基于捕捞努力量的中西太平洋鲣鱼围网渔业入渔预测分析

中西太平洋是全球主要的鲣鱼（Katsuwonus pelamis）围网作业渔场,渔场极易受到海洋环境的影响,但渔场分布在众多岛国的管辖海域,如何科学指导企业准确入渔是重要的研究课题。本文根据1995-2012年中西太平洋鲣鱼围网捕捞生产统计数据,选取产量最高的22个海区（5°×5°）,结合Niño3.4区海表温度距平值（SSTA）和作业海域表温（SST）,研究中西太平洋鲣鱼围网渔场的空间分布规律,同时,以各海区捕捞努力量（作业次数）所占的百分比为入渔指标,建立基于环境因子的入渔决策模型。研究认为,中西太平洋鲣鱼捕捞努力量在纬度方向上主要分布于5°S~5°N,其累计捕捞努力量占所有作业海区的87.4%,其中以130°~140°E经度范围为最高,其捕捞努力量占22个海区的45.08%。入渔指标与Niño3.4区的SSTA、作业海域SST均符合正态模型（P<0.01）,Niño3.4区的SSTA最适值为0.25℃,作业海域SST最适值在29.5℃左右。对预测和实际排名前十的海域进行统计发现,预测值与实际值基本一致。研究认为,所建立的入渔预测模型可有效指导企业的渔业生产,为提高企业生产效率提供支撑。     

Interannual variability and predictability of summertime significant wave heights in the western north pacific

We propose and validate a linear regression model which enables us to predict the summer (June–August) mean of the monthly 90th percentile of significant wave heights (H₉₀) in the western North Pacific (WNP). The most prevailing interannual variability of H⁹⁰ is identified by applying an Empirical Orthogonal Function analysis to H⁹⁰ obtained from the ERA-40 wave reanalysis as well as from the optimally interpolated TOPEX/Poseidon (OITP) wave data. It is found that the increase of H⁹⁰ is correlated with cyclonic circulation in the WNP which links with warm SST anomalies in the Niño-3.4 region. We adopt zonal wind anomaly averaged over the region 5°N–15°N, 130°E–160°E (U^10N) as a predictor of the first principal component (PC1) of H⁹⁰, since U^10N is closely correlated with the PC1 of H⁹⁰. It is revealed that regression models obtained from two different wave datasets are nearly identical. The predictability of the regression model is assessed in terms of the reduction of the root-mean-square (rms) errors between H⁹⁰ and the reconstructed data. The predictor is found to be successful in reducing the rms errors by up to 40% for the ERA-40 wave reanalysis and by up to 70% for the OITP wave data within the latitudinal band 10°N–25°N, though rms errors exceeding 0.3 m still remain, particularly in the East China Sea.     

北太平洋海表温度及各贡献因子的变化

采用1958年1月至2007年12月SODA海洋上层温度的月平均资料,基于海温变化方程和统计分析方法,分析了北太平洋海表面温度(SST)异常特征及各局地因子贡献比例的变化。结果表明,伴随着1976/1977风场最强中心位置的南北移动,形成了两个北太平洋SST年际-年代际变化的异常中心:一个是位于30°N附近的副热带海盆内区,SST异常主要受风应力强度的主导;一个是位于40°N附近的副热带和副极地环流交汇区,SST异常主要受风应力旋度的位置即风场位置的影响。在副热带海盆内区,最强降温发生在1978-1982年,SST异常的主要局地贡献因子为海表热通量和经向平流,二者所占比例和约为50%~60%,均为同相增温或降温作用,余项所占比例约为20%~50%。在副热带和副极地环流交汇区,海盆内区和西部边界区的SST异常的跃变时间同为1975年,但是内区的垂直混合项的跃变时间早于西部5年左右。SST异常的主要贡献因子为海表热通量和经向平流,但在1983-1988年海温强降温期间,经向平流项贡献大于海表热通量项的贡献。两个区域的垂直混合项均为降温贡献,虽然量值小却显示出很强的年代际变化信号。平流项中经向平流最大,垂直平流最小。     

浪致混合对2016年北太平洋海表温度季节性预测的影响

上层海洋通过海气交换影响大气-海洋耦合系统，海浪引起的垂向混合影响上层海洋结构，从而在气候预测过程中发挥着重要的作用。本文基于国家海洋局第一海洋研究所地球系统模式（FIO-ESM），以2016年为例，分别开展了耦合和关闭海浪模式情况下的短期气候预测实验，分析浪致混合对北太平洋海表温度（SST）季节性预测的影响。通过对模式预测的SST异常（SSTA）进行定量评估发现，浪致混合能够显著降低北太平洋高纬度海区预测误差，在（45°N，150°E）附近海区SSTA改善可达1℃，气候模式能够更好地预测SSTA的经向分布特征，特别是能够准确地反映25°~45°N海区SSTA分布特征。通过分析有浪和无浪两个实验的热收支贡献发现，垂向混合是导致上层海洋温度差异的主导影响因子。海浪通过改变垂向混合，使2016年北太平洋SST在高纬度海区大幅降低，在低纬度海区略有升高，最终提升了模式对北太平洋SST的季节性预测能力。     

Spatial classification of La Niña events

Thirty La Niña events have been selected from monthly mean sea surface temperature (SST) data of the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) and Centennial Observation-Based Estimates (COBE SST2) datasets from 1870 to 2013 based on a criterion of –0.5°С for a cold anomaly in the Niño 3.4 region (5° N–5° S, 170°–120° W) and its minimum duration of 5 months. The selected events are classified by hierarchical clustering analysis according to two characteristics: geographic coordinates and SST anomalies during the mature phase of La Niña. The objective classification method identifies two types of La Niña differing by the evolution of negative SST anomalies in the equatorial Pacific and by the Southern Oscillation Index.     

两类El Niño事件对中国近海及毗邻海域海表温度的影响

为研究东部型和中部型两类厄尔尼诺(El Ni?o)事件与中国近海海表温度(sea surface temperature,SST)变化间的联系,基于中国科学院大气物理研究所连续80年(1940—2019年)的SST再分析数据,采用EOF分解、合成分析等方法做了初步分析,发现中国近海及毗邻海域近80年SST变化与全球变暖密切相关。并且两类El Ni?o事件对中国近海SST变化的影响存在显著差异。东部型El Ni?o事件发展过程中,中国近海及毗邻海域SST在发展年主要为负异常,衰退期为正异常;中部型ElNi?o事件发展过程中, SST变化区域差异大,发展年日本附近海域为正异常, 28°N以南为弱的负异常。两类El Ni?o事件引发西太平洋风场反气旋涡的时间、位置与强度等的不同,是造成中国近海风场与海表温度异常(sea surface temperature anomaly, SSTA)差异的主要原因。     

Coastal upwelling along the north coast of Papua New Guinea and SST cooling over the pacific warm pool: A case study for the 2002/03 El Niño event

We investigate an overlooked mechanism—coastal upwelling—for sea surface temperature (SST) cooling in the western side of the mean location of the Pacific warm pool (WSWP: 5°S–5°N, 140°E–150°E) prior to El Niño onset. We analyze various observed data such as the TRIangle Trans-Ocean buoy Network (TRITON) moored buoy data, Conductivity-Temperature-Depth (CTD) data, satellite data and a hindcast experiment output by a high-resolution ocean general circulation model (OGCM). We focus on the precondition of the 2002/03 El Niño event, for which many datasets are available. Relatively cool water upwelled along the north coast of Papua New Guinea (PNG) during December 2001, prior to the onset of the 2002/03 El Niño event, and then spread out over a wider area to the northeast. Simultaneously, strong west-northerly surface winds occur along the north coast. Heat budget analysis of TRITON buoy data in the WSWP reveals that negative zonal heat advection due to eastward current is the main factor for cooling the mixed layer in the WSWP in contrast to the warming effect of the surface heat flux during the period. This cooling requires a source of colder water to the west. Similar analysis of OGCM outputs also suggests that the upwelled relatively cool water along the PNG north coast, and its northeastward extension to the equatorial region, contributes to cooling of the surface water over the WSWP mainly via negative zonal heat advection. Similar mechanisms are confirmed also for the 1982/83 and 1997/98 El Niño events by analyses of OGCM outputs and historical SST data. The low SST in the WSWP generated a positive zonal SST gradient together with high SST east of the WSWP. It may contribute to enhancement of the westerly surface wind in this region, leading to the onset of the 2002/03 El Niño event.     

基于产卵场环境因子的阿根廷滑柔鱼资源补充量预报模型研究

西南大西洋阿根廷滑柔鱼Illex argentinus是短生命周期种类,其资源量极易受到海洋环境变化的影响。根据2003—2011年我国鱿钓船队在西南大西洋的生产统计数据,以及产卵场海洋表面温度(SST)、海表温度距平值(SSTA),计算分析了阿根廷滑柔鱼在产卵期产卵场各月最适表层水温范围占总面积的比例(用PS表示)以及表征海流强度的SST、SSTA等多种环境变量因子与单位捕捞量渔获量(CPUE)的相关性,建立多种基于主要环境因子的资源补充量预报模型,同时分析比较预报模型的优劣。相关性分析表明:6月份有3片连续区域的SST与CPUE之间存在强相关性,分别为38°~39°S、54°~55°W,40.5°~41.5°S、51°~52°W,39.9°~40.4°S、42.6°~43.1°W。利用6月份此3片连续区域SST与次年CPUE建立的三元线性模型,模型符合统计检验,偏差解释率为82.4%。在此基础上加入7月份PS影响因子建立3种方案下的误差反向传播(EBP)神经网络模型。结果认为,包含了福克兰寒流与巴西暖流表温信息的方案3模型优于其他两种模型,其准确率可以达到90%以上。     

SST Availabilities of Satellite Infrared and Microwave Measurements

To investigate the feasibility and methodology of new generation sea surface temperature (SST) maps that combine various satellite measurements, we have quantitatively evaluated SST availabilities of NOAA AVHRR (National Oceanic and Atmospheric Administration, Advanced Very High Resolution Radiometer), GMS S-VISSR (Geostationary Meteorological Satellite, Stretched-Visible Infrared Spin Scan Radiometer) and TRMM MI (Tropical Rainfall Measuring Mission, Microwave Imager: TMI), during the one-year period from October 1999 to September 2000. The advantage of satellite microwave SST measurements is the ability to penetrate the clouds that contaminate satellite infrared measurements. Daily SST availabilities were calculated in the overlapping coverage from 20°N to 38°N and 120°E to 160°E. The annual-mean SST availabilities of AVHRR, S-VISSR and TMI are 48%, 56% and 78%, respectively. There are large seasonal variations in the availabilities of infrared measurements. The latitude-time plots of one-degree zonal mean SST availabilities of S-VISSR and TMI in the region from 38°S to 38°N and 80°E to 160°W show significant zonal variations, which are influenced by the atmospheric circulation such as the Subtropical High and the Intertropical Convergence Zone. The SST availabilities of S-VISSR and TMI in the five selected regions have large regional variations, ranging from 35% to 74% and 62% to 88% for S-VISSR and TMI, respectively. The present statistical analyses of SST availabilities in the infrared and microwave measurements indicate that 1) a daily cloud-free high-spatial resolution may be achieved by merging various SST measurements since their deficiencies compensate each other, and 2) nevertheless, it is necessary to take account of the seasonal and regional variations of SST availabilities of different satellite sensors for the development of merging technology. This revised version was published online in July 2006 with corrections to the Cover Date.     

集合同化方法在黄海海域海表面温度同化中的应用

The effects of sea surface temperature(SST) data assimilation in two regional ocean modeling systems were examined for the Yellow Sea(YS). The SST data from the Operational Sea Surface Temperature and Sea Ice Analysis(OSTIA) were assimilated. The National Marine Environmental Forecasting Center(NMEFC) modeling system uses the ensemble optimal interpolation method for ocean data assimilation and the Kunsan National University(KNU) modeling system uses the ensemble Kalman filter. Without data assimilation, the NMEFC modeling system was better in simulating the subsurface temperature while the KNU modeling system was better in simulating SST. The disparity between both modeling systems might be related to differences in calculating the surface heat flux, horizontal grid spacing, and atmospheric forcing data. The data assimilation reduced the root mean square error(RMSE) of the SST from 1.78°C(1.46°C) to 1.30°C(1.21°C) for the NMEFC(KNU) modeling system when the simulated temperature was compared to Optimum Interpolation Sea Surface Temperature(OISST) SST dataset. A comparison with the buoy SST data indicated a 41%(31%) decrease in the SST error for the NMEFC(KNU) modeling system by the data assimilation. In both data assimilative systems, the RMSE of the temperature was less than 1.5°C in the upper 20 m and approximately 3.1°C in the lower layer in October. In contrast, it was less than 1.0°C throughout the water column in February. This study suggests that assimilations of the observed temperature profiles are necessary in order to correct the lower layer temperature during the stratified season and an ocean modeling system with small grid spacing and optimal data assimilation method is preferable to ensure accurate predictions of the coastal ocean in the YS.     

两类El Niño不同衰减型的演变特征及其与我国夏季降水的联系

利用中国气象局743站日降水、NCEP-/NCAR大气环流、英国气象局Hadley中心全球月平均海表温度（SST）等资料,探讨了两类El Niño不同衰减型的演变特征及其对衰减阶段夏季（6-8月）我国降水异常分布的可能影响。根据海表温度异常（SSTA）沿赤道（5°S~5°N）的演变特征,EP-El Niño存在两种衰减型:自东向西（E-W）衰减（大于0.5℃的海温正距平首先在南美沿岸消失,并向西扩展）和自西向东（W-E）衰减（大于0.5℃的海温正距平首先在赤道中太平洋消失,并向东扩展）;CP-El Niño存在3种衰减方式:对称（S）衰减（赤道中太平洋暖海温的发展和衰减关于某一峰值对称）、延迟（P）衰减（衰减阶段紧接着呈现EP-El Niño分布）、突然（A）衰减（衰减阶段紧接着发生EP-La Niña事件）。对于EP-El Niño,在华北、华南、长江和黄河（简称两河）之间及两河的上游地区,E-W与W-E衰减阶段夏季降水呈现完全相反的异常分布特征。E-W衰减阶段夏季两河之间及上游地区偏旱的可能性显著增大,华北地区降水异常偏多,长江以南略偏多;而W-E衰减阶段夏季,两河之间及上游地区降水偏多,降水异常大值中心主要位于沿江地区,华南大部和华北地区降水明显偏少。对于CP-El Niño的3种衰减方式:夏季降水异常大值带在S衰减方式下主要位于黄河和淮河之间;在P方式衰减时,出现在长江流域;而在A型衰减时,主要位于黄河下游地区。S和A衰减方式下,东北大部尤其东北北部降水偏少,而处于P衰减时,东北大部降水明显偏多;在西南地区,S衰减时夏季降水总体偏多,A衰减时情况相反;在西北北部地区,A衰减时偏旱,而S和P衰减时降水总体偏多。不同的衰减方式均对应不同的降水异常空间分布,区分衰减型使得两类El Niño次年我国夏季降水异常显著区的分布范围和信号强度均较未区分衰减型时有较好的改善,为我国汛期降水短期气候预测工作提供了重要依据。     

On the influence of the sea surface temperature on the carbon dioxide exchange with the atmosphere

The influence of the sea surface temperature (SST) on the carbon dioxide (CO₂) exchange with the atmosphere at different spatial and temporal scales, which has a multidirectional character, was studied. The initial data included the monthly averages of the CO₂ flux during the period of 1982–2011 at grid nodes of 4° by latitude and 5° by longitude, as well as the SST satellite data from January 1, 1982 to December 31, 2012 at the geographical grid nodes of 0.25° × 0.25°. Statistical models of estimation of the resulting global CO₂ flux were suggested on the basis of data on SST anomalies. It is demonstrated that the SST variations in the equatorial zone mostly control the interannual fluctuations of the resulting CO₂ flux in the ocean-atmosphere system.     

南海南部海域海面温度异常的时空分布特征

基于1982年1月—2006年12月NOAA Optimum Interpolation Sea Surface Temperature（OISST）的逐月平均海面温度（SST）资料，采用经验正交函数分解（EOF）方法分析了南海南部海面温度异常场典型的空间分布形态及其时间变化特征。结果表明，南海南部海域海面温度异常场空间上主要表现为三种典型的分布结构，即以研究区域北部为中心的海盆尺度的单涡结构、东西反相的经向偶极子分布结构和南北反相的纬向偶极子分布结构，这三种分布结构都以2—4年的年际变化周期为主，反映了研究海域海面温度异常与ENSO现象高度相关。此外，研究海域还存在显著的半年和季节内周期变化，这种变化周期主要以南北反相的纬向偶极子分布结构（第三模态）存在，反映了大气动力强迫和热力强迫共同影响的结果。     

基于最优插值方法的微波-红外辐射计数据融合全球海面温度网格产品

A new 0.1° gridded daily sea surface temperature(SST) data product is presented covering the years 2003–2015. It is created by fusing satellite SST data retrievals from four microwave(Wind Sat, AMSR-E, ASMR2 and HY-2 A RM)and two infrared(MODIS and AVHRR) radiometers(RMs) based on the optimum interpolation(OI) method. The effect of including HY-2 A RM SST data in the fusion product is studied, and the accuracy of the new SST product is determined by various comparisons with moored and drifting buoy measurements. An evaluation using global tropical moored buoy measurements shows that the root mean square error(RMSE) of the new gridded SST product is generally less than 0.5℃. A comparison with US National Data Buoy Center meteorological and oceanographic moored buoy observations shows that the RMSE of the new product is generally less than 0.8℃. A comparison with measurements from drifting buoys shows an RMSE of 0.52–0.69℃. Furthermore, the consistency of the new gridded SST dataset and the Remote Sensing Systems microwave-infrared SST dataset is evaluated, and the result shows that no significant inconsistency exists between these two products.     

Spatial variations in the air turbidity factor above the European part of Russia under conditions of abnormal summer of 2010

We analyze spatial variations in the air turbidity factor T obtained from the interpolation of ground-based solar radiometry data within the territory (40°–70° N, 30°–60° E) in summer 2010. The abnormal heat and connected fires of summer 2010 changed the mean values of air turbidity and the character of its spatial variations. As a result, a “tongue” of increased values of the turbidity factor was observed in the south-to-north direction in July, and a closed region of anomalous high T was formed over the territory (48°–55° N, 37°–42° E) to the south of Moscow and partly covered the Moscow region in August. Such a pattern resulted from blockage preventing from ingress of air masses from the west and producing closed air circulation over the European Part of Russia (EPR).     

Variability of sea surface temperature in the Japan Sea and its relationship to the wind-curl field

The variability of sea surface temperature (SST) in the Japan Sea is investigated using the complex EOF analysis of daily data produced at Tohoku University, Japan (New Generation SST; 2002–2006). The relationship with the wind field is investigated from the daily NCEP/NCAR reanalysis data with a 1° spatial resolution. Anomalies in the SST (SSTAs) are calculated by subtracting the basin-average annual variation estimated as a leading mode of temperature. The leading mode of an SSTA represents a adjustment to the annual mean variation, most significant in December in the zone of subtropical waters entering the sea through the Korean Strait and in the northwestern sea, over which a cyclonic wind curl develops in the cold period. The semiannual variability mode is identified, which is characterized by the largest temperature increase (decrease) in the western branch of the subarctic front (in the Tatar Strait), which lags by two months behind the semiannual changes in wind curl over the sea. An episodic SSTA movement is detected in the northern part of the sea, which moves from east to west along the western branch of the Tsushima Warm Current with a speed corresponding in magnitude to an advective scale.     

基于Stokes公式的扰动重力梯度张量无奇异计算模型

为有效解决Stokes积分奇异性问题,以扰动重力梯度张量的计算为例,采用双二次多项式插值和非奇异变换推导了解决计算点和临近格网点积分奇异的统一公式,分析了数据分辨率对中央区选取范围及积分奇异性的影响。选取某海域8°×8°范围的重力异常数据进行数值实验,结果表明,该方法与传统去奇异方法在一些分量的差异可达数E,使用该方法更有助于提高计算精度。此外,针对不同分辨率的数据,合理选取中央区范围可有效避免计算结果产生舍入误差或奇异。     

Structure and mechanisms of the Arabian Sea variability during the winter monsoon

In the southern Arabian Sea (between the Equator and 10°N), the shoaling of isotherms at subsurface levels (20 °C isotherm depth is located at ∼90 m) leads to cooling at 100 m by 2–3 °C relative to surrounding waters during the winter monsoon. The annual and interannual variations of this upwelling zone, which we call the Arabian Sea dome (ASD), are studied using results from an eddy-permitting ocean general circulation model in conjunction with hydrography and TOPEX/ERS altimeter data. The ASD first appears in the southeastern Arabian Sea during September–October, maturing during November–December to extend across the entire southern Arabian Sea (along ∼5°N). It begins to weaken in January and dissipates by March in the southwestern Arabian Sea. From the analysis of heat-budget balance terms and a pair of model control experiments, it is shown that the local Ekman upwelling induced by the positive wind-stress curl of the winter monsoon generates the ASD in the southeastern Arabian Sea. The ASD decays due to the weakening of the cyclonic curl of the wind and the westward penetration of warm water from the east (Southern Arabian Sea High). The interannual variation of the ASD is governed by variations in the Ekman upwelling induced by the cyclonic wind-stress curl. Associated with the unusual winds during 1994–1995 and 1997–1998 Indian Ocean dipole (IOD) periods, the ASD failed to develop. In the absence of the ASD during the IOD events, the 20 °C isotherm depth was 20–30 m deeper than normal in the southern Arabian Sea resulting in a temperature increase at 97 m of 4–5 °C. An implication is that the SST evolution in the southern Arabian Sea during the winter monsoon is primarily controlled by advective cooling: the shoaling of isotherms associated with the ASD leads to SST cooling.     

Advanced sea surface temperature retrieval using the Japanese geostationary satellite,Himawari-6

Producing high-quality match-ups coupling the Japanese geostationary satellite, Himawari-6 (H6), and buoy SST observations, we have developed the new SST retrieval method. Kawamura et al. (2010) developed the previous version of SST product called MTSAT SST, which left several scientific/technical questions. For solving them, 6,711 algorithm tuning match-ups with precise navigation and 240,476 validation match-ups are generated for covering all seasons and wide ocean coverage. For discriminating the previous MTSAT SST, we call the new version of SST H6 SST. It is found that the SZA dependences of MTSAT SST algorithm are different from area to area of SZA > 40–50° N/S. The regionally different SZA dependences are treated by dividing the H6 disk coverage into five areas by the latitude lines of 40° N/S first and the longitude lines of 100° K and 180° K. Using the algorithm tuning match-ups, Nonlinear SST (NLSST) equations are derived for all of the five areas. Though the sun zenith angle dependency correction term is also examined, there is no significant regional difference. Therefore, this term is used in the H6 SST algorithm again. The new H6 SST equation is formed by the areal NLSST and the sun zenith angle dependency term for each area. The statistical evaluation of H6 SST using the validation match-ups show the small negative biases and the RMS errors of about 0.74° K for each area. For the full H6 disk, the bias is −0.1° K and the RMS error 0.74° K. The histogram of H6 SST minus the in situ SST for each area has a similar Gaussian shape with small negative skewness, and the monthly validation of H6 SST for each area is consistent with those for the whole period and the histograms     

A-HIGHERS—The System to Produce the High Spatial Resolution Sea Surface Temperature Maps of the Western North Pacific Using the AVHRR/NOAA

To study on the oceanic variations in the western North Pacific, we developed a system to produce a high spatial resolution sea surface temperature (SST) map from the data obtained by the Advanced Very High Resolution Radiometer (AVHRR) aboard the National Oceanic and Atmospheric Administration (NOAA) satellites. As the system has been improved on the HIGHERS (Sakaida and Kawamura, 1996), it is called the Advanced-HIGHERS (A-HIGHERS). The A-HIGHERS has been developed on the super computer in the Tohoku University, which is favorable for handling of a large volume of data. Mainly because of improvements in the cloud detection algorithm, the A-HIGHERS can deal with the data obtained at dawn and dusk around the year, and at daytime in summer more effectively. The A-HIGHERS are used to produce SST maps spanning from (60°N, 120°E) to (20°N, 160°E) with a grid size of 0.01 degree.