Interannual variability of tropical cyclone activity along the Pacific coast of North America

The interannual variability of near-coastal eastern North Pacific tropical cyclones is described using a data set of cyclone tracks constructed from U.S. and Mexican oceanic and atmospheric reports for the period 1951-2006. Near-coastal cyclone counts are enumerated monthly, allowing us to distinguish interannual variability during different phases of the May-November tropical cyclone season. In these data more tropical cyclones affect the Pacific coast in May-July, the early months of the tropical cyclone season, during La Niña years, when equatorial Pacific sea surface temperatures are anomalously cool, than during El Niño years. The difference in early season cyclone counts between La Niña and El Niño years was particularly pronounced during the mid-twentieth century epoch when cool equatorial temperatures were enhanced as described by an index of the Pacific Decadal Oscillation. Composite maps from years with high and low near-coastal cyclone counts show that the atmospheric circulation anomalies associated with cool sea surface temperatures in the eastern equatorial Pacific are consistent with preferential steering of tropical cyclones northeastward toward the west coast of Mexico.     

Climatology of landfalling tropical cyclones in Bangladesh 1877–2003

Bangladesh is highly susceptible to tropical cyclones. Unfortunately, there is a dearth of climatological studies on the tropical cyclones of Bangladesh. The Global Tropical Cyclone Climatic Atlas (GTCCA) lists historical storm track information for all the seven tropical cyclone ocean basins including the North Indian Ocean. Using GIS, tropical cyclones that made landfall in Bangladesh during 1877–2003 are identified and examined from the climatological perspective. For the convenience of study, the coast of Bangladesh is divided into five segments and comparisons are made among the coastal segments in terms of cyclone landfall and vulnerability. There is a large variability in the year-to-year occurrence of landfalling tropical cyclones in Bangladesh. Most of the tropical cyclones (70%) hit in the months of May–June and October–November generally show the well-known pattern of pre- and post-monsoon cyclone seasons in that region.     

ITCZ rather than ENSO signature for abrupt climate changes across the tropical Pacific?

Latitudinal movements of the Intertropical Convergence Zone (ITCZ), analogous to its present-day seasonal shifts, and El Niño Southern Oscillation (ENSO)-type variability both potentially impacted rainfall changes at the millennial timescale during the last glacial period. In this study we compare tropical Pacific sedimentary records of paleoprecipitation to decipher which climate mechanism was responsible for the past rainfall changes. We find that latitudinal movements of the ITCZ are consistent with the observed rainfall patterns, challenging the ENSO hypothesis for explaining the rapid rainfall changes at low latitudes. The ITCZ-related mechanism appears to reflect large-scale atmospheric rearrangements over the tropical belt, with a pronounced Heinrich-Dansgaard/Oeschger signature. This observation is coherent with the simulated tropical rainfall anomalies induced by a weakening of the Atlantic thermohaline circulation in modeling experiments.     

Relationship between all-India summer monsoon rainfall and southern oscillation/eastern equatorial Pacific sea surface temperature

The interannual variability of all-India summer monsoon (June to September) rainfall and its teleconnections with the southern oscillation index (SOI) and sea surface temperature (SST) anomaly of the eastern equatorial Pacific ocean have been examined for the period 1871–1978 for different seasons (i.e., winter, spring, summer and autumn). The relationship (correlation coefficient) between all-India summer monsoon rainfall andSOI for different seasons is positive and highly significant. Further examination of 10-, 20- and 30-year sliding window lengths’ correlations, brings out the highly consistent and significant character of the relationships. The relationship between all-India monsoon rainfall andSST for different seasons is negative and is significant at 1 % level or above. Drought years are characterised by negative anomalies ofSOI and positive anomalies ofSST and vice versa with flood years. The relationship betweenSOI andSST is negative and significant at 0.1 % level. The relationships between all-India summer monsoon rainfall,SOI and sst are expected to improve our understanding of the interannual variability of the summer monsoon.     

Rainfall–runoff temporal variability in Kermanshah province,Iran and distinguishing anthropogenic effects from climatic effects

Investigation of changes in rainfall and runoff patterns in various regions and determining their relationship in the sense of hydrology and climatology are of great importance, considering those patterns efficiently reveal the human and natural factors in this variability. One of the mathematical methods to recognise and model these fluctuations is Wavelet Analysis. This is a spectral method used in multivariate analysis and also tracing fluctuations in temporal series. In this study, continuous wavelet transformation is used to identify temporal changes in rainfall–runoff patterns. The hydrological and rain gauge data were collected from in situ measurements of Kermanshah province located in the western border of Iran. Precipitation anomalies were reconsidered in a number of stations, including Kermanshah, for a period of 55 years (1955–2010) and discharge of Gamasiab River in Polchehr station, discharge of Khoram Rood River in Aran-Gharb station and discharge of Gharasoo River in Polekohne station. In addition, anomalies of the climatic teleconnections were studied to emphasise the climatological effects on the runoff pattern in the region. The role of natural and anthropogenic effects (land use changes) has been distinguished and identified, using the comparison of the teleconnections and hydrological data. The results achieved from three stations show that there was an approximate correlation between rainfall, runoff and teleconnections until the year 1995; however, after 1995, a great difference appeared among them, specifically for the Aran-Gharb station (Khoram Rood River). The post-1995 slope of cumulative standardised anomaly is much steeper in the case of runoff compared to rainfall. As there were no significant climate changes in the region, it could be concluded that the runoff decrease is not caused by climate changes, but by anthropogenic effects, human interventions and extra water usage from the surface and underground water resources for agriculture and economic purposes.     

Spatial variability of rainfall trends in Iran

The main objective of this paper is to analyze the spatial variability of rainfall trends using the spatial variability methods of rainfall trend patterns in Iran. The study represents a method on the effectiveness of spatial variability for predicting rainfall trend patterns variations. In rainfall trend analysis and spatial variability methods, seven techniques were used: Mann–Kendall test, Sen’s slope method, geostatistical tools as a global polynomial interpolation and the spatial autocorrelation (Global Moran’s I), high/low clustering (Getis-Ord General G), precipitation concentration index, generate spatial weights matrix tool, and activation functions of semiliner, sigmoid, bipolar sigmoid, and hyperbolic tangent in the artificial neural network technique .For the spatial variability of monthly rainfall trends, trend tests were used in 140 stations of spatial variability of rainfall trends in the 1975–2014 period. We analyzed the long and short scale spatial variability of rainfall series in Iran. Spatial variability distribution of rainfall series was depicted using geostatistical methods (ordinary kriging). Relative nugget effect (RNE) predicted from variograms which showed weak, moderate, and strong spatial variability for seasonal and annual rainfall series. Moreover, the rainfall trends at each station were examined using the trend tests at a significance level of 0.05. The results show that temporal and spatial trend patterns are different in Iran and the monthly rainfall had a downward (decreasing) trend in most stations, and the trend was statistically significant for most of the series (73.5% of the stations demonstrated a decreasing trend with 0.5 significance level). Rainfall downward trends are generally temporal-spatial patterns in Iran. The monthly variations of rainfall decreased significantly throughout eastern and central Iran, but they increased in the west and north of Iran during the studied interval. The variability patterns of monthly rainfall were statistically significant and spatially random. Activation functions in the artificial neural network models, in annual time scale, had spatially dispersed distribution with other clustering patterns. The results of this study confirm that variability of rainfall revealing diverse patterns over Iran should be controlled mainly by trend patterns in the west and north parts and by random and dispersed patterns in the central, southern, and eastern parts.     

Climate change impact on rainfall spatio-temporal variability (Macta watershed case,Algeria)

This work describes the climate change impact study on rainfall patterns in Macta watershed, located in the northwest of Algeria. The monthly rainfall data collection, verification and validation have built a database with 42 stations, each with 42 years of observations from 1970 to 2011. The study of annual total rainfall has identified a downward trend and quantifies the deficits that are within the observation time series. The division of the annual rainfall series into four periods allowed to highlighting the increase in inter-year temporal variability with the coefficient of variation increases from 17 to 27%. The study shows an annual rainfall deficit increment from 13 to 25%. The standard deviation values decrease significantly for the last two periods showing a spatial variability. Multivariate statistical study by the hierarchical clustering method resulted in the formation of station groups indicating the unification of monthly rainfall patterns.     

Global temperature and monsoon activity

In this paper an attempt has been made to search a new parameter for the prediction of the Indian summer monsoon rainfall. For this purpose the relationship of the global surface-air temperature of four standard seasons viz., Winter (December-January-February), Spring (March-April-May), Summer (June-July-August), Autumn (September-October-November) with the Indian summer monsoon rainfall has been carried out. The same analysis is also carried out with surface-air temperature anomalies within the tropical belt (30°S to 30°N) and Indian summer monsoon rainfall. For the present study data for 30 years period from 1958 to 1988 have been used. The analysis reveals that there is a strong inverse relationship between the monsoon activity and the tropical belt temperature.     

The role of natural ecosystems and socio-economic factors in the vulnerability of coastal villages to cyclone and storm surge

Vulnerability assessment due to tropical storms has been attempted for larger spatial units, and the roles played by natural ecosystems like mangroves or hydrological variables like proximity to rivers or various socio-economic factors determining economic well-being are rarely taken into account. During cyclones, evacuation and relief works are undertaken at the village level, and thus, knowledge of relative vulnerability of the coastal villages is important to the policy makers. The paper studies 262 villages lying within a 10?km of the coast in one of the most cyclone prone districts of India and estimates the probability of expected human fatality due to severe cyclone for these villages. Such probabilities are calculated from a cyclone impact (human deaths) function where a wide range of factors including natural ecosystems are used to control for the exposure and adaptive capacity of the villages. The results show villages established in mangrove habitat areas (after clearing the forest) and those with more marginal workers (without any regular jobs) to face a very high death risk. In contrast, villages situated in the leeward side of existing mangrove forest or near a major river are seen to be facing a much lower risk of deaths. The results have important implications like conserving mangroves in cyclone-prone areas, priority evacuation of villages established in the mangrove habitat before a high-intensity cyclone, etc., for cyclone hazard management.     

China’s tropical cyclone disaster risk source analysis based on the gray density clustering

In recent years, tropical cyclones on the Pacific Northwest have decreased. We cannot infer that tropical cyclones impact China have reduced, because the Pacific Northwest is not homogeneous, and the variation characteristics of tropical cyclones in different sea areas are not clear. This paper uses gray relational density clustering algorithm to cluster tropical cyclone data sets between 1949 and 2008, according to the generated position of tropical cyclones, generated density and the possibility of landing. The Pacific Northwest is divided into different sea areas. Then, we analyze the risk of tropical cyclones generated in these sea areas. The results show that the probability of tropical cyclones landing generated in some sea areas is very high, reached 74 %, but the probability of tropical cyclones landing generated in other sea areas is only 2 %. Tropical cyclones generated in some sea areas are more likely to develop into typhoons, strong typhoons and so on, but the intensity of tropical cyclones generated in other sea areas is lower, there is little risk for China. Finally, according to the climate change stage trends, we divide the period 1949–2008 into three stages and analyze the tropical cyclone risk of each sea areas.     

Vulnerability from storm surges and cyclone wind fields on the coast of Andhra Pradesh,India

The results presented here are from a study conducted for the government of the state of Andhra Pradesh (GOAP) in India, as part of a World Bank project on cyclone mitigation. A set of detailed maps were prepared depicting the Physical Vulnerability (PV), specifically storm surge inundation zones are shown for frequent occurrence, 50-year return period, likely scenario for global warming and extreme global warming. Similarly vulnerable areas from strong wind field from tropical cyclones (TCS) are also presented for the same four parameters. Vulnerability zones are presented from a social point of view also based upon certain socio-economic parameters that were included in determining the overall vulnerability of each Mandal in a coastal district (a Mandal represents a group of villages and towns) include: population, senior citizens, women, children under different age groups, type of housing, income level, cyclone shelters, hospitals and medical centres, schools and caste based population. The study is about scenarios that could happen if global warming and the predicted intensification of TCS actually occur as predicted by some numerical models.     

http://www.sciencedirect.com/science/article/pii/S167498711400036X

Global warming and climate change is one of the most extensively researched and discussed topical issues affecting the environment.Although there are enough historical evidence to support the theory that climate change is a natural phenomenon,many research scientists are widely in agreement that the increase in temperature in the 20 th century is anthropologically related.The associated effects are the variability of rainfall and cyclonic patterns that are being observed globally.In Southeast Asia the link between global warming and the seasonal atmospheric flow during the monsoon seasons shows varying degree of fuzziness.This study investigates the impact of climate change on the seasonality of monsoon Asia and its effect on the variability of monsoon rainfall in Southeast Asia.The comparison of decadal variation of precipitation and temperature anomalies before the 1970 s found general increases which were mostly varying.But beyond the 1970 s,global precipitation anomalous showed increases that almost corresponded with increases in global temperature anomalies for the same period.There are frequent changes and a shift westward of the Indian summer monsoon.Although precipitation is observed to be 70%below normal levels,in some areas the topography affects the intensity of rainfall.These shifting phenomenon of other monsoon season in the region are impacting on the variability of rainfall and the onset of monsoons in Southeast Asia and is predicted to delay for 15 days the onset of the monsoon in the future.The variability of monsoon rainfall in the SEA region is observed to be decadal and the frequency and intensity of intermittent flooding of some areas during the monsoon season have serious consequences on the human,financial,infrastructure and food security of the region.     

The economic impact of future increase in tropical cyclones in Japan

This article estimates the non-first-order economic loss in Japan due to a future increase in tropical cyclones. One possible effect of global warming could be the increase in intensity of tropical cyclones. Using historical storm tracks between the years 1978 and 2007 and altering their intensities due to this potential increase in their intensity, this paper calculates the future potential regional GDP loss in a certain area that is affected by tropical cyclones. Most of the literature is concerned with physical damage and the loss of lives due to tropical cyclones. However, there are additional economic costs when sustained wind speeds are higher than 30 knots (55.56 km/h), a level that generally will lead to a precautionary cessation of many human activities. Using a Monte Carlo simulation, the paper calculates the potential economic costs for the year 2085 under a climate change scenario with a linear one-per cent yearly increase in CO₂. Using a spatial distribution of economic activity in Japan, it is possible to forecast which parts of the country are likely to experience the highest loss risk.     

Swarm intelligence and neural nets in forecasting the maximum sustained wind speed along the track of tropical cyclones over Bay of Bengal

Tropical cyclones are well-known extreme weather and the cause of considerable damages, injuries and loss of life. The assessment of the maximum sustained wind speed along the track of the tropical cyclones is very important for estimating the strength of the cyclones. The swarm intelligence in the form of ant colony optimization (ACO) technique is introduced in this study to compute the pheromone deposition along the track of tropical cyclones followed by neural nets to forecast the maximum sustained wind speed of the cyclones occurring over the Bay of Bengal of North Indian Ocean. The ACO is a nonlinear problem-based meta-heuristic optimization method for finding approximate solutions to discrete optimization problems and simulates the decision-making processes of ant colony similar to other adaptive learning techniques. The method has shown its application potential in various fields including the prediction of monsoon rainfall. In this study, the amount of pheromone deposition during the successive stages of the cyclones has been estimated. A range of minimum central pressure (MCP), central pressure drop (PD), maximum sustained wind speed (MSWS) and intensity (T-No) associated with the cyclones of Bay of Bengal are utilized to form the input matrix of the neural nets. The neural nets are trained to forecast the maximum sustained wind speed along the track of the tropical cyclones over Bay of Bengal. The result reveals that the errors in forecasting the MSWS along the track of tropical cyclones with 6, 12, 18 and 24 h lead time are 2.6, 2.9, 3.1 and 4.8, respectively. The result is compared with the existing dynamical, statistical and adaptive models to evaluate the skill of the present model. The result is well validated with observation.     

Assessment of economic losses from tropical cyclone disasters based on PCA-BP

Tropical cyclones are the most common natural disasters in coastal regions and are the most costly in terms of economic losses. Economic loss assessment is the basis for disaster prevention and alleviation and for insurance indemnification. We use data from 1970 to 2008 for Zhejiang Province, China, in this study evaluating economic losses. We convert direct economic losses from tropical cyclone disasters in Zhejiang Province into indices of direct economic losses. To establish our assessment model, we process disaster-inducing assessment factors, disaster-formative environments and disaster-affected bodies using the principal component analysis method, and we abstract the principal component as the input of a BP neural network model. We found in the actual assessments of five tropical cyclones affecting Zhejiang Province in 2007 and 2008 that the post-disaster loss assessment values of tropical cyclones were higher than the actual losses, but that for more severe storms, the gap was smaller. This reflects the beneficial effect of efforts toward disaster prevention and alleviation for severe tropical cyclones. Pre-assessments based on relatively accurate forecast values of wind and precipitation at the start of a tropical cyclone have been in accordance with the post-disaster assessment values, while the pre-assessment results using less accurate forecast values have been unsatisfactory. Therefore, this model can be applied in the actual assessment of direct economic loss from tropical cyclone damage, but increasingly accurate forecasting of wind and precipitation remains crucial to improving the accuracy of pre-assessments.     

A global context for megadroughts in monsoon Asia during the past millennium

Proxy reconstructions of precipitation from central India, north-central China, and southern Vietnam reveal a series of monsoon droughts during the mid 14th–15th centuries that each lasted for several years to decades. These monsoon megadroughts have no analog during the instrumental period. They occurred in the context of widespread thermal and hydrologic climate anomalies marking the onset of the Little Ice Age (LIA) and appear to have played a major role in shaping significant regional societal changes at that time. New tree ring-width based reconstructions of monsoon variability suggest episodic and widespread reoccurrences of monsoon megadroughts continued throughout the LIA. Although the El-Niño Southern Oscillation (ENSO) plays an important role in monsoon variability, there is no conclusive evidence to suggest that these megadroughts were associated with anomalous sea surface temperature anomalies that were solely the result of ENSO-like variability in the tropical Pacific. Instead, the causative mechanisms of these megadroughts may reside in protracted changes in the synoptic-scale monsoon climatology of the Indian Ocean. Today, the intra-seasonal monsoon variability is dominated by ‘active’ and the ‘break’ spells – two distinct oscillatory modes of monsoon that have radically different synoptic scale circulation and precipitation patterns. We suggest that protracted locking of the monsoon into the “break-dominated” mode – a mode that favors reduced precipitation over the Indian sub-continent and SE Asia and enhanced precipitation over the equatorial Indian Ocean, may have caused these exceptional droughts. Impetus for periodic locking of the monsoon into this mode may have been provided by cooler temperatures at the extratropical latitudes in the Northern Hemisphere which forced the mean position of the Inter-Tropical Convergence Zone (ITCZ) further southward in the Indian Ocean.     

Influence of soil moisture content on surface albedo and soil thermal parameters at a tropical station

Half hourly data of soil moisture content, soil temperature, solar irradiance, and reflectance are measured during April 2010 to March 2011 at a tropical station, viz., Astronomical Observatory, Thiruvananthapuram, Kerala, India (76°59’E longitude and 8°29’N latitude). The monthly, seasonal and seasonal mean diurnal variation of soil moisture content is analyzed in detail and is correlated with the rainfall measured at the same site during the period of study. The large variability in the soil moisture content is attributed to the rainfall during all the seasons and also to the evaporation/movement of water to deeper layers. The relationship of surface albedo on soil moisture content on different time scales are studied and the influence of solar elevation angle and cloud cover are also investigated. Surface albedo is found to fall exponentially with increase in soil moisture content. Soil thermal diffusivity and soil thermal conductivity are also estimated from the subsoil temperature profile. Log normal dependence of thermal diffusivity and power law dependence of thermal conductivity on soil moisture content are confirmed.     

Relationship between northeast monsoon rainfall and near-surface atmospheric wind convergence over the North Indian Ocean using multisatellite data

The northeast monsoon rainfall (NEMR) contributes about 20–40 % of annual rainfall over the North Indian Ocean (NIO). In the present study, the relationship between the NEMR and near-surface atmospheric wind convergence (NSAWC) over the NIO is demonstrated using high-resolution multisatellite data. The rainfall product from the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis and near-surface wind product from the Cross-Calibration Multi-Platform available at 0.25° × 0.25° spatial resolution are used for the study. Large-scale NSAWC and divergence maps over the tropical Indian Ocean are generated at monthly scale from the wind product for the period of 1988–2010. A preliminary analysis is carried out for two consecutive anomalous Indian Ocean Dipole (IOD) years 2005 (negative) and 2006 (positive). The distinct spatial patterns of rainfall rate and NSAWC fields over the NIO clearly show the evolution of the anomalous IOD events in the south eastern equatorial Indian Ocean (EEIO). The spatially averaged time-series of pentad NSAWC over the south EEIO box suggests that the variability occurs in phase with rainfall rate during both the northeast monsoon years. Furthermore, the scatter plot between area-averaged pentad rainfall and convergence over the south EEIO box for the period of 1998–2010 shows statistically significant linear correlation which reveals that NSAWC plays a key role in regulating the NEMR.     

A simple model for preliminary evaluation of rainfall-induced slope instability

Slope failures in the tropical regions, particularly Malaysia are commonly triggered by frequent rainfall. The tropical rainfall can be characterized as short and intense throughout the year, and prolonged and less intense during monsoon seasons. Under such circumstances, various rainfall patterns should be included in the analysis of rainfall-induced slope failure in the tropical regions. This paper is aimed to demonstrate a simple model for preliminary evaluation of rainfall-induced slope failure. The critical rainfall patterns for four typical types of soil were first determined. Seepage finite element analyses were conducted using the extreme rainfall of ten-year return period for Johor Bahru, Malaysia. The results showed that the ratio of rainfall intensity to soil saturated permeability (i.e., I/k_sat) plays an important role in determining the critical rainfall pattern. Two critical combinations of antecedent rainfall and major rainfall, 1-day, 2-day, 3-day, 5-day, 7-day, 14-day, and 30-day antecedent rainfalls and the redistribution of the critical combination of antecedent rainfall and 1-day major rainfall were responsible for the formation of suction envelope in soil. The suction envelope, representing the worst suction distribution in soil, was used for the computation of factor of safety of soil slope through the modified infinite-slope–limit-equilibrium method. A model, PERISI, was developed based on the findings from numerical simulation. The suction envelope and factor of safety computed from the PERISI model showed good agreements with the results obtained from Seep/W and Slope/W computer programs and the results derived from the model of Rahardjo et al. developed in 1995.     

南京市强降水天气长期动态及变异性规律

基于南京市1951～2016年汛期(6～9月)各月降水资料,分析研究区强降水天气的长期动态及变异性规律。长期动态结果表明,近66年来南京市强降水天气发生频率显著增加,平均每10年增加0.31次;不同规模强降水中,暴雨、大暴雨天气发生频率均呈增加趋势,其中暴雨天气呈显著增加。多年(7a、10a、15a)月际排序值滑动标准差均通过置信度99%显著性检验,强降水天气变异性呈显著下降趋势;强降水天气汛期盛行月份趋于集中(7月),月间格局趋于稳定,与多年的月际排序值滑动标准差得出强降水天气变异性呈下降趋势的结论相吻合。