical Research: Atmospheres, 2017, 122 (17): 9060-9075 |
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