Assessment of the Skill and Source of Decadal Climate Prediction of Warming and Humidification in Northwest China
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摘要:
基于1962-2020年的观测和第六次耦合模式比较计划（CMIP6）中年代际气候预测计划（DCPP）的多模式年代际回报和历史模拟试验数据，本文主要评估了DCPP多模式对我国西北地区近60年来夏季显著暖湿化的年代际预测技巧及其主要来源.对西北变暖的多模式年代际预测技巧（与观测的相关系数）都在0.9以上，较高的预测技巧主要来源于外强迫分量，其贡献可达80%~99%；而受初始化与外强迫的共同作用，对西北变湿的多模式年代际预测技巧存在较大差异，其中多模式初始化分量对预测技巧的贡献可分别达到19%~94%.这表明，对我国西北地区未来短期温度和降水变化的订正预估不仅需要重点考虑外强迫的影响，更需要考虑初始化对降水的影响.
Abstract:Based on observational data from 1962 to 2020 and the multi-model decadal hindcast and historical simulation experiments from the Decadal Climate Prediction Project (DCPP) under the Coupled Model Intercomparison Project Phase 6 (CMIP6), this paper primarily evaluates the interdecadal predictive skill of the significant summer warming and wetting trends in northwestern China over the past 60 years and its main sources. The interdecadal predictive skill of the multi-model ensemble for warming in Northwestern China, as indicated by the correlation coefficient with observations, is above 0.9. The high predictive skill is mainly attributed to the external forcing component, contributing between 80% and 99%. However, due to the combined influence of external forcing and initialization, there is significant variation in the predictive skill for wetting trends. The contribution of initialize to the predictive skill varies widely among models, ranging from 19% to 94%. This suggests that to achieve accurate short-term projections of future temperature and precipitation changes in Northwestern China, it is crucial to consider not only the impact of external forcing but also the influence of initialize on precipitation.
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图 1 西北地区1962-2020年夏季9年平滑的温度和降水时空变化特征
a. 温度距平（℃）；b. 降水距平（mm）；c.温度趋势（℃/10a）；d.降水趋势（mm/10a）；距平相对于1971-2000年.图中加点区域表示p<0.05
Fig. 1. Spatiotemporal characteristics of temperature and precipitation in Northwest China during summer from 1962 to 2020 based on 9-year averages
图 2 DCPP多模式预测的西北地区1962-2020年夏季9年（第2~10年）平滑的温度和降水时空变化特征
a. 温度距平（℃）；b. 降水距平（mm）；c. 温度趋势（℃/10a）；d. 降水趋势（mm/10a）；距平相对于1971-2000年.图a、b中的阴影表示集合平均±1个标准差，图c、d中右上角数值为模式预测趋势与观测趋势的空间相关系数，加点区域表示p<0.05
Fig. 2. Spatiotemporal characteristics of temperature and precipitation in Northwest China during summer from 1962 to 2020 based on 9-year (years 2-10) averages from DCPP multi-model predictions
图 3 DCPP多模式集合平均预测的西北地区1962-2020年夏季9年（第2~10年）平滑温度和降水的预测技巧空间分布
a. 温度（T）预测的ACC和MSSS；b. 降水（Pr）预测的ACC和MSSS.图中加点区域表示p<0.10
Fig. 3. Spatial distribution of predictive skill for temperature and precipitation in Northwest China during summer from 1962 to 2020 based on 9-year (years 2-10) average from DCPP multi-model ensemble mean predictions
图 4 1962-2020年夏季DCPP多模式年代际预测西北地区温度和降水的预测技巧随预测范围的变化
a. 温度预测的潜在技巧；b. 温度预测的实际技巧；c. 降水预测的潜在技巧；d. 降水预测的实际技巧；图中黑色为总技巧，红色为内部变率的技巧，蓝色为外强迫的技巧
Fig. 4. Variation of DCPP multi-model prediction skills for summer temperature and precipitation in Northwest China from 1962 to 2020
图 5 DCPP预测的西北地区1962-2020年夏季9年（第2~10年）平滑温度和降水趋势的模式间差异
a. 温度趋势（℃/10a）；b. 降水趋势（mm/10a）.右上角数值为模式预测趋势与观测趋势的空间相关系数，加点区域表示p<0.05
Fig. 5. Inter-model differences in predicted trends of summer temperature and precipitation in Northwest China from 1962 to 2020 based on 9-year (years 2-10) average from DCPP predictions
图 6 DCPP预测的西北地区1962-2020年夏季9年（第2~10年）平滑的温度和降水
a. 温度趋势（℃/10a）；b. 温度预测泰勒图；c. 降水趋势（mm/10a）；d. 降水预测泰勒图.图a、c中蓝线为最大/小值，绿线为集合平均±标准差
Fig. 6. Predictions of temperature and precipitation in Northwest China during summer from 1962 to 2020 based on 9-year (years 2-10) average from DCPP predictions
图 7 DCPP预测的西北地区1962-2020年夏季9年（第2~10年）平滑温度的预测技巧
a. ACC；b. MSSS.图中加点区域表示p<0.10
Fig. 7. Predicted skill for summer temperature in Northwest China from 1962 to 2020 based on 9-year (years 2-10) average from DCPP predictions
图 8 DCPP预测的西北地区1962-2020年夏季9年（第2~10年）平滑降水的预测技巧
a. ACC；b. MSSS.图中加点区域表示p<0.10
Fig. 8. Predicted skill for summer precipitation in Northwest China from 1962 to 2020 based on 9-year (years 2-10) average from DCPP predictions
图 9 DCPP多模式集合平均对西北地区1962-2020夏季9年（第2~10年）平滑温度的预测技巧分解
a. 预测结果与观测的相关系s数rXY；b. 历史模拟与观测的相关系数rX$ {}_{{}_{\mathrm{u}}} $；c. 初始化分量的技巧ri；d. 外强迫分量的技巧ru；e. 初始化分量与观测的相关系数$ {r}_{X{Y}_{\mathrm{i}}} $；f. 外强迫分量与观测的相关系数$ {r}_{X{Y}_{\mathrm{u}}} $.图中加点区域表示p<0.10
Fig. 9. Predictive skill for summer temperature in Northwest China from 1962 to 2020 based on 9-year (years 2-10) average from DCPP multi-model ensemble mean predictions
图 10 DCPP多模式集合平均对西北地区1962-2020夏季9年（第2~10年）平滑降水的预测技巧分解
a. 预测结果与观测的相关系数rXY；b. 历史模拟与观测的相关系数r$ {}_{{X}_{\mathrm{u}}} $；c. 初始化分量的技巧ri；d. 外强迫分量的技巧ru；e. 初始化分量与观测的相关系数$ {r}_{X{Y}_{\mathrm{i}}} $；f. 外强迫分量与观测的相关系数$ {r}_{X{Y}_{\mathrm{u}}} $.图中加点区域表示p<0.10
Fig. 10. Predictive skill for summer precipitation in Northwest China from 1962 to 2020 based on 9-year (years 2-10) average from DCPP multi-model ensemble mean predictions
图 11 DCPP多模式对西北地区1962-2020年夏季9年(第2~10年)平滑温度的预测技巧分解
a.初始化分量的技巧ri; b.外强迫分量的技巧ru; c.预测结果与观测的相关系数rXY右上角数值为ri或ru在rXY>0区域的占比, 图中加点区域表示p<0.10
Fig. 11. Predicted skill for summer temperature in Northwest China from 1962 to 2020 based on 9-year (years 2-10) average from DCPP predictions
图 12 DCPP多模式对西北地区1962-2020年夏季9年(第2~10年)平滑降水的预测技巧分解
a.初始化分量的技巧ri; b.外强迫分量的技巧ru; c.预测结果与观测的相关系数rXY.右上角为ri或ru在rXY>0区域的占比, 图中加点区域表示p<0.10
Fig. 12. Predicted skill for summer precipitation in Northwest China from 1962 to 2020 based on 9-year (years 2-10) average from DCPP predictions
表 1 CMIP6年代际气候预测计划试验数据
Table 1. CMIP6 Decadal Climate Prediction Project experimental data
模式 Hindcast Historical、SSP245 分辨率 BCC-CSM2-MR 8 1 160×320 CanESM5 40 50 64×128 CMCC-CM2-SR5 20 1 192×288 EC-Earth3 10 23 256×512 FGOALS-f3-L 9 1 180×288 IPSL-CM6A-LR 10 11 143×144 MIROC6 10 50 128×256 MPI-ESM1-2-LR 16 30 96×192 合计 123 167 
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