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Frontiers of Earth Science

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Front. Earth Sci.    2021, Vol. 15 Issue (1) : 23-37    https://doi.org/10.1007/s11707-020-0847-8
RESEARCH ARTICLE
Projection of temperature and precipitation under SSPs-RCPs Scenarios over northwest China
Jiancheng QIN1,2,3, Buda SU1(), Hui TAO1, Yanjun WANG4, Jinlong HUANG4, Tong JIANG1,4()
1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2. College of Resource and Environment Sciences, Xinjiang University, Urumqi 830046, China
3. University of Chinese Academy of Sciences, Beijing 100049, China
4. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Institute for Disaster Risk Management/School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China
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Abstract

Climate change significantly affects the environmental and socioeconomic conditions in northwest China. Here we evaluate the ability of five general circulation models (GCMs) from 6th phase of the Coupled Model Inter-comparison Project (CMIP6) to reproduce regional temperature and precipitation over northwest China from 1961 to 2014, and project the future temperature and precipitation during 2021 to 2100 under SSPs-RCPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0 and SSP5-8.5). The results show that the CMIP6 models can simulate temperature better than precipitation. Projections show that the annual mean temperature will further increase under different SSPs-RCPs scenarios in the 21st century. Future climate changes in the near-term (2021–2040), mid-term (2041–2060) and long-term (2081–2100) are analyzed relative to the reference period (1995–2014). In the long term, warming will be significantly higher than the near and mid-terms. In the long term, annual mean temperature will increase by 1.4°C, 1.9°C, 3.3°C, 5.5°C, 2.7°C, 3.8°C and 6.0°C under SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0 and SSP5-8.5, respectively. Spatially, warming in the Junggar Basin will be higher than those in the Tarim Basin. Seasonally, the maximum warming zone will be in the mountainous areas of Tarim Basin during spring and autumn, in the southern basin during winter, and in the east during summer. Precipitation shows an increasing trend under different SSPs-RCPs in the 21st century. In the long term, increase in precipitation will be significantly higher than in the near and mid-terms. Increase in annual precipitation in the long term will be 4.1% under SSP1-1.9, 13.9% under SSP1-2.6, 28.4% under SSP2-4.5, 35.2% under SSP3-7.0, 6.9% under SSP4-3.4, 8.9% under SSP4-6.0, and 27.3% under SSP5-8.5 relative to the reference period of 1995–2014. Spatially, precipitation increase will be higher in the south than the north, especially higher in mountainous regions than the basin under SSP2-4.5, SSP3-7.0, and SSP5-8.5. Seasonally, highest increase can be expected for winter, followed by spring, with significant increase in mountainous regions of southern Tarim Basin. Summer precipitation will reduce in Tian Shan and basins but will significantly increase in the northern margin of the Kunlun Mountain.
Keywords temperature      precipitation      projection      SSPs-RCPs      northwest China     
Corresponding Author(s): Buda SU,Tong JIANG   
Online First Date: 22 March 2021    Issue Date: 19 April 2021
 Cite this article:   
Jiancheng QIN,Buda SU,Hui TAO, et al. Projection of temperature and precipitation under SSPs-RCPs Scenarios over northwest China[J]. Front. Earth Sci., 2021, 15(1): 23-37.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-020-0847-8
https://academic.hep.com.cn/fesci/EN/Y2021/V15/I1/23
Fig.1  Location and spatial patterns of temperature and precipitation of the study area.
Name Modeling group Original resolution (lon × lat)
CanESM5 Centre for Climate Modeling and Analysis, Canada 2.81° × 2.81°
CNRM-ESM2-1 National Centre for Scientific Experiments,France 1.25° × 2.5°
IPSL-CM6A-LR Institute Pierre Simon Laplace, France 1.25° × 2.5°
MIROC6 Atmosphere and Ocean Research Institute, Japan 1.4° × 1.4°
MPI-ESM2-0 Planck Meteorological Institute, Germany 0.93° × 0.93°
Tab.1  List of CMIP6 models used in this study
CanESM5 CNRM-ESM2-1 IPSL-CM6A-LR MIROC6 MPI-ESM2-0
Temperature Original outputs 0.77 0.89 0.85 0.84 0.91
Bias-corrected 0.97 0.99 0.96 0.98 0.99
Precipitation Original outputs 0.68 0.67 0.59 0.47 0.66
Bias-corrected 0.98 0.95 0.98 0.99 0.99
Tab.2  Correlation coefficient of CMIP6 model outputs and observations
Fig.2  Spatial patterns of observed and simulated temperature and precipitation during the reference period (1961–2014).
Fig.3  Variations of temperature and precipitation by the observation and multi-model ensemble mean during baseline period (1961–2014).
Fig.4  Taylor diagram of (a) temperature and (b) precipitation for CMIP6 models compared to observations (1961–2014).
Fig.5  Temporal changes in annual mean temperature during 1961-2100 under SSPs-RCPs (relative to 1995–2014).
SSP1-1.9 SSP1-2.6 SSP2-4.5 SSP3-7.0 SSP4-3.4 SSP4-6.0 SSP5-8.5
2021-2040 1.5 1.5 1.6 1.7 1.5 1.7 1.8
2041-2060 1.6 2.0 2.6 3.0 2.3 2.7 3.4
2081-2100 1.4 1.9 3.3 5.5 2.7 3.8 6.0
Tab.3  Temperature changes with relative to 1995-2014 under SSPs-RCPs (°C)
Fig.6  Spatial patterns of temperature changes in periods of 2021-2040, 2041-2060 and 2081-2100 relative to the reference period (1995–2014) under SSP1-1.9, SSP2-4.5, and SSP5-8.5.
SSP1-1.9 SSP1-2.6 SSP2-4.5 SSP3-7.0 SSP4-3.4 SSP4-6.0 SSP5-8.5
Spring 2021–2040 1.6 1.6 1.8 1.9 1.8 2.0 2.2
2041–2060 1.7 2.2 3.2 4.0 2.5 3.4 4.2
2081–2100 1.6 2.1 3.3 5.1 2.8 3.7 5.7
Summer 2021–2040 2.1 2.0 2.2 2.2 2.2 2.2 2.5
2041–2060 2.2 2.6 3.6 4.3 3.2 3.9 5.1
2081–2100 2.1 2.6 4.0 5.9 3.3 4.6 6.7
Autumn 2021–2040 1.8 1.8 2.0 2.2 1.9 2.0 2.3
2041–2060 1.9 2.3 3.5 4.7 3.0 3.7 5.1
2081–2100 1.8 2.4 3.9 6.2 3.2 4.2 6.7
Winter 2021–2040 1.5 1.5 1.4 1.8 1.5 1.6 1.6
2041–2060 1.6 1.9 2.7 4.1 2.5 3.2 4.3
2081–2100 1.3 1.8 3.1 5.7 2.7 3.6 6.1
Tab.4  Seasonal temperature change in periods of 2021-2040, 2041-2060 and 2081-2100 relative to the reference period (1995-2014) under SSPs-RCPs (°C)
Fig.7  Spatial patterns of summer temperature change in periods of 2021-2040, 2041-2060 and 2081-2100 relative to the reference period (1995-2014) under SSP1-1.9, SSP2-4.5 and SSP5-8.5.
Fig.8  Temporal changes of annual averaged precipitation during 1961-2100 under SSPs-RCPs (relative to 1995-2014)
SSP1-1.9 SSP1-2.6 SSP2-4.5 SSP3-7.0 SSP4-3.4 SSP4-6.0 SSP5-8.5
2021–2040 3.9 11.0 14.2 16.8 0.3 0.9 6.7
2041–2060 8.6 13.5 19.4 25.5 2.7 6.2 14.4
2081–2100 4.1 13.9 28.4 35.2 6.9 8.9 27.3
Tab.5   Percentage change of annual precipitation in the 21st century under SSPs-RCPs with relative to 1995-2014 (%).
Fig.9  Spatial patterns of precipitation change in periods of 2021–2040, 2041–2060 and 2081–2100 relative to the reference period (1995–2014) under SSP1-1.9, SSP2-4.5, and SSP3-7.0.
SSP1-1.9 SSP1-2.6 SSP2-4.5 SSP3-7.0 SSP4-3.4 SSP4-6.0 SSP5-8.5
Spring 2021–2040 7.7 21.2 27.8 30.6 2.5 2.3 13.1
2041–2060 11.0 22.6 30.4 38.7 5.9 8.7 27.5
2081–2100 8.5 23.0 47.0 60.8 11.8 16.0 49.3
Summer 2021–2040 0.1 5.1 5.5 5.0 -1.9 -1.1 -0.4
2041–2060 3.6 4.3 6.5 6.9 -1.7 1.3 2.3
2081–2100 0.2 8.5 14.9 10.9 2.6 1.3 6.3
Autumn 2021–2040 8.4 7.2 13.1 19.8 5.7 4.0 10.6
2041–2060 8.3 15.0 21.4 26.3 3.7 6.9 13.6
2081–2100 5.8 11.1 25.4 35.7 8.9 10.8 27.4
Winter 2021–2040 18.3 39.4 44.0 56.0 7.5 13.7 35.6
2041–2060 25.8 40.2 57.7 73.2 19.0 22.6 50.6
2081–2100 23.4 39.7 78.0 122.3 27.4 42.8 104.8
Tab.6  Seasonal precipitation changes in periods of 2021-2040, 2041-2060 and 2081-2100 relative to the reference period (1995-2014) under SSPs-RCPs. (%)
Fig.10  Spatial patterns of winter precipitation changes in periods of 2021-2040, 2041-2060 and 2081-2100 relative to the reference period (1995–2014) under SSP1-1.9, SSP2-45 and SSP3-7.0.
Fig.11  Spatial patterns of summer precipitation changes in periods of 2021-2040, 2041-2060 and 2081-2100 relative to the reference period (1995–2014) under SSP1-1.9, SSP2-4.5 and SSP3-7.0.
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