Influence of climatic warming in the Southern and Northern Hemi-sphere on the tropical cyclone over the western North Pacific Ocean

Based on analyzing the surface air temperature series in the Southern and Northern Hemisphere and the tropical cyclone (TC) over the western North Pacific Ocean, the relationships between climatic warming and the frequency and intensity of tropical cyclone are investigated. The results showed that with the climatic warming in both hemispheres, the frequency of the tropical cyclone over the western North Pacific Ocean reduces and its intensity weakens simultaneously. A possible explanation might be that the cold air invasion from the Southern Hemisphere weakens due to global warming.

The Relationship Between Indian Ocean SST and Tropical Cyclone Genesis Frequency over North Indian Ocean in May

Tropical cyclone(TC)activities in the North Indian Ocean(NIO)peak in May during the pre-monsoon period,but the TC frequency shows obvious inter-annual variations.By conducting statistical analysis and dynamic diagnosis of long-term data from 1948 to 2016,the relationship between the inter-annual variations of Indian Ocean SST and NIO TC genesis frequency in May is analyzed in this paper.Furthermore,the potential mechanism concerning the effect of SST anomaly on TC frequency is also investigated.The findings are as follows:1)there is a broadly consistent negative correlation between NIO TC frequency in May and SST in the Indian Ocean from March to May,with the key influencing area located in the southwestern Indian Ocean(SWIO);2)the anomalies of SST in SWIO(SWIO-SST)are closely related to a teleconnection pattern surrounding the Indian Ocean,which can significantly modulate the high-level divergence,mid-level vertical motion and other related environmental factors and ultimately influence the formation of TCs over the NIO;3)the increasing trend of SWIO-SST may play an essential role in the downward trend of NIO TC frequency over the past 69 years.

Southern and Tropical Indian Ocean SST: A Possible Predictor of Winter Monsoon Rainfall over South India

The complexities in the relationship between winter monsoon rainfall (WMR) over South India and Sea Surface temperature (SST) variability in the southern and tropical Indian Ocean (STIO) are evaluated statistically. The data of the time period of our study (1950-2003) have been divided exactly in two halves to identify predictors. Correlation analysis is done to see the effect of STIO SST variability on winter monsoon rainfall index (WMRI) for South India with a lead-lag of 8 seasons (two years). The significant positive correlation is found between Southern Indian Ocean (SIO) SST and WMRI in July-August-September season having a lag of one season. The SST of the SIO, Bay of Bengal and North Equatorial Indian Ocean are negatively correlated with WMRI at five, six and seven seasons before the onset of winter monsoon. The maximum positive correlation of 0.61 is found from the region south of 500 S having a lag of one season and the negative correlations of 0.60, 0.53 and 0.57 are found with the SST of the regions SIO, Bay of Bengal and North Equatorial Ocean having lags of five, six and seven seasons respectively and these correlation coefficients have confidence level of 99%. Based on the correlation analysis, we defined Antarctic Circumpolar Current Index A and B (ACCIA (A) & ACCIB (B)), Bay of Bengal index (BOBI (C)) and North Equatorial Index (NEI (D)) by averageing SST for the regions having maximum correlation (positive or negative) with WMRI index. These SST indices are used to predict the WMRI using linear and multivariate linear regression models. In addition, we also attempted to detect a dynamic link for the predictability of WMRI using Nino 3.4 index. The predictive skill of these indices is tested by error analysis and Willmott’s index.

Climatological and Seasonal Variations of the Tropical Cyclone Genesis Potential Index Based on Oceanic Parameters in the Global Ocean

This study investigates the global performance of the tropical cyclone(TC)genesis potential index based on oceanic parameters(GPI_(ocean))proposed by Zhang et al.(2016).In six major TC formation basins,GPI_(ocean)can represent the seasonal variations of TC genesis over most basins,except for the North Indian Ocean(NIO).The monthly climatological GPI_(ocean)shows only a single peak in the NIO,which cannot describe the bimodal pattern of the annual cycle of TC genesis.To determine the cause of the poor performance of GPI_(ocean)in the NIO,the relative contributions of different parameters related to GPI_(ocean)are calculated and compared with those related to the genesis potential index developed by Emanuel and Nolan(2004)(GPI04).Results show that the net longwave radiation on the sea surface is responsible for the single peak of TC genesis in the NIO in boreal summer.Compared with GPI04,vertical wind shear is not involved in GPI_(ocean).Vertical wind shear is the dominant factor inhibiting TC genesis in the NIO in boreal summer.Therefore,the absence of vertical wind shear in GPI_(ocean)results in the failure of the annual cycle of TC genesis in the NIO.

Analysing the atmospheric-oceanic conditions driving the sustained long track and intensity of Tropical Cyclone Freddy

During February–March 2023,the record-breaking tropical cyclone(TC)Freddy caused widespreadflooding and damages across southeastern Africa.While<5%of TCs make landfall into southern Africa,TC Freddy made landfall twice and is the only TC in the past two decades that has tracked over 8000 km across the entire southern Indian Ocean.To understand why TC Freddy was so unique,this study investigated the evolution,track and atmospheric-oceanic mechanisms driving TC Freddy using the ERA5,CFSv2,OSTIA,NCEP-NCAR datasets and track data from various sources.It was found that SSTs were>27◦C during TC Freddy’s lifetime,while TC Dingani and a split Mascarene High played a role in steering TC Freddy across the southern Indian Ocean.Leading up to the development of TC Freddy,conditions were favourable for TC genesis,as indicated by the levels of the Genesis Potential Parameter(GPP)and its modified version(GPPI),the tropical cyclone heat potential levels,and elevated SSTs.Ridging subtropical anticyclones and the Mascarene High alongside favourable steeringflow and GPP(and GPPI)conditions resulted in Freddy’s double landfall in Mozambique.In assessing the tracks,it was found that there are discrepancies in the track of the commonly used IBTrACS when compared to ERA5 and RSMC tracks,which has implications for impact studies due to the underestimation of landfall considerations.This study reveals the unique characteristics and atmospheric-oceanic mechanisms driving TC Freddy,emphasising the impor-tance of accurate representation of favourable conditions and track data for enhancing TC forecasting and impact assessments.

The influence of tropical Indian Ocean warming on the Southern Hemispheric stratospheric polar vortex

During the past decades, concurrent with global warming, most of global oceans, particularly the tropical Indian Ocean, have become warmer. Meanwhile, the Southern Hemispheric stratospheric polar vortex (SPV) exhibits a deepening trend. Although previous modeling studies reveal that radiative cooling effect of ozone depletion plays a dominant role in causing the deepening of SPV, the simulated ozone-depletion-induced SPV deepening is stronger than the observed. This suggests that there must be other factors canceling a fraction of the influence of the ozone depletion. Whether the tropical Indian Ocean warming (IOW) is such a factor is unclear. This issue is addressed by conducting ensemble atmospheric general circulation model (AGCM) experiments. And one idealized IOW with the amplitude as the observed is prescribed to force four AGCMs. The results show that the IOW tends to warm the southern polar stratosphere, and thus weakens SPV in austral spring to summer. Hence, it offsets a fraction of the effect of the ozone depletion. This implies that global warming will favor ozone recovery, since a warmer southern polar stratosphere is un-beneficial for the formation of polar stratospheric clouds (PSCs), which is a key factor to ozone depletion chemical reactions.

DEVELOPMENT OF NWP BASED OBJECTIVE CYCLONE PREDICTION SYSTEM(CPS) FOR NORTH INDIAN OCEAN TROPICAL CYCLONES——EVALUATION OF PERFORMANCE

An objective NWP based Cyclone Prediction System(CPS) has been developed and implemented at IMD for operational cyclone forecasting over the north Indian Ocean(NIO). The five forecast components of CPS are(a) Genesis Potential Parameter(GPP),(b) Multi-Model Ensemble(MME) technique for track prediction,(c) Statistical Cyclone Intensity Prediction(SCIP),(d) rapid intensification and(e) decay model to forecast intensity after the landfall.Verification shows GPP had higher probability of detection(0.98) and lower false alarm ratio(0.27) with higher critical success index(0.72). Mean track error of MME ranged from 74 km at 12 h to 200 km at 72 h and reduced by 27% to 52% for 36 h to 72 h forecast during 2009-2013. The mean forecast errors of landfall position ranged from 56 km at 24 h to 137 km at 72 h and landfall time error ranged from 3.6 h at 24 h to 6.1 h at 72 h. Mean intensity errors of SCIP ranged from 5.4 kt at 12 h to 16.9 kt at 72 h. The probabilistic rapid intensification forecast was skillful compared to climatology. The 6-hourly decaying intensity(after landfall) errors ranged from 3 kt to 4.9 kt. Results demonstrate the potential of CPS for operational cyclone forecast over the NIO.

EVALUATION OF CONE OF UNCERTAINTY IN TROPICAL CYCLONE TRACK FORECAST OVER NORTH INDIAN OCEAN ISSUED BY INDIA METEOROLOGICAL DEPARTMENT

India Meteorological Department(IMD) introduced cone of uncertainty(COU) in cyclonic disturbances(CDs) alongwith the 72 hr track forecast over the north India Ocean(NIO) in 2009. The track forecast for CDs is issued for +6, +12, +18, +24, +36, +48, +60 and +72 hrs time period from the stage of deep depression onwards. An attempt is made to evaluate COU forecast issued by IMD during 2009-2011(3 years). The size of the cone is deduced from climatological track forecast errors. The accuracy of COU forecast has been analysed with respect to basin of formation, season of formation, intensity and type of track(climatological/straight moving and recurving/looping type) of CDs by calculating percentage of total number of forecasts in each category lying within COU. The observed track lies within the forecast COU in about 60% of the cases over the NIO. The accuracy of COU forecast is about 66% in post-monsoon season and about 50% in pre-monsoon season. The observed track lies within the forecast COU in 90% cases of climatological/straight moving CDs and 39% cases of recurving/looping CDs. The observed track lies within COU forecast in about 71% cases of severe cyclonic storm and 37% cases of cyclonic storm/deep depression.

North Indian Ocean tropical cyclone activities influenced by the Indian Ocean Dipole mode

Using Joint Typhoon Warning Center tropical cyclone(TC)track data over the North Indian Ocean(NIO),National Centers for Environmental Prediction monthly reanalysis wind and outgoing long-wave radiation data,and National Oceanic and Atmospheric Administration sea surface temperature data from 1981 to 2010,spatiotemporal distributions of NIO TC activity and relationships with local sea surface temperature(SST)were studied with statistical diagnosis methods.Results of empirical orthogonal function(EOF)analysis of NIO TC occurrence frequency show that the EOF1 mode,which accounts for 16%of total variance,consistently represents variations of TC occurrence frequency over the whole NIO basin.However,spatial dis- tributions of EOF1 mode are not uniform,mainly indicating variations of westward-moving TCs in the Bay of Bengal.The prevailing TC activity variation mode oscillates significantly on a quasi-5 year interannual time scale.NIO TC activity is notably influenced by the Indian Ocean dipole(IOD)mode.When the Indian Ocean is in a positive(negative)phase of the IOD, NIO SST anomalies are warm in the west(east)and cold in the east(west),which can weaken(strengthen)convection over the Bay of Bengal and eastern Arabian Sea,and cause anticyclonic(cyclonic)atmospheric circulation anomalies at low levels. This results in less(more)TC genesis and reduced(increased)opportunities for TC occurrence in the NIO.In addition,positive(negative)IOD events may strengthen(weaken)westerly steering flow over the Bay of Bengal,which further leads to fewer(more)westward-moving TCs which appear in regions west of 90°E in that bay.

APPLICATION OF FUZZY CLUSTERING TECHNIQUE FOR ANALYSIS OF NORTH INDIAN OCEAN TROPICAL CYCLONE TRACKS

A fuzzy, c-means(FCM) clustering technique is explored to investigate the track of tropical cyclones over the North Indian Ocean(NIO) for the period(1976-2014). A total of fi ve clusters is objectively identifi ed based on partition index,partition coeffi cient, Dunn Index and separation index. The results obtained during analysis emphasized that each cluster has the unique features in terms of their genesis location, landfall, travel duration, trajectory, seasonality, accumulated cyclone energy and Intensity. Analysis of large scale environmental parameters, constructed preceding day of genesis show some of these parameters to be potential precursors to TC formation for almost all the clusters, most prominently, mid-tropospheric humidity, zonal wind,vorticity and outgoing long wave radiation of the main developing regions. The individual clusters have the several distinct features in their seasonal cycles.The cluster C5 shows distinct bimodal distributions where as other clusters are formed throughout the year. ENSO infl uenced the cyclone frequency in two of the fi ve clusters. The MJO is found to play an important role in the genesis of the cyclone. The post monsoon season cyclone frequency is more in MJO phase 2, 3 and 4. The technique(FCM) can be used as a guideline in terms of the probable affected zone of TC Tracks by the operational forecasters.

Improvement of wind field forecasts for tropical cyclones over the North Indian Ocean

This paper demonstrates a modification method for real-time improvement of wind field forecasts for a typical cyclone VARDAH,which formed over the Bay of Bengal(Bo B)in 2016.The proposed method to improve the wind field forecasts associated with tropical cyclone consists of two components.The first one is the relocation method,which relocates the wind field forecasts obtained from the Global Forecast System(GFS)data of National Centres for Environmental Prediction(NCEP).The relocation of the model forecasts wind field is made on forecast locations generated by Multi Model Ensemble(MME)track forecast of India Meteorological Department(IMD).The second one is the modification of wind speed,which directly modifies the NCEP GFS wind speed forecasts based on intensity forecasts by Statistical Cyclone Intensity Prediction(SCIP)model of IMD.Applying these two methods,the displacement of wind field and underestimation/overestimation of wind speed in the model forecast field can be improved.Both modification methods show considerable improvements in the displacement and speed of wind field forecasts.The displacement error of wind field is found to have improved by about 51%at 48 h and about 80%at 72 h forecast.Overestimation of maximum wind speed in the forecast field is found to be improved by about 88%at 48 h and about 38%at 72 h forecast.The spatial distributions of corrected wind speed forecasts are also found to be more analogous than direct model forecasts with the corresponding analysis wind at all forecast hours.Two proposed modification methods could provide improved wind field forecast associated with tropical cyclones in real-time.

Impact of Tropical Cyclones over the North Indian Ocean on Weather in China and Related Forecasting Techniques:A Review of Progress

Tropical cyclones(TCs)over the North Indian Ocean(NIO)are closely related to Asian summer monsoon activities and have a great impact on the precipitation in the Tibetan Plateau,southwestern China,and even the middle and lower reaches of the Yangtze River.In this paper,the research progress on the impacting mechanisms of NIO TCs on the weather in China and associated forecasting techniques is synthesized and reviewed,including characteristics of the NIO TC activity,its variability under climate change,related precipitation mechanism,and associated forecasting techniques.On this basis,the limitations and deficiencies in previous research on the physical mechanisms and forecasting techniques of NIO TCs affecting the weather in China are elucidated and the directions for future investigations are discussed.

Tropical cyclone genesis over the western north Pacific in La Ni?a decay summers: Comparison between 2018 and 2021

As the primary interannual signal of variability in the tropical ocean-atmosphere interaction, the El Ni?o-Southern Oscillation has a considerable impact on tropical cyclone(TC) activity over the western North Pacific(WNP). Both 2018 and2021 were La Ni?a decay years, but TC activity over the WNP during the two summers(June–August) showed notable differences. In 2018, summer TC activity was unusually high with a total of 18 TCs, and the region of TC genesis was mainly in the central and eastern WNP. In contrast, only 9 TCs were generated in summer 2021, and the region of TC genesis was primarily in the western WNP. By comparing the characteristics of the large-scale environmental conditions over the regions of TC genesis, the thermal factors of the tropical oceans, and the activity of the Madden-Julian Oscillation(MJO), this study revealed the possible causes for the marked differences in TC genesis over the WNP during the two summers, which both had a similar background of La Ni?a decay. The Indian Ocean Basin Mode(IOBM) transitioned of a cold anomaly in the winter of 2017/2018and persisted until summer 2018. At the same time, the Pacific Meridional Mode(PMM) maintained a positive phase, leading to eastward and northward displacement of the Western Pacific Subtropical High in summer, and eastward extension of the tropical monsoon trough, which presented conditions conducive to TC genesis over the Northwest Pacific. Moreover, the days when the MJO stagnated in phases 5 and 6 in the summer of 2018 increased by approximately 150% relative to climatological state,providing dynamic conditions favorable for TC formation. In 2021, the IOBM quickly turned to a warm anomaly in March and persisted until summer, whereas the PMM became a negative phase in January and remained so until summer. At the same time,the MJO stagnated in phases 2 and 3 for up to 47 days, with the center of convection located over the western Maritime Continent, producing conditions unconducive to TC genesis over the Northwest Pacific. Thus, despite being under a similar background of La Ni?a decaying year, the distinct evolutions of the IOBM, PMM, and MJO in spring and summer of 2018 and2021 were the main causes of the notable differences in TC activity over the WNP during these two summers, and the anomalies in IOBM and MJO contributed more significantly than those of the PMM.

Forecasting of tropical cyclones ASANI(2022)and MOCHA(2023)over the Bay of Bengal-real time challenges to forecasters

This study examines the track and intensity forecasts of two typical Bay of Bengal tropical cyclones(TC)ASANI and MOCHA.The analysis of various Numerical Weather Prediction(NWP)model forecasts[ECMWF(European Centre for Medium range Weather Forecast),NCEP(National Centers for Environmental Prediction),NCUM(National Centre for Medium Range Weather Forecast-Unified Model),IMD(India Meteorological Department),HWRF(Hurricane Weather Research and Forecasting)],MME(Multi-model Ensemble),SCIP(Statistical Cyclone Intensity Prediction)model,and OFCL(Official)forecasts shows that intensity forecasts of ASANI and track forecasts of MOCHA were reasonably good,but there were large errors and wide variation in track forecasts of ASANI and in intensity forecasts of MOCHA.Among all model forecasts,the track forecast errors of IMD model and MME were least in general for ASANI and MOCHA respectively.Also,the landfall point forecast errors of IMD were least for ASANI,and the MME and OFCL forecast errors were least for MOCHA.No model is found to be consistently better for landfall time forecast for ASANI,and the errors of ECMWF,IMD and HWRF were least and of same order for MOCHA.The intensity forecast errors of OFCL and SCIP were least for ASANI,and the forecast errors of HWRF,IMD,NCEP,SCIP and OFCL were comparable and least for MOCHA up to 48 h forecast and HWRF errors were least thereafter in general.The ECMWF model forecast errors for intensity were found to be highest for both the TCs.The results also show that although there is significant improvement of track forecasts and limited or no improvement of intensity forecast in previous decades but challenges still persists in real time forecasting of both track and intensity due to wide variation and inconsistency of model forecasts for different TC cases.

北印度洋热带气旋统计特征及年代际变化

本研究利用基于统一卫星观测和识别方法产生的ADT-HURSAT气旋数据集,对北印度洋热带气旋在1978~2017共40年的整体特征及年代际变化进行了统计分析。研究发现,春季和秋季是北印度洋热带气旋的高发季节,孟加拉湾气旋数量达到峰值的时间在两个高发季节中均比阿拉伯海提前约一个月。北印度洋气旋的生成区域主要分布于阿拉伯海东部海域和孟加拉湾中部偏西海域。CS(Cyclone Storm)等级气旋更多生成于在北印度洋的偏北海域,ESCS(Extremely Severe Cyclone Storm)等级及以上的强气旋全部在5°N~15°N纬度范围内生成。对于年代际变化,北印度洋热带气旋在秋季的生成数量平均每十年增加5个,生成区域在后二十年呈现向西北方向移动的特点,其中阿拉伯海热带气旋生成位置分别向西移动1.3°和3.2°(p<0.01),较孟加拉湾气旋变化更加显著,平均增强速率也超过孟加拉湾约20%。特别是,相比于前10年(1998~2007),阿拉伯海近10年(2008~2017年)热带气旋数量减少,气旋达到的最大强度提高至120 kt,孟加拉湾气旋数量自1998年以来较为稳定,气旋最大强度却持续降低,这与使用其他数据集的研究结果不同,表明数据集质量对气旋特征变化的重要性。进一步分析发现,北印度洋潜热通量的年代际差异是控制北印度洋热带气旋生成位置年代际变化的主要因素。

Improvement of displacement error of rainfall and wind field forecast associated with landfalling tropical cyclone AMPHAN

Spatial distribution of rainfall and wind speed forecast errors associated with landfalling tropical cyclones(TC)occur significantly due to incorrect location forecast by numerical models.Two major areas of errors are:(i)over-estimation over the model forecast locations and(ii)underestimation over the observed locations of the TCs.A modification method is proposed for real-time improvement of rainfall and wind field forecasts and demonstrated for the typical TC AMPHAN over the Bay of Bengal in 2020.The proposed method to improve the model forecasts is a relocation method through shifting of model forecast locations of TC to the real-time official forecast locations of India Meteorological Department(IMD).The modification is applied to the forecasts obtained from the operational numerical model,the Global Forecast System(GFS)of IMD.Application of the proposed method shows considerable improvement of both the parameters over both the locations.The rainfall forecast errors due to displacement are found to have improved by 44.1%–69.8%and 72.1%–85.2%over the GFS forecast locations and over the observed locations respectively for the respective forecast lead times 48 h,72 h,and 96 h.Similarly,the wind speed forecasts have improved by 27.6%–56.0%and 63.7%–84.6%over the GFS forecast locations and over the observed locations respectively for the respective forecast lead times 60 h,72 h,and 84 h.The results show that the proposed technique has capacity to provide improved spatial distributions of rainfall and wind speed forecasts associated with landfalling TCs and useful guidance to operational forecasters.

印度洋海盆增暖及ENSO对西北太平洋热带气旋活动的影响

本文主要分析1950～2010年间印度洋海盆增暖和西北太平洋热带气旋(TC)活动的关系,并与ENSO对西北太平洋TC活动的影响相比较,结果表明:印度洋海盆异常增暖与西北太平洋地区总TC生成年频数尤其是弱TC相关较好,印度洋海盆异常增暖,西北太平洋地区为异常的反气旋,对流抑制,降水偏少,不利于TC的生成,反之亦然。而ENSO对西北太平洋热带气旋的影响,主要体现在对强TC的年生成频数的影响,ElNio发展年,季风槽加深东伸,TC生成位置偏东,由于TC在海洋上的生命史较长,TC的平均强度偏强,因而强TC年生成频数偏多;La Nia发展年,季风槽较浅,TC生成位置偏西,TC的平均强度偏弱,强TC年生成频数偏少。但是ENSO指数与强TC年频数的相关有着年代际的变化,在1950～1969年和1990～2009年间,ENSO指数和强TC年频数相关很好,分别为0.532和0.687,而在1970～1989这二十年间,两者相关很弱,只有0.081。

2015/2016超强El Nio对中国南方冬春季降水的影响分析

利用1981—2016年的中国160站降水资料、OISST海温资料和NCEP/NCAR大气环流资料,对比分析了中等强度El Nio和2015/2016超强El Nio对中国东南部、江淮流域和西南地区冬春季降水影响的异同。结果表明:在中等强度El Nio的冬季,偏暖的赤道中东太平洋海表面温度(Sea Surface Temperature,SST)所激发的西北太平洋和日本附近的异常反气旋环流,其异常的西南风会加强南海—西北太平洋的水汽向中国东部输送,造成中国东南部和江淮流域的降水一致偏多。2015/2016超强El Nio的冬季,赤道中东太平洋SST的强度异常偏强,中国东部异常偏冷的表面气温和对流层低层温度加强大陆冷高压,长江流域及其以北地区受异常强的北风控制,从而造成中国东南部降水增多、江淮流域降水减少。在2015/2016超强El Nio事件衰减位相的春季,中国东南部和西南部降水的增加主要归因于异常偏暖的西北印度洋和东南印度洋SST的作用。经CAM5模式试验证明,西北印度洋异常偏暖的SST引起了北印度洋的异常西南风,激发了孟加拉湾—西北太平洋的异常反气旋,加强了印度洋和南海—西北太平洋的水汽向中国西南和东南部输送。此外,东南印度洋异常偏暖的SST还会激发局地异常上升运动,通过经向垂直环流加强南海—西北太平洋异常下沉运动,诱使中国东南部的上升运动加强,导致降水增多。

北印度洋热带气旋月季变化特征及成因分析

采用美国联合台风警报中心(JTWC)提供的北印度洋1977年至2008年热带气旋(TC)资料、NOAA提供提供的1977—2008年月平均海表面温度(SST)资料、逐日的高度场(HGT)资料和NCEP提供1982—2008年全球再分析资料,对北印度洋热带气旋的月季变化的双峰结果进行分析,结果表明:500 hPa流场上热带辐合带的北进南退和500hPa高度场上南亚高压季节性进退跟双峰结构的季节变化有很好的对应关系。此外,海温的季节性变化和季风的爆发对热带气旋的月季变化有很大的影响,海温较高的时期,热带气旋发生频数较多,反之依然。当季风爆发时,存在着强的垂直风切变,不利于热带气旋的生成。正是这些综合因素,才造成了北印度洋热带气旋的双峰结构。

1977-2008年北印度洋热带气旋统计特征分析

采用美国联合台风警报中心(JTWC)提供的北印度洋1977-2008年热带气旋资料、NOAA提供的1982-2008年高分辨率合成资料和NCEP提供的1982-2008年全球再分析资料,对北印度洋上167个热带气旋个例进行了统计分析,结果表明:1)北印度洋热带气旋通常发生在阿拉伯海东部和孟加拉湾中部,阿拉伯海上活动的热带气旋要比孟加拉湾的频繁。由于印度半岛地形的影响,阿拉伯海上的热带气旋常常是沿着西高止山脉向西北方向运动,最后在巴基斯坦的南部登陆;孟加拉湾上热带气旋常常在孟加拉国和缅甸的南部登陆。2)小波分析结果表明,北印度洋热带气旋的年际变化具有2～4 a和4～8 a的显著周期。3)通过对热带气旋强度分析可以得出,有20个热带气旋(TC)达到了台风(TY)标准,3个达到强台风(STY)标准,18个达到超强台风(Super TY)标准。4)热带气旋出现频数季节性变化非常明显,春、夏、秋、冬呈现出高-低-高-低的形式,春季和秋季是北印度洋热带气旋高发季节。通过对500 hPa流场分析发现,500 hPa流场上辐合带的北进南退很好地解释了热带气旋的季节性变化。5)海温和季风对热带气旋发生频数有很大的影响,高海温和弱的垂直风切变有利于TC的生成。