气候变暖背景下中国风速（能）变化及其影响因子研究
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摘要
本文采用均一化的540个气象台站风速观测数据以及再分析数据利用统计诊断等方法对近40年来中国近地层风速的变化特征进行了全面和系统的研究、对比。其次根据Weibull分布模型研究了中国日平均风速的概率分布,据此计算并分析了1971-2007年中国平均风能密度的时空分布及变化特征。然后主要从大气环流变化的角度对中国区域近地层风速多时间尺度变化的原因进行了探讨。最后,评估了国际耦合模式比较计划5(CMIP5)最新的9个大气海洋耦合模式(AOGCMs)对中国1971-2005年平均风速及其变化的模拟能力并对未来风速变化特征进行预估。主要结论概况如下：
(1)1971-2007年间,全国大部分地区年平均风速呈下降趋势,春季风速和风速高百分位的下降幅度更明显。空间分布上,东南沿海岛屿和东北地区风速减弱趋势最明显。均一化风速资料的挑选会给平均风速时间变化趋势的计算带来影响,需引起重视。风速观测资料和NCEP/NCAR以及ERA-40再分析产品在空间上呈现高度一致性,但后者低估了观测风速值的大小,其无明显变化趋势。
(2) Weibull分布以函数形式表示概率密度,克服了用样本频率不可避免的随机振荡,能较好地描述中国日平均风速呈现的偏态分布,风能密度的变化同风速变化一致。若不进行风速观测资料的均一性检验,年和各季节的平均风能密度的下降趋势偏弱。
(3)大气环流的变化是中国风速呈显著减小趋势的主要原因。理由包括：a)对流层中下层风速均呈减弱趋势；b)作为风速的驱动器—气压梯度在中低层近几十年来呈现下降趋势；c)亚洲冬、夏季风减弱,经向环流减弱；d)冬(夏)季欧亚大陆海平面气压下降(上升),使东西向的海陆气压梯度减弱；e)我国北方地区纬向风垂直切变减弱,大气稳定度增加,高空自由大气动量下传效应逐渐减弱。
(4)在年际尺度上,北极涛动(AO)与我国风速呈负相关,受AO影响的区域主要集中在30°N以北的地区。冬季AO异常正位相时,东亚西风急流、500hPa位势高度场、对流层低层风场以及海平面气压场均表现出有利于风速减弱的分布形势。春季,(80-100°E,50～65°N)区域500hPa平均高度场对地面风速有强烈负影响。
(5) AOGCMs的初始化条件对1971-2005年风速输出及其时间变率模拟的影响很小,但每个模式模拟的风速均表现出平均值的正偏差、年际变化的负偏差。所有模式都不能很好地模拟出中国近地层风速下降的事实,但至少重现了中国风速的季节变率。2066-2100年风速的时间序列以及季节变率的空间分布与1971-2005年风速的模拟高度一致。模式预估的未来平均风速并不依赖于辐射强迫的大小,与风速在当代的模拟输出值也并无关联。未来风速气候变化的信号远小于不同模式对风速模拟的结果之间的差异。
First of all, temporal trends (1971to2007) in10-m wind speeds from homogeneous observational data sets from540weather stations and reanalysis data sets are quantified and compared. Then, the probability distribution of daily average wind speed and average energy density in mainland of China are studied by using Weibull distribution model. Thirdly, possible physical causes of multi-time scale changes in near surface wind speeds are investigated in terms of large-scale atmospheric circulation primarily. Finally, The ability of current generation coupled Atmosphere-Ocean General Circulation Models (AOGCMs), released by Coupled Model Intercomparison Project Phase5(CMIP5), to accurately simulate the near-surface wind climate over China is evaluated by comparing output from the historical period (1971-2005) with an observational data set and reanalysis output. Also, Outputs for the current century from the same AOGCMs are examined relative to the contemporary wind climate. The main conclusions are summed up as follows:
(1) Annual mean wind speeds computed from in situ measurements of daily mean wind speeds exhibit declining trends over much of the country during the period1971-2007. The trend is of larger magnitude in the upper percentiles of the wind speed probability distribution and during the spring months. The downward trend of wind speed is greast in the south-east coastal islands and the Northeast. It is worthy of note that there will be different temporal trends if homogeneity test is not performed for observerd wind speeds. Intercomparison of direct in situ observations and those from the NCEP/NCAR and ERA-40reanalysis data sets indicates the patterns exhibit a high degree of spatial similarity. However, data from the ERA-40reanalysis reanalysis are negatively biased and exhibit little trend.
(2) Weibull distribution is better to describe the skewness and kurtosis of wind speed probability than normal distribution, overcoming the inevitable random oscillation caused by sample frequency. The geographical distribution of the average wind power density and its variation is consistent with wind speed correspondingly. The declining trends of annual and seasonal wind energy are weaker before rejecting inhomogeneous wind speed data sets.
(3) The decreased wind speed over China is mainly due to the change of lare-scale atmospheric circulation because:a) the wind speed in mid-low troposphere consistently show weakening trend and the spatial distribution of the trend is highly consistent with the near-surface wind speed; b) as the major driver of wind speed, the pressure gradient in surface and mid-low troposphere exhibit downward trend; c) Asian monsoon and Asian meridional circulation index are weakened; d) decreasing (increasing) sea level pressure in Eurasia in winter (summer) leads to the declining of zonal pressure gradient between the land and sea; e) in north China, weakend vertical zonal wind shear results in increased atmospheric stability and further air momentum down from upper levels is becoming weak.
(4) In terms of the interannual scale, the Arctic Oscillation (AO) has significant influence on wind speed over north of30°N. During wintertime, under the background of positive AO phases, the patterns of East Asia westerly jet,500hPa height field, wind field at lower levels and sea-level pressure are favorable to weaker wind speeds. During winter season, average of500hPa height field over (80～100°E,50～65°N) has negative impact on near-surface wind speed.
(5) The AOGCM initialization condition has little influence on the simulated wind speed and temporal variability during1971to2005, however each of the CMIP-5generation AOGCMs considered display both positive bias in mean near-surface wind speeds and negative bias in the inter-annual variability relative to reanalysis output and observations and no AOGCM exhibit uniformly best agreement with either the reanalysis products or the in situ observations. Some AOGCMs reproduce at least some aspects of the seasonality of wind speeds over China. The spatially averaged and spatial fields of seasonal wind speeds for2066-2100exhibit very close accord with simulations from the AOGCM for the historical period (1971-2005). The mean wind speeds from each model computed for2066to2100do not show a substantial, consistent dependence on the degree of radiative forcing or the simulated mean wind speed during the historical period. Thus, any climate change signal is considerably smaller than the discrepancies between the different AOGCMs during the historical period.
(1)1971-2007年间,全国大部分地区年平均风速呈下降趋势,春季风速和风速高百分位的下降幅度更明显。空间分布上,东南沿海岛屿和东北地区风速减弱趋势最明显。均一化风速资料的挑选会给平均风速时间变化趋势的计算带来影响,需引起重视。风速观测资料和NCEP/NCAR以及ERA-40再分析产品在空间上呈现高度一致性,但后者低估了观测风速值的大小,其无明显变化趋势。
(2) Weibull分布以函数形式表示概率密度,克服了用样本频率不可避免的随机振荡,能较好地描述中国日平均风速呈现的偏态分布,风能密度的变化同风速变化一致。若不进行风速观测资料的均一性检验,年和各季节的平均风能密度的下降趋势偏弱。
(3)大气环流的变化是中国风速呈显著减小趋势的主要原因。理由包括：a)对流层中下层风速均呈减弱趋势；b)作为风速的驱动器—气压梯度在中低层近几十年来呈现下降趋势；c)亚洲冬、夏季风减弱,经向环流减弱；d)冬(夏)季欧亚大陆海平面气压下降(上升),使东西向的海陆气压梯度减弱；e)我国北方地区纬向风垂直切变减弱,大气稳定度增加,高空自由大气动量下传效应逐渐减弱。
(4)在年际尺度上,北极涛动(AO)与我国风速呈负相关,受AO影响的区域主要集中在30°N以北的地区。冬季AO异常正位相时,东亚西风急流、500hPa位势高度场、对流层低层风场以及海平面气压场均表现出有利于风速减弱的分布形势。春季,(80-100°E,50～65°N)区域500hPa平均高度场对地面风速有强烈负影响。
(5) AOGCMs的初始化条件对1971-2005年风速输出及其时间变率模拟的影响很小,但每个模式模拟的风速均表现出平均值的正偏差、年际变化的负偏差。所有模式都不能很好地模拟出中国近地层风速下降的事实,但至少重现了中国风速的季节变率。2066-2100年风速的时间序列以及季节变率的空间分布与1971-2005年风速的模拟高度一致。模式预估的未来平均风速并不依赖于辐射强迫的大小,与风速在当代的模拟输出值也并无关联。未来风速气候变化的信号远小于不同模式对风速模拟的结果之间的差异。
First of all, temporal trends (1971to2007) in10-m wind speeds from homogeneous observational data sets from540weather stations and reanalysis data sets are quantified and compared. Then, the probability distribution of daily average wind speed and average energy density in mainland of China are studied by using Weibull distribution model. Thirdly, possible physical causes of multi-time scale changes in near surface wind speeds are investigated in terms of large-scale atmospheric circulation primarily. Finally, The ability of current generation coupled Atmosphere-Ocean General Circulation Models (AOGCMs), released by Coupled Model Intercomparison Project Phase5(CMIP5), to accurately simulate the near-surface wind climate over China is evaluated by comparing output from the historical period (1971-2005) with an observational data set and reanalysis output. Also, Outputs for the current century from the same AOGCMs are examined relative to the contemporary wind climate. The main conclusions are summed up as follows:
(1) Annual mean wind speeds computed from in situ measurements of daily mean wind speeds exhibit declining trends over much of the country during the period1971-2007. The trend is of larger magnitude in the upper percentiles of the wind speed probability distribution and during the spring months. The downward trend of wind speed is greast in the south-east coastal islands and the Northeast. It is worthy of note that there will be different temporal trends if homogeneity test is not performed for observerd wind speeds. Intercomparison of direct in situ observations and those from the NCEP/NCAR and ERA-40reanalysis data sets indicates the patterns exhibit a high degree of spatial similarity. However, data from the ERA-40reanalysis reanalysis are negatively biased and exhibit little trend.
(2) Weibull distribution is better to describe the skewness and kurtosis of wind speed probability than normal distribution, overcoming the inevitable random oscillation caused by sample frequency. The geographical distribution of the average wind power density and its variation is consistent with wind speed correspondingly. The declining trends of annual and seasonal wind energy are weaker before rejecting inhomogeneous wind speed data sets.
(3) The decreased wind speed over China is mainly due to the change of lare-scale atmospheric circulation because:a) the wind speed in mid-low troposphere consistently show weakening trend and the spatial distribution of the trend is highly consistent with the near-surface wind speed; b) as the major driver of wind speed, the pressure gradient in surface and mid-low troposphere exhibit downward trend; c) Asian monsoon and Asian meridional circulation index are weakened; d) decreasing (increasing) sea level pressure in Eurasia in winter (summer) leads to the declining of zonal pressure gradient between the land and sea; e) in north China, weakend vertical zonal wind shear results in increased atmospheric stability and further air momentum down from upper levels is becoming weak.
(4) In terms of the interannual scale, the Arctic Oscillation (AO) has significant influence on wind speed over north of30°N. During wintertime, under the background of positive AO phases, the patterns of East Asia westerly jet,500hPa height field, wind field at lower levels and sea-level pressure are favorable to weaker wind speeds. During winter season, average of500hPa height field over (80～100°E,50～65°N) has negative impact on near-surface wind speed.
(5) The AOGCM initialization condition has little influence on the simulated wind speed and temporal variability during1971to2005, however each of the CMIP-5generation AOGCMs considered display both positive bias in mean near-surface wind speeds and negative bias in the inter-annual variability relative to reanalysis output and observations and no AOGCM exhibit uniformly best agreement with either the reanalysis products or the in situ observations. Some AOGCMs reproduce at least some aspects of the seasonality of wind speeds over China. The spatially averaged and spatial fields of seasonal wind speeds for2066-2100exhibit very close accord with simulations from the AOGCM for the historical period (1971-2005). The mean wind speeds from each model computed for2066to2100do not show a substantial, consistent dependence on the degree of radiative forcing or the simulated mean wind speed during the historical period. Thus, any climate change signal is considerably smaller than the discrepancies between the different AOGCMs during the historical period.
引文
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