Observed vs. predicted variability in non-algal suspended particulate matter concentration in the English Channel in relation to tides and waves

The study of water clarity is essential to understand variability in biological production, particularly in coastal seas. The spatial and temporal variability of non-algal suspended particulate matter (SPM) in surface waters of the English Channel was investigated and related to local forcing by means of a large satellite dataset covering the study area with a spatial resolution of 1.2 km and a daily temporal resolution. This analysed dataset is a time series of non-algal SPM images derived from MODIS and MERIS remote-sensing reflectance by application of an IFREMER semi-analytical algorithm over the period 2003–2009. In a first step, the variability of time series of MODIS images was analysed through temporal autocorrelation functions. Then, non-algal SPM concentrations were assessed in terms of site-specific explanatory variables such as tides, wind-generated surface-gravity wave amplitudes and chlorophyll-a (Chl-a), based on three statistical models with fitting parameters calibrated on a dataset of merged MERIS/MODIS images gathered from 2007 to 2009 over the whole English Channel. Correlogram analysis and the first model highlight the local patterns of the influence of the tide, especially the neap–spring cycle, on non-algal surface SPM. Its effect is particularly strong in the central and eastern English Channel and in the western coastal areas. The second model shows that waves prevail as driver at the entrance of the English Channel. The most sophisticated of the three statistical models, although involving only three explanatory variables—the tide, waves and Chl-a—is able to estimate non-algal surface SPM with a coefficient of determination reaching 70% at many locations.     

Retrieval of total suspended matter from MODIS 250?m imagery in the Bohai Sea of China

Moderate Resolution Imaging Spectroradiometer (MODIS) on the Aqua and Terra satellites have unique advantages for monitoring coastal waters, owing to their high spatial resolution (250?m), short revisit period (1–2?days), and freedom from cost. An empirical retrieval model for concentration of total suspended matter (TSM) has been developed based on a statistical analysis of field surveys of TSM and remote sensing reflectance (R _rs) in the Bohai Sea of China. A robust linear relationship was established between the equivalent remote sensing reflectance (converting ASD-measured R _rs by spectral response function) in the 620–670?nm band (band 1) of MODIS and the concentration of TSM (R ²?=?0.95; n?=?27; RMS?=?0.512) acquired in August and September 2008. The model was validated via in situ measurements in September 2009, resulting in a mean relative error of 12.9?%. Then, the corresponding MODIS products of monthly average concentration of TSM were produced from January to December 2009. The distribution characteristics of TSM in the Bohai Sea of China are closely related with the spatial pattern and seasonal variability. This study demonstrates that the moderately high resolution of MODIS 250?m data is available for monitoring the transport and fate of materials in relatively smaller bodies of water.     

Comparative Analysis of Chlorophyll-a Distribution from SeaWiFS,MODIS-Aqua,MODIS-Terra and MERIS in the Arabian Sea

The variability of Chlorophyll-a (Chl-a) distribution derived from MODIS (on Aqua and Terra platforms) and MERIS sensors have been compared with SeaWiFS data in the Arabian Sea. MODIS Aqua has overestimated the SeaWiFS Chl-a within 25–32% in the coastal turbid (eutrophic) waters and underestimated in open ocean waters with error within 20%. However, there is no significant bias (?0.1 on log-scale) observed as the slope is well within 0.97-1.1 (log transformed). MODIS-Terra has underestimated the Chl-a concentration in open ocean waters by about 29–31%, which is higher than MODIS-Aqua. MODIS-Terra is observed to be more accurate than MODIS-Aqua in the coastal waters. MERIS is overestimating the SeaWiFS Chl-a with log RMS error of ～0.15 and log bias of ～0.13–0.2. The differences in the Chl-a estimates between each sensor are possibly due to differences in the sensor design, bio-optical algorithms and also due to the time differences between the satellites over passes. We have examined that the MERIS is performing similar to SeaWiFS and the MODIS-Aqua (Terra) data are reliable in open ocean (coastal) waters. However, Chl-a retrieval algorithms need to be improved especially for coastal turbid waters to continue with SeaWiFS data for long-term studies.     

Assessment of GOCI radiometric products using MERIS, MODIS and field measurements

The first Geostationary Ocean Color Imager (GOCI) launched by South Korea in June 2010 constitutes a major breakthrough in marine optics remote-sensing for its capabilities to observe the diurnal cycles of the ocean. The light signal recorded at eight wavelengths by the sensor allows, after correction for Solar illumination and atmospheric effects, the retrieval of coloured biogeochemical products such as the chlorophyll, suspended sediment and coloured dissolved organic matter concentrations every hour between 9:00 am and 4:00 pm local time around the Korean peninsula. However operational exploitation of the mission needs beforehand a sound validation of first the radiometric calibration, i.e. inspection of the top-of-atmosphere reflectance, and second atmospheric corrections for retrieval of the water-leaving reflectance at sea surface. This study constitutes a contribution to the quality assessment of the GOCI radiometric products generated by the Korea Ocean Satellite Center (KOSC) through comparison with concurrent data from the MODerate-resolution Imaging Spectroradiometer (MODIS, NASA) and MEdium Resolution Imaging Spectrometer (MERIS, ESA) sensors as well as in situ measurements. These comparisons are made with spatially and temporally collocated data. We focus on Rayleigh-corrected reflectance (?? _RC ) and normalized remote-sensing marine reflectance (nRrs). Although GOCI compares reasonably well with MERIS and MODIS, what demonstrates the success of Ocean Colour in geostationary orbit, we show that the current GOCI atmospheric correction systematically masks out data over very turbid waters and needs further examination and correction for future release of the GOCI products.     

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.     

Dynamic of ENSO towards upwelling and thermal front zone in the east coast of Peninsular Malaysia

The El Ni?o Southern Oscillation(ENSO) is a natural phenomenon that relates to the fluctuation of temperatures over the Pacific Ocean. The ENSO significantly affects the ocean dynamics including upwelling event and coastal front. A recent study discovered the seasonal upwelling in the east coast of Peninsular Malaysia(ECPM), which is significant to the fishery industry in this region. Thus, it is vital to have a better understanding of the influence of ENSO towards the coastal upwelling and thermal front in the ECPM. The sea surface temperature(SST) data achieved from moderate resolution imaging spectroradiometer(MODIS) aboard Aqua satellite are used in this study to observe the SST changes from 2005 to 2015. However, due to cloud cover issue, a reconstruction of data set is applied to MODIS data using the data interpolating empirical orthogonal function(DINEOF) to fill in the missing gap in the dataset based on spatial and temporal available data. Besides, a wavelet transformation analysis is done to determine the temperature fluctuation throughout the time series. The DINEOF results show the coastal upwelling in the ECPM develops in July and reaches its peak in August with a clear cold water patch off the coast. There is also a significant change of SST distribution during the El Ni?o years which weaken the coastal upwelling event along the ECPM. The wavelet transformation analysis shows the highest temperature fluctuation is in 2009–2010 which indicates the strongest El Ni?o throughout the time period. It is suggested that the El Ni?o is favourable for the stratification in water column thus it is weakening the upwelling and thermal frontal zone formation in ECPM waters.     

A global analysis of multi-mode sea surface temperature pattern

1 IntroductionThe variability of the air -sea system orches-trates a complex climate system of our earth, andthis variability gives rise to an array of naturally oc-curring dynamical modes at different time scales.These modes are important attributes of c…     

一种基于不同表面强迫方式对CFSR表面通量资料进行修正的方法探讨

海表面温度(SST)的变化是海气相互作用的重要体现,SST的准确模拟也是海洋内部温度模拟的基础。基于区域海洋模式,本文通过对比分析两种强迫方式对SST的模拟效果,诊断了各辐射场对SST模拟效果的贡献,基于EOF分析法提出了一种针对CFSR表面大气强迫辐射数据的修正方案,并获取一套高频辐射场修正数据。数值对比试验结果显示,利用COARE 3.0公式计算所得表面强迫的方式模拟的SST结果更好,其均方根误差比直接强迫方式降低约39%;潜热辐射差异是两种强迫方式对SST模拟效果差异的主要原因,感热辐射差异次之,同时对两者进行修正可以显著改进SST的模拟效果;而长波辐射的修正则对冬季的SST模拟效果改善比较明显,但贡献仍弱于潜热辐射。相对于海洋模式而言,准确可靠的大气强迫数据的选择要优于强迫方式的选择。     

基于CORA资料的中国海海表面温度季节和年际变化特征分析

基于1986-2008年的中国近海及邻近海域再分析产品(CORA),采用经验正交函数分解方法(EOF)分析了海表面温度(SST)的季节及年际变化特征,并用相应的SODA、AVHRR以及Levitus资料对CORA做了对比评估。相比于AVHRR而言,CORA资料SST的偏差和均方根误差均小于SODA,相比Levitus资料而言CORA资料温度盐度的均方根误差随深度的变化皆小于SODA。 CORA与SODA资料相比,两者前3个模态的时空分布大体一致,区别在于CORA资料能更好地反映参量的一些细微特征。结果表明,CORA资料能很好的刻画中国近海SST的季节、年际变化特征,尤其是黑潮流经区域SST的局地变化特征。季节EOF第二模态显示的是SST对由风引起的潜热释放的响应特征。第三模态刻画了冬夏转换季的分布特征,主要揭示了东北-西南走向的锋面特征。SST年际变化与ENSO密切相关,区域平均的南海SSTA与Nino指数的吻合程度CORA优于SODA。     

Interannual SST variability in the Japan/East Sea and relationship with environmental variables

Interannual variability of the Japan/East Sea (JES) sea surface temperature (SST) is investigated from the reconstructed NOAA/AVHRR Oceans Pathfinder best SST data (1985–2002) using the complex empirical function (CEOF) analysis. The iterative empirical function analysis is used for the SST data reconstruction. The first two leading CEOFs account for 86.0% of total variance with 66.4% for the first mode and 19.6% for the second mode. The first CEOF mode represents a standing oscillation and a maximum belt in the central JES. There are two near-7-year events and one 2–3-year event during the period of 1985–2002. The first mode oscillates by adjacent atmospheric systems such as the Aleutian Low, the North Pacific High, the Siberian High, and the East Asian jet stream. Positive correlation in a zonal belt between the first mode JES SST anomaly and the background surface air temperature/SST anomaly reveals intensive ocean-atmosphere interaction near the Polar Front in the North Pacific. The second CEOF mode represents two features: standing oscillation and propagating signal. The standing oscillation occurs in the northern (north of 44°N) and southern (south of 39°N and west of 136°E) JES with around 180° phase difference. A weak southwestward propagating signal is detected between the two regions. The eastward propagating signal is detected from the East Korean Bay to near 135°E. The second mode contains 4–5-year periodicity before 1998 and 2–3-year periodicity thereafter. It is associated with the Arctic Oscillation, which leads it by 1–5-year. Furthermore, a strong correlation with the background surface air temperature/SST anomaly is detected in the tropical to subtropical western Pacific.     

基于SOM的海表温度遥感数据集的EOF算法重构

针对海表温度数据集的数据缺失,提出了一种基于自组织映射算法(SOM)和经验正交函数算法(EOF)有机结合的重构缺失值的新方法。该方法应用了SOM的非线性估计,能够很好的反映数据集的非线性结构,并把SOM估计的结果用于EOF算法的初始化,克服了EOF对数据集初始化敏感的问题。在处理过程中,对奇异值分解使用了lanczos算子分解矩阵,提高了程序运行效率。此外,该方法还引入蒙特卡罗交叉校正集,确定最佳重构的EOF模态数,最终高精度计算出重构误差。使用AQUA遥感卫星海表温度数据进行实验,结果表明该方法能够很好地重构出缺失率高达83.23%的数据集,且重构精度高。     

3套不同的SST再分析数据与中国近海浮标观测的对比研究

基于自然资源部浮标数据,通过分析均值差、均方根误差、相关系数和标准差偏差4个统计量,检验了2018年7月1日至8月6日全时段及该时段内3个台风(1808号台风"玛利亚"、1810号台风"安比"、1812号台风"云雀")过境期间,3套海表面温度(Sea Surface Temperature,SST)再分析资料(OISST、OSTIA SST、RTG SST)在中国近海区域的可靠性。对比结果表明,在全时段内,3套SST再分析资料都能在一定程度上反映中国近海SST的基本状况,其中OSTIA SST资料同浮标实测SST数据的均值差为0.12℃、相关系数为0.94,均优于OISST资料(均值差为–0.85℃、相关系数为0.90)和RTG SST资料(均值差为–0.17℃、相关系数为0.86)。通过对比单个浮标数据发现,相较约80%的MF浮标实测SST数据,OSTIA SST资料都显著优于RTG SST资料和OISST资料,具有较高的可信度。在台风过境期间,较之RTG SST资料和OISST资料,OSTIA SST资料同大部分浮标实测数据的均值差绝对值及均方根误差更小、相关系数更大,表明在高海况...     

Coastal phytoplankton blooms in the Southern California Bight

Surface chlorophyll (CHL) measured at the Scripps Pier in the Southern California Bight (SCB) for 18 years (1983–2000) reveals that the spring bloom occurs with irregular timing and intensity each year, unlike sea-surface temperature (SST), which is dominated by a regular seasonal cycle. In the 1990s, the spring bloom occurred earlier in the year and with larger amplitudes compared to those of the 1980s. Seasonal anomalies of the Pier CHL have no significant correlation with local winds, local SST, or upwelling index, which implies that classical coastal upwelling is not directly responsible for driving chlorophyll variations in nearshore SCB.The annual mean Pier CHL exhibits an increasing trend, whereas the Pier SST has no evident concomitant trend during the CHL observation period. The interannual variation of the Pier CHL is not correlated with tropical El Niño or La Niña conditions over the entire observing period. However, the Pier CHL was significantly influenced by El Nino/Southern Oscillation during the 1997/1998 El Niño and 1998/1999 La Niña transition period. The Pier CHL is highly coherent at long periods (3–7 years) with nearby offshore in situ surface CHL at the CalCOFI (California Cooperative Fisheries Investigations) station 93.27.     

Evidence of multidecadal climate variability and the Atlantic Multidecadal Oscillation from a Gulf of Mexico sea-surface temperature-proxy record

A comparison of a Mg/Ca-based sea-surface temperature (SST)-anomaly record from the northern Gulf of Mexico, a calculated index of variability in observed North Atlantic SST known as the Atlantic Multidecadal Oscillation (AMO), and a tree-ring reconstruction of the AMO contain similar patterns of variation over the last 110 years. Thus, the multidecadal variability observed in the instrumental record is present in the tree-ring and Mg/Ca proxy data. Frequency analysis of the Gulf of Mexico SST record and the tree-ring AMO reconstruction from 1550 to 1990 found similar multidecadal-scale periodicities (~30–60 years). This multidecadal periodicity is about half the observed (60–80 years) variability identified in the AMO for the 20th century. The historical records of hurricane landfalls reveal increased landfalls in the Gulf Coast region during time intervals when the AMO index is positive (warmer SST), and decreased landfalls when the AMO index is negative (cooler SST). Thus, we conclude that alternating intervals of high and low hurricane landfall occurrences may continue on multidecadal timescales along the northern Gulf Coast. However, given the short length of the instrumental record, the actual frequency and stability of the AMO are uncertain, and additional AMO proxy records are needed to establish the character of multidecadal-scale SST variability in the North Atlantic.     

台湾海峡MODIS遥感SST的初步验证

海表层温度（SST）是一个决定海气相互作用以及生物栖息条件适宜性的海洋环境关键参数,可以通过卫星遥感手段获取,对检验锋面多发、水文条件复杂的近岸区域卫星遥感SST产品的真实性,具有重要意义．本文采用大型海洋环境多层监测浮标获取的SST数据对台湾海峡MODIS遥感SST产品进行检验．结果表明,MODIS遥感与实测SST数据具有很好的一致性,两者的均方根误差为0．5l℃,平均偏差为一0．02℃,平均绝对偏差为0．42℃,相关系数为0．988;MODIS遥感与实测SST数据之间可能存在季节性差异,均方根误差以夏季最大．     

一个重构的153年热带太平洋次表层上卷海温资料

次表层上卷海温对改进ENSO(厄尔尼诺-南方涛动,El Ni o-Southern Oscillation)模拟水平及ENSO年代际变化均具有重要作用。利用一个中等复杂程度耦合模式(intermediate coupled model,简称ICM)和Nudging(张弛逼近)同化方法,重构了1856—2008年间热带太平洋地区的次表层上卷海温。统计检验表明,重构的次表层上卷海温与近50年的3种分析资料间具有较高的相关性和较小的均方根误差。此外,通过此重构的次表层上卷海温资料重新驱动ICM模式,模拟得到的海表温度距平(sea surface temperature anomaly,简称SSTA)可以真实地反映出ENSO的年际和年代际变化,表明此重构的次表层上卷海温资料可用于气候研究,特别是用于ENSO的大尺度低频变化或年代际气候变化研究。     

The optimization algorithm for the pathfinder sea surface temperature in the East China Seas

Based on the analysis of the quality level in a Pathfinder 4km daily nighttime Sea Surface Temperature product (PFSST) in the East China Seas (ECS) from 1985 to 2004, the proportion of high-quality data was lower than that in the global level. Additionally, the PFSST maps showed clearly the void and anomaly data impacted by atmospheric contamination. In order to solve the above problem, an optimal algorithm was established through introducing the structure function, setting up the daily first-guess sea surface temperature (SST) field and taking PFSST product of the highest quality as reference points. Comparisons were done between this optimally interpolated SST and the selected original PFSST and the simultaneous in situ measurements. It illustrated it was possible to exactly estimate the SST values in the ECS during the recent two decades. The mean bias error and the root mean square error between data sets optimally evaluated and in situ observed were lower than those between the previous global estimations and in situ measurnments.     

The Pacific Decadal Oscillation

The Pacific Decadal Oscillation (PDO) has been described by some as a long-lived El Niño-like pattern of Pacific climate variability, and by others as a blend of two sometimes independent modes having distinct spatial and temporal characteristics of North Pacific sea surface temperature (SST) variability. A growing body of evidence highlights a strong tendency for PDO impacts in the Southern Hemisphere, with important surface climate anomalies over the mid-latitude South Pacific Ocean, Australia and South America. Several independent studies find evidence for just two full PDO cycles in the past century: “cool” PDO regimes prevailed from 1890–1924 and again from 1947–1976, while “warm” PDO regimes dominated from 1925–1946 and from 1977 through (at least) the mid-1990's. Interdecadal changes in Pacific climate have widespread impacts on natural systems, including water resources in the Americas and many marine fisheries in the North Pacific. Tree-ring and Pacific coral based climate reconstructions suggest that PDO variations—at a range of varying time scales—can be traced back to at least 1600, although there are important differences between different proxy reconstructions. While 20th Century PDO fluctuations were most energetic in two general periodicities—one from 15-to-25 years, and the other from 50-to-70 years—the mechanisms causing PDO variability remain unclear. To date, there is little in the way of observational evidence to support a mid-latitude coupled air-sea interaction for PDO, though there are several well-understood mechanisms that promote multi-year persistence in North Pacific upper ocean temperature anomalies.     

Principal Modes and Related Frequencies of Sea Surface Temperature Variability in the Pacific Coast of North America

We examined monthly time-series (1950 to 1999) of sea surface temperature (SST) anomalies in 47 quadrants (2° × 2°) along the Pacific coast of North America. Correlation, clustering and principal components analyses were applied to identify the spatial structure in coastal SST. The resulting modes and the individual series were investigated using spectral analysis to identify the most significant time-scales of variability, and the propagation of the main signals was explored by computing the wavenumber-frequency spectrum of each spatial mode. Results showed that coastal SST variability in the northeast Pacific conformed to three main geographical modes. A tropical mode extends from the equator to about the entrance to the Gulf of California. This mode appears related to two low frequency components of the El Niño-Southern Oscillation of about 3 and 5 years. The SST anomaly related to these signals propagates poleward, seemingly at low speeds (≈0.08 m s^?1). A temperate (or transitional) mode, which includes the coastal areas along the California Current System, also shows the 5-year signal plus a decadal-scale component (periods between 10–17 years). Finally, a subarctic mode includes the coastal areas along the Gulf of Alaska and is dominated by the interdecadal variability that is characterized by the Pacific Decadal Oscillation.     

Spatio-temporal variability in sea surface temperatures for the Yellow Sea based on MODIS dataset

The spatio-temporal variabilities in sea surface temperature (SST) were analyzed using a time series of MODIS datasets for four separate regions in the Yellow Sea (YS) that were located along a north-south axis. The space variant temporal anomaly was further decomposed using an empirical orthogonal function (EOF) for estimating spatially distributed SST. The monthly SSTs showed similar temporal patterns in each region, which ranged from 2.4°C to 28.4°C in the study years 2011 to 2013, with seasonal cycles being stronger at the higher latitudes and weaker at the lower latitudes. Spatially, although there were no significant differences among the four regions (p < 0.05) in any year, the geographical distribution of SST was characterized by an obvious gradient whereby SST decreased along the north-south axis. The monthly thermal difference among regions was largest in winter since the SST in the southeast was mainly affected by the Yellow Sea Warm Currents. The EOF1 mode accounted for 56% of the total spatial variance and exhibited a warming signal during the study period. The EOF2 mode accounted for 8% of the total variance and indicated the warm current features in the YS. The EOF3 mode accounted for 6% of the total variance and indicated the topographical features. The methodology used in this study demonstrated the spatio-temporal variabilities in the YS.