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1.
年际增量方法在西南夏季降水预测中的应用 总被引:1,自引:0,他引:1
利用中国西南地区80站逐月降水资料及NCEP/NCAR再分析资料等,采用降水预测新方法——年际增量法,考察影响中国西南地区夏季降水年际增量的前期冬、春季大气环流年际增量状况,并选取5个关键影响因子,采用多元回归法建立中国西南夏季降水年际增量预测模型。对降水年际增量进行预测,在1971—2010年的建模阶段,预测模型的拟合率为0.78,在2011—2017的后报检验7年中,有6年与实况值同位相。后报检验2011—2017年的降水距平百分率,均方根误差为16%。为考察对降水异常分布型的预报效果,逐站建立回归方程,并进行趋势预报检验,近5年的趋势异常综合评分高于发布预测,预报效果较好。因此,该方法的应用及模型的建立对提高西南地区夏季降水预测水平有重要意义。 相似文献
2.
陕西汛期降水年际增量预测新技术研究 总被引:1,自引:3,他引:1
应用年际增量预测方法,通过分析影响陕西汛期降水的物理机制,建立了具有较高预测效能的陕西汛期降水年际增量预测模型。研究表明,赤道太平洋中东部海温年际增量、500 hPa高度年际增量与陕西汛期降水具有很好的相关性。当前一年秋、冬季赤道太平洋中东部海温增量在南北方向上表现为“-+-”分布型时,陕西当年汛期降水偏多,反之,陕西当年汛期降水偏少。当前一年秋、冬季500 hPa高度年际增量在赤道附近呈带状正值分布时,陕西当年汛期降水偏多;呈带状负值分布时,陕西当年汛期降水偏少。国家气候中心提供的74项环流特征量、陕西省0 cm地温增量因子与陕西汛期降水也有很好的相关关系。在对预测因子物理意义分析的基础上,用逐步回归方法引入因子,建立陕西10个气候区域的汛期(6—8月)降水总量和各分月(6、7、8月)的降水年际增量预测模型(共40个),汛期降水总量预测模型交叉检验距平同号率达78.4%。对2010—2013年汛期降水总量和各分月降水量进行试报,其准确率PS评分分别达到75.8和66分。增量预测方法具有较强的预测能力,能够在一定程度上提高陕西汛期降水预测水平,可作为有效方法投入实际业务应用。 相似文献
3.
利用1961—2010年重庆34个气象观测站夏季降水资料及国家气候中心130项环流指数,采用机器学习的决策树和随机森林方法建立重庆夏季旱涝预测模型,通过2011—2018年预测效果检验发现,夏季同期环流指数决策树模型和前冬海温指数决策树模型预测的8 a降水异常趋势均正确,比考虑单一指数的PC评分分别提高37.5%和12.5%。此外,用随机森林模型预测重庆2014—2018年的夏季降水,5 a平均PS、CC和PC评分分别是84.6、0.27和67.1,相比于业务发布预报质量均有明显提高,且随机森林的预测质量较为稳定。 相似文献
4.
淮河流域夏季极端降水事件的统计预测模型研究 总被引:2,自引:1,他引:2
采用年际增量预测方法, 通过考察与淮河流域夏季极端降水事件发生频次(HRF)年际增量相关的环流, 确定了5个预测因子:冬季北太平洋涛动、12月南极涛动、春季3~4月南印度洋气压、春季3~4月白令海气压、春季3~4月印尼—澳洲附近经向风垂直切变;然后利用这5个预测因子, 通过多元线性回归方法建立HRF年际增量的预测模型, 进而预测HRF。交叉检验表明, 在1962~2005年的后报中, 这个预测模型对HRF显示了较高的预测技巧, 预测结果与实测间的相关系数为0.67, 表现出较高的预测潜力, 对淮河流域夏季极端降水事件的预测具有较大的应用价值。 相似文献
5.
利用1980—2016年第二松花江流域(SSR)夏季(6—8月)平均降水量资料、NCEP/NCAR再分析月平均环流场资料、NOAA的月平均海温场资料,采用年际增量预测方法,通过分析与SSR夏季降水年际增量相关的环流及海温,确定了超前12个月内的6个预测因子,包括:11月东亚200 hPa纬向风、12月西藏高原-2指数、12月赤道中东太平洋200 hPa纬向风、2月印度洋海温、10月西太平洋暖池海温、4月东亚100 hPa经向风。在此基础上利用这6个预测因子,利用1980—2010资料建立SSR夏季降水年际增量的统计预测模型,最后根据年际增量给出SSR夏季降水的预测结果。经检验,1981—2010年SSR夏季降水年际增量的预测拟合系数是0.83,SSR夏季降水预测结果拟合系数为0.67,SSR夏季降水预测结果相对均方根误差为15%,均通过了显著性检验;对2011—2016年进行试报实验,该模型也很好地预测出降水的年际增量变化趋势,除2014年以外,SSR夏季降水预测结果相对均方根误差绝对值都控制在23%以内,2016年仅为-9.9%。因此,通过预测降水的年际增量,进而再预测降水的方法,具... 相似文献
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利用广西87个气象站6月月平均降水量及NCEP/NCAR再分析资料,通过普查1960—2021年广西6月月降水量年际增量与前期500 hPa位势高度场的相关性,选取影响广西6月降水异常相关性较高的前期预测因子,研究其主要影响机制,并采用模糊神经网络与熵度量相结合的方法构建月降水年际增量的集合预报模型,对预测模型进行1960—2013年的拟合检验和2014—2021年的独立样本预报检验。结果发现,该模型的预测准确率较高,独立样本的回报年份同号率为87.5%,拟合平均绝对误差为26.64 mm,拟合平均相对误差为9.06%,预报效果优于利用逐步回归方法构建的预测模型,而且模型性能比较稳定,具有较好的业务应用前景。 相似文献
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基于中国气象局国国家气候中心海气耦合模式(CGCM/NCC)预测产品和山西省50站夏季降水资料,利用典型因子回归的方法(CCA),建立了山西省夏季降水的统计降尺度预测模型。该预测模型选取了CGCM/NCC模式夏季500 h Pa高度场和海平面气压作为预测因子,分别选取了长江中下游地区和热带中东太平洋作为预报关键区。统计降尺度模型对2007~2014年山西省夏季降水的回算较模式原始结果有显著提高,除2008年外,空间距平相似系数(ACC)均通过了0.01的显著性检验,时间相关系数(TCC)在山西省大部分地区都有显著提高,最大可达0.6,降水预测(PS)评分在70分以上。检验结果显示,基于CCA降尺度方法建立的预测模型对山西省夏季降水模态预测的准确率较高且比较稳定,其预测效果远高于CGCM/NCC直接输出降水结果。 相似文献
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基于普洱雨季开始期年际增量变化规律和影响雨季开始期的环流形势及物理过程,采用年际增量方法和多元线性回归分析方法,选取5个具有物理意义的预测因子(包括前期1月南半球绕极环流、前期2月南太平洋高压、前期4月孟加拉湾至南海海平面气压、前期冬季加拿大北部海冰和前期冬季伊朗高原积雪深度),建立了普洱雨季开始期的预测模型,并对预测模型进行1967—2017年的交叉检验和1998—2017年的逐年独立样本检验。交叉检验中,雨季开始期预测值和观测值年际增量的相关系数为0.84,相对均方根误差为24%;独立样本检验中,雨季开始期年际增量的相对均方根误差为15%,模型对雨季开始期异常年份的预测误差小于7 d,表明该预测模型能很好再现1967—2017年雨季开始期的变化趋势。 相似文献
9.
将前冬的500 hPa位势高度、向外长波辐射和海表温度的年际增量作为预测因子,建立基于卷积神经网络(Convolutional Neural Network, CNN)的非线性预测模型,对中国160个测站夏季降水展开预测研究,并与基于线性奇异值分解(Singular Value Decomposition, SVD)的预测模型进行效果对比。结果表明:CNN在1981—2020年的交叉检验中所回报的降水平均PS评分和距平相关系数(ACC)分别为74.33和0.12,比SVD高2.15和0.06,说明CNN比SVD在整体上对夏季降水具有更好的预测能力。其中,CNN对SVD预测较好年份的预测效果提升较为明显,对SVD预测较差的年份则改进不大。CNN对中国降水预测存在一定的系统性偏差,订正后CNN对拉尼娜年的降水预测改进较大。结果表明,基于年际增量法的CNN预测模型展示出较好的潜在应用价值。 相似文献
10.
利用影响南海夏季风年际变化的主要气候现象厄尔尼诺-南方涛动(El Ni?o-Southern Oscillation,ENSO)和对流层准两年振荡(Tropospheric Biennial Oscillation,TBO)相关的气候因子,提出了以过程判别函数确定物理过程的持续性,建立年际尺度的集成物理统计预测模型,而非年际尺度变率由经验统计模型预测,二者相结合,发展了集成物理-经验统计预测模型。经验模型在拟合时段的回报结果很好,但在独立样本预测时效果明显降低,其中预测评分(PS)降低了23%,距平相关系数(ACC)降低了63%;相比之下,集成物理-经验统计预测模型在独立样本预测时比经验模型有更好的预测结果(PS评分提高了9.5%,ACC提高了75%),且预测结果相对稳定。此外,集成物理-经验统计预测模型对南海夏季风降水的空间分布也有一定预测能力。 相似文献
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Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter. 相似文献
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Fei LIU Chen XING Jinbao LI Bin WANG Jing CHAI Chaochao GAO Gang HUANG Jian LIU Deliang CHEN 《大气科学进展》2020,37(7):663-670
<正>The Taal Volcano in Luzon is one of the most active and dangerous volcanoes of the Philippines. A recent eruption occurred on 12 January 2020(Fig. 1a), and this volcano is still active with the occurrence of volcanic earthquakes. The eruption has become a deep concern worldwide, not only for its damage on local society, but also for potential hazardous consequences on the Earth’s climate and environment. 相似文献
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The moving-window correlation analysis was applied to investigate the relationship between autumn Indian Ocean Dipole (IOD) events and the synchronous autumn precipitation in Huaxi region, based on the daily precipitation, sea surface temperature (SST) and atmospheric circulation data from 1960 to 2012. The correlation curves of IOD and the early modulation of Huaxi region’s autumn precipitation indicated a mutational site appeared in the 1970s. During 1960 to 1979, when the IOD was in positive phase in autumn, the circulations changed from a “W” shape to an ”M” shape at 500 hPa in Asia middle-high latitude region. Cold flux got into the Sichuan province with Northwest flow, the positive anomaly of the water vapor flux transported from Western Pacific to Huaxi region strengthened, caused precipitation increase in east Huaxi region. During 1980 to 1999, when the IOD in autumn was positive phase, the atmospheric circulation presented a “W” shape at 500 hPa, the positive anomaly of the water vapor flux transported from Bay of Bengal to Huaxi region strengthened, caused precipitation ascend in west Huaxi region. In summary, the Indian Ocean changed from cold phase to warm phase since the 1970s, caused the instability of the inter-annual relationship between the IOD and the autumn rainfall in Huaxi region. 相似文献
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The atmospheric and oceanic conditions before the onset of EP El Ni?o and CP El Ni?o in nearly 30 years are compared and analyzed by using 850 hPa wind, 20℃ isotherm depth, sea surface temperature and the Wheeler and Hendon index. The results are as follows: In the western equatorial Pacific, the occurrence of the anomalously strong westerly winds of the EP El Ni?o is earlier than that of the CP El Ni?o. Its intensity is far stronger than that of the CP El Ni?o. Two months before the El Ni?o, the anomaly westerly winds of the EP El Ni?o have extended to the eastern Pacific region, while the westerly wind anomaly of the CP El Ni?o can only extend to the west of the dateline three months before the El Ni?o and later stay there. Unlike the EP El Ni?o, the CP El Ni?o is always associated with easterly wind anomaly in the eastern equatorial Pacific before its onset. The thermocline depth anomaly of the EP El Ni?o can significantly move eastward and deepen. In addition, we also find that the evolution of thermocline is ahead of the development of the sea surface temperature for the EP El Ni?o. The strong MJO activity of the EP El Ni?o in the western and central Pacific is earlier than that of the CP El Ni?o. Measured by the standard deviation of the zonal wind square, the intensity of MJO activity of the EP El Ni?o is significantly greater than that of the CP El Ni?o before the onset of El Ni?o. 相似文献
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Various features of the atmospheric environment affect the number of migratory insects, besides their initial population. However, little is known about the impact of atmospheric low-frequency oscillation(10 to 90 days) on insect migration. A case study was conducted to ascertain the influence of low-frequency atmospheric oscillation on the immigration of brown planthopper, Nilaparvata lugens(Stl), in Hunan and Jiangxi provinces. The results showed the following:(1) The number of immigrating N. lugens from April to June of 2007 through 2016 mainly exhibited a periodic oscillation of 10 to 20 days.(2) The 10-20 d low-frequency number of immigrating N. lugens was significantly correlated with a low-frequency wind field and a geopotential height field at 850 h Pa.(3) During the peak phase of immigration, southwest or south winds served as a driving force and carried N. lugens populations northward, and when in the back of the trough and the front of the ridge, the downward airflow created a favorable condition for N. lugens to land in the study area. In conclusion, the northward migration of N. lugens was influenced by a low-frequency atmospheric circulation based on the analysis of dynamics. This study was the first research connecting atmospheric low-frequency oscillation to insect migration. 相似文献
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基于最新的GTAP8 (Global Trade Analysis Project)数据库,使用投入产出法,分析了2004年到2007年全球贸易变化下南北集团贸易隐含碳变化及对全球碳排放的影响。结果显示,随着发展中国家进出口规模扩张,全球贸易隐含碳流向的重心逐渐向发展中国家转移。2004年到2007年,发达国家高端设备制造业和服务业出口以及发展中国家资源、能源密集型行业及中低端制造业出口的趋势加强,该过程的生产转移导致全球碳排放增长4.15亿t,占研究时段全球贸易隐含碳增量的63%。未来发展中国家的出口隐含碳比重还将进一步提高。贸易变化带来的南北集团隐含碳流动变化对全球应对气候变化行动的影响日益突出,发达国家对此负有重要责任。 相似文献
17.
The spatial and temporal variations of daily maximum temperature(Tmax), daily minimum temperature(Tmin), daily maximum precipitation(Pmax) and daily maximum wind speed(WSmax) were examined in China using Mann-Kendall test and linear regression method. The results indicated that for China as a whole, Tmax, Tmin and Pmax had significant increasing trends at rates of 0.15℃ per decade, 0.45℃ per decade and 0.58 mm per decade,respectively, while WSmax had decreased significantly at 1.18 m·s~(-1) per decade during 1959—2014. In all regions of China, Tmin increased and WSmax decreased significantly. Spatially, Tmax increased significantly at most of the stations in South China(SC), northwestern North China(NC), northeastern Northeast China(NEC), eastern Northwest China(NWC) and eastern Southwest China(SWC), and the increasing trends were significant in NC, SC, NWC and SWC on the regional average. Tmin increased significantly at most of the stations in China, with notable increase in NEC, northern and southeastern NC and northwestern and eastern NWC. Pmax showed no significant trend at most of the stations in China, and on the regional average it decreased significantly in NC but increased in SC, NWC and the mid-lower Yangtze River valley(YR). WSmax decreased significantly at the vast majority of stations in China, with remarkable decrease in northern NC, northern and central YR, central and southern SC and in parts of central NEC and western NWC. With global climate change and rapidly economic development, China has become more vulnerable to climatic extremes and meteorological disasters, so more strategies of mitigation and/or adaptation of climatic extremes,such as environmentally-friendly and low-cost energy production systems and the enhancement of engineering defense measures are necessary for government and social publics. 相似文献
18.
Analysis of Atmospheric Boundary Layer Height Characteristics over the Arctic Ocean Using the Aircraft and GPS Soundings
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正ERRATUM to: Atmospheric and Oceanic Science Letters, 4(2011), 124-130 On page 126 of the printed edition (Issue 2, Volume 4), Fig. 2 was a wrong figure because the contact author made mistake giving the wrong one. The corrected edition has been updated on our website. The editorial office is sincerely sorry for any 相似文献
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《大气科学进展》2014,(6)
正AN Junling;see LI Ying et al.;(5),1221—1232AN Junling;see QU Yu et al.;(4),787-800AN Junling;see WANG Feng et al.;(6),1331-1342Ania POLOMSKA-HARLICK;see Jieshun ZHU et al.;(4),743-754Baek-Min KIM;see Seong-Joong KIM et al.;(4),863-878BAI Tao;see LI Gang et al.;(1),66-84BAO Qing;see YANG Jing et al.;(5),1147—1156BEI Naifang; 相似文献