Meiyu in the Yangtze River Delta and its extended-range forecast associated with intraseasonal evolution of atmospheric circulation
-
摘要: 基于1981—2020年长江三角洲（简称长三角）地区62个国家基本气象站的逐日降水量资料及NCEP/NCAR全球大气逐日再分析资料，分析了长三角地区梅汛期降水与前期大气环流季节内协同演变的关系，在此基础上利用改进的时空投影方法（STPM）构建了针对该地区梅汛期降水的延伸期预报模型。结果表明：（1）长三角地区梅汛期降水存在显著的10—80 d季节内振荡，且振荡强度有明显的空间差异和年际变化，降水量越大对应的季节内振荡越强。（2）梅汛期降水发生前15—10天大气环流发生季节内调整，热带低频对流活跃并出现经向传播，在西北太平洋、长江流域至黄淮—日本海的对流层低层（高层）激发反气旋（气旋）—气旋（反气旋）—反气旋（气旋）的低频波列，建立起低层辐合、高层辐散的环流配置，长三角地区对流增强；大气低频响应导致南亚高压季节内南北振荡和东西进退明显，西太平洋副热带高压在长三角东南侧稳定维持，上述低、中和高纬度环流的季节内动态协同演变共同促进了该地区梅汛期低频降水的发生。（3）将影响梅汛期降水的前期大气环流季节内动态演变过程作为预报因子，基于STPM方法训练得到长三角梅汛期降水的延伸期逐候预报模型，近10年的独立回报评估显示该模型对梅汛期未来10—25 d降水有较高的预报技巧。Abstract: Based on daily precipitation data obtained from 62 national basic meteorological stations in the Yangtze River Delta (YRD) and the NCEP/NCAR reanalysis dataset from 1981 to 2020, the relationship of intraseasonal precipitation in Meiyu season with the evolution of atmospheric circulation over the YRD is studied. The extended-range precipitation forecast model based on atmospheric circulation evolution is then constructed by using improved Spatial-temporal Projection Method (STPM). 10—80 d intraseasonal oscillation is found in the daily variation of Meiyu precipitation, and the amplitude differs in spatial and temporal scales. The stronger intraseasonal oscillation denotes heavier precipitation. From 15 to 10 d lead, the tropical intraseasonal convections become active with meridional propagations. The anomalously strong convections over the YRD enhance. The intraseasonal anticyclone (cyclone) — cyclone (anticyclone) — anticyclone (cyclone) wave train is triggered in the lower troposphere (upper troposphere), allowing divergence (convergence) to gradually establish. The intraseasonal atmosphere response leads to a stable Western Pacific subtropical high and obvious north-south and east-west oscillations of the South Asian High. All these cooperative intraseasonal changes of atmosphere from different levels and latitudes accelerate the development of precipitation. Based on the dynamic intraseasonal evolution of atmospheric circulation, the extended-range pentadly precipitation forecast model for the Meiyu season is constructed by using STPM. The independent evaluation of historic forecasts shows that the model has useful forecast skills at lead time of 10—25 d in the YRD.
-
图 1 长三角地区国家基本气象站分布
Figure 1. Locations of national basic meteorological stations in the Yangtze River Delta
图 2 1981—2020年长三角地区梅汛期逐日降水的功率谱分析 （绿线为马尔可夫红噪声谱；蓝、红线分别为5%、95%信度水平临界值）
Figure 2. Power spectrum analysis of daily precipitation in Meiyu season over the Yangtze River Delta from 1981 to 2020 with Markov red noise spectrum （green line），and a priori 5%，95% confidence bound （blue，red line）
图 3 1981—2020年长三角地区梅汛期 （a）降水10—80 d季节内分量方差 （单位：mm）、（b）候平均降水量 （单位：mm） 空间分布及 （c） 候降水量与季节内变化分量散点、（d） 季节内振荡强度与总降水量的逐年变化
Figure 3. Spatial distribution in the Meiyu season over the Yangtze River Delta from 1981 to 2020 （a. the variance of 10—80 d intraseasonal precipitation components，unit：mm；b. pentad mean precipitation，unit：mm） and （c） the scatter distribution of pentad mean precipitation and 10—80 d intraseasonal component of precipitation，（d） the annual variation of regional average 10—80 d intraseasonal component of precipitation oscillation intensity and total precipitation
图 4 1981—2010年长三角区域平均的梅汛期逐日降水与前35—0 天的向外长波辐射对流活动 （a） 和700 hPa相对湿度 （b） 季节内分量的时间相关系数空间分布场 （×表示通过95%置信水平的显著性t检验；下标数字1—5分别表示前35、25、15、10、0天）
Figure 4. Temporal correlation coefficient maps of outgoing longwave radiation （a） and 700 hPa relative humidity （b） with the intraseasonal component of daily precipitation averaged over the Yangtze River Delta at lead times of 35 to 0 days （cross areas denote values at the 95% confidence level by t-test；the numbers 1—5 denote lead 35，25，15，10，0 d，respectively）
图 5 1981—2010年长三角区域平均的梅汛期逐日降水与前35—0天的850 hPa （a） 和200 hPa （b） 矢量风场季节内分量的时间相关系数场空间分布 （加粗箭头表示矢量相关系数通过了95%置信水平的显著性t检验；色阶为根据风矢量相关计算的散度相关系数；“A”“C”分别代表反气旋、气旋；下标数字1—5分别表示前35、25、15、10、0天）
Figure 5. Temporal correlation coefficient maps of 850 hPa （a） and 200 hPa （b） winds with the intraseasonal component of daily precipitation over the Yangtze River Delta at lead times of 35 to 0 days （the bold vector arrows indicate the vector correlation coefficients at the 95% confidence level by t-test，and the shaded areas are divergence values calculated based on the zonal and meridional winds correlation coefficients；the "A" "C" stands for anticyclone/cyclone； the numbers 1—5 denote lead 35，25，15，10，0 d，respectively）
图 6 1981—2010年长三角区域平均的梅汛期逐日降水与前35—0天的500 hPa （a） 和200 hPa （b） 位势高度季节内分量的时间相关系数空间分布场 （×表示通过了95%置信水平的显著性t检验；下标数字1—5分别表示前35、25、15、10、0天）
Figure 6. Temporal correlation coefficient maps of 500 hPa （a） and 200 hPa （b） geopotential height with the intraseasonal component of daily precipitation averaged over the Yangtze River Delta at lead times of 35 to 0 days （cross areas denote values at the 95% confidence level by t-test；the numbers 1—5 denote lead 35，25，15，10，0 d，respectively）
图 7 基于最外围闭合等值线客观识别方法的长三角梅汛期降水延伸期预报的大气环流关键区
Figure 7. Key areas of atmospheric circulation for the Yangtze River Delta precipitation extended-range forecast in Meiyu season based on the objective identification method detecting the outermost closed contour
图 8 2011—2020年长三角地区梅汛期季节内降水独立回报值和实际观测值的时间相关系数空间分布 （a—f分别为提前10、15、20、25、30、35 d起报，打点区域表示通过了95%置信水平的显著性t检验）
Figure 8. Spatial distributions of temporal correlation coefficient between independent forecasts and observations of intraseasonal precipitation in Meiyu season over the Yangtze River Delta from 2011 to 2020 （a—f are for forecasts at lead times of 10，15，20，25，30，35 d，respectively；dotted areas denote values at the 95% confidence level by t-test）
图 9 季节内振荡偏强年 （a1—f1） 和偏弱年 （a2—f2） 长三角地区梅汛期季节内降水独立回报值和实际观测值的时间相关系数空间分布 （a—f分别为提前10、15、20、25、30、35 d起报，打点区域表示通过了95%置信水平的显著性t检验）
Figure 9. Spatial distributions of temporal correlation coefficient between independent forecasts and observations of intraseasonal precipitation in Meiyu season over the Yangtze River Delta in strong （a） and weak （b） intraseasonal oscillation years （a—f are for forecasts at lead times of 10，15，20，25，30，35 d，respectively；dotted areas denote values at the 95% confidence level by t-test）
表 1 长三角梅汛期降水延伸期预报的大气环流关键区经纬度
Table 1. Key areas of atmospheric circulation for extended-range precipitation forecast in Meiyu season over the Yangtze River Delta
大气环流要素 关键区 大气向外长波辐射（olr） 7.5°—57.5°N，95°—140°E 700 hPa相对湿度（rhum700） 7.5°—47.5°N，95°—140°E 850 hPa纬向风（u850） 5°—42.5°N，107.5°—127.5°E 850 hPa经向风（v850） EQ—45°N，95°—135°E 200 hPa纬向风（u200） 5°—45°N，102.5°—147.5°E 200 hPa经向风（v200） EQ—45°N，100°—145°E 500 hPa高度（h500） 2.5°—42.5°N，100°—135°E 200 hPa高度（h200） 2.5°—45°N，102.5°—127.5°E 
下载: 导出CSV
-
[1] 丑纪范,郑志海,孙树鹏. 2010. 10~30 d延伸期数值天气预报的策略思考:直面混沌. 气象科学,30(5):569-573 doi: 10.3969/j.issn.1009-0827.2010.05.001Chou J F,Zheng Z H,Sun S P. 2010. The think about 10~30 d extended-range numerical weather prediction strategy-facing the atmosphere chaos. Scientia Meteor Sinica,30(5):569-573 (in Chinese) doi: 10.3969/j.issn.1009-0827.2010.05.001 [2] 丁一汇. 1993. 1991年江淮流域持续性特大暴雨研究. 北京:气象出版社,255ppDing Y H. 1993. The Study about Heavy Rainfalls in Yangtze River and Huai River in 1991. Beijing:China Meteorological Press,255pp (in Chinese) [3] 郭渠,黄安宁,付志鹏等. 2021. 北京气候中心次季节-季节预测系统对西南地区夏季降水次季节预报技巧评估及误差订正. 高原气象,40(3):644-655Guo Q,Huang A N,Fu Z P,et al. 2021. Evaluation and bias correction on the subseasonal forecast of summer precipitation over Southwestern China forecasted by the Beijing Climate Center sub-seasonal to seasonal predication system. Plateau Meteor,40(3):644-655 (in Chinese) [4] 何金海,梁萍,孙国武. 2013. 延伸期预报的思考及其应用研究进展. 气象科技进展,3(1):11-17He J H,Liang P,Sun G W. 2013. Consideration on extended-range forecast and its application study. Adv Meteor Sci Technol,3(1):11-17 (in Chinese) [5] 黄荣辉. 1990. 引起我国夏季旱涝的东亚大气环流异常遥相关及其物理机制的研究. 大气科学,14(1):108-117 doi: 10.3878/j.issn.1006-9895.1990.01.14Huang R H. 1990. Studies on the teleconnections of the general circulation anomalies of East Asia causing the summer drought and flood in China and their physical mechanism. Sci Atmos Sinica,14(1):108-117 (in Chinese) doi: 10.3878/j.issn.1006-9895.1990.01.14 [6] 黄燕燕,钱永甫. 2004. 长江流域、华北降水特征与南亚高压的关系分析. 高原气象,23(1):68-74 doi: 10.3321/j.issn:1000-0534.2004.01.010Huang Y Y,Qian Y F. 2004. Relationship between South Asian High and characteristic of precipitation in Mid- and Lower- Reaches of Yangtze River and North China. Plateau Meteor,23(1):68-74 (in Chinese) doi: 10.3321/j.issn:1000-0534.2004.01.010 [7] 胡鹏,谷湘潜,康红文. 2005. 泛相似预报法在汛期降水预报中的应用. 气象学报,63(2):250-256 doi: 10.3321/j.issn:0577-6619.2005.02.012Hu P,Gu X Q,Kang H W. 2005. Pan-similarity method and its forecast experiments on summer precipitation in China. Acta Meteor Sinica,63(2):250-256 (in Chinese) doi: 10.3321/j.issn:0577-6619.2005.02.012 [8] 贾燕,管兆勇. 2010. 江淮流域夏季降水异常与西北太平洋副热带30~60天振荡强度年际变化的联系. 大气科学,34(4):691-702 doi: 10.3878/j.issn.1006-9895.2010.04.03Jia Y,Guan Z Y. 2010. Associations of summertime rainfall anomalies over the Changjiang-Huaihe River valley with the interannual vari ability of 30-60-day oscillation intensity in the northwestern Pacific. Chinese J Atmos Sci,34(4):691-702 (in Chinese) doi: 10.3878/j.issn.1006-9895.2010.04.03 [9] 靳振华,管兆勇. 2013. 海洋性大陆区域OLR的气候低频振荡及其与中国降水的可能联系. 热带气象学报,29(5):705-716 doi: 10.3969/j.issn.1004-4965.2013.05.001Jin Z H,Guan Z Y. 2013. The climatological low-frequency oscillations in maritime continent region and their possible relations with precipitation changes in China. J Trop Meteor,29(5):705-716 (in Chinese) doi: 10.3969/j.issn.1004-4965.2013.05.001 [10] 李桂龙,李崇银. 1999. 江淮流域夏季旱涝与不同时间尺度大气扰动的关系. 大气科学,23(1):39-50 doi: 10.3878/j.issn.1006-9895.1999.01.06Li G L,Li C Y. 1999. Drought and flood in the Changjiang-Huaihe River basin associated with the multi-time-scale oscillation. Chinese J Atmos Sci,23(1):39-50 (in Chinese) doi: 10.3878/j.issn.1006-9895.1999.01.06 [11] 李洪权,陈中赟,骆丽楠等. 2012. 南亚高压和高低空急流对2010年浙江梅汛期暴雨的影响. 气象科学,32(3):310-316 doi: 10.3969/2012jms.0040Li H Q,Chen Z Y,Luo L N,et al. 2012. The effect of south Asia high and upper and lower-level jets on Meiyu rainstorm in Zhejiang province during 2010. J Meteor Sci,32(3):310-316 (in Chinese) doi: 10.3969/2012jms.0040 [12] 李维京,陈丽娟. 1999. 动力延伸预报产品释用方法的研究. 气象学报,57(3):338-345 doi: 10.11676/qxxb1999.032Li W J,Chen L J. 1999. Research on reexplanation and reanalysis method of dynamical extended range forecast products. Acta Meteor Sinica,57(3):338-345 (in Chinese) doi: 10.11676/qxxb1999.032 [13] 梁萍,丁一汇. 2012a. 东亚梅雨季节内振荡的气候特征. 气象学报,70(3):418-435Liang P,Ding Y H. 2012a. Climatologic characteristics of the intraseasonal oscillation of East Asian Meiyu. Acta Meteor Sinica,70(3):418-435 (in Chinese) [14] 梁萍,丁一汇. 2012b. 基于季节内振荡的延伸预报试验. 大气科学,36(1):102-116Liang P,Ding Y H. 2012b. Extended range forecast experiment based on intraseasonal oscillation. Chinese J Atmos Sci,36(1):102-116 (in Chinese) [15] 刘芸芸,丁一汇. 2020. 2020年超强梅雨特征及其成因分析. 气象,46(11):1393-1404 doi: 10.7519/j.issn.1000-0526.2020.11.001Liu Y Y,Ding Y H. 2020. Characteristics and possible causes for the extreme Meiyu in 2020. Meteor Mon,46(11):1393-1404 (in Chinese) doi: 10.7519/j.issn.1000-0526.2020.11.001 [16] 马杰,尹姗,金荣花等. 2021. 一次梅汛期极端降雨过程雨带位置模式预报性能对比分析. 大气科学,45(3):487-498Ma J,Yin S,Jin R H,et al. 2021. Comparative analysis of forecast evaluation for rain band position in an extreme Meiyu rainfall event. Chinese J Atmos Sci,45(3):487-498 (in Chinese) [17] 马悦,梁萍,李文铠等. 2018. 时空投影法在上海地区梅汛期降水延伸期预报中的应用. 气象,44(12):1593-1603 doi: 10.7519/j.issn.10000526.2018.12.009Ma Y,Liang P,Li W K,et al. 2018. Application of spatial-temporal projection model for extended-range forecast during Meiyu season in Shanghai. Meteor Mon,44(12):1593-1603 (in Chinese) doi: 10.7519/j.issn.10000526.2018.12.009 [18] 毛江玉,吴国雄. 2005. 1991年江淮梅雨与副热带高压的低频振荡. 气象学报,63(5):762-770 doi: 10.3321/j.issn:0577-6619.2005.05.020Mao J Y,Wu G X. 2005. Intraseasonal variability in the Yangtze-Huaihe River rainfall and Subtropical High during the 1991 Meiyu period. Acta Meteor Sinica,63(5):762-770 (in Chinese) doi: 10.3321/j.issn:0577-6619.2005.05.020 [19] 孙国武,李震坤,信飞等. 2013. 延伸期天气过程预报的一种新方法:低频天气图. 大气科学,37(4):945-954 doi: 10.3878/j.issn.1006-9895.2012.12125Sun G W,Li Z K,Xin F,et al. 2013. Low-frequency synoptic map:New method for extended range forecasting. Chinese J Atmos Sci,37(4):945-954 (in Chinese) doi: 10.3878/j.issn.1006-9895.2012.12125 [20] 孙树鹏,封国林,郑志海等. 2021. 2016年梅雨持续性强降水期间大气环流稳定分量研究. 大气科学,45(2):245-256Sun S P,Feng G L,Zheng Z H,et al. 2021. Study on the stable components of atmospheric circulation during the continuous heavy rainfall of Meiyu in 2016. Chinese J Atmos Sci,45(2):245-256 (in Chinese) [21] 陶诗言,张庆云,张顺利. 1998. 1998年长江流域洪涝灾害的气候背景和大尺度环流条件. 气候与环境研究,3(4):290-299 doi: 10.3878/j.issn.1006-9585.1998.04.01Tao S Y,Zhang Q Y,Zhang S L. 1998. The great floods in the Changjiang River valley in 1998. Climatic Environ Res,3(4):290-299 (in Chinese) doi: 10.3878/j.issn.1006-9585.1998.04.01 [22] 王遵娅,丁一汇. 2008. 中国雨季的气候学特征. 大气科学,32(1):1-13 doi: 10.3878/j.issn.1006-9895.2008.01.01Wang Z Y,Ding Y H. 2008. Climatic characteristics of rainy seasons in China. Chinese J Atmos Sci,32(1):1-13 (in Chinese) doi: 10.3878/j.issn.1006-9895.2008.01.01 [23] 吴楚樵,刘玉芝,贾瑞等. 2019. 江淮流域梅雨期气候对全球气候变暖的响应. 气象学报,77(1):84-99 doi: 10.11676/qxxb2018.046Wu C Q,Liu Y Z,Jia R,et al. 2019. Response of climate during the Meiyu period over the Yangtze-Huai River Valley to global warming. Acta Meteor Sinica,77(1):84-99 (in Chinese) doi: 10.11676/qxxb2018.046 [24] 武英娇,杨浩,钱仙桃等. 2019. ECMWF集合预报在安徽大别山区降水预报中的检验. 暴雨灾害,38(1):66-71Wu Y J,Yang H,Qian X T,et al. 2019. Verification of ECMWF ensemble prediction in precipitation forecast of Ta-pieh Mountains area in Anhui Province. Torrential Rain Disaster,38(1):66-71 (in Chinese) [25] 信飞,马悦,王蔚等. 2020. 2020年上海梅雨异常特征及延伸期预报分析. 暴雨灾害,39(6):578-585Xin F,Ma Y,Wang W,et al. 2020. Analysis on the characteristics and extended range forecast of Meiyu anomaly in Shanghai in 2020. Torrential Rain Disaster,39(6):578-585 (in Chinese) [26] 徐邦琪,臧钰歆,朱志伟等. 2020. 时空投影模型(STPM)的次季节至季节(S2S)预测应用进展. 大气科学学报,43(1):212-224Xu B Q,Zang Y X,Zhu Z W,et al. 2020. Subseasonal-to-seasonal (S2S) prediction using the spatial-temporal projection model (STPM). Trans Atmos Sci,43(1):212-224 (in Chinese) [27] 闫昊明,钟敏,朱耀仲. 2003. 时间序列数字滤波后自由度的确定——应用于日长变化与南方涛动指数的相关分析. 天文学报,44(3):324-329 doi: 10.3321/j.issn:0001-5245.2003.03.011Yang H M,Zhong M,Zhu Y Z. 2003. The Determination of degrees of freedom for digital filtered time series:An application in the correlation analysis between length of day variation and SOI. Acta Astron Sinica,44(3):324-329 (in Chinese) doi: 10.3321/j.issn:0001-5245.2003.03.011 [28] 杨秋明. 2014. 基于20-30 d振荡的长江下游地区夏季低频降水延伸期预报方法研究. 气象学报,72(3):494-507 doi: 10.11676/qxxb2014.028Yang Q M. 2014. Study of the method of the extended-range forecast for the low frequency rainfall over the lower reaches of the Yangtze River in summer based on the 20-30 day oscillation. Acta Meteor Sinica,72(3):494-507 (in Chinese) doi: 10.11676/qxxb2014.028 [29] 杨士瑛,国守华. 1985. 杭州湾区的气候特征分析. 东海海洋,(4):12-22Yang S Y,Guo S H. 1985. Features analysis of the climate in the Hangzhou Bay. Donghai Mar Sci,(4):12-22 (in Chinese) [30] 章大全,郑志海,陈丽娟等. 2019. 10~30 d延伸期可预报性与预报方法研究进展. 应用气象学报,30(4):416-430 doi: 10.11898/1001-7313.20190403Zhang D Q,Zheng Z H,Chen L J,et al. 2019. Advances on the predictability and prediction methods of 10-30 d extended range forecast. J Appl Meteor Sci,30(4):416-430 (in Chinese) doi: 10.11898/1001-7313.20190403 [31] 郑志海, 黄建平, 封国林等. 2013. 延伸期可预报分量的预报方案和策略. 中国科学: 地球科学, 43（4）: 594-605.Zheng Z H, Huang J P, Feng G L, et al. 2013. Forecast scheme and strategy for extended-range predictable components. Sci China Earth Sci, 56（5）: 878-889. [32] Buizza R,Bidlot J R,Wedi N,et al. 2007. The new ECMWF VAREPS (variable resolution ensemble prediction system). Quart J Roy Meteor Soc,133(624):681-695 doi: 10.1002/qj.75 [33] Fang Y J,Wu P L,Wu T W,et al. 2017. An evaluation of boreal summer intra-seasonal oscillation simulated by BCC_AGCM2.2. Climate Dyn,48(9-10):3409-3423 doi: 10.1007/s00382-016-3275-4 [34] Fisher R A. 1922. On the mathematical foundations of theoretical statistics. Phil Trans Roy Soc A,222:309-368 [35] Fu X H,Lee J Y,Wang B,et al. 2013. Intraseasonal forecasting of the Asian summer monsoon in four operational and research models. J Climate,26(12):4186-4203 doi: 10.1175/JCLI-D-12-00252.1 [36] Hsu P C,Li TM,Lin Y C,et al. 2012. A spatial-temporal projection method for seasonal prediction of spring rainfall in northern Taiwan. J Meteor Soc Japan,90(2):179-190 doi: 10.2151/jmsj.2012-202 [37] Jie W H,Vitart F,Wu T W,et al. 2017. Simulations of the Asian summer monsoon in the sub-seasonal to seasonal prediction project (S2S) database. Quart J Roy Meteor Soc,143(706):2282-2295 doi: 10.1002/qj.3085 [38] Kim H M,Webster P J,Curry J A,et al. 2012. Asian summer monsoon prediction in ECMWF System 4 and NCEP CFSv2 retrospective seasonal forecasts. Climate Dyn,39(12):2975-2991 doi: 10.1007/s00382-012-1470-5 [39] Lau K M,Yang G J,Shen S H. 1988. Seasonal and intraseasonal climatology of summer monsoon rainfall over East Asia. Mon Wea Rev,116(1):18-37 doi: 10.1175/1520-0493(1988)116<0018:SAICOS>2.0.CO;2 [40] Lee S S,Wang B,Waliser D E,et al. 2015. Predictability and prediction skill of the boreal summer intraseasonal oscillation in the intraseasonal variability hindcast experiment. Climate Dyn,45(7-8):2123-2135 doi: 10.1007/s00382-014-2461-5 [41] Lu C H. 2017. A modified algorithm for identifying and tracking extratropical cyclones. Adv Atmos Sci,34(7):909-924 doi: 10.1007/s00376-017-6231-2 [42] Pan B X,Hsu K,Aghakouchak A,et al. 2019. Precipitation prediction skill for the West Coast United States:From short to extended range. J Climate,32(1):161-182 doi: 10.1175/JCLI-D-18-0355.1 [43] Seo K H,Wang W Q,Gottschalck J,et al. 2009. Evaluation of MJO forecast skill from several statistical and dynamical forecast models. J Climate,22(9):2372-2388 doi: 10.1175/2008JCLI2421.1 [44] Tao S Y,Chen L X. 1987. A review of recent research on the East Asian summer monsoon in China∥Chang C P,Krishnamurti T N. Monsoon Meteorology. Oxford:Oxford University Press,60-92 [45] Vitart F. 2014. Evolution of ECMWF sub-seasonal forecast skill scores. Quart J Roy Meteor Soc,140(683):1889-1899 doi: 10.1002/qj.2256 [46] Yasunari T. 1980. A quasi-stationary appearance of 30 to 40 day period in the cloudiness fluctuations during the summer monsoon over India. J Meteor Soc Japan,58(3):225-229 doi: 10.2151/jmsj1965.58.3_225 [47] Zhao C B,Zhou T J,Song L C,et al. 2014. The boreal summer intraseasonal oscillation simulated by four Chinese AGCMs participating in the CMIP5 project. Adv Atmos Sci,31(5):1167-1180 [48] Zhu Z W,Li T,Hsu P C,et al. 2015. A spatial-temporal projection model for extended-range forecast in the tropics. Climate Dyn,45(3-4):1085-1098 -
下载:
点击查看大图
计量
- 文章访问数: 535
- HTML全文浏览量: 144
- PDF下载量: 190
- 被引次数: 0
