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Journal of Arid Land
Journal of Arid Land  2020, Vol. 12 Issue (3): 374-396    DOI: 10.1007/s40333-020-0065-y     CSTR: 32276.14.s40333-020-0065-y
Research article     
Performance and uncertainty analysis of a short-term climate reconstruction based on multi-source data in the Tianshan Mountains region, China
LI Xuemei1,2,3,*(), Slobodan P SIMONOVIC4, LI Lanhai5, ZHANG Xueting6,7, QIN Qirui1,3
1 Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
2 National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China
3 Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China
4 Facility for Intelligent Decision Support, Department of Civil and Environmental Engineering, Western University, London N6A 3K7, Canada
5 State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
6 Qilian Alpine Ecology & Hydrology Research Station, Key Laboratory of Ecohydrology of Inland River Basin, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
7 University of Chinese Academy of Sciences, Beijing 100049, China
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Abstract  

Short-term climate reconstruction, i.e., the reproduction of short-term (several decades) historical climatic time series based on the relationship between observed data and available longer-term reference data in a certain area, can extend the length of climatic time series and offset the shortage of observations. This can be used to assess regional climate change over a much longer time scale. Based on monthly grid climate data from a Coupled Model Inter-comparison Project phase 5 (CMIP5) dataset for the period of 1850-2000, the Climatic Research Unit (CRU) dataset for the period of 1901-2000 and the observed data from 53 meteorological stations located in the Tianshan Mountains region (TMR) of China during the period of 1961-2011, we calibrated and validated monthly average temperature (MAT) and monthly accumulated precipitation (MAP) in the TMR using the delta, physical scaling (SP) and artificial neural network (ANN) methods. Performance and uncertainty during the calibration (1971-1999) and verification (1961-1970) periods were assessed and compared using traditional performance indices and a revised set pair analysis (RSPA) method. The calibration and verification processes were subjected to various sources of uncertainty due to the influence of different reconstructed variables, different data sources, and/or different methods used. According to traditional performance indices, both the CRU and CMIP5 datasets resulted in satisfactory calibrated and verified MAT time series at 53 meteorological stations and MAP time series at 20 meteorological stations using the delta and SP methods for the period of 1961-1999. However, the results differed from those obtained by the RSPA method. This showed that the CRU dataset produced a low degree of uncertainty (positive connection degree) during the calibration and verification of MAT using the delta and SP methods compared to the CMIP5 dataset. Overall, the calibrated and verified MAP had a high degree of uncertainty (negative connection degree) regardless of the dataset or reconstruction method used. Therefore, the reconstructed time series of MAT for the period of 1850 (or 1901)-1960 based on the CRU and CMIP5 datasets using the delta and SP methods could be used for further study. The results of this study will be useful for short-term (several decades) regional climate reconstruction and longer-term (100 a or more) assessments of regional climate change.

Key words： climate reconstruction      climate change      delta method      physical scaling method      artificial neural network (ANN)      CRU dataset      CMIP5 dataset     
Received: 16 May 2019      Published: 10 May 2020
Corresponding Authors:
About author: *Corresponding author: LI Xuemei (E-mail: lixuemei@mail.lzjtu.cn)
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Xuemei LI
P SIMONOVIC Slobodan
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Qirui QIN
Cite this article:

LI Xuemei, Slobodan P SIMONOVIC, LI Lanhai, ZHANG Xueting, QIN Qirui. Performance and uncertainty analysis of a short-term climate reconstruction based on multi-source data in the Tianshan Mountains region, China. Journal of Arid Land, 2020, 12(3): 374-396.

URL:

http://jal.xjegi.com/10.1007/s40333-020-0065-y     OR     http://jal.xjegi.com/Y2020/V12/I3/374

Fig. 1 Distribution of the meteorological stations in the Tianshan Mountains region (TMR) of China. The full name and descriptive information of all meteorological stations can be seen in Table S1 in the Appendix.
Fig. 2 Flow chart of methods and approaches used in this study. MAT, monthly average temperature; MAP, monthly accumulated precipitation; CRU, Climate Research Unit; CMIP5, Coupled Model Inter-comparison Project phase 5; TMR, Tianshan Mountains region; SP, physical scaling; ANN, artificial neural network; RSPA, revised set pair analysis.
Performance rating Grade NSC PBLAS
Very good A NSC≥0.75 PBIAS≤ ±15%
Good B 0.65≤NSC<0.75 PBIAS≤ ±20%
Satisfactory C 0.50≤NSC<0.65 PBIAS≤ ±25%
Unsatisfactory D NSC<0.50 Any value
Table 1 Climate reconstruction performance criteria (revised from Moriasi et al. (2007))
Grade
0-s1 s1-s2 s2-s3 s3-s4 s4-s5
Range of MAT (°C) 0.0-0.5 0.5-1.0 1.0-1.5 1.5-2.0 2.0-+∞
Range of MAP (mm) 0.0-2.0 2.0-4.0 4.0-6.0 6.0-8.0 8.0-+∞
Performance Very good Good Normal Bad Very bad
Degree G1 G2 G3 G4 G5
Table 2 Assessment of grade standards for the calibration and verification of monthly average temperature (MAT) and monthly accumulated precipitation (MAP) time series in the Tianshan Mountains region (TMR) of China
Fig. 3 The 128 satisfactory calibrated, verified and observed monthly average temperature (MAT) time series at Zhaosu station. Obs, observed data; SP, physical scaling; ANN, artificial neural network. Delta.ACCESS1-0, the reconstructed data based on ACCESS1-0 data using the delta method; the others all follow this nomenclature scheme.
Fig. 4 Distribution of numbers of satisfactory calibrated and verified MAT time series in the TMR. The value at each station represents the number of satisfactory calibrated and verified MAT time series based on the CMIP5 and CRU datasets using the delta, SP and ANN methods.
Fig. 5 The 26 satisfactory calibrated, verified and observed monthly accumulated precipitation (MAP) time series at Zhaosu station. Obs, the observed data; SP, physical scaling. Delta.ACCESS1.0, the reconstructed data based on ACCESS1.0 data using the delta method; the others all follow this nomenclature scheme.
Fig. 6 Distribution of numbers of satisfactory calibrated and verified MAP time series in the TMR. The value at each station represents the number of satisfactory calibrated and verified MAT time series based on the CMIP5 and CRU datasets using the delta, SP and ANN methods.
No. Station name Station code Latitude Longitude Elevation (m) Time period
1 Akqi AKQ 78.45°N 40.93°E 1985.700 1961-2011
2 Aksu AKS 80.23°N 41.17°E 1104.730 1961-2011
3 Baicheng BCH 81.90°N 41.78°E 1230.000 1961-2011
4 Balguntay BLGT 86.30°N 42.73°E 1739.470 1961-2011
5 Barkol BKL 93.05°N 43.60°E 1675.370 1961-2011
6 Bayanbulak BYBLK 84.15°N 43.03°E 2459.270 1961-2011
7 Bole BL 82.07°N 44.90°E 532.567 1961-2011
8 Caijiahu CJH 87.53°N 44.20°E 440.967 1961-2011
9 Dabancheng DBCH 88.32°N 43.35°E 1104.770 1961-2011
10 Daxigou DXG 86.83°N 43.10°E 3539.000 1961-2011
11 Gongliu GL 82.23°N 43.47°E 775.970 1961-2011
12 Hami HM 93.52°N 42.82°E 738.200 1961-2011
13 Hejing HJ 86.40°N 42.32°E 1102.370 1961-2011
14 Hoxud HX 86.80°N 42.25°E 1086.130 1961-2011
15 Hutubi HTB 86.82°N 44.13°E 522.970 1961-2011
16 Jiashi JSH 76.73°N 39.50°E 1208.600 1961-2011
17 Jimsar JMS 89.17°N 44.02°E 735.570 1961-2011
18 Jinghe JH 82.90°N 44.60°E 320.870 1961-2011
19 Kalpin KP 79.05°N 40.50°E 1162.630 1961-2011
20 Kashi KSH 75.99°N 39.27°E 1291.200 1961-2011
21 Khorgas KG 80.42°N 44.20°E 772.970 1961-2011
22 Korla KL 86.13°N 41.25°E 932.433 1961-2011
23 Kumux KM 88.22°N 42.23°E 923.470 1961-2011
24 Kuqa KQ 82.97°N 41.73°E 1082.930 1961-2011
25 Manas MNS 86.20°N 44.32°E 471.400 1961-2011
26 Mori MR 90.28°N 43.83°E 1271.970 1961-2011
27 Mosuowan MSW 86.10°N 45.02°E 347.230 1961-2011
28 Naomaohu NMH 95.13°N 43.77°E 479.030 1961-2011
29 Nilka NLK 82.62°N 43.80°E 1106.130 1961-2011
30 Paotai PT 85.25°N 44.85°E 337.100 1961-2011
31 Qapqal QPQ 81.15°N 43.83°E 603.800 1961-2011
32 Qitai QT 89.57°N 44.02°E 794.100 1961-2011
33 Shanshan SHSH 90.23°N 42.85°E 398.930 1961-2011
34 Shawan SHW 85.62°N 44.33°E 522.200 1961-2011
35 Shihezi SHHZ 86.05°N 44.32°E 443.730 1961-2011
36 Shisanjianfang SHSJF 91.73°N 43.22°E 722.900 1961-2011
37 Tekes TKS 81.77°N 43.18°E 1210.530 1961-2011
38 Tianchi TCH 88.12°N 43.88°E 1942.170 1961-2011
39 Toksun TKS 88.63°N 42.80°E 1.670 1961-2011
40 Tuergate TEGT 75.40°N 40.52°E 3506.400 1961-2011
41 Turpan TP 89.20°N 42.93°E 34.970 1961-2011
42 Urumqi URMQ 87.65°N 43.78°E 935.670 1961-2011
43 Usu US 84.67°N 44.43°E 478.970 1961-2011
44 Wenquan WEQ 81.02°N 44.97°E 1358.600 1961-2011
45 Wuqia WUQ 75.25°N 39.72°E 2176.900 1961-2011
46 Wushi WSH 79.23°N 41.22°E 1396.470 1961-2011
47 Xiaoquzi XQZ 87.10°N 43.49°E 1873.800 1961-2011
48 Xinhe XH 82.61°N 41.53°E 1014.200 1961-2011
49 Xinyuan XY 83.30°N 43.45°E 929.200 1961-2011
50 Yanqi YQ 86.57°N 42.08°E 1056.600 1961-2011
51 Yining YN 81.33°N 43.95°E 663.200 1961-2011
52 Yiwu YW 94.70°N 43.27°E 1728.600 1961-2011
53 Zhaosu ZHS 81.13°N 43.15°E 1853.400 1961-2011
Table S1 Descriptive information of the meteorological stations selected in the Tianshan Mountains region (TMR)
No. Model name Source and country Resolution Historical period
1 ACCESS1-0 CSIRO-BOM, Australia 192×145 Jan 1850-Dec 2005
2 ACCESS1-3 CSIRO-BOM, Australia 192×145 Jan 1850-Dec 2005
3 BCC-CSM1-1 BCC, China 128×64 Jan 1850-Dec 2012
4 BCC-CSM1-1-M BCC, China 320×160 Jan 1850-Dec 2012
5 BNU-ESM GCESS, China 128×64 Jan 1850-Dec 2005
6 CanCM4 CCCMA, Canada 128×64 Jan 1850-Dec 2005
7 CanESM2 CCCMA, Canada 128×64 Jan 1850-Dec 2005
8 CCSM4 NCAR, U.S. 288×192 Jan 1850-Dec 2005
9 CESM1-BGC NSF-DOE-NCAR, U.S. 288×192 Jan 1850-Dec 2005
10 CESM1-CAM5 NSF-DOE-NCAR, U.S. 288×192 Jan 1850-Dec 2005
11 CESM1-FASTCHEM NSF-DOE-NCAR, U.S. 288×192 Jan 1850-Dec 2005
12 CESM1-WACCM NSF-DOE-NCAR, U.S. 144×96 Jan 1850-Dec 2005
13 CMCC-CESM CMCC, Italy 96×48 Jan 1850-Dec 2005
14 CMCC-CM CMCC, Italy 480×240 Jan 1850-Dec 2005
15 CMCC-CMS CMCC, Italy 192×96 Jan 1850-Dec 2005
16 CNRM-CM5 CNRM-CERFACS, French 256×128 Jan 1850-Dec 2005
17 CSIRO-Mk3-6-0 CSIRO-QCCCE, Australia 192×96 Jan 1850-Dec 2005
18 EC-EARTH EC-EARTH, 10-European nations 320×160 Jan 1950-Dec 2012
19 FGOALS-g2 FGOALS, China 128×60 Jan 1960-Jan 1999
20 FGOALS-s2 FGOALS, China 128×108 Jan 1850-Dec 2005
21 FIO-ESM FIO, China 128×64 Jan 1850-Dec 2005
22 GFDL-ESM2G NOAA GFDL, U.S. 144×90 Jan 1961-Dec 2000
23 GFDL-ESM2M NOAA GFDL, U.S. 144×90 Jan 1961-Dec 2000
24 GISS-E2-H NASA GISS, U.S. 144×90 Jan 1951-Dec 2005
25 GISS-E2-H-CC NASA GISS, U.S. 144×90 Jan 1951-Dec 2010
26 GISS-E2-R NASA GISS, U.S. 144×90 Jan 1951-Dec 2005
27 GISS-E2-R-CC NASA GISS, U.S. 144×90 Jan 1951-Dec 2005
28 HadCM3 MOHC, England 96×73 Jan 1959-Dec 2005
29 HadGEM2-AO NIMR/KMA, SK/England 192×145 Jan 1860-Dec 2005
30 HadGEM2-CC MOHC, England 192×145 Dec 1959-Nov 2005
31 HadGEM2-ES MOHC, England 192×145 Dec 1959-Nov 2005
32 INMCM4 INM, Russia 180×120 Jan 1850-Dec 2005
33 IPSL-CM5A-LR IPSL, French 96×96 Jan 1850-Dec 2005
34 IPSL-CM5A-MR IPSL, French 144×143 Jan 1850-Dec 2005
35 IPSL-CM5B-LR IPSL, French 96×96 Jan 1850-Dec 2005
36 MIROC4h MIROC, Japan 640×320 Jan 1961-Dec 2000
37 MIROC5 MIROC, Japan 256×128 Jan 1850-Dec 2012
38 MIROC-ESM MIROC, Japan 128×64 Jan 1950-Dec 2005
39 MIROC-ESM-CHEM MIROC, Japan 128×64 Jan 1850-Dec 2005
40 MRI-CGCM3 MRI, Japan 320×160 Jan 1850-Dec 2005
41 NorESM1-M NCC, Norway 144×96 Jan 1850-Dec 2005
42 NorESM1-ME NCC, Norway 144×96 Jan 1850-Dec 2005
Table S2 Basic information of the CMIP5 (Coupled Model Inter-comparison Project phase 5) models
No. Station name Number of satisfactory calibrated and verified MAT time series
Total A (very good) Delta method SP method ANN method No method CRU CMIP5
1 Akqi 88 87 41 42 0 5 2 86
2 Aksu 90 85 41 42 0 7 3 87
3 Baicheng 91 86 41 42 0 8 2 89
4 Balguntay 102 89 41 42 0 19 2 100
5 Barkol 69 55 41 27 0 1 2 67
6 Bayanbulak 82 82 41 41 0 0 2 80
7 Bole 91 84 41 42 0 8 2 89
8 Caijiahu 92 84 41 41 0 10 2 90
9 Dabancheng 93 87 41 42 0 10 3 90
10 Daxigou 83 83 41 42 0 0 2 81
11 Gongliu 90 88 41 42 0 7 2 88
12 Hami 91 86 41 42 0 8 3 88
13 Hejing 93 91 41 42 0 10 3 90
14 Hoxud 93 90 41 42 0 10 3 90
15 Hutubi 91 85 41 42 0 8 3 88
16 Jiashi 86 83 41 42 0 3 2 84
17 Jimsar 92 86 41 42 0 9 2 90
18 Jinghe 102 93 41 42 0 19 2 100
19 Kalpin 86 83 41 42 0 3 2 84
20 Kashi 102 93 41 42 0 19 2 100
21 Khorgas 99 89 41 42 0 16 3 96
22 Korla 102 93 41 42 0 19 3 99
23 Kumux 101 90 41 42 0 18 3 98
24 Kuqa 91 85 41 42 0 8 3 88
25 Manas 101 90 41 42 0 18 2 99
26 Mori 100 90 41 42 0 17 3 97
27 Mosuowan 102 90 41 42 0 19 2 100
28 Naomaohu 85 84 41 42 0 2 3 82
29 Nilka 91 89 41 42 0 8 2 89
30 Paotai 101 91 41 42 0 18 2 99
31 Qapqal 102 98 41 42 0 19 3 99
32 Qitai 99 90 41 42 0 16 3 96
33 Shanshan 83 83 41 42 0 0 2 81
34 Shawan 105 99 41 42 0 22 2 103
35 Shihezi 109 91 41 42 0 26 2 107
36 Shisanjianfang 97 87 41 42 0 14 3 94
37 Tekes 87 87 41 42 0 4 2 85
38 Tianchi 82 75 41 40 0 1 1 81
39 Toksun 85 83 41 42 0 2 3 82
40 Tuergate 87 85 41 42 0 4 2 85
41 Turpan 84 83 41 42 0 1 2 82
42 Urumqi 100 89 41 42 0 17 2 98
43 Usu 101 90 41 42 0 18 3 98
44 Wenquan 127 94 41 41 35 10 2 125
45 Wuqia 83 83 41 42 0 0 2 81
46 Wushi 85 83 41 41 0 3 1 84
47 Xiaoquzi 91 79 41 41 1 8 2 89
48 Xinhe 95 91 41 42 0 12 3 92
49 Xinyuan 90 88 41 42 0 7 2 88
50 Yanqi 98 90 41 42 0 15 3 95
51 Yining 89 86 41 42 0 6 2 87
52 Yiwu 135 106 41 42 37 15 3 132
53 Zhaosu 128 119 41 42 42 3 3 125
Table S3 Numbers of satisfactory calibrated and verified monthly average temperature (MAT) time series based on the CMIP5 and Climatic Research Unit (CRU) datasets using the delta, physical scaling (SP), artificial neural network (ANN) and No methods
No. Station name Number of satisfactory calibrated and verified MAP time series
Total C/B C/C Delta method SP method ANN method No method CRU CMIP5
1 Bayanbulak 13 0 12 12 1 0 0 0 13
2 Daxigou 8 5 2 8 0 0 0 0 8
3 Kashi 3 0 0 1 1 1 0 3 0
4 Korla 3 0 0 1 1 1 0 3 0
5 Kuqa 1 0 0 1 0 0 0 1 0
6 Manas 3 1 2 1 1 1 0 3 0
7 Mori 2 2 0 0 1 1 0 2 0
8 Qitai 3 0 0 1 1 1 0 3 0
9 Tekes 1 0 1 0 1 0 0 0 1
10 Tianchi 3 0 0 1 1 1 0 3 0
11 Tuergate 1 0 0 1 0 0 0 1 0
12 Turpan 1 0 0 1 0 0 0 1 0
13 Urumqi 2 0 0 0 1 1 0 2 0
14 Usu 4 0 0 1 1 1 1 4 0
15 Xiaoquzi 7 0 5 2 3 2 0 3 4
16 Xinyuan 1 0 1 0 1 0 0 1 0
17 Yanqi 1 0 1 1 0 0 0 1 0
18 Yining 4 0 0 1 1 1 1 4 0
19 Yiwu 4 0 0 1 1 1 1 4 0
20 Zhaosu 26 6 20 9 9 6 2 0 26
Table S4 Numbers of satisfactory calibrated and verified monthly accumulated precipitation (MAP) time series based on the CRU and CMIP5 datasets using the delta, SP, ANN and No methods
No. Connection
degree		 a b1 b2 b3 c
C V C V C V C V C V
1 μ(Rdelta CRU, T) 0.58 0.59 0.24 0.26 0.11 0.06 0.04 0.06 0.03 0.03
2 μ(RSP CRU, T) 0.53 0.56 0.28 0.28 0.13 0.08 0.04 0.06 0.03 0.03
3 μ(RANN cru, T) 0.51 0.56 0.31 0.27 0.13 0.10 0.03 0.05 0.02 0.03
4 μ(RANN CanCM4, T) 0.26 0.25 0.15 0.13 0.17 0.10 0.10 0.13 0.32 0.39
5 μ(RSP FGOALS-g2, T) 0.26 0.19 0.16 0.24 0.13 0.14 0.14 0.13 0.32 0.30
6 μ(RSP BNU-ESM, T) 0.25 0.14 0.15 0.27 0.16 0.13 0.11 0.13 0.33 0.33
7 μ(RSP CESM1-BGC, T) 0.25 0.26 0.19 0.16 0.14 0.15 0.10 0.15 0.32 0.28
8 μ(RSP CESM1-WACCM, T) 0.25 0.23 0.16 0.14 0.14 0.16 0.11 0.14 0.34 0.33
9 μ(Rdelta CSIRO-Mk3-6-0, T) 0.24 0.20 0.16 0.16 0.14 0.19 0.11 0.15 0.35 0.30
10 μ(RSP MIROC-ESM-CHEM, T) 0.24 0.15 0.16 0.25 0.14 0.17 0.11 0.09 0.36 0.34
11 μ(RSP GISS-E2-R, T) 0.24 0.19 0.20 0.19 0.13 0.11 0.11 0.18 0.32 0.33
12 μ (RANN CESM1-BGC, T) 0.24 0.23 0.22 0.20 0.14 0.15 0.11 0.13 0.30 0.28
13 μ(RANN CESM1-FASTCHEM, T) 0.24 0.22 0.17 0.24 0.14 0.11 0.10 0.11 0.35 0.33
14 μ(RANN GISS-E2-R, T) 0.24 0.23 0.19 0.18 0.14 0.15 0.12 0.14 0.32 0.30
15 μ(RSP CESM1-FASTCHEM, T) 0.23 0.23 0.21 0.18 0.11 0.10 0.11 0.11 0.34 0.35
16 μ(RSP FGOALS-g2, T) 0.23 0.23 0.15 0.19 0.17 0.17 0.10 0.12 0.35 0.30
17 μ(RSP GISS-E2-H, T) 0.23 0.17 0.18 0.24 0.13 0.18 0.12 0.08 0.34 0.33
18 μ(RSP CMCC-CM, T) 0.23 0.21 0.18 0.15 0.14 0.18 0.12 0.12 0.34 0.35
19 μ(RANN MIROC5, T) 0.23 0.21 0.21 0.19 0.15 0.18 0.11 0.09 0.29 0.33
20 μ(RANN HanGEM2-ES, T) 0.23 0.18 0.18 0.21 0.15 0.14 0.12 0.13 0.32 0.34
Table S5 Connection degree expressions between calibrated (verified) and observed MAT time series (first 20 entries) at Zhaosu station
No. Connection
degree		 a b1 b2 b3 c
C V C V C V C V C V
1 μ(Rdelta CRU, P) 0.22 0.23 0.16 0.10 0.10 0.07 0.06 0.08 0.46 0.53
2 μ(Rdelta MIROC4h, P) 0.18 0.13 0.11 0.09 0.11 0.13 0.08 0.06 0.53 0.58
3 μ(Rdelta bcc-csm1-1-m, P) 0.16 0.13 0.12 0.09 0.10 0.13 0.06 0.08 0.57 0.56
4 μ(Rdelta inmcm4, P) 0.16 0.12 0.14 0.13 0.09 0.11 0.07 0.05 0.54 0.60
5 μ(RANN MIROC4h, P) 0.16 0.10 0.08 0.08 0.11 0.10 0.07 0.11 0.57 0.62
6 μ(Rdelta MIROC5, P) 0.15 0.12 0.13 0.13 0.10 0.08 0.08 0.08 0.55 0.59
7 μ(Rdelta CCSM4, P) 0.15 0.17 0.14 0.13 0.11 0.06 0.07 0.07 0.53 0.58
8 μ(Rdelta CESM1-FASTCHEM, P) 0.15 0.13 0.11 0.13 0.10 0.11 0.11 0.04 0.53 0.60
9 μ(Rdelta CSIRO-Mk3-6-0, P) 0.15 0.13 0.13 0.13 0.07 0.08 0.09 0.10 0.56 0.57
10 μ(Rdelta MRI-CGCM3, P) 0.15 0.18 0.12 0.13 0.11 0.10 0.07 0.07 0.55 0.53
11 μ(Rdelta NorESM1-M, P) 0.15 0.13 0.11 0.10 0.10 0.09 0.08 0.11 0.56 0.57
12 μ(Rdelta CMCC-CM, P) 0.15 0.14 0.11 0.08 0.11 0.10 0.09 0.10 0.54 0.58
13 μ(RNo ACCESS1-0, P) 0.14 0.13 0.11 0.10 0.08 0.11 0.08 0.08 0.59 0.58
14 μ(RNo HadGEM2-CC, P) 0.14 0.12 0.09 0.06 0.06 0.08 0.06 0.10 0.66 0.64
15 μ(RNo HadGEM2-ES, P) 0.14 0.11 0.09 0.08 0.08 0.09 0.07 0.07 0.61 0.65
16 μ(Rdelta ACCESS1-0, P) 0.14 0.08 0.13 0.14 0.11 0.12 0.08 0.09 0.54 0.58
17 μ(Rdelta CESM1-BGC, P) 0.14 0.13 0.14 0.15 0.12 0.12 0.08 0.07 0.53 0.53
18 μ(Rdelta IPSL-CM5A-MR, P) 0.14 0.14 0.13 0.11 0.09 0.13 0.08 0.07 0.56 0.55
19 μ(Rdelta MIROC-ESM, P) 0.14 0.1 0.13 0.16 0.09 0.08 0.09 0.06 0.56 0.60
20 μ(Rdelta CNRM-CM5, P) 0.14 0.15 0.14 0.08 0.09 0.12 0.07 0.05 0.56 0.60
Table S6 Connection degree expressions between calibrated (verified) and observed MAP (first 20 entries) at Zhaosu station
No. Station
name		 Number of positive connection degrees for calibrated and verified MAT time series
Total Delta method SP method ANN method No
method		 CRU CMIP5
1 Akqi 4 2 2 0 0 2 2
2 Aksu 19 8 10 0 1 3 16
3 Baicheng 2 1 1 0 0 2 0
4 Barkol 2 1 1 0 0 2 0
5 Balguntay 19 1 18 0 0 2 17
6 Bayanbulak 2 1 1 0 0 2 0
7 Bole 2 1 1 0 0 2 0
8 Caijiahu 2 1 1 0 0 2 0
9 Dabancheng 3 1 1 0 1 3 0
10 Daxigou 14 1 13 0 0 2 12
11 Gongliu 2 1 1 0 0 2 0
12 Hami 3 1 1 0 1 3 0
13 Hejing 3 1 2 0 0 2 1
14 Hoxud 2 1 1 0 0 2 0
15 Hutubi 2 1 1 0 0 2 0
16 Jiashi 4 1 3 0 0 2 2
17 Jinghe 2 1 1 0 0 2 0
18 Kalpin 3 2 1 0 0 2 1
19 Khorgas 2 1 1 0 0 2 0
20 Korla 10 4 6 0 0 2 8
21 Kuqa 5 3 1 0 1 3 2
22 Kumux 4 2 2 0 0 2 2
23 Manas 2 1 1 0 0 2 0
24 Mori 3 1 1 0 1 3 0
25 Mosuowan 2 1 1 0 0 2 0
26 Naomaohu 2 1 1 0 0 2 0
27 Nilka 2 1 1 0 0 2 0
28 Paotai 2 1 1 0 0 2 0
29 Qapqal 2 1 1 0 0 2 0
30 Qitai 3 1 1 0 1 3 0
31 Shanshan 1 1 0 0 0 1 0
No. Station
name		 Number of positive connection degrees for calibrated and verified MAT time series
Total Delta method SP method ANN method No
method		 CRU CMIP5
32 Shawan 2 1 1 0 0 2 0
33 Shihezi 2 1 1 0 0 2 0
34 Shisanjianfang 3 1 1 0 1 3 0
35 Tekes 2 1 1 0 0 2 0
36 Tianchi 3 1 1 1 0 3 0
37 Toksun 2 1 1 0 0 2 0
38 Tuergate 5 2 3 0 0 2 3
39 Turpan 2 1 1 0 0 2 0
40 Urumqi 2 1 1 0 0 2 0
41 Usu 2 1 1 0 0 2 0
42 Wenquan 1 1 0 0 0 1 0
43 Wuqia 2 1 1 0 0 2 0
44 Wushi 3 2 1 0 0 3 0
45 Xiaoquzi 4 1 1 1 1 4 0
46 Xinhe 22 10 11 0 1 3 19
47 Xinyuan 2 1 1 0 0 2 0
48 Yanqi 15 6 8 0 1 3 12
49 Yining 2 1 1 0 0 2 0
50 Yiwu 3 1 2 0 0 2 1
51 Zhaosu 3 1 1 1 0 3 0
Table S7 Number of positive connection degrees for calibrated and verified MAT time series based on the CMIP5 and CRU datasets using the delta, SP, ANN and No methods
No. Station
name		 Number of positive connection degrees for calibrated and verified MAP time series
Total Delta method SP
method		 ANN method No
method		 CRU CMIP5
1 Aksu 101 43 30 28 0 3 98
2 Balguntay 48 43 0 0 5 2 46
3 Bayanbulak 7 7 0 0 0 0 7
4 Caijiahu 3 1 1 1 0 3 0
5 Dabancheng 97 43 30 24 0 3 94
6 Hami 137 43 41 36 17 3 134
7 Hejing 121 43 38 34 6 4 117
8 Hoxud 61 43 4 10 4 3 58
9 Jiashi 110 43 34 28 5 3 107
10 Jinghe 54 34 3 8 9 3 51
11 Kalpin 53 43 3 4 3 4 49
12 Kashi 127 43 43 40 1 4 123
13 Korla 135 43 41 34 17 4 131
14 Kuqa 105 43 29 29 4 4 101
15 Kumux 129 43 39 37 10 4 125
16 Manas 4 1 1 1 1 4 0
17 Mosuowan 4 1 1 1 1 4 0
18 Naomaohu 137 43 43 42 9 4 133
19 Paotai 3 1 1 0 1 3 0
20 Qitai 4 1 1 1 1 4 0
21 Shanshan 132 43 43 43 3 3 129
22 Shisanjianfang 131 43 43 43 2 3 128
23 Toksun 63 0 42 21 0 1 62
24 Tuergate 1 1 0 0 0 1 0
25 Turpan 63 1 41 21 0 1 62
26 Urumqi 3 1 1 1 0 3 0
27 Usu 4 1 1 1 1 4 0
28 Wuqia 1 1 0 0 0 1 0
29 Wushi 10 9 1 0 0 2 8
30 Xinhe 61 43 3 10 5 4 57
31 Yanqi 59 43 4 7 5 4 55
32 Yining 4 1 1 1 1 4 0
33 Yiwu 58 43 1 3 11 4 54
Table S8 Number of positive connection degrees for calibrated and verified MAP time series based on the CMIP5 and CRU datasets using the delta, SP, ANN and No methods
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