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1.
本文利用ERA5 1979-2019年逐月大气再分析资料计算南北印度洋热带气旋生成指数，并和IBTrACS观测数据进行比较，探讨用热带气旋生成指数研究南北印度洋热带气旋变化特征的适用性.研究发现热带气旋生成指数能较好地刻画南北印度洋热带气旋的空间分布特征、北印度洋热带气旋个数月变化的双峰结构，以及南印度洋比北印度洋热带气旋发生概率高等特征.最新的IBTrACS v4.0观测资料显示，40年来北印度洋热带气旋每年总生成个数平均每10年增加1.3个，频数的增加主要来源于热带低压和热带风暴，而南印度洋热带气旋每年总生成个数每10年减少2.8个.热带气旋生成指数能很好地描述北印度洋热带气旋生成个数的上升趋势，但对南印度洋热带气旋生成个数趋势的刻画与观测不一致，可能原因需要进一步深入研究.  相似文献   

2.
李畅  姜霞  沈新勇 《山东气象》2021,41(4):62-72
利用印度气象局（India Meteorological Department,IMD）、国际气候管理最佳路径档案库（International Best Track Archive for Climate Stewardship,IBTrACS）提供的1982—2020年阿拉伯海热带气旋路径资料,美国国家环境预报中心（National Centers for Environmental Prediction,NCEP）再分析资料,对近39 a阿拉伯海热带气旋源地和路径特征、活跃区域、频数及气旋累积能量（accumulated cyclone energy,ACE）指数的季节特征和年际变化特征进行分析,并结合环境因素,说明其物理成因。结果表明：阿拉伯海热带气旋多发于10°~25°N,65°~75°E海域,5—6月、9—12月发生频数较高且强度较强,1—4月、7—8月发生频数较低且气旋近中心最大风速均小于35 kn;频数的季节变化主要受控于垂直风切变要素;阿拉伯海热带气旋发生频数和ACE近年有上升趋势,年际变化主要受控于海面温度（sea surface temperature,SST）和850 hPa相对湿度要素。  相似文献   

3.
利用美国联合台风警报中心(Joint Typhoon Warning Centre,JTWC)发布的1979—2018年北印度洋热带气旋(tropical cyclone,TC)数据和ERA-Interim提供的分辨率为1°×1°的同期再分析资料,分析影响北印度洋热带气旋生成的不同环境因子月际变化特征。结果表明：5月北印度洋海温明显增暖,适宜的200 hPa与850 hPa垂直风速切变(5～10 m·s-1)和充足的水汽供应使得热带气旋的生成数达到全年第一个峰值。7—9月对流层中低层相对湿度条件很好,但200 hPa与850 hPa垂直风速切变过大,使得扰动对流很难形成暖心结构,不利于热带气旋的生成。10—11月北印度洋平均海温27～29℃,中层大气相对湿度条件较好,850 hPa多气旋性环流,200 hPa与850 hPa垂直风速切变为5～15 m·s-1,在这种有利的环境条件下北印度洋热带气旋生成数达到全年第二个峰值。对影响北印度洋两个海域热带气旋月际变化的不同环境因子定量研究发现,尽管阿拉伯海和孟加拉湾的热带气旋生成数都呈现双峰型变化,...  相似文献   

4.
基于1979～2019年日本气象厅提供的地表感热与大气环流再分析资料,美国国家海洋和大气管理局提供的月均海表温度数据和国家气象信息中心提供的月降水数据,分析了夏季伊朗高原感热和热带印度洋海温与同期塔里木盆地降水的可能联系。奇异值分解分析表明,两个地区热力异常均与塔里木盆地夏季降水联系紧密,可以通过影响500 hPa风场和水汽输送来调制塔里木盆地夏季降水的变化。当伊朗高原感热和热带印度洋海温均偏强（弱）时,对应中亚上空受异常气旋（反气旋）控制,蒙古高原上空为反气旋（气旋）控制,二者共同作用塔里木盆地上空盛行异常偏南（北）风,形成有利（不利）的动力条件;同时印度半岛上空受异常反气旋（气旋）环流控制,中亚上空为异常气旋（反气旋）,阿拉伯海水汽可（不可）由以上两个系统两步输送至新疆上空,导致盆地夏季降水整体偏多（少）。当伊朗高原和热带印度洋热力异常反相变化时,盆地降水空间差异性较大,部分区域降水偏多,部分地区降水偏少。  相似文献   

5.
不同海域影响热带气旋强度变化的环境动力因素对比   总被引：1，自引：0，他引：1  
利用1982-2007年NCEP/NCAR再分析资料、月平均海平面温度(SST)资料和西北太平洋、北大西洋以及北印度洋热带气旋(TC)资料,对比分析了环境动力因素对不同海域TC强度在不同时间尺度变化的影响.结果表明,在各时间尺度上,TC强度变化与垂直风切变变化有密切的联系.在西北太平洋,使TC过程强度增强或减弱的风切变...  相似文献   

6.
柳龙生  许映龙 《气象》2022,(2):245-253
利用1979—2018年美国联合台风警报中心发布的热带气旋数据和ERA-Interim提供的1°×1°再分析资料分析了北印度洋秋季超级气旋风暴的活动特征。结果表明:1998年以后,北印度洋秋季生成的超级气旋风暴数目显著增多;1999—2018年北印度洋平均最大潜在强度指数高于1979—1998年;与1979—1998年相比,1999—2018年更高的平均海面温度和海洋热含量为超级气旋风暴的生成和发展提供了有利的条件,更弱的垂直风切变、更强的水汽通量和低层气旋性涡度输送促进了热带风暴强度的持续增长。  相似文献   

7.
采用恒定的现代外部强迫驱动第一版NUIST地球系统模式,进行了40年全球热带气旋活动模拟,分析了热带气旋活动的气候特征,并与1977—2016年观测资料对比分析。结果表明：该模式能够模拟出与热带气旋类似的结构特征,在热带气旋活动活跃的海区,模拟热带气旋生成的空间分布和影响范围与观测基本一致,但是各个海区热带气旋的生成频数与观测还存在差异。除了北印度洋海区,各个海区热带气旋生成频数的季节变化与观测相似。模式在西北太平洋海区模拟结果最好,能模拟出热带气旋的生成范围和盛行路径;在北印度洋地区模拟结果较差,北印度洋海区的相对涡度模拟与观测存在较大差异,这是模式未能模拟出北印度洋热带气旋双峰特征的主要原因。  相似文献   

8.
利用1979~2015年NCEP/NCAR发布的月平均全球再分析资料,分析了热带印度洋-西太平洋水汽输送异常对中国东部夏季降水的影响及其形成机理。研究结果表明:热带印度洋-西太平洋地区（10°S~30°N,60°~140°E）夏季异常水汽输送主要包括两个模态,他们可以解释总的水汽输送异常34%的方差。其中,第一模态（EOF1）表现为异常水汽沿反气旋从热带西太平洋经过南海及孟加拉湾输送到中国东部上空,对应南海、孟加拉湾水汽路径输送均偏多,此时西太平洋副热带高压显著偏强,异常水汽在长江中下游地区辐合并伴随显著上升运动,有利于长江中下游降水偏多;第二模态（EOF2）表现为异常水汽从热带印度洋沿阿拉伯海、印度半岛、中南半岛等呈反气旋式输送,华南上空相应出现气旋式水汽输送异常,并对应异常水汽辐合和上升运动,有利于华南降水偏多。就可能的外部成因而言,EOF1与ENSO关系密切,表现为前冬热带中东太平洋显著偏暖,夏季同期热带北印度洋、南海上空显著偏暖,造成西太平洋副热带高压显著偏强,异常水汽主要来源于热带西太平洋和南海;EOF2与同期热带印度洋偶极子（TIOD）异常有关,TIOD为正位相时热带印度洋上空出现异常东风,华南上空出现异常气旋并伴随水汽异常辐合,异常水汽主要来源于热带南印度洋。  相似文献   

9.
利用NCEP/NCAR再分析环流资料、CMAP降水量和NOAA海温资料研究了热带印度洋夏季水汽输送的时空变化特征,并考察其对南亚季风区夏季降水的影响.热带印度洋夏季异常水汽输送第一模态表现为异常水汽从南海向西到达孟加拉湾后分成两支,其中一支继续往西到达印度次大陆和阿拉伯海,对应印度半岛南端和中南半岛的西风水汽输送减弱,导致这些区域降水减少;第二模态表现为异常水汽从赤道东印度洋沿赤道西印度洋、阿拉伯海、印度半岛、中南半岛的反气旋输送,印度和孟加拉湾南部为反气旋异常水汽输送,水汽辐散、降水减少,而印度东北部为气旋性水汽输送,水汽辐合、降水增多.就水汽输送与局地海温的关系而言,水汽输送第一模态与热带印度洋海温整体增暖关系密切,而第二模态与同期印度洋偶极子关系密切.  相似文献   

10.
影响南海夏季风爆发年际变化的关键海区及机制初探   总被引：1，自引：7，他引：1  
利用1958—2011年NCEP/ NCAR再分析资料和ERSST资料,采用Lanczos时间滤波器、相关分析、回归分析、合成分析和交叉检验等方法,研究了影响南海夏季风爆发年际变化的关键海区海温异常的来源与可能机制。结果表明,前冬(12—2月)热带西南印度洋和热带西北太平洋是影响南海夏季风爆发年际变化的关键海区。冬季热带西南印度洋(热带西北太平洋)的异常增暖是由前一年夏季El Ni?o早爆发(强印度季风异常驱动的行星尺度东-西向环流)触发、热带印度洋(西北太平洋)局地海气正反馈过程引起并维持到春季。冬季热带西北太平洋反气旋性环流(气旋性环流)及印度洋(热带西北太平洋)的暖海区局地海气相互作用使得印度洋(热带西北太平洋)海温异常维持到春末。春季,逐渐加强北移到10 °N附近的低层大气对北印度洋(热带西北太平洋)暖海温异常响应的东风急流(异常西风)及南海-热带西北太平洋维持的反气旋性环流(气旋性环流)异常,使得南海夏季风晚(早)爆发。   相似文献   

11.
Changes in the frequency of tropical cyclones over the North Indian Ocean   总被引：3，自引：0，他引：3  
Summary  Changes in the frequency of tropical cyclones developing over the Arabian Sea and the Bay of Bengal have been studied utilizing 122 year (1877–1998) data of tropical cyclone frequency. There have been significant increasing trends in the cyclone frequency over the Bay of Bengal during November and May which are main cyclone months. During transitional monsoon months; June and September however, the frequency has decreased. The results have been presented for five months, i.e., May-November which are relevant as far as tropical cyclone frequency over the Arabian Sea and the Bay of Bengal are concerned. The tropical cyclone frequency in the Arabian Sea has not shown any significant trend, probably due to small normal frequency. The frequency time series has been subjected to the spectral analysis to obtain the significant periods. The cyclone frequency over the Bay of Bengal during May has shown a 29 year cycle. A significant 44 year cycle has been found during November. Over the Arabian Sea significant cycles of 13 and 10 years have been observed during May-June and November, respectively. The tropical cyclone frequency in the North Indian Ocean has a prominent El Ni?o-Southern Oscillation (ENSO) scale cycle (2–5 years) during all above five months. The annual cyclone frequency exhibits 29 year and ENSO scale (2–4 years) oscillations. There is a reduction in tropical cyclone activity over the Bay of Bengal in severe cyclone months May and November during warm phases of ENSO. Examination of the frequencies of severe cyclones with maximum sustained winds ≥ 48 knots has revealed that these cyclones have become more frequent in the North Indian Ocean during intense cyclone period of the year. The rate of intensification of tropical disturbances to severe cyclone stage has registered an upward trend. Received June 7, 1999/Revised March 20, 2000  相似文献   

12.
A statistical comparative analysis of tropical cyclone activity over the Arabian Sea and Bay of Bengal (BoB) has been conducted using best-track data and wind radii information from 1977 to 2018 issued by the Joint Typhoon Warning Center. Results have shown that the annual variation in the frequency and duration of tropical cyclones has a significant increasing trend over the Arabian Sea and an insignificant decreasing trend over the BoB. The monthly frequency of tropical cyclones in both the Arabian Sea and the BoB shows a notable bimodal character, with peaks occurring in May and October–November, respectively. The maximum frequency of tropical cyclones occurs in the second peak as a result of the higher moisture content at mid-levels in the autumn. However, the largest proportion of strong cyclones (H1–H5 grades) occurs in the first peak as a result of the higher sea surface temperatures in early summer. Tropical cyclones in the Arabian Sea break out later during the first peak and activity ends earlier during the second peak, in contrast with those in the over BoB. This is related to the onset and drawback times of the southwest monsoon in the two basins. Tropical cyclones in the Arabian Sea are mainly generated in the eastern basin, whereas in the BoB the genesis locations have a meridional (zonal) distribution in May–June (October–November) as a result of the seasonal movement of the low-level positive vorticity belt. The Arabian Sea is dominated by western and northwestern tropical cyclones by that track west and NW, accounting for about 74.6%, whereas the tropical cyclones with a NE track account for only 25.4%. The proportions of the three types of tracks are similar in the BoB, with each accounting for about 33% of the tropical cyclones. The mean intensity and size of tropical cyclones over the Arabian Sea are stronger and larger, respectively, than those over the BoB and the size of tropical cyclones over the North Indian Ocean in early summer is larger than that in autumn. The asymmetrical structure of tropical cyclones over North Indian Ocean is affected by the topography and the longest radius of the 34 kt surface wind often lies in the eastern quadrant of the tropical cyclone circulation in both sea areas. FAN Xiao-ting (樊晓婷), LI Ying (李 英), et al.  相似文献   

13.
The time series of the sea surface temperature(SST) anomaly,covering the eastern (western) equatorial Pacific,central Indian Ocean,Arabian Sea.Bay of Bengal and South China Sea(SCS),have been analyzed by using wavelet transform.Results show that there exists same interdeeadal variability of SST in the tropical Pacific and tropical Indian Ocean,and also show that the last decadal abrupt change occurred in the 1970s.On the interannual time scale,there is a similar interannual variability among the equatorial central Indian Ocean and the adjacent three sea basins(Arabian Sea.Bay of Bengal and South China Sea).but the SST interannual changes of the Indian Ocean lagged 4-5 months behind that of the equatorial central-east Pacific.Meanwhile,the interannual variability and long-range change between SST anomaly and Indian summer monsoon rainfall in recent decades have been explained and analyzed.It indicates that there existed a wet(dry) period in India when the tropical SST was lower(higher)than normal,but there was a lag of phase between them.  相似文献   

14.
Cyclonic storms having maximum winds of 34 knots and above that had genesis in north Indian Ocean have been studied with respect to the eastward passage of Madden–Julian Oscillation (MJO). In the three decades (1979–2008), there were a total of 118 cyclones reported in which 96 formed in the region chosen (0–15oN, 60oE–100oE) for the study. Although the percentage of MJO days inducing cyclogenesis is small, it is found that tropical cyclone genesis preferentially occurred during the convective phase of MJO. This accounted for 44 cyclones of the total 54 cyclones (i.e., 81.5%) formed under MJO amplitude 1 and above. The study has shown that, when the enhanced convection of MJO is over the maritime continent and the adjoining eastern Indian Ocean, it creates the highest favorable environment for cyclogenesis in the Bay of Bengal. During this phase, westerlies at 850 hPa are strong in the equatorial region south of Bay of Bengal creating strong cyclonic vorticity in the lower troposphere along with the low vertical wind shear.  相似文献   

15.
Weather Research and Forecasting (WRF-ARW) model and its three-dimensional variational data assimilation (3D-Var) system are used to investigate the impact of the Quick Scatterometer (QuikSCAT) near surface winds, Special Sensor Microwave/Imager (SSM/I)-derived Total Precipitable Water (TPW), and Meteosat-7-derived Atmospheric Motion Vectors (AMVs) on the track and intensity prediction of tropical cyclones over the North Indian Ocean. The case of tropical cyclone, Gonu (June 2007; Arabian Sea), is first tested and the results show significant improvements particularly due to the assimilation of QuikSCAT winds. Three other cases, cyclone Mala (April 2006; Bay of Bengal), Orissa super cyclone (October 1999; Bay of Bengal), and Very Severe Cyclonic storm (October 1999; Bay of Bengal), are then examined. The prediction of cyclone tracks improved significantly with the assimilation of QuikSCAT winds. The track improvement resulted from the relocation of the initial cyclonic vortices after the assimilation of QuikSCAT wind vectors. After the assimilation of QuikSCAT winds, the mean (for four cyclone cases) track errors for first, second, and third day forecasts are reduced to 72, 101, and 166?km, respectively, from 190, 250, and 381?km of control (without QuikSCAT winds) runs. The assimilation of QuikSCAT winds also shows positive impact on the intensity (in terms of maximum surface level winds) prediction particularly for those cyclones, which are at their initial stages of the developments at the time of data assimilation. The assimilation of SSM/I TPW has significant influence (negative and positive) on the cyclone track. In three of the four cases, the assimilation of the SSM/I TPW resulted in drying of lower troposphere over cyclonic region. This decrease of moisture in TPW assimilation experiment resulted in reduction of cyclonic intensity. In three of the four cyclones, the assimilation of Meteosat-7 AMVs shows negative impact on the track prediction.  相似文献   

16.
2017年春季（3—5月）大气环流特征为：北半球极涡呈单极型分布,主体位于北冰洋上空,中高纬西风带呈5波型分布。3月,地面冷高压偏强,冷空气活动频繁。4月,环流由纬向型向经向型逐渐调整,冷空气势力减弱。5月,东北气旋明显加强,冷暖势力相当,入海气旋增多。春季,我国近海海域主要有16次8级以上大风过程,其中冷空气大风过程有7次,冷空气和温带气旋共同影响的大风过程有1次,入海温带气旋过程有4次,东北冷涡影响大风过程有3次,强对流导致雷暴大风过程1次;且有8次明显的浪高在2 m以上的大浪过程。春季共有6次比较明显的海雾过程,分别为3月1次、4月2次、5月3次。西北太平洋和南海共生成1个台风“梅花”和1个热带低压,其他各大洋共有热带气旋15个,分别为大西洋1个、东太平洋1个、南太平洋5个、南印度洋6个、北印度洋2个。  相似文献   

17.
The Weather Research and Forecasting (WRF-ARW) model and its three-dimensional variational data assimilation (3D-Var) system are used to investigate the impact of the Advanced Microwave Sounding Unit-A (AMSU-A) radiances on the prediction of Indian Ocean tropical cyclones. Three tropical cyclones are selected for this study: cyclone Mala (April 2006; Bay of Bengal), cyclone Gonu (June 2007; Arabian Sea), and cyclone Sidr (November 2007; Bay of Bengal). For each case, observing system experiments are designed, by producing two sets of analyses from which forecasts are initialized. Both sets of analyses contain all conventional and satellite observations operationally used, including, but not limited to, Quick Scatterometer (QuikSCAT) surface winds, Special Sensor Microwave/Imager (SSM/I) surface winds, Meteosat-derived atmospheric motion vectors (AMVs), and differ only in the exclusion (CNT) or inclusion (EXP) of AMSU-A radiances. Results show that the assimilation of AMSU-A radiances changes the large-scale thermodynamic structure of the atmosphere, and also produce a stronger warm core. These changes cause large forecast track improvements. In particular, without AMSU-A assimilation, most forecasts do not produce landfall. On the contrary, the forecasts initialized from improved EXP analyses in which AMSU-A data are included produce realistic landfall. In addition, intensity forecast is also improved. Even if the analyzed cyclone intensity is not affected by the assimilation of AMSU-A radiances, the predicted intensity improves substantially because of the development of warm cores which, through creation of stronger gradients, helps the model in producing intense low centre pressure.  相似文献   

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