Quantifying the Uncertainty Sources of Future Climate Projections and Narrowing Uncertainties with Bias Correction Techniques in Tibetan Plateau
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摘要: 在全球变暖加剧的背景下，准确预估未来时期气候变化至关重要．本文基于最新发布的CMIP6（Coupled Model Intercomparison Project 6）中的15个GCM模式（Global Climate Model），在未来4种共享社会经济路径和典型浓度路径组合情景下，量化青藏高原地区气温和降水预估的不确定性．然后使用DT方法（Daily Translation），对CMIP6模式输出数据进行偏差校正．通过对比DT前后不确定性的大小，讨论偏差校正方法在降低气温和降水预估不确定性的潜力．结果显示，DT方法校正结果与实测值更为接近；气候预估不确定性从长期来看，模式不确定性占据主导地位，而情景不确定性和内部变异性的贡献相对较低；DT方法对于降低降水预估不确定性的效果较好，其中模式不确定性降低最多，对情景不确定性的大小影响不大，但影响了不确定性的相对贡献大小．综合来看，利用DT方法进行偏差校正能在一定程度上降低预估不确定性．研究结果可为揭示气候变化对高寒区水循环的影响机制提供科学依据．Abstract: In the context of intensifying global warming, accurate predictions of climate change in the coming period are essential. Based on the 15 GCM models (GCMs) in the newly released Coupled Model Intercomparison Project 6 (CMIP6), this paper quantifies the uncertainty of temperature and precipitation estimates in the Tibetan Plateau under the next four shared socioeconomic pathways and typical concentration pathway combination scenarios. Then, the CMIP6 mode output data is biased corrected using the DT method. By comparing the magnitude of the uncertainty before and after DT, the potential of the bias correction method in reducing the uncertainty of temperature and precipitation estimates is discussed. The results show that the correction results of the DT method are closer to the measured values. In the long run, model uncertainty dominates, while the contribution of scenario uncertainty and internal variability is relatively low. The DT method has a good effect on reducing the uncertainty of precipitation prediction, and almost reduces the model uncertainty by 80%, which has little effect on the size of scenario uncertainty but affects the relative contribution of uncertainty. In summary, the use of the DT method for deviation correction can reduce the uncertainty of estimation to a certain extent. Results have important implications for the impact of climate change on water cycles in alpine regions.
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Key words:
- climatic change /
- temperature /
- precipitation /
- bias correction /
- uncertainty /
- Tibetan Plateau
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表 1 CMIP6模式具体信息
编号 模式名称 所属机构及国家 分辨率 1 ACCESS‒CM2 Commonwealth Scientific and Industrial Research Organization, Australia 1.25° × 1.675° 2 CanESM5 Canadian Centre for Climate Modelling and Analysis, Canada 2.7673° × 2.8125° 3 CESM2‒WACCM National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, USA 0.9424° × 1.25° 4 CMCC‒CM2‒SR5 Fondazione Centro Euro‒Mediterraneo sui Cambiamenti Climatici, Italy 0.9424° × 1.25° 5 GFDL‒ESM4 Geophysical Fluid Dynamics Laboratory, Princeton, USA 1°×1.25° 6 INM‒CM4‒8 Institute for Numerical Mathematics, Russian Academy of Science, Russia 1.5°×2° 7 IPSL‒CM6A‒LR Institut Pierre Simon Laplace, France National Institute of Meteorological 1.2676°×2.5° 8 KACE‒1‒0‒G Sciences/Korea Meteorological Administration, Republic of Korea 1.25°×1.875° 9 MIROC6 Agency for Marine‒Earth Science and Technology, Atmosphere and Ocean Research Institute, and National Institute for Environmental Studies, Ibaraki, Japan 1.389°×1.406° 10 MPI‒ESM1‒2‒HR Max Planck Institute for Meteorology , Germany 1.865°×1.875° 11 MPI‒ESM1‒2‒LR Max Planck Institute for Meteorology , Germany 1.865°×1.875° 12 MRI‒ESM2‒0 Meteorological Research Institute, Tsukuba, Japan 1.124°×1.125° 13 NESM3 Nanjing University of Information Science and Technology, China 1.865°×1.875° 14 NorESM2‒LM Norwegian Climate Centre, Norway 1.895°×2.5° 15 NorESM2‒MM Norwegian Climate Centre, Norway 0.942°×1.25° 
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表 2 未来情景变化具体信息
编号 组合形式 具体含义 SSP126 SSP1（低强迫情景）+RCP2.6 到2100年，辐射强迫水平为2.6W·m−2的绿色发展路径 SSP245 SSP2（中强迫情景）+RCP4.5 到2100年，辐射强迫水平为4.5W·m−2的中等发展路径 SSP370 SSP3（中高强迫情景）+RCP7.0 到2100年，辐射强迫水平为7.0W·m−2的中高等发展路径 SSP585 SSP5（高强迫情景）+RCP8.5 到2100年，辐射强迫水平为8.5W·m−2的高等发展路径
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表 3 验证期模式输出和偏差校正降水量各统计指标评价结果
Ibias（%） FREQ INT Q90 月份 GCMs DT GCMs DT GCMs DT 1 409.66 ‒18.44 1229.05 40.66 397.77 ‒25.48 2 408.14 ‒20.44 28.85 ‒3.34 366.44 ‒31.02 3 416.45 ‒14.85 31.63 ‒0.69 353.22 ‒14.55 4 344.20 ‒13.31 34.49 ‒0.55 394.83 ‒11.95 5 72.49 ‒17.35 13.43 ‒7.59 105.39 ‒18.36 6 22.15 ‒8.78 7.40 ‒4.82 31.70 ‒11.12 7 ‒10.03 ‒6.34 1.50 ‒7.02 5.97 ‒11.77 8 ‒16.91 ‒1.32 4.39 ‒3.78 4.49 ‒1.61 9 ‒22.58 ‒11.48 6.58 ‒2.01 ‒13.02 ‒11.23 10 171.57 ‒18.52 15.04 0.29 200.53 ‒16.90 11 342.56 ‒20.69 52.64 ‒7.56 755.68 ‒22.62 12 519.97 ‒4.82 613.24 44.68 713.22 ‒13.37 C FREQ INT Q90 月份 GCMs DT GCMs DT GCMs DT 1 0.43 0.96 0.42 0.96 0.48 0.98 2 0.52 0.97 0.65 0.98 0.60 0.99 3 0.37 0.98 0.56 0.97 0.64 0.99 4 0.29 0.99 0.48 0.96 0.60 0.99 5 0.51 0.98 0.67 0.96 0.71 0.98 6 0.62 0.97 0.66 0.96 0.68 0.96 7 0.43 0.93 0.68 0.96 0.68 0.96 8 0.53 0.92 0.68 0.96 0.70 0.97 9 0.72 0.94 0.72 0.95 0.76 0.97 10 0.63 0.99 0.67 0.95 0.72 0.98 11 0.43 0.98 0.58 0.93 0.56 0.98 12 0.36 0.91 0.53 0.90 0.27 0.91 Enr FREQ INT Q90 月份 GCMs DT GCMs DT GCMs DT 1 0.21 0.00 0.01 0.02 0.46 0.04 2 0.19 0.03 0.03 0.01 0.26 0.06 3 0.08 0.02 0.03 0.01 0.06 0.03 4 0.06 0.01 0.03 0.01 0.06 0.00 5 0.12 0.01 0.07 0.07 0.00 0.05 6 0.07 0.01 0.07 0.02 0.04 0.02 7 0.04 0.00 0.32 0.01 0.28 0.03 8 0.04 0.01 0.16 0.00 0.15 0.01 9 0.04 0.00 0.02 0.04 0.03 0.00 10 0.01 0.02 0.02 0.15 0.03 0.04 11 0.14 0.01 0.09 0.00 0.19 0.01 12 0.22 0.02 0.02 0.06 0.51 0.06
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表 4 验证期模式输出和偏差校正平均气温各统计指标评价结果
Ibias/% Q90 Q10 月份 GCMs DT GCMs DT 1 ‒12.02 0.80 ‒163.82 146.00 2 ‒9.28 4.46 ‒190.76 ‒0.63 3 10.61 0.62 ‒31.56 ‒0.05 4 ‒25.01 ‒12.01 ‒94.30 ‒6.08 5 ‒4.06 7.52 ‒21.58 ‒0.51 6 ‒16.34 2.98 ‒66.84 ‒20.55 7 ‒9.13 0.62 ‒33.63 ‒4.84 8 ‒4.15 ‒0.35 ‒9.61 ‒4.77 9 ‒5.90 ‒3.59 ‒74.83 ‒22.02 10 13.92 15.36 ‒40.94 ‒0.76 11 ‒5.65 30.27 ‒125.46 ‒13.52 12 ‒7.79 7.46 ‒11.68 3.96 C Q90 Q10 月份 GCMs DT GCMs DT 1 0.7426 0.9972 0.8346 0.9967 2 0.7736 0.9975 0.8256 0.9947 3 0.7910 0.9981 0.8028 0.9974 4 0.8090 0.9979 0.7859 0.9971 5 0.8041 0.9971 0.7998 0.9979 6 0.7903 0.9983 0.8071 0.9961 7 0.8021 0.9972 0.7800 0.9923 8 0.8062 0.9973 0.7793 0.9961 9 0.7720 0.9973 0.7750 0.9940 10 0.7755 0.9975 0.8042 0.9967 11 0.7695 0.9964 0.7944 0.9953 12 0.7029 0.9962 0.8049 0.9962 Enr Q90 Q10 月份 GCMs DT GCMs DT 1 0.0387 0.0032 0.0360 0.0001 2 0.0293 0.0036 0.0412 0.0011 3 0.0298 0.0029 0.0550 0.0014 4 0.0355 0.0023 0.0604 0.0057 5 0.0366 0.0046 0.0665 0.0026 6 0.0488 0.0035 0.0604 0.0005 7 0.0564 0.0015 0.0750 0.0015 8 0.0586 0.0010 0.0764 0.0040 9 0.0616 0.0021 0.0701 0.0026 10 0.0505 0.0020 0.0496 0.0019 11 0.0408 0.0005 0.0429 0.0002 12 0.0393 0.0011 0.0398 0.0028
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表 5 DT前后未来不同时期不同情景的年降水量变化范围
年份 SSP DT前降水量范围/mm DT后降水量范围/mm 2030—2039年 126 684~1218 376~474 245 673~1236 365~684 370 691~1203 368~670 585 696~1242 354~589 2060—2069年 126 728~1361 387~534 245 738~1299 402~678 370 738~1295 391~741 585 742~1351 394~704 2090—2099年 126 738~1365 395~572 245 765~1388 401~664 370 814~1396 409~860 585 860~1568 449~862
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表 6 DT前后未来不同时期不同情景的年平均气温变化范围
年份 SSP水平 DT前年平均
气温范围/°CDT后年平均
气温范围/°C2030—2039年 126 −6.36~3.18 −0.16~1.42 245 −6.57~3.08 −0.09~2.55 370 −6.39~3.35 −0.14~3.15 585 −6.62~3.56 −0.15~3.39 2060—2069年 126 −5.81~3.48 0.23~3.15 245 −5.12~4.25 0.99~3.90 370 −4.55~4.54 1.28~5.63 585 −3.52~5.38 1.82~5.89 2090—2099年 126 −6.27~3.61 0.21~6.18 245 −3.89~4.74 1.34~4.50 370 −1.64~6.40 1.72~7.73 585 0.53~7.98 3.15~9.35
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