Based on near-term climate simulations for IPCC-AR5 （The Fifth Assessment Report）, probabilistic multimodel ensemble prediction （PMME） of decadal variability of surface air temperature in East Asia （20°-50&#...Based on near-term climate simulations for IPCC-AR5 （The Fifth Assessment Report）, probabilistic multimodel ensemble prediction （PMME） of decadal variability of surface air temperature in East Asia （20°-50°N, 100°- 145°E） was conducted using the multivariate Gaussian ensemble kernel dressing （GED） methodology. The ensemble system exhibited high performance in hindcasting the deeadal （1981-2010） mean and trend of temperature anomalies with respect to 1961-90, with a RPS of 0.94 and 0.88 respectively. The interpretation of PMME for future decades （2006-35） over East Asia was made on the basis of the bivariate probability density of the mean and trend. The results showed that, under the RCP4.5 （Representative Concentration Pathway 4.5 W m-2） scenario, the annual mean temperature increases on average by about 1.1-1.2 K and the temperature trend reaches 0.6-0.7 K （30 yr）-1. The pattern for both quantities was found to be that the temperature increase will be less intense in the south. While the temperature increase in terms of the 30-yr mean was found to be virtually certain, the results for the 30-yr trend showed an almost 25% chance of a negative value. This indicated that, using a multimodel ensemble system, even if a longer-term warming exists for 2006-35 over East Asia, the trend for temperature may produce a negative value. Temperature was found to be more affected by seasonal variability, with the increase in temperature over East Asia more intense in autumn （mainly）, faster in summer to the west of 115°E, and faster still in autumn to the east of 115°E.展开更多
There are well coherences between annual averaged air temperatures at every meteorological station along the Qinghai-Xizang railway, and its 10-year moving average correlation coefficient is 0.92. Thus, the regional a...There are well coherences between annual averaged air temperatures at every meteorological station along the Qinghai-Xizang railway, and its 10-year moving average correlation coefficient is 0.92. Thus, the regional averaged annual mean temperature series along the Qinghai-Xizang railway (Trw) from 1935 to 2000 are constructed. The investigation is suggested that: Trw had significant responses to the 5-year lagged sunspot cycle length (SCL) and 15-year lagged concentration of atmospheric carbon dioxide (CO2), and the correlation coefficients between them are -0.76 (SCL) and 0.88 (CO2), respectively. The future SCL is predicted by the model of average generated function constructed with its main cycles of 76a, 93a, 108a, 205a and 275a. The result shows that the SCL would be becoming longer in the first half of the 21st century, and then it could be becoming shorter in the second half of the 21st century. Based on the natural change of SCL and the effect of double CO2 concentration, Trw in the 21st century is forecasted. It could warm up about 0.50℃ in the first half of the 21st century compared with the last decade of last century. The mean maximum air temperature could be likely about 0.20℃ in July and from 0.40℃ to 1.10℃ in January. The annual air temperature difference would likely reduce 0.3-1.00℃. The probability of above predictions ranges from 0.64 to 0.73.展开更多
利用1979—2015年中国国家气候中心整编的160站月平均气温和NCEP/NCAR全球大气再分析资料,从1979/1980—2008/2009年冬季前期500 h Pa高度场、200 h Pa势函数和850 h Pa势函数场选择预测因子,考虑不同时效因子的组合及其独立性,综合应...利用1979—2015年中国国家气候中心整编的160站月平均气温和NCEP/NCAR全球大气再分析资料,从1979/1980—2008/2009年冬季前期500 h Pa高度场、200 h Pa势函数和850 h Pa势函数场选择预测因子,考虑不同时效因子的组合及其独立性,综合应用多因子回归集合、交叉检验集合、逐月滚动集合,建立了针对中国冬季气温的逐月滚动预测模型,并利用该模型对2010/2011—2014/2015年冬季气温进行了独立预测试验和检验。结果表明,综合运用多种集合可提高短期气候客观定量预测的可行性和稳定性。多因子回归集合能增加可预测站点数,交叉检验集合可减少因统计关系不稳定而产生的对预报效果的影响,逐月滚动集合的应用不仅增加了可预测站点数,而且使预测效果更加稳定。本文建立的预测模型可对中国冬季气温进行长时效的预测,且有一定的预报技巧,对实际的季节预测业务有重要应用价值。展开更多
基金supported by the National Key Basic Research and Development (973) Program of China (Grant No. 2012CB955204)the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)the Research open-fund of Jiangsu Meteorology Bureau (Grant Nos. Q201205, KM201107, and K201009)
文摘Based on near-term climate simulations for IPCC-AR5 （The Fifth Assessment Report）, probabilistic multimodel ensemble prediction （PMME） of decadal variability of surface air temperature in East Asia （20°-50°N, 100°- 145°E） was conducted using the multivariate Gaussian ensemble kernel dressing （GED） methodology. The ensemble system exhibited high performance in hindcasting the deeadal （1981-2010） mean and trend of temperature anomalies with respect to 1961-90, with a RPS of 0.94 and 0.88 respectively. The interpretation of PMME for future decades （2006-35） over East Asia was made on the basis of the bivariate probability density of the mean and trend. The results showed that, under the RCP4.5 （Representative Concentration Pathway 4.5 W m-2） scenario, the annual mean temperature increases on average by about 1.1-1.2 K and the temperature trend reaches 0.6-0.7 K （30 yr）-1. The pattern for both quantities was found to be that the temperature increase will be less intense in the south. While the temperature increase in terms of the 30-yr mean was found to be virtually certain, the results for the 30-yr trend showed an almost 25% chance of a negative value. This indicated that, using a multimodel ensemble system, even if a longer-term warming exists for 2006-35 over East Asia, the trend for temperature may produce a negative value. Temperature was found to be more affected by seasonal variability, with the increase in temperature over East Asia more intense in autumn （mainly）, faster in summer to the west of 115°E, and faster still in autumn to the east of 115°E.
文摘There are well coherences between annual averaged air temperatures at every meteorological station along the Qinghai-Xizang railway, and its 10-year moving average correlation coefficient is 0.92. Thus, the regional averaged annual mean temperature series along the Qinghai-Xizang railway (Trw) from 1935 to 2000 are constructed. The investigation is suggested that: Trw had significant responses to the 5-year lagged sunspot cycle length (SCL) and 15-year lagged concentration of atmospheric carbon dioxide (CO2), and the correlation coefficients between them are -0.76 (SCL) and 0.88 (CO2), respectively. The future SCL is predicted by the model of average generated function constructed with its main cycles of 76a, 93a, 108a, 205a and 275a. The result shows that the SCL would be becoming longer in the first half of the 21st century, and then it could be becoming shorter in the second half of the 21st century. Based on the natural change of SCL and the effect of double CO2 concentration, Trw in the 21st century is forecasted. It could warm up about 0.50℃ in the first half of the 21st century compared with the last decade of last century. The mean maximum air temperature could be likely about 0.20℃ in July and from 0.40℃ to 1.10℃ in January. The annual air temperature difference would likely reduce 0.3-1.00℃. The probability of above predictions ranges from 0.64 to 0.73.
文摘利用1979—2015年中国国家气候中心整编的160站月平均气温和NCEP/NCAR全球大气再分析资料,从1979/1980—2008/2009年冬季前期500 h Pa高度场、200 h Pa势函数和850 h Pa势函数场选择预测因子,考虑不同时效因子的组合及其独立性,综合应用多因子回归集合、交叉检验集合、逐月滚动集合,建立了针对中国冬季气温的逐月滚动预测模型,并利用该模型对2010/2011—2014/2015年冬季气温进行了独立预测试验和检验。结果表明,综合运用多种集合可提高短期气候客观定量预测的可行性和稳定性。多因子回归集合能增加可预测站点数,交叉检验集合可减少因统计关系不稳定而产生的对预报效果的影响,逐月滚动集合的应用不仅增加了可预测站点数,而且使预测效果更加稳定。本文建立的预测模型可对中国冬季气温进行长时效的预测,且有一定的预报技巧,对实际的季节预测业务有重要应用价值。
