Assessment of the Spring Sensible Heat Flux over the Central and Eastern Tibetan Plateau Simulated by CMIP6 Multi-models
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摘要: 利用青藏高原（以下简称高原）气象台站常规观测资料、国家青藏高原科学数据中心的青藏高原地气相互作用过程高分辨率（逐小时）综合观测数据集（2005～2016）、国际耦合模式比较计划第六阶段（CMIP6）的历史模拟试验数据和卫星辐射资料，定量评估了12个全球气候模式对1979～2014年高原中东部地表感热通量的模拟能力，并对其模拟偏差进行了成因分析。结果表明，CMIP6模式可较好地重现高原地表感热通量的年循环和季节平均的空间分布型，但数值较计算感热通量偏低，主要表现为对感热通量大值区严重低估。区域平均而言，12个模式模拟的春季高原中东部感热通量的时间演变序列整体较计算感热通量偏低，其中偏差最大的模式为MIROC6，其多年均值仅为计算值的1/3左右。进一步分析发现多模式模拟的春季高原10 m高度处风速和地气温差分别偏强和偏弱，说明CMIP6模拟的春季高原感热通量偏低可主要归因于地气温差的模拟冷偏差。地气温差的模拟冷偏差在高原中东部地区普遍存在，且地表温度和空气温度均存在明显冷偏差，尤其地表温度偏差更大，这很大程度上可能与CMIP6多模式模拟的春季高原降水偏强有关。Abstract: On the basis of historical observations at 77 meteorological stations and a long-term dataset of integrated land–atmosphere interaction observations on the Tibetan Plateau (TP) (2005–2016), the historical simulations of the 12 models that participated in CMIP6 (the sixth phase of the coupled model intercomparison project), and GEWEX-SRB satellite radiation products, the authors have quantitatively examined the ability of CMIP6 models to simulate the surface sensible heat flux over the TP during 1979–2014 and analyzed the possible causes of simulation biases. The results show that CMIP6 models can well reproduce the annual cycle and seasonal spatial patterns of the sensible heat over the TP, albeit with lower amplitudes than the calculated sensible heat flux, particularly showing obvious underestimation over the strong, sensible heat regions. The area-weighted long-term spring sensible heat fluxes over the central and eastern TP simulated by the 12 models are generally lower than calculated values, with the minimum sensible heat amplitude in the MIROC6 simulation, which has approximately 1/3 of the climatological amplitude in calculated sensible heat flux. Furthermore, the authors find that the wind speed at 10-m height and the springtime land–air temperature difference simulated by models are larger and smaller than the calculated values, respectively, implying that the lower sensible heat amplitudes simulated by CMIP6 multi-models are mainly due to the cold biases of the land–air temperature difference. Spatially, the cold biases of the land–air temperature difference widely exist over the central and eastern TP, in which, more specifically, the surface and air temperatures show the cold biases but with colder biases in surface temperature. The cold biases mechanistically are likely related to the simulated stronger precipitation over the TP in CMIP6 models.
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Key words:
- Tibetan Plateau /
- CMIP6 models /
- Sensible heat flux /
- Land–air temperature difference /
- Cold bias
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图 1 高原80个常规气象台站（黑色实心点）和6个最新的综合观测台站（红色五角星）地理位置分布。彩色阴影表示地形高度（单位：m），蓝色框区域（27°～39°N，85°～105°E）为下文中CMIP6模拟数据的区域平均范围，红色框内是互相做对比的两测站位置
Figure 1. Geographical distributions of the 80 meteorological stations (black solid dots) and the six latest integrated observation stations (red stars) on the Tibetan Plateau (TP). Colored shadings indicate terrain height (units: m), the blue box indicates the regional average range (27°–39°N, 85°–105°E) of the CMIP6 (the sixth phase of the Coupled Model Intercomparison Project) simulations below, and the red box shows the positions of the two stations being compared to each other
图 2 高原高分辨率综合观测数据集（红线）与Duan2018（黑线）的5个对应测站地表感热通量（单位：W m−2）的逐月时间演变。左下角数字为两条序列的相关系数
Figure 2. Temporal evolutions of sensible heating flux (units: W m−2) at the corresponding five stations for the high-resolution integrated observational dataset (red lines) and Duan2018 (black lines). The correlation coefficients of the two sequences are shown in the bottom left corner of the figures
图 3 1979～2014年气候平均的高原中东部地表感热通量的年循环序列。黑色实线为77个测站平均，即Duan2018，12条虚线分别为12个模式的区域（27°～39°N，85°～105°E）平均，红色实线则为12条虚线的中位数
Figure 3. Annual cycle of the climatological mean sensible heating flux over the central and eastern TP during 1979–2014. The black and red solid lines represent the sensible heating flux of the 77-station average (Duan2018) and median of the 12-CMIP6 modes, respectively. The other 12 dashed lines indicate the regional (27°–39°N, 85°–105°E) averaged sensible heating flux of the 12 models
图 4 1979～2014年平均的高原中东部（a、c）Duan2018和（b、d）多模式模拟的（a、b）春季、（c、d）夏季高原感热通量的空间分布（单位：W m−2）
Figure 4. Spatial distributions of the (a, b) spring and (c, d) summer mean sensible heating flux (units: W m−2) over the central and eastern TP for the (a, c) Duan2018 and (b, d) CMIP6 multi-models during 1979–2014
图 5 1979～2014年春季观测、模拟的高原中东部（a）感热通量、（b）10 m风速和（c）地气温差的时间演变序列。黑色实线为Duan2018，红色实线为所有模式序列的中位数，其余曲线分别为12个模式的模拟结果
Figure 5. Temporal evolutions of the (a) sensible heating flux, (b) wind speed at 10-m height, and (c) land–air temperature differences for observations (Duan2018) and multi-models during 1979–2014. The black and red solid lines indicate the elements of Duan2018 and the median of the multi-models, respectively, the other 12 dashed lines indicate the regional averaged elements of the 12 models
图 6 1979～2014年12个模式模拟结果与观测在感热通量（红色柱）、风速（绿色柱）、地气温差（黄色柱）和系数C（灰色柱）上的偏差的相对变化
Figure 6. Relative variations in the deviation between the 12-models simulations and observation for sensible heating flux (red bars), wind speed (green bars), land–air temperature difference (yellow bars), and coefficient C (gray bars) during 1979–2014
图 7 1979～2014年观测（左）和CMIP6模式集合平均（右）的春季高原中东部（a、d）地气温差、（b、e）地表温度和（c、f）气温的空间分布
Figure 7. Spatial distributions of the (a, d) land–air temperature difference, (b, e) surface temperature, and (c, f) air temperature over the central and eastern TP for the observation (left) and ensemble mean of CMIP6 models (right) during 1979–2014
图 8 1979～2014年平均的（a、c）观测和（b、d）CMIP6多模式模拟的春季高原（a、b）地表净短波辐射通量（来自GEWEX-SRB卫星辐射资料，单位：W m−2）和（c、d）降水量距平（单位：mm d−1）的空间分布
Figure 8. Spatial distributions of the spring mean (a, b) net shortwave radiation flux (from the GEWEX-SRB dataset, units: W m−2) and (c, d) precipitation anomalies (units: mm d−1) over the central and eastern TP for the (a, c) observations and (b, d) CMIP6 multi-model simulations during 1979–2014
表 1 本文使用的12个模式的名称、国家、模拟集合数、分辨率和参考文献
Table 1. List of 12 models used in this study, including the model names, countries, numbers of ensembles, resolutions, and data references
模式名称 国家 模拟集合数 分辨率 参考文献 BCC-CSM2-MR 中国 3 160×320 Xin et al., 2018 BCC-ESM1 中国 3 64×128 Wu et al., 2020 CESM2 美国 10 192×288 Danabasoglu et al., 2020 CESM2-WACCM 美国 3 192×288 Danabasoglu, 2019 CNRM-CM6-1 法国 10 128×256 Voldoire et al., 2019 CNRM-ESM2-1 法国 5 128×256 Séférian et al., 2019 GISS-E2.1G 美国 10 90×144 NASA Goddard Institute for Space Studies (NASA/GISS), 2018b GISS-E2.1H 美国 10 90×144 NASA Goddard Institute for Space Studies (NASA/GISS), 2018a IPSL-CM6A-LR 法国 31 143×144 BoucherO2020 MIROC6 日本 10 128×256 Tatebe et al., 2019 MRI-ESM2.0 日本 5 160×320 Yukimoto2019 UKESM1.0-LL 英国 6 144×192 Tang2019 
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表 2 高原高分辨率综合观测数据集与Duan2018中对应站点的相关信息，包括站点名称，经、纬度及对应测站间的直线距离
Table 2. List of the stations in the high-resolution integrated observational dataset and Duan2018, including the station names, latitude, longitude, and the straight-line distance between the two corresponding stations
综合观测数据集 Duan2018 站点名称 纬度（°N） 经度（°E） 站点名称 纬度（°N） 经度（°E） 两站点直线距离/km BJ 31.37 91.90 Nagqu 31.29 92.04 16 QOMS 28.36 86.95 Dingri 28.38 87.05 10 SETORS 29.77 94.73 Linzhi 29.40 94.20 65 NADORS 33.39 79.70 Shiquanhe 32.30 80.05 125 NAMORS 30.77 90.98 Tangxiong 30.29 91.06 54
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表 3 1979～2014年观测、12个模式及12个模式平均计算所得高原中东部区域春季平均感热通量（单位：W m−2）、感热通量年际变率（单位：W m−2）、10 m风速（单位：m s−1）和地气温差（单位：°C）的气候态
Table 3. Climatological mean of the spring sensible heating flux (units: W m−2) and its interannual variability (units: W m−2), wind speed (units: m s−1) at 10-m height, and land–air temperature differences (units: °C) obtained from observations, 12-models simulations, mean of 12-models simulations over the central and eastern during 1979–2014
感热通量/W m−2 感热通量年际变率/W m−2 10 m风速/m s−1 地气温差/°C 观测 62.86 1.90 2.73 4.52 BCC-CSM2-MR 32.25 1.68 5.66 0.49 BCC-ESM1 35.39 1.67 4.64 0.82 CESM2 47.69 3.22 3.58 1.49 CESM2-WACCM 47.77 1.56 3.57 1.53 CNRM-CM6-1 43.16 4.33 3.46 0.39 CNRM-ESM2-1 46.56 1.42 3.46 0.61 GISS-E2.1G 53.47 5.23 3.12 0.02 GISS-E2.1H 41.20 3.13 3.43 0.14 IPSL-CM6A-LR 37.75 1.72 4.67 1.75 MIROC6 21.29 0.89 2.79 0.94 MRI-ESM2.0 35.12 1.49 5.90 0.57 UKESM1.0-LL 48.36 1.09 2.39 2.20 12个模式的中位数 41.88 1.64 3.53 0.76
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