基于HY-2A散射计数据的极区海冰范围反演方法及其评估

A sea ice extent retrieval algorithm over the polar area based on scatterometer data of HY-2A satellite has been established.Four parameters are used for distinguishing between sea ice and ocean with Fisher's linear discriminant analysis method.The method is used to generate polar sea ice extent maps of the Arctic and Antarctic regions of the full 2013–2014 from the scatterometer aboard HY-2A(HY-2A-SCAT) backscatter data.The time series of the ice mapped imagery shows ice edge evolution and indicates a similar seasonal change trend with total ice area from DMSP-F17 Special Sensor Microwave Imager/Sounder(SSMIS) sea ice concentration data.For both hemispheres,the HY-2A-SCAT extent correlates very well with SSMIS 15% extent for the whole year period.Compared with Synthetic Aperture Radar(SAR) imagery,the HY-2A-SCAT ice extent shows good correlation with the Sentinel-1 SAR ice edge.Over some ice edge area,the difference is very evident because sea ice edges can be very dynamic and move several kilometers in a single day.     

An improved QuikSCAT wind retrieval algorithm and eye locating for typhoon

This paper proposes a rain considered geophysical model function (GMF), to be noted as GMF plus Rain. GMF plus Rain is based on the basic raidative transfer model with attenuation and scattering effects of rain on radar signal considered. Combined with the NSCAT2 GMF and the rain correction model, the GMF plus Rain model is used to retrieve the ocean wind vectors from the collocated QuikSCAT and SSM/I rain rate data for typhoon Melor. The resulting wind speed estimates of typhoon Melor show improved agreement with the wind fields derived from the best track analysis of Japan Meteorological Agency (JMA). The results imply that compared with the GMF model, the GMF plus Rain model can improve the precision of wind retrieval under the rain condition. Then, a new general algorithm of locating the eye of typhoon through the normalized radar cross section (NRCS) is proposed. The implementation of this algorithm in the ten QuikSCAT observations of typhoon Melor suggests that this algorithm is effective.     

降雨导致的海面粗糙度对Aquarius卫星盐度反演的影响研究

Rainfall has two significant effects on the sea surface, including salinity decreasing and surface becoming rougher,which have further influence on L-band sea surface emissivity. Investigations using the Aquarius and TRMM 3B42 matchup dataset indicate that the retrieved sea surface salinity(SSS) is underestimated by the present Aquarius algorithm compared to numerical model outputs, especially in cases of a high rain rate. For example, the bias between satellite-observed SSS and numerical model SSS is approximately 2 when the rain rate is 25 mm/h. The bias can be eliminated by accounting for rain-induced roughness, which is usually modeled by rain-generated ring-wave spectrum. The rain spectrum will be input into the Small Slope Approximation(SSA) model for the simulation of sea surface emissivity influenced by rain. The comparison with theoretical model indicated that the empirical model of rain spectrumis more suitable to be used in the simulation. Further, the coefficients of the rain spectrum are modified by fitting the simulations with the observations of the 2–year Aquarius and TRMM matchup dataset. The calculations confirm that the sea surface emissivity increases with the wind speed and rain rate. The increase induced by the rain rate is rapid in the case of low rain rate and low wind speed. Finally, a modified model of sea surface emissivity including the rain spectrum is proposed and validated by using the matchup dataset in May 2014. Compared with observations, the bias of the rain-induced sea surface emissivity simulated by the modified modelis approximately 1e–4, and the RMSE is slightly larger than 1e–3. With using more matchup data, thebias between model retrieved sea surface salinities and observationsmay be further corrected,and the RMSE may be reduced to less than 1 in the cases of low rain rate and low wind speed.     

Monitoring the TOPEX and Jason-1 Microwave Radiometers with GPS and VLBI Wet Zenith Path Delays

Monitoring of altimeter microwave radiometer measurements is necessary in order to identify radiometer drifts or offsets that if uncorrected will introduce systematic errors into ocean height measurements. To examine TOPEX Microwave Radiometer (TMR) and Jason-1 Microwave Radiometer (JMR) behavior, we have used coincident wet zenith delay estimates from Very Long Baseline Interferometry (VLBI) and Global Positioning System (GPS) geodetic sites near altimeter ground tracks. We derived a TMR path delay drift rate of -1.1 ± 0.1 mm/yr using GPS data for the period from 1993.0-1999.0 and -1.2 ± 0.5 mm/yr using VLBI data. Thereafter, the drift appears to have leveled off. Already after 2.3 years (82 cycles) of the Jason-1 mission, it is clear that there have been significant systematic errors in the JMR path delay measurements. From comparison with GPS wet delays, there is an offset of -5.2 ± 0.6 mm at about cycle 30 and a more abrupt offset of -11.5 ± 0.8 mm at cycle 69. If we look at the behavior of the JMR coldest brightness temperatures, we see that the offsets near cycle 30 and cycle 69 are mainly caused by corresponding offsets in the 23.8 GHz channel of -0.49 ± 0.12 K and -1.18 ± 0.13 K, although there is a small 34.0 GHz offset at cycle 69 of 0.75 ± 0.22 K. Drifts in the 18.0 and 34.0 GHz channels produce a small path delay drift of 0.3 ± 0.5 mm/yr.     

基于海面多普勒谱模型的海浪反演精度分析

Microwave remote sensing is one of the most useful methods for observing the ocean parameters. The Doppler frequency or interferometric phase of the radar echoes can be used for an ocean surface current speed retrieval,which is widely used in spaceborne and airborne radars. While the effect of the ocean currents and waves is interactional. It is impossible to retrieve the ocean surface current speed from Doppler frequency shift directly. In order to study the relationship between the ocean surface current speed and the Doppler frequency shift, a numerical ocean surface Doppler spectrum model is established and validated with a reference. The input parameters of ocean Doppler spectrum include an ocean wave elevation model, a directional distribution function, and wind speed and direction. The suitable ocean wave elevation spectrum and the directional distribution function are selected by comparing the ocean Doppler spectrum in C band with an empirical geophysical model function(CDOP). What is more, the error sensitivities of ocean surface current speed to the wind speed and direction are analyzed. All these simulations are in Ku band. The simulation results show that the ocean surface current speed error is sensitive to the wind speed and direction errors. With VV polarization, the ocean surface current speed error is about 0.15 m/s when the wind speed error is 2 m/s, and the ocean surface current speed error is smaller than 0.3 m/s when the wind direction error is within 20° in the cross wind direction.     

Monitoring the TOPEX and Jason-1 Microwave Radiometers with GPS and VLBI Wet Zenith Path Delays

Monitoring of altimeter microwave radiometer measurements is necessary in order to identify radiometer drifts or offsets that if uncorrected will introduce systematic errors into ocean height measurements. To examine TOPEX Microwave Radiometer (TMR) and Jason-1 Microwave Radiometer (JMR) behavior, we have used coincident wet zenith delay estimates from Very Long Baseline Interferometry (VLBI) and Global Positioning System (GPS) geodetic sites near altimeter ground tracks. We derived a TMR path delay drift rate of ?1.1 ± 0.1 mm/yr using GPS data for the period from 1993.0–1999.0 and ?1.2 ± 0.5 mm/yr using VLBI data. Thereafter, the drift appears to have leveled off. Already after 2.3 years (82 cycles) of the Jason-1 mission, it is clear that there have been significant systematic errors in the JMR path delay measurements. From comparison with GPS wet delays, there is an offset of ?5.2 ± 0.6 mm at about cycle 30 and a more abrupt offset of ?11.5 ± 0.8 mm at cycle 69. If we look at the behavior of the JMR coldest brightness temperatures, we see that the offsets near cycle 30 and cycle 69 are mainly caused by corresponding offsets in the 23.8 GHz channel of ?0.49 ± 0.12 K and ?1.18 ± 0.13 K, although there is a small 34.0 GHz offset at cycle 69 of 0.75 ± 0.22 K. Drifts in the 18.0 and 34.0 GHz channels produce a small path delay drift of 0.3 ± 0.5 mm/yr.     

HY-2 扫描辐射计风速数据产品与平台基观测数据的比较研究

基于南海北部PY30-1平台上2012年2月至9月测风仪观测的风速数据,开展了HY-2扫描辐射计风速数据比较研究。选取时空匹配窗口为5 min和25 km,利用HY-2扫描辐射计RM 100,70和35 km分辨率3种风速数据,分别与平台观测数据进行了比较。比较结果表明:在南海北部海域,HY-2扫描辐射计100 km分辨率风速和平台观测风速的均方根偏差为3.86 m/s;70 km分辨率风速和平台观测风速的均方根偏差为10.52 m/s;35 km分辨率风速和平台观测风速的均方根偏差为5.54 m/s。还进一步比较了有雨和无雨两种情况下HY-2扫描辐射计和平台数据的偏差,结果表明:有雨和无雨条件下都是100 km分辨率的数据偏差最小。这为在我国南海北部海域应用HY-2扫描辐射计的风速数据产品的选择提供了依据。     

An improved wind speed algorithm for “Jason-1” altimeter under tropical cyclone conditions

Rain effect and lack of in situ validation data are two main causes of tropical cyclone wind retrieval errors. The National Oceanic and Atmospheric Administration＇s Climate Prediction Center Morphing technique （CMORPH） rain rate is introduced to a match-up dataset and then put into a rain correction model to remove rain effects on ＂Jason-1＂ normalized radar cross section （NRCS）; Hurricane Research Division （HRD） wind sPeed, which integrates all available surface weather observations, is used to substitute in situ data for establishing this relationship with ＂Jason-l＂ NRCS. Then, an improved ＂Jason-l＂ wind retrieval algorithm under tropical cyclone conditions is proposed. Seven tropical cyclones from 2003 to 2010 are studied to validate the new algorithm. The experimental results indicate that the standard deviation of this algorithm at C-band and Ku-band is 1.99 and 2.75 m/s respectively, which is better than the existing algorithms. In addition, the C-band algorithm is more suitable for sea surface wind retrieval than Ku-band under tropical cyclone conditions.     

基于SAR图像雨团足印的海面风向提取方法

利用地球物理模式函数进行SAR海面风速反演时，需以风向作为地球物理模式函数的输入。本文应用了一种利用SAR图像上雨团足印顺风一侧比逆风一侧明亮的图像特征的海面风向提取方法，以进行海面风速反演。4景RADARSAT-2卫星SAR示例数据风向提取结果相对于ASCAT散射计的风向均方根误差满足不大于16°。分别以本文方法提取的风向和ASCAT散射计风向作为输入，利用地球物理模式函数CMOD5进行海面风速的SAR反演，两者的风速反演结果基本一致，其均方根误差差值不超过0.3 m/s。本文利用SAR图像雨团足印信息的风向提取方法准确可靠，可应用于SAR海面风速反演。     

Satellite-derived SST validation based on in-situ data during summer in the East China Sea and western North Pacific

Satellite-derived sea surface temperature (SST) is validated based on in-situ data from the East China Sea (ECS) and western North Pacific where most typhoons, which make landfall on the Korean peninsula, are formed and pass. While forecasting typhoons in terms of intensity and track, coupled ocean-typhoon models are significantly influenced by initial ocean condition. Potentially, satellite-derived SST is a very useful dataset to obtain initial ocean field because of its wide spatial coverage and high temporal resolution. In this study, satellite-derived SST from various sources such as Tropical Rainfall Measuring Mission Microwave Imager (TMI), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and New Generation Sea Surface Temperature for Open Ocean (NGSST-O) datasets from merged SSTs were compared with in-situ observation data using an indirect method which is using near surface temperature for validation of satellite derived SST. In-situ observation data included shipboard measurements such as Expendable Bathythermograph (XBT), and Conductivity, Temperature, Depth (CTD), and Argo buoy data. This study shows that in-situ data can be used for microwave derived SST validation because homogeneous features of seawater prevail at water depths of 2 m to 10 m under favorable wind conditions during the summer season in the East China Sea. As a result of validation, root-mean-square errors (RMSEs) are shown to be 0.55 °C between microwave SST and XBT/CTD data mostly under weak wind conditions, and 0.7 °C between XBT/CTD measurement and NGSST-O data. Microwave SST RMSE of 0.55 °C is a potentially valuable data source for general application. Change of SST before and after typhoon passing may imply strength of ocean mixing due to upwelling and turbulent mixing driven by the typhoon. Based on SST change, ocean mixing, driven by Typhoon Nari, was examined. Satellite-derived SST reveals a significant SST drop around the track immediately following the passing of Typhoon Nari in October, 2007.     

HY-2微波辐射计降雨条件下海面风速反演算法研究

由于降雨改变了海洋-大气的辐射/散射特性,长期以来星载遥感器在降雨条件下进行海面风速信息提取存在困难。本文针对自主海洋动力环境卫星海洋2号（HY-2）搭载的扫描微波辐射计,分析了不同频段亮温对降雨和海面风速敏感性,自此基础上获得了一种对降雨不敏感的亮温通道组合,该亮温通道组合对海面风速的敏感性甚至高于原有亮温通道。本文利用该亮温通道组合建立了降雨条件下的风速反演算法,并将反演结果与WindSat全天候风速产品、HY-2微波辐射计原有风速产品以及浮标实测数据进行了比较。结果表明本文算法在降雨条件下的反演误差小于2m/s,明显优于原有HY-2微波辐射计风速产品,验证了本文发展的算法在降雨条件下的风速反演能力。     

Assessment of the Jason Microwave Radiometer's Measurement of Wet Tropospheric Path Delay Using Comparisons to SSM/I and TMI

The Jason microwave radiometer (JMR) provides a crucial correction due to water vapor in the troposphere, and a much smaller correction due to liquid water, to the travel time of the Jason-1 altimeter radar pulse. An error of any size in the radiometer's measurement of wet path delay translates as an error of equal size in the measurement of sea surface height, the ultimate quantity that the altimetric system should yield. The estimate of globally-averaged sea surface height change associated with climate change, requires that uncertainties in the trends in such a global average be accurate to much better than the signal of 1-2 mm/yr. We first compare the JMR observations to those from the TOPEX/Poseidon radiometer (TMR) over approximately six months, since the intent of Jason is to continue the 10-year time series of precision ocean surface topography initiated by T/P. We then assess the stability of the JMR measurement by comparing its wet path delay to those of other orbiting radiometers over 22 months, specifically the Special Sensor Microwave Imager aboard the Defense Meteorological Satellite Program (DMSP-SSM/I) series of satellites, and the Tropical Rainfall Mapping Mission's Microwave Imager (TMI), as well as the European Center for Medium Range Weather Forecasting's (ECMWF) atmospheric numerical model estimate of water vapor. From the combined set, we obtain a robust assessment of the stability of JMR measurements. We find, that JMR is in remarkable agreement with TMR, only 2.5 mm longer, and 6-7 mm standard deviation on their difference in 0.5 degree averages; that JMR has experienced a globally-averaged step-function change, yielding an apparent shortening in wet path delay estimates of 4-5 mm around October 2002 (Jason cycles 28-32); that this step-function is visible only in the 23.8 GHz channel; and that the 34 GHz channel appears to drift at a rate of -0.4K/year. In addition, we find that, while in 2002 there was no evidence of sensitivity to the Jason satellite's attitude (a correlation of the wet path delay with yaw state), in 2003 there are strong (2-3 mm, up to 7 mm globally averaged) changes associated with such yaw state. These JMR issues were all found in the first 22 months of Jason's geophysical data records (GDR) data, and thus they apply to any investigations that use such data without further corrections.     

Assessment of the Jason Microwave Radiometer's Measurement of Wet Tropospheric Path Delay Using Comparisons to SSM/I and TMI

The Jason microwave radiometer (JMR) provides a crucial correction due to water vapor in the troposphere, and a much smaller correction due to liquid water, to the travel time of the Jason-1 altimeter radar pulse. An error of any size in the radiometer's measurement of wet path delay translates as an error of equal size in the measurement of sea surface height, the ultimate quantity that the altimetric system should yield. The estimate of globally-averaged sea surface height change associated with climate change, requires that uncertainties in the trends in such a global average be accurate to much better than the signal of 1–2 mm/yr. We first compare the JMR observations to those from the TOPEX/Poseidon radiometer (TMR) over approximately six months, since the intent of Jason is to continue the 10-year time series of precision ocean surface topography initiated by T/P. We then assess the stability of the JMR measurement by comparing its wet path delay to those of other orbiting radiometers over 22 months, specifically the Special Sensor Microwave Imager aboard the Defense Meteorological Satellite Program (DMSP-SSM/I) series of satellites, and the Tropical Rainfall Mapping Mission's Microwave Imager (TMI), as well as the European Center for Medium Range Weather Forecasting's (ECMWF) atmospheric numerical model estimate of water vapor. From the combined set, we obtain a robust assessment of the stability of JMR measurements. We find, that JMR is in remarkable agreement with TMR, only 2.5 mm longer, and 6–7 mm standard deviation on their difference in 0.5 degree averages; that JMR has experienced a globally-averaged step-function change, yielding an apparent shortening in wet path delay estimates of 4–5 mm around October 2002 (Jason cycles 28–32); that this step-function is visible only in the 23.8 GHz channel; and that the 34 GHz channel appears to drift at a rate of ?0.4K/year. In addition, we find that, while in 2002 there was no evidence of sensitivity to the Jason satellite's attitude (a correlation of the wet path delay with yaw state), in 2003 there are strong (2–3 mm, up to 7 mm globally averaged) changes associated with such yaw state. These JMR issues were all found in the first 22 months of Jason's geophysical data records (GDR) data, and thus they apply to any investigations that use such data without further corrections.     

Assessing the global averaged sea-level budget from 2003 to 2010

A global mass balance （Greenland and Antarctica ice sheet mass loss, terrestrial water storage） and differ- ent sea-level components （observed sea-level from satellite altimetry, steric sea-level from Ishii data, and ocean mass from gravity recovery and climate experiment, GRACE） are estimated, in terms of seasonal and interannual variabilities from 2003 to 2010. The results show that a detailed analysis of the GRACE time series over the time period 2003-2010 unambiguously reveals an increase in mass loss from the Greenland ice sheet and Antarctica ice sheet. The mass loss of both ice sheets accelerated at a rate of （392.8±70.0） Gt/a during 2003-2010, which contributed （1.09±0.19） mm/a to the global mean sea-level during this time. The net terrestrial water storage （TWS） trend was negative over the 8 a time span, which gave a small positive contribution of （0.25±0.12） mm/a. The interannual variability of the global mean sea-level was at least part- ly caused by year-to-year variability of land water storage. Estimating GRACE-based ice sheet mass balance and terrestrial water storage by using published estimates for melting glaciers, the results further show that the ocean mass increase since 2003 has resulted half from an enhanced contribution of the polar ice sheets, and half from the combined ice sheet and terrestrial water storage loss. Taking also into account the melt- ing of mountain glaciers （0.41 mm/a） and the small GRACE-based contribution from continental waters （0.25 mm/a）, a total ocean mass contribution of （1.75±0.57） mm/a from 2003 to 2010 is found. Such a value represented 75% of the altimetry-based rate of sea-level rise over that period. The contributions to steric sea-level （i.e., ocean thermal expansion plus salinity effects） are estimated from： （1） the difference between altimetry-based sea-level and ocean mass change and （2） the latest Ishii data. The inferred steric sea-level rate from （1） （1.41 mm/a from 2003 to 2010） did not agree well with the Ishii-based value also estimated here （0.44 mm/a from 2003 to 2010）, but phase. The cause for such a discrepancy is not yet known but may be related to inadequate sampling of in situ ocean temperature and salinity measurements.     

一种基于Envisat ASAR波模式数据的有效波高反演算法

The main objective of this paper is to propose a newly developed ocean Significant Wave Height(SWH) retrieval method from Envisat Advanced Synthetic Aperture Radar(ASAR) imagery. A series of wave mode imagery from January, April and May of 2011 are collocated with ERA-Interim reanalysis SWH data. Based on the matched datasets, a simplified empirical relationship between 22 types of SAR imagery parameters and SWH products is developed with the Genetic Algorithms Partial Least-Squares(GA-PLS) model. Two major features of the backscattering coefficient σ_0 and the frequency parameter S_(10) are chosen as the optimal training feature subset of SWH retrieval by using cross validation. In addition, we also present a comparison of the retrieval results of the simplified empirical relationship with the collocated ERA-Interim data. The results show that the assessment index of the correlation coefficient, the bias, the root-mean-square error of cross validation(RMSECV) and the scattering index(SI) are 0.78, 0.07 m, 0.76 m and 0.5, respectively. In addition, the comparison of the retrieved SWH data between our simplifying model and the Jason-2 radar altimeter data is proposed in our study.Moreover, we also make a comparison of the retrieval of SWH data between our developed model and the wellknown CWAVE_ENV model. The results show that satisfying retrieval results are acquired in the low-moderate sea state, but major bias appears in the high sea state, especially for SWH5 m.     

FY-3A/MERSI, ocean color algorithm, products and demonstrative applications

A medium resolution spectral imager (MERSI) on-board the first spacecraft of the second generation of China’s polar-orbit meteorological satellites FY-3A, is a MODIS-like sensor with 20 bands covering visible to thermal infrared spectral region. FY-3A/MERSI is capable of making continuous global observations, and ocean color application is one of its main targets. The objective is to provide information about the ocean color products of FY-3A/MERSI, including sensor calibration, ocean color algorithms, ocean color products validation and applications. Although there is a visible on-board calibration device, it cannot realize the on-board absolute radiometric calibration in the reflective solar bands. A multisite vicarious calibration method is developed, and used for monitoring the in-flight response change and providing post-launch calibration coefficients updating. FY-3A/MERSI ocean color products consist of the water-leaving reflectance retrieved from an atmospheric correction algorithm, a chlorophyll a concentration (CHL1) and a pigment concentration (PIG1) from global empirical models, the chlorophyll a concentration (CHL2), a total suspended mater concentration (TSM) and the absorption coefficient of CDOM and NAP (YS443) from China’s regional empirical models. The atmospheric correction algorithm based on lookup tables and ocean color components concentration estimation models are described. By comparison with in situ data, the FY-3A/MERSI ocean color products have been validated and preliminary results are presented. Some successful ocean color applications such as algae bloom monitoring and coastal suspended sediment variation have demonstrated the usefulness of FY-3A/MERSI ocean color products.     

Assessing the Measurement Consistency Between the Jason-2/AMR and SARAL/AltiKa/DFMR Microwave Radiometers Using Simultaneous Nadir Observations

SARAL/AltiKa has a Dual Frequency Microwave Radiometer (DFMR), and Jason-2 has an Advanced Microwave Radiometer (AMR). Both microwave radiometer sensors include a 23.8 GHz primary water sensing channel. The measurement consistencies between DFMR and AMR are important for establishing a consistent altimetry data set between SARAL/AltiKa and Jason-2 in order to accurately assess sea level rise in a long-term time series. This study investigates the measurement consistency in the 23.8 GHz channel between DFMR and AMR at the Simultaneous Nadir Overpasses (SNO's) between the two satellites and also at coldest ocean brightness temperature locations. Preliminary results show that while both instruments show no significant trends over the one year since the launch of SARAL, a consistent relative bias of 2.88 K (DFMR higher than AMR) with a standard deviation of 0.98 K is observed. The relative bias at the lowest brightness temperature from the SNO method (-3.82 K) is consistent with that calculated from coldest ocean method (-3.74 K). The relative bias exhibits strong latitude (and scene temperature) dependency, changing from -3.82 K at high latitudes to -0.92 K near the equator. There also exists an asymmetry between the northern and southern hemisphere. The relative bias increases toward the lower end of brightness temperature.     

降雨条件下的导航X波段雷达海浪参数反演算法研究

X波段的电磁波受降雨影响容易产生衰减,这导致导航X波段雷达在降雨时无法用于海浪观测。本文提出了一种新的降低降雨影响的算法来反演海浪参数。首先,对X波段雷达图像做主成分分析,获得波浪变化的主成分,利用一维傅里叶变换得到波数谱,对其滤波减小降雨对雷达图像的影响;然后,选取JONSWAP(Joint North Sea Wave Project)谱作为理论谱,建立以观测谱与理论谱的最小化差异为目标函数的模型,求解该模型估算海浪的有效波高。与浮标测量的有效波高相比,该方法反演的有效波高的均方根误差是0.23 m,证明了该方法的可行性。     

Influence of temperature on the physiological responses of the bivalve Brachidontes striatulus and its significance in fouling control.

Heat treatment offers an alternative method of fouling control to chlorination in power plants. In order to optimise such a procedure it is important to understand the responses of fouling organisms to elevated water temperatures. In this paper we report results of experiments on the lethal and sub-lethal effects of temperature on the bivalve Brachidontes striatulus which is one of the major foulants in the process seawater heat exchangers of Madras Atomic Power Station located at Kalpakkam, on the east coast of India. The important physiological activities, such as, oxygen consumption, filtration rate, byssus thread production and faecal matter production were studied at temperatures varying from 20 to 38 degrees C. Three different size groups [3-5 mm shell length (group 1), 6-10 mm (group 2), 11-15 mm (group 3)] of B. striatulus were used for the experiments. The results showed physiological activities were maximum at 35 degrees C, minimum at 20 and 38 degrees C. Physiological activities increased with size except for byssus thread production, which did not show any trend. Survival times showed a reduction from 30 h at 39 degrees C to < 1 h at 45 degrees C and were independent of body size.     

Variability of suspended particulate matter in the Bohai Sea from the geostationary Ocean Color Imager (GOCI)

This study assesses the performance of the Geostationary Ocean Imager (GOCI) for mapping of suspended particulate matter in the Bohai Sea, a turbid water region. GOCI imagery for remote sensing reflectance and Total Suspended Solids (TSS) is analysed in detail for two days in June 2011 (8 images per day). Both instantaneous and daily composite maps are considered and a comparison is made with corresponding reflectance and TSS products from MODIS-AQUA. Results show TSS distributions corresponding to previous studies of the region. The advantage of the higher acquisition frequency (8 images/day instead of 1) offered by GOCI is clearly demonstrated in the daily composite which is more complete during this period of scattered but moving clouds. Consideration of temporal variation over the day indicates low natural variability but some artificial variability from processing errors ?? this analysis provides a first indication of how the higher frequency of data from geostationary ocean colour could lead to improved data quality control via temporal coherency outlier detection. While there is room for improvement on the GOCI calibration, atmospheric correction and retrieval algorithms, the current study suggests that the GOCI data can already be used now to study qualitatively sediment dynamics except in the extremely turbid waters which are masked out of the current dataset. In a wider context, it is considered that the technical challenges of geostationary ocean colour have been met by the GOCI concept, and, notwithstanding potential improvements on the concept and data processing methods, it is recommended that this mission serve as a model for future geostationary ocean colour sensors over Europe/Africa and the Americas.