On the relationship between convection intensity of South China Sea summer monsoon and air-sea temperature difference in the tropical oceans

The annual, interannual and inter-decadal variability of convection intensity of South China Sea (SCS) summer monsoon and air-sea temperature difference in the tropical ocean is analyzed, and their relationship is discussed using two data sets of 48-a SODA (simple ocean data assimilation) and NCEP/NCAR. Analyses show that in wintertime Indian Ocean (WIO), springtime central tropical Pacific (SCTP) and summertime South China Sea-West Pacific (SSCSWP), air-sea temperature difference is significantly associated with the convection intensity of South China Sea summer monsoon. Correlation of the inter-decadal time scale (above 10 a) is higher and more stable. There is inter-decadal variability of correlation in scales less than 10 a and it is related with the air-sea temperature difference itself for corresponding waters. The inter-decadal variability of the convection intensity during the South China Sea summer monsoon is closely related to the inter-decadal variability of the general circulation of the atmosphere. Since the late period of the 1970s, in the lower troposphere, the cross-equatorial flow from the Southern Hemisphere has intensified. At the upper troposphere layer, the South Asian high and cross-equatorial flow from the Northern Hemisphere has intensified at the same time. Then the monsoon cell has also strengthened and resulted in the reinforcing of the convection of South China Sea summer monsoon.

The Relationship of Land-Ocean Thermal Anomaly Difference with Mei-yu and South China Sea Summer Monsoon

Based on the NCEP/NCAR reanalysis data for the period of 1948-2004 and the monthly rainfall data at 160 stations in China from 1951 to 2004, the relationships among the land-ocean temperature anomaly difference in the mid-lower troposphere in spring （April-May）, the mei-yu rainfall in the Yangtze River- Huaihe River basin, and the activities of the South China Sea summer monsoon （SCSSM） are analyzed by using correlation and composite analyses. Results show that a significant positive correlation exists between mei-yu rainfall and air temperature in the middle latitudes above the western Pacific, while a significant negative correlation is located to the southwest of the Baikal Lake. When the land-ocean thermal anomaly difference is stronger in spring, the western Pacific subtropical high （WPSH） will be weaker and retreat eastward in summer （June-July）, and the SCSSM will be stronger and advance further north, resulting in deficient moisture along the mei-yu front and below-normal precipitation in the mid and lower reaches of the Yangtze River, and vice versa for the weaker difference case. The effects and relative importance of the land and ocean anomalous heating on monsoon variability is also compared. It is found that the land and ocean thermal anomalies are both closely related to the summer circulation and mei-yu rainfall and SCSSM intensity, whereas the land heating anomaly is more important than ocean heating in changing the land-ocean thermal contrast and hence the summer monsoon intensity.

Dynamicity of Land Use/Land Cover(LULC):An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation(DMC)in India

The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods,changing the landscape of regions outside the city and fostering the growth of physical infrastructure.Using multi-temporal satellite images,the dynamics of Land Use/Land Cover(LULC)changes,the impact of urban growth on LULC changes,and regional environmental implications were investigated in the peri-urban and rural neighbourhoods of Durgapur Municipal Corporation in India.The study used different case studies to highlight the study area’s heterogeneity,as the phenomenon of change is not consistent.Landsat TM and OLI-TIRS satellite images in 1991,2001,2011,and 2021 were used to analyse the changes in LULC types.We used the relative deviation(RD),annual change intensity(ACI),uniform intensity(UI)to show the dynamicity of LULC types(agriculture land;built-up land;fallow land;vegetated land;mining area;and water bodies)during 1991-2021.This study also applied the Decision-Making Trial and Evaluation Laboratory(DEMATEL)to measure environmental sensitivity zones and find out the causes of LULC changes.According to LULC statistics,agriculture land,built-up land,and mining area increased by 51.7,95.46,and 24.79 km^(2),respectively,from 1991 to 2021.The results also suggested that built-up land and mining area had the greatest land surface temperature(LST),whereas water bodies and vegetated land showed the lowest LST.Moreover,this study looked at the relationships among LST,spectral indices(Normalized Differenced Built-up Index(NDBI),Normalized Difference Vegetation Index(NDVI),and Normalized Difference Water Index(NDWI)),and environmental sensitivity.The results showed that all of the spectral indices have the strongest association with LST,indicating that built-up land had a far stronger influence on the LST.The spectral indices indicated that the decreasing trends of vegetated land and water bodies were 4.26 and 0.43 km^(2)/a,respectively,during 1991-2021.In summary,this study can help the policy-makers to predict the increasing rate of temperature and the causes for the temperature increase with the rapid expansion of built-up land,thus making effective peri-urban planning decisions.

Impact of land cover change on land surface temperature: A case study of Spiti Valley

Land surface temperature(LST) is the skin temperature of the earth surface. LST depends on the amount of sunlight received by any geographical area. Apart from sun light, LST is also affected by the land cover, which leads to change in land surface temperature. Impact of land cover change(LCC) on LST has been assessed using Landsat TM5, Landsat 8 TIRS/OLI and Digital Elevation Model(ASTER) for Spiti Valley, Himachal Pradesh, India. In the present study, Spiti valley was divided into three altitudinal zones to check the pattern of changing land cover along different altitudes and LST was calculated for all the four land cover categories extracted from remote sensing data for the years of 1990 and 2015. Matrix table was used as a technique to evaluate the land cover change between two different years. Matrix table shows that as a whole, about 2,151,647 ha(30%) area of Spiti valley experienced change in land cover in the last 25 years. The result also shows vegetation and water bodies increased by 107,560.2 ha(605.87%) and 45 ha(0.98%), respectively. Snow cover and barren land decreased by 19,016.5 ha(23.92%) and 88,589(14.14%), during the study period. A significant increase has been noticed in vegetation amongst all land cover types. Minimum, maximum and mean LST for three altitudinal zones have been calculated. The mean LST recorded was 11℃ in 1990 but it rose by 2℃ and reached to 13℃ in 2015. Changes in LST were obtained for each land cover categories. The mean temperature of different land cover types was calculated by averaging value of all pixels of a given land cover types. The mean LST of vegetation, barren land, snow cover and water body increased by 6℃, 9℃, 1℃, and 7℃, respectively. Further, relationships between LST, Normalized Difference Snow Index(NDSI), and Normalised Difference Vegetation Index(NDVI) were established using Linear Regression.

Estimation of Land Surface Temperature from Landsat-8 OLI Thermal Infrared Satellite Data. A Comparative Analysis of Two Cities in Ghana

This study employs Landsat-8 Operational Land Imager (OLI) thermal infrared satellite data to compare land surface temperature of two cities in Ghana: Accra and Kumasi. These cities have human populations above 2 million and the corresponding anthropogenic impact on their environments significantly. Images were acquired with minimum cloud cover (<10%) from both dry and rainy seasons between December to August. Image preprocessing and rectification using ArcGIS 10.8 software were used. The shapefiles of Accra and Kumasi were used to extract from the full scenes to subset the study area. Thermal band data numbers were converted to Top of Atmospheric Spectral Radiance using radiance rescaling factors. To determine the density of green on a patch of land, normalized difference vegetation index (NDVI) was calculated by using red and near-infrared bands i.e. Band 4 and Band 5. Land surface emissivity (LSE) was also calculated to determine the efficiency of transmitting thermal energy across the surface into the atmosphere. Results of the study show variation of temperatures between different locations in two urban areas. The study found Accra to have experienced higher and lower dry season and wet season temperatures, respectively. The temperature ranges corresponding to the dry and wet seasons were found to be 21.0985oC to 46.1314oC, and, 18.3437oC to 30.9693oC respectively. Results of Kumasi also show a higher range of temperatures from 32.6986oC to 19.1077oC during the dry season. In the wet season, temperatures ranged from 26.4142oC to -0.898728oC. Among the reasons for the cities of Accra and Kumasi recorded higher than corresponding rural areas’ values can be attributed to the urban heat islands’ phenomenon.

Land Characterization Analysis of Surface Temperature of Semi-Arid Mountainous City Abha, Saudi Arabia Using Remote Sensing and GIS

This knowledge of land surface temperature and its spatial variations within a city environment is of prime importance to the study of urban climate and human-environment interactions. Few studies have examined the influence of land use and terrain on the surface temperature effects of semi-arid mountainous urban areas. This study investigates the urban environment characterization and its effects on surface temperature using remote sensing. The methodologies adapted for this study are geometric and radiometric corrections of satellite data, extraction of land use/land cover and digital elevation model, estimation of vegetation density using Normalized Difference Vegetation Index (NDVI), and estimation of surface temperature and emissivity using temperature emissivity separation (TES) algorithm. Finally geospatial model and statistical techniques are used for assessing the overall impact of urban environmental characterization on urban climate of semi-arid region of Abha, Kingdom of Saudi Arabia. Herein, results reveal that the spatial distribution of surface temperature was affected by land use/land cover (LULC) and topography. The high dense built-up and commercial/industrial areas display higher surface temperature in comparison with surrounding lands. There is gradual decrease of LULC classes’ surface temperature with the increase in altitude. The cooling effect towards the surrounding urban built-up area is found increasing at the hill located vegetated area, the downward slope and valley terrain inside the recreational park. Therefore the spatial variation in surface temperature also reflected the effects of topography on LULC classes. Suitable mountainous land use utilization would help to expand the cooling effect. In the future, the outcomes of this study could be used to build environmentally sustainable urban planning suitable to semi-arid regions and to create practices that consider the local weather environment in urban planning.

基于Landsat数据地表特征参数与地表温度关系

以成都市为研究区,定量分析了各地表特征参数与地表温度之间的线性关系。通过对地表温度与归一化植被指数(NDVI)、归一化建筑指数(NDBI)、归一化水汽指数(NDMI)进行局部区域逐像元分析和总体区域统计分析,结果表明NDVI,NDMI,NDBI与地表温度间都存在明显的线性关系,可用于说明地表温度的动态变化,在3月份,NDMI与地温的相关性更优于NDVI。对传统城市热现象研究中,NDMI与NDBI能够用来以NDVI作为分析地表温度随季节而变化的互补的度量标准。

基于Landsat ETM+影像的干旱半干旱地区地表温度反演研究与分析

利用武威地区2008年5月30日的Landsat ETM+第六波段数据,经过大气和比辐射率校正后,运用单窗算法反演武威地区地表温度,得出该地区夏季地面温度场的分布规律。结果表明,冰川表面温度最低,针叶林及绿洲次之,沙漠最高,地表温度以绿洲为中心从里到外呈带状分布。并运用归一化植被指数(NDVI)计算该地区植被覆盖度(Fg),进一步研究植被盖度及归一化植被指数与地表温度的相互关系,结果表明几种典型地物随NDVI值的减小,温度呈递增关系,植被盖度与地表温度成线性负相关。

Impact of Desert Urbanization on Urban Heat Islands Effect

The United Arab Emirates (UAE) has undergone major urban transformation after the establishment of the country in 1971. One noticeable change is urban expansion in terms of massive infrastructure, including new residential areas, highways, airports, and sophisticated transportation systems. Major landscape changes and disturbances, such as urban development, are among the major contributors to global climate change. Urban areas can be 3.5°C - 4.5°C warmer than neighboring rural areas, a phenomenon known as urban heat islands (UHIs). As such, urban development in the UAE was expected to follow a similar pattern and to be a major contributor to the country’s impact on global climate change. Analyses of multi-temporal (1988-2017) land surface temperature (LST) data obtained from Landsat satellite datasets over a desert city in the UAE showed unexpected results. Urbanization of desert surfaces in the study area led to a decrease of 3°C - 5°C in the overall LST. This was attributed to the associated expansion of green spaces in the newly developed urban areas, the expansion of date plantations and perhaps a cooling in the previously desert surface. Therefore, the UHI effect was not well demonstrated in the studied desert surfaces converted to urban areas.

INTERDECADAL VARIATIONS OF INTERACTION BETWEEN NORTH PACIFIC SSTA AND EAST ASIAN SUMMER MONSOON

Identification of key SST zones is essential in predicting the weather / climate systems in East Asia. With the SST data by the U.K. Meteorological Office and 40-year geopotential height and wind fields by NCAR / NCEP, the relationship between the East Asian summer monsoon and north Pacific SSTA is studied, which reveals their interactions are of interdecadal variation. Before mid-1970’s, the north Pacific SSTA acts upon the summer monsoon in East Asia through a great circle wavetrain and results in more rainfall in the summer of the northern part of China. After 1976, the SSTA weakens the wavetrain and no longer influences the precipitation in North China due to loosened links with the East Asian summer monsoon. It can be drawn that the key SST zones having potential effects on the weather / climate systems in East Asia do not stay in one particular area of the ocean but rather shift elsewhere as governed by the interdecadal variations of the air-sea interactions. It is hoped that the study would help shed light on the prediction of drought / flood spans in China.

基于Landsat数据热岛效应与植被的关系研究——以开封市为例

随着城市经济的不断发展,城市热岛现象日益严重,不仅制约社会经济绿色健康发展,而且危害人体健康。基于Landsat5、Landsat8数据,利用大气校正法对河南省开封市地表温度进行反演,分析开封市热环境空间分布,并对该市植被覆盖度进行空间变化分析,以期为开封市城市绿色健康规划建设及缓解热岛效应提供借鉴。结果表明,开封市城市热岛效应明显,高温由开封市区向祥符区、尉氏县、通许县、杞县、兰考县扩散;从各区热环境分布看,开封市年平均气温和高温区面积均呈升高趋势,开封市中温区、次高温区面积显著增加,次低温区面积显著减少,城区气温增加速度大于郊区,为热岛的形成提供了热量基础。地表温度与植被覆盖呈负相关,因此在开封市经济建设过程中应对城镇土地使用合理规划、加强城镇绿地规划、增加城镇绿地覆盖度、选用透水地面铺装以缓解开封市热岛效应。

基于广义积分变换法海洋温差能大口径冷水管强迫振动分析

复杂多变的海洋工况将诱发大口径冷水管强迫振动,为探明均布载荷、线性变化的静水压力、集中载荷和周期载荷作用下冷水管振动响应机制。基于Euler-Bernoulli梁理论,建立了管道动力学控制方程,采用广义积分变换法,求解了系统强迫振动的解析解,并与同伦摄动法相对比,验证了该方法的高精度和有效性,分析了内流、黏弹性耗散系数、阻尼比和质量比对管道振动特性的影响。结果表明:当内流流速对应的振动频率与固有频率接近时,管道将出现动态失稳。增大黏弹性耗散系数、阻尼比和质量比对横向位移的抑制效果呈现依次递减的规律,改变激振位置和激振频率可显著改变管道横向位移。该研究成果可对冷水管的初期设计提供一定的指导作用。

垂直洋流下500 kV海缆电热耦合场和载流量研究

发展海上风电是实现“双碳”目标的重要举措。直流海缆是海上风电输电工程的重要装置,而海缆稳态载流量等研究对推动远海风电大规模开发具有重要意义。近年来高压直流海缆稳态载流量的相关研究考虑海洋环境因素较为单一且未充分考虑绝缘层温差的限制。文中建立了500 kV直流海缆与海水系统的电-热-流耦合模型,研究了单根和双极海缆在不同敷设方式下垂直洋流(垂直于海缆长度方向流动的洋流)流速,考虑绝缘层温差限制、双极不同间距等对载流量的影响。结果表明,相较于仅考虑线芯温度70℃限制,综合考虑绝缘层温差20℃限制的载流量更小,且相较于其他敷设方式,直埋敷设时绝缘层温差20℃限制对载流量的影响更小;双极海缆的载流量随双极间距增大而增加,流速为0.1 m/s时涡旋对海缆载流量有较小的提升作用;在绝缘层温差为6℃附近,电场发生翻转。研究结果可为敷设方式的选择以及载流量的预测和评估提供重要指导和参考。

基于MODIS数据的中国东部地区海陆温差时空变化特征

海陆温差是海-陆间热力对比的重要表征,对区域乃至全球气候产生重要影响。研究基于2001—2021年中分辨率成像光谱仪(MODIS)遥感数据,研究了中国东部地区地表温度、海表温度以及海陆温差的时空变化及区域差异特征。结果表明:2001—2021年中国东部地区地表温度和海表温度均呈显著上升趋势,上升幅度分别为0.34℃/10a和0.32℃/10a;夜间地表温度和海表温度的上升态势更突出;各季节中,冬季地表温度和夏季海表温度增幅最大,分别达0.45℃/10a和0.43℃/10a(P<0.05);空间上,中国东部地表温度总体呈南高北低的格局特征,海表温度则表现出从东北向西南递增、近岸低于远岸的特征。研究时段内,中国东部地区海陆温差通常为负值,海表温度总体高于地表温度,且离海岸线越近的缓冲区范围内海陆温差越小;100 km、200 km和300 km缓冲区范围内年际海陆温差总体呈减小趋势,其中100 km缓冲区范围内的降幅最大;各季节中,春季和冬季海陆温差呈减小趋势,夏季和秋季的呈增大趋势;空间上,以30°N为界,以北和以南区域的海陆温差分别呈减小和增大趋势。

喀斯特区与非喀斯特区的地表温度与近地表气温差异分析

地表温度与近地表气温的关系是识别下垫面与近地表大气相互作用的重要依据,对维持能量良好循环与改善气候环境具有重要意义。喀斯特区的自然背景与非喀斯特区有明显差异,陆地-大气间能量传输的规律在两类地区具有差异。基于近邻成对像元选择,获取贵州西南紫云、望谟两县2000—2018年的地表温度和近地表气温,并对比分析它们在喀斯特区与非喀斯特区的差异。结果表明:①就年平均状况而言,喀斯特区地表温度与近地表气温的差异及其波动性比非喀斯特区大,陆地-大气之间能量传输的稳定性为非喀斯特区大于喀斯特区。②从季节状况看,地表温度与近地表气温的差异在春、夏、秋三季为喀斯特区比非喀斯特区明显,冬季无明显差异;地表温度与近地表气温差异的波动性在冬季为喀斯特区大于非喀斯特区;喀斯特区陆地-大气之间能量传输的稳定性在4个季节均大于非喀斯特区。③从各月看,喀斯特区地表温度与近地表气温差异在各月均比非喀斯特区明显,差异波动性在4月份大于非喀斯特区,其余月份基本一致;除去3月份和4月份,其余各月的非喀斯特区陆地-大气之间能量传输均比喀斯特区稳定。结果可为研究气候变化、解析地表环境模式和保护生态环境等方面提供参考。

北京园林树木秋色盛期的空间异质性及其对热环境差异的响应

【目的】城市化进程影响下,城市内部热环境的空间分布不均导致植物物候的空间异质性突出。秋色盛期作为落叶树种生长季的终点,其空间异质性对于城市植被的年周期固碳量及整个城市生态系统的初级生产力具有重要影响,同时会引起秋季季相景观的空间变化,是监测城市生态及景观动态的一个关键角度,值得深入探究。本研究以此为切入点,旨在揭示北京城市环境中秋色盛期的空间异质性特征及其对下垫面热环境的响应。【方法】本研究以北京主城区西北城郊梯度上9处公园绿地中的5种秋色叶树种为研究对象,基于地面物候观测对2017—2019年的秋色盛期数据进行采集,基于MODIS地温反演对样地热环境数据进行采集,对秋色盛期空间差异及其与秋季热环境的相关性进行分析。【结果】(1)北京主城区各树种的秋色盛期整体发生于10月中旬至12月上旬、集中于11月上中旬,由早到晚依次为洋白蜡、元宝枫、银杏、水杉、旱柳,且银杏雌株的秋色盛期显著早于雄株。(2)各树种秋色盛期整体上由二环—三环—五环—五环外逐渐提前,城郊物候天数差异达(10.1±0.3) d;样地间物候期整体差异显著,尤其四环外样地的秋色盛期显著早于三环内。(3)各树种秋色盛期与样地秋季平均地温(LST_(a))呈显著正相关(P <0.01),表明北京主城区内秋季地表热量的大量积累会导致秋色盛期延后;各树种秋色盛期对LST_(a)空间差异的响应敏感度平均为(4.11±0.83) d/℃,以洋白蜡和水杉响应最为敏感。【结论】北京主城区的秋色盛期表现出对城市秋季热环境空间差异的显著响应,城市热岛效应是未来气候变化的一个缩影,城市环境中物候期对热环境空间差异的响应可反映未来气候变化对植物物候的潜在影响,即具有“空间代替时间”的研究价值。

极端干旱生态移民区不同土地利用类型土壤呼吸对温湿度的响应

探究极端干旱生态移民区不同土地利用类型土壤温度与含水率对土壤呼吸速率影响,为准确揭示研究区不同土地利用类型碳循环特征提供科学支撑。采用LI-8100土壤碳通量测量系统和土壤墒情监测仪,在2023年5、6、7月中旬,将研究区分为荒草地、柠条林、原地貌和耕地4种土地利用类型测定了土壤呼吸速率、土壤温度和土壤含水率。结果表明:(1)土壤呼吸速率整体表现为:耕地>荒草地>柠条林地>原地貌。在达到最适温度前不同土地利用类型的土壤呼吸速率均与温度呈显著正相关(P<0.05),超过最适温度会降低土壤呼吸速率。(2)不同土地利用类型土壤呼吸速率均能与5cm深度土壤温度进行较好的指数模型拟合,Q10值介于3.18~4.66之间,且原地貌、耕地的土壤呼吸速率与10 cm深度土壤温度的相关性显著(P<0.05)。(3)土壤呼吸速率与土壤含水率(10 cm)之间线性相关性不显著(P>0.05),除柠条林地外其余3种土地利用类型土壤温度(5 cm)和土壤含水率(10 cm)的交互作用显著相关(P<0.05)。不同土地利用类型对极端干旱生态移民区的CO_(2)排放影响显著,土壤温度与含水率共同作用是土壤呼吸速率变化的主要影响因素,结合区域气候、制定合理的土地利用政策可进一步助力实现“双碳目标”,以期为极端干旱生态移民区的土地利用总体规划提供理论依据。

Soil temperature estimation at different depths,using remotely-sensed data

Soil temperatures at different depths down the soil profile are important agro-meteorological indicators which are necessary for ecological modeling and precision agricultural activities. In this paper, using time series of soil temperature(ST) measured at different depths(0, 5, 10, 20, and 40 cm) at agro-meteorological stations in northern China as reference data, ST was estimated from land surface temperature(LST) and normalized difference vegetation index(NDVI) derived from AQUA/TERRA MODIS data, and solar declination(Ds) in univariate and multivariate linear regression models. Results showed that when daytime LST is used as predictor, the coefficient of determination(R^2) values decrease from the 0 cm layer to the 40 cm layer. Additionally, with the use of nighttime LST as predictor, the R^2 values were relatively higher at 5, 10 and 15 cm depths than those at 0, 20 and 40 cm depths. It is further observed that the multiple linear regression models for soil temperature estimation outperform the univariate linear regression models based on the root mean squared errors(RMSEs) and R^2. These results have demonstrated the potential of MODIS data in tandem with the Ds parameter for soil temperature estimation at the upper layers of the soil profile where plant roots grow in. To the best of our knowledge, this is the first attempt at the synergistic use of LST, NDVI and Ds for soil temperature estimation at different depths of the upper layers of the soil profile, representing a significant contribution to soil remote sensing.

Influence of Climatic Conditions on the Time Series Fluctuation of Yellowfin Tuna <i>Thunnus albacares</i>in the South Pacific Ocean

Yellowfin tuna (Thunnus albacares) is one of the most commercially important fish species for South Pacific island nations and territories and for effective conservation efforts it is important to understand the factors which affect its time series pattern. Our research was aimed at elucidating the climatic factors which affected the trajectory of the yellowfin tuna stock in the Eastern and Western South Pacific Ocean. We utilized various climatic factors for the years t - n with n = 0, 1, ..., 8 and investigated their statistical relationship with the catch per unit effort (CPUE) of yellowfin tuna stock from 1957-2008 for three South Pacific zones ranging from the East to the West Pacific Ocean within the coverage area of the Western and Central Pacific Convention Area. Results showed that the climatic conditions of: (i) the global mean land and ocean temperature index (LOTI), (ii) the Pacific warm pool index (PWI) and (iii) Southern Oscillation Index (SOI) had significant relationship with the CPUE of yellowfin tuna in all three zones. LOTI, PWI and SOI were used as independent variables and fitted through modeling to replicate the CPUE trajectory of the yellowfin tuna in Zone 1, Zone 2 and Zone 3. Model selection was based on significant parameter estimates (p < 0.05), Akaikes Information Criterion (AIC) and R2 values. Models selected for all three zones had LOTI, PWI and SOI as the independent variables. This study shows that LOTI, PWI and SOI are climatic conditions which have significant impact on the fluctuation pattern of the yellowfin tuna CPUE in the Eastern and Western South Pacific Ocean. From the findings of this study it can be recommended that when management decisions are made for yellowfin tuna fishery conservation and sustainability in the Eastern and Western South Pacific, it is imperative to take the effect of climatic factors into account.

Impact of Climatic Factors on Albacore Tuna <i>Thunnus alalunga</i>in the South Pacific Ocean

Over the years there has been growing interest regarding the effects of climatic variations on marine biodiversity. The exclusive economic zones of South Pacific Islands and territories are home to major international exploitable stocks of albacore tuna (Thunnus alalunga);however the impact of climatic variations on these stocks is not fully understood. This study was aimed at determining the climatic variables which have impact on the time series stock fluctuation pattern of albacore tuna stock in the Eastern and Western South Pacific Ocean which was divided into three zones. The relationship of the climatic variables for the global mean land and ocean temperature index (LOTI), the Pacific warm pool index (PWI) and the Pacific decadal oscillation (PDO) was investigated against the albacore tuna catch per unit effort (CPUE) time series in Zone 1, Zone 2 and Zone 3 of the South Pacific Ocean from 1957 to 2008. From the results it was observed that LOTI, PWI and PDO at different lag periods exhibited significant correlation with albacore tuna CPUE for all three areas. LOTI, PWI and PDO were used as independent variables to develop suitable stock reproduction models for the trajectory of albacore tuna CPUE in Zone 1, Zone 2 and Zone 3. Model selection was based on Akaike Information Criterion (AIC), R2 values and significant parameter estimates at p < 0.05. The final models for albacore tuna CPUE in all three zones incorporated all three independent variables of LOTI, PWI and PDO. From the findings it can be said that the climatic conditions of LOTI, PWI and PDO play significant roles in structuring the stock dynamics of the albacore tuna in the Eastern and Western South Pacific Ocean. It is imperative to take these factors into account when making management decisions for albacore tuna in these areas.