Using sentinel-1A SAR wind retrievals for enhancing scatterometer and radiometer regional wind analyses

Scatterometer surface wind speed and direction observations in combination with radiometer wind speeds allow to generate surface wind analyses with high space and time resolutions over global as well as at regional scales. Regarding scatterometer sampling schemes and physics, the resulting surface wind analyses suffer from lack of accuracy in areas near coasts. The use of the synthetic aperture radar (SAR) onboard the Sentinel-1A satellite attempts to address the enhancement of surface wind analyses issues. In this study, SAR wind speeds and directions retrieved from backscatter coefficients acquired in interferometric wide (IW) swath mode are used. Their accuracy is determined through comprehensive comparisons with moored buoy wind measurements. SAR and buoy winds agree well at offshore and nearshore locations. The statistics characterizing the comparison of SAR and buoy wind speeds and directions are of the same order as those obtained from scatterometer (Advanced SCATterometer (ASCAT) and RapidScat) and buoy wind comparisons. The main discrepancy between SAR and buoy data are found for high wind speeds. SAR wind speeds exceeding 10 m s^–1 tend to be underestimated. A similar conclusion is drawn from SAR and scatterometer wind speed comparisons. It is based on the underestimation of SAR backscatter coefficient (σ°) with respect to σ° estimated from scatterometer winds and the geophysical model function (GMF) named CMOD-IFR2 (Ifremer C band MODel). New SAR wind speeds are retrieved using CMOD-IFR2. The corrected SAR retrievals allow better determination of the spatial characteristics of surface wind speeds and of the related wind components in near-coast areas. They are used for enhancing the determination of the spatial structure function required for the estimation of wind fields gridded in space and time at the regional scale. The resulting wind fields are only determined from scatterometer wind observations in combination with radiometer retrievals. Their qualities are determined through comparisons with SAR wind speeds and directions, and through their application for determination of wind power off Brittany coasts.     

Comparison of Oceansat-2 scatterometer- to buoy-recorded winds and spatial distribution over the Arabian Sea during the monsoon period

For this wind resource assessment (WRA) study, wind speed and direction are the fundamental inputs. Also, these studies are data driven and require large historical wind speed data sets available on the site. This work explores the application of space-based scatterometer winds for assimilation into WRA studies towards the development of offshore wind energy. This article focuses on estimating the performance of Oceansat-2 scatterometer (OSCAT)-derived wind vector using in situ data from buoys at different locations in the Arabian Sea. A comparative study between three methods for estimating the equivalent neutral winds (ENW) for buoys is carried out. OSCAT winds were closest to ENW estimated by the Liu–Katsaros–Businger (LKB) method. The spatial and temporal windows for comparison were 0.5° and ±60 minutes, respectively. The monsoon months (June–September) of 2011 were selected for study. The root mean square deviation for wind speed is less than 2.5 m s^?1 and wind direction is less than 20°, and a small positive bias is observed in the OSCAT wind values. From the analysis, the OSCAT wind values are consistent with in situ-observed values. Furthermore, wind atlas maps were developed with OSCAT winds, representing the spatial distribution of winds at a height of 10 m over the Arabian Sea.     

Global structure of marine wind speed variability derived from TOPEX altimeter data

As the largest source of momentum for the ocean surface, wind affects the full range of oceanic motion—from individual surface waves to complete current systems. The marine surface wind is among the critical geophysical parameters which determine the most fundamental aspects of the ocean. Using six years (1993–1998) of TOPEX altimeter data with an unprecedented accuracy and continuity, a detailed investigation of the global structure of marine wind climatology and variability is carried out. It is found that the overall pattern of wind climatology is basically determined by solar radiation and therefore dominated by zonal features, while that of the wind variability is largely ‘event’ determined and thereby dominated by regional features. Consequently, wind climatology and wind variability show a complex relationship in their magnitude of intensity. Strong winds may be associated with high variabilities, such as in the westerlies of the North Atlantic and North Pacific; they may also be associated with low variabilities, such as in the westerlies of the Southern Ocean. Meanwhile, weak wind zones like the doldrums in the western equatorial Pacific can have a very low level of annual variability, while a very high level of interannual variability. The Asian monsoon system has a lower than average climatological mean speed, but exhibits extremely high annual variability. The phase distributions of wind variations carry combined information of climatology and variability. Effects of the Asian monsoon and marine storms are manifested on top of the basically zonal phase pattern. Statistics suggest that semiannual variability exceeds annual variability for 12.2% of the world's oceans, and interannual variability exceeds annual variability for 26.4% of the world's oceans.     

Response of Vietnam coastal upwelling to the 1997-1998 ENSO event observed by multisensor data

In this paper, we examine the behavior of the Vietnam coastal upwelling during the 1997-1998 El Niño-Southern Oscillation (ENSO) event. The baseline is 4 years of National Oceanic and Atmospheric Administration (NOAA) satellite Advanced Very High Resolution Radiometer (AVHRR) sea surface temperature (SST) data taken from 1997 to 2000. Comparison of upwelling images to simultaneous ERS-2 (European Remote Sensing Satellite) wind fields indicates that the summer monsoon winds constitute a major generation forcing. During the 1997 El Niño, the monsoon winds enhanced the upwelling and induced the upwelling center to move southward. During the 1998 La Niña, the monsoon winds weakened the upwelling. In contrast with the tropical Pacific, in the study area, La Niña implies a warm event and El Niño a cold event. We use empirical orthogonal function (EOF) methods to analyze the spatial and temporal variance of the upwelling. The three principal modes account for 37%, 15%, and 8% of the total variance, respectively. The first EOF modes reveal that the SST variance in the north and south subregions underwent a positive-negative sign switch in summer 1997. The second EOF modes represent the monthly evolution in normal years. The third modes seem to be sensitive to the 1998 La Niña event. Simultaneous TOPEX/POSEIDON and ERS-2 altimeter data provide further evidence for our analysis. Comparison with California coastal upwelling and mid-Atlantic Bight (MAB) coastal upwelling indicates that the Vietnam coastal upwelling is the most intensive one.     

Impact of sub-daily wind forcing on mixed-layer depth and sea surface temperature: study using observations and a one-dimensional upper ocean model

The impact of sub-daily wind sampling on the diurnal cycle of oceanic mixed-layer depth (MLD) and sea surface temperature (SST) is investigated using a one-dimensional upper ocean model and observations at two locations: the Central Arabian Sea (CAS) and Eastern Equatorial Indian Ocean (EEIO). Motivation to carry out this study is twofold: first, it will help in understanding the possible error in model-simulated MLD and SST due to the non-inclusion of high-temporal wind sampling; and second, it will also emphasize the requirements of temporal sampling from space-based measurements of surface winds. Temporal decorrelation analysis suggests that over a 24-hour period, auto-correlation falls rapidly in the EEIO region, whereas the fall is less even at a lag of 24 hours in CAS. Time series analysis with different sub-daily sampling rates suggests that the optimum sampling rate is three hours for MLD and SST. A suite of one-dimensional model simulations performed at the CAS and EEIO locations with sub-daily wind suggests that once-daily synoptic measurements of wind, which is the most likely scenario with one scatterometer, results in small biases but large standard deviations in MLD. In the case of SST, there is a small positive bias in the order of 0.1°C at the CAS buoy location while at the EEIO location, no such bias is observed. With two scatterometers in a constellation resulting in two observations per day, one can obtain a small standard deviation in MLD, but the bias is greater in this case. For SST, except for a small bias (about 0.1°C) at the CAS location, the distribution is mostly well-behaved Gaussian in all cases. The present study suggests the advisability of acquiring more frequent wind measurements from space-borne scatterometers. A well-coordinated satellite scatterometer constellation will help in resolving the diurnal variability and associated feedback mechanism of air–sea exchange processes, enhancing the understanding of large-scale phenomena such as the Indian summer monsoon, El Niño-southern oscillations, and the Madden–Julian oscillation.     

卫星遥感海面风场的进展

空间技术的发展使得卫星遥感成为获取海面风速信息的重要手段。对卫星微波遥感海面风场的各种传感器的性能、特点等作了较全面地评述,并指出了卫星微波遥感信息的复合分析和数值同化将是获取海面风场的两个主要方法。     

Interannual variability of NDVI over Africa and its relation to El Niño/Southern Oscillation

The array of Normalized Difference Vegetation Index (NDVI) products now being derived from satellite imagery open up new opportunities for the study of short and long-term variability in climate. Using a time series analysis procedure based on the Principal Components transform, and a sequence of monthly Advanced Very High Resolution Radiometer (AVHRR)-derived NDVI imagery from 1986 through 1990, we examine trends in variability of vegetation greenness for Africa for evidence of climatic trends. In addition to the anticipated seasonal trends, we identify signals of interannual variability. The most readily identified is one that periodically affects Southern Africa. It is shown that the temporal loadings for this component exhibit a very strong relationship with the El Nino/Southern Oscillation (ENSO) Index derived from atmospheric pressure patterns in the Pacific, Pacific sea surface temperature (SST) anomalies, and with anomalous Outgoing Longwave Radiation (OLR). However, we have also detected a second interannual variation, affecting most particularly East Africa and the Sahel, that does not exhibit a consistent ENSO relationship. The results show the teleconnection patterns between climatic conditions in the Pacific Ocean basin and vegetation conditions at specific regional locations over Africa. The comprehensive spatial character and high temporal resolution of these data offer exciting prospects for deriving a land surface index of ENSO and mapping the impacts of ENSO activity at continental scale. This study illustrates that vegetation reflectance data derived from polar orbiting satellites can serve as good proxy for the study of interannual climate variability.     

Interannual variability of cirrus clouds in the tropics in El Niño Southern Oscillation (ENSO) regions based on International Satellite Cloud Climatology Project (ISCCP) satellite data

The percentage of the interannual variance of cirrus clouds, explained by the variability of the El Niño Southern Oscillation (ENSO), the Quasi-biennial Oscillation (QBO) and solar activity over the tropics, is presented in this article. Analysis is focused on the eastern and western tropical Pacific Ocean, which is strongly affected by the ENSO. It is shown that over the eastern tropical Pacific Ocean, the amplitude of the ENSO in cirrus-cloud cover (CCC) is about 8.0%. The amplitude of the annual cycle is about 0.8% and the amplitudes of the QBO, solar cycle and long-term trends are the order of 1.0%, 0.1% and 0.3%, respectively. Using as an index of convective activity in the upper troposphere the vertical velocities at 300 hPa, we have calculated a vertical velocity related to cloud component. It is shown that the total contribution, from all related cloud components examined explains about 65% of the variance in cirrus clouds over the eastern Pacific and about 50% of the variance in cirrus clouds over its western part.     

Interannual variability of chlorophyll-a concentration along the southwest coast of India

The interannual variability of chlorophyll concentration along the southwest coast of India is studied using remote-sensing data from SeaWiFS. The data are analysed in conjunction with satellite-measured sea surface winds. The satellite-measured chlorophyll data for a period of 10 years from 1998 to 2007 were made use of for indexing the maximum offshore extent of chlorophyll along the coast for each month. From the empirical orthogonal functional analysis of chlorophyll data, it is observed that the dominant mode is annual. Interestingly, intraseasonal variability and the influence of climatic events like El Niño are observed in the secondary principle component of the time series. The variability of chlorophyll coincided well with variability of Ekman transport all along the coast with higher chlorophyll (>1 mg m^?3) when the Ekman transport is greater than 1000 kg/m/s. During the years 2005–2007, reduction in the meridional (along shore) component of wind resulted in reduction of Ekman transport, the phenomenon which leads to a decrease in chlorophyll. This is due to the reduction in the amount of nutrients that entrained to surface layers during upwelling of the southwest monsoon. The chlorophyll-a is minimum when Ekman transport is less than 0.5 kg/m/s on the normalized scale. For higher values of chlorophyll, the Ekman transport is higher, indicating the contribution of wind in enhancing the already upwelled chlorophyll production. The smaller value of R ² infers that there exist other forces as well involved in augmenting the surface chlorophyll. The enhanced knowledge on the offshore extent and the intraseasonal and interannual variability of chlorophyll can provide valuable inputs on fisheries and primary productivity for this region.     

The relationship between tibetan snow depth,ENSO, river discharge and the monsoons of Bangladesh

Using satellite estimates of snow depth, we examine the interannual variability of the monsoon rains of Bangladesh, an area greatly affected by land surface hydrological processes including Himalayan snowpack size, snowmelt river flooding, and Bay of Bengal storm surge. For the twentieth century, we found Bangladesh monsoon rainfall (BMR) to be uncorrelated with the All‐Indian Monsoon Index. This result is consistent with previous findings for shorter time records. We next used a short 9‐year record of satellite estimates of April snow depth for the Himalayan region and concurrent seasonal El Niño–Southern Oscillation (ENSO) conditions in the equatorial Pacific to develop an empirical model that explains a high percentage of BMR interannual variability. Inclusion of late spring river discharge levels further improves the empirical model representation of BMR for June–September. These results, though with a limited length satellite record, suggest that BMR interannual variability is constrained by concurrent ENSO conditions, spring Himalayan snowpack size and land surface flooding. The same results could not be obtained from analyses using satellite estimates of snow cover. These findings stress the need for development of a quality longer record of satellite estimated snow depth. The twentieth‐century analysis also indicates that BMR should be considered independently of Indian monsoon rainfall.     

Aerosol optical depth variability over the southeastern Arabian Sea

Aerosol optical depth (AOD), an index of aerosol concentration, is used to study atmospheric features. Accordingly, spatiotemporal variability of AOD in the atmospheric column over the southeastern Arabian Sea (SEAS) is investigated utilizing monthly data obtained from both the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), from September 1997 to December 2010, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Aqua, from July 2002 to December 2010. A comparison between the data from both sensors showed similar averages (~0.13), but with different standard deviations (0.03 and 0.02) over the SEAS. The AOD distribution was found to be dominated by an annual cycle controlled by the monsoon climate, with maximum aerosol concentration during July/August (~0.2) and minimum during November/December (<0.1). Empirical mode decomposition (EMD) analysis revealed the influence of the Quasi-Biennial Oscillation (QBO) and El Niño Southern Oscillation (ENSO) in producing inter-annual variability of 2% and 1%, respectively. Simulated backwards trajectories of aerosols, using Hybrid Single-Particle Lagrangian Integrated Trajectory models, indicated two main remote sources, i.e. sea salt from the Arabian Sea and dust particles from the Arabian Peninsula are the key factors contributing to an increase in the concentration of aerosols over the study area during the southwest monsoon period, irrespective of the opposing phases of QBO.     

Calculation of the sensible heat flux of the global ocean using satellite data

The sensible heat flux of the global ocean is derived using satellite data of Special Sensor Microwave/Imager (SSM/I) precipitable water, Advanced Very High Resolution Radiometer (AVHRR) sea-surface temperature (SST) and scatterometer wind speed. Prior to heat flux derivation, the air temperature over the sea surface in the global ocean is obtained with an iterative solving technique applied to a simplified equation that specifies the relationship among boundary-layer parameters. It is found that a bias exists between the calculated air temperature and the climatology data, which is corrected by a linear model based on the climatology of air temperature. Using the corrected air temperature and the bulk formula, we calculate the sensible heat flux from January 1992 to October 1998. The heat flux calculation is consistent with previous results. An error analysis suggests that based on the bulk formula, the uncertainty caused by the air temperature is comparable with the error components from the SST and wind. Empirical orthogonal function (EOF) analysis is used to extract the temporal and spatial characteristics of the calculated sensible heat flux. The first EOF is characterized by a winter and summer oscillation with an annual cycle, the second shows another annual cycle in spring and autumn oscillation, the third EOF is related to the El Niño and La Niña cycle, reflecting a certain relationship between El Niño Southern Oscillation (ENSO) events and the global ocean sensible heat flux, and the fourth EOF indicates an increasing trend with a quasi-biennial oscillation and atmospheric influences.     

Spatio-temporal variability of surface chlorophyll-a in the Halmahera Sea and its relation to ENSO and the Indian Ocean Dipole

ABSTRACT

Long-term satellite data are used to investigate the variability of ocean surface chlorophyll-a (chl-a) concentration in the Halmahera Sea (HS) under influence of the Australian-Indonesian Monsoon (AIM), the El Niño-Southern Oscillation (ENSO), and the Indian Ocean Dipole (IOD). In this study, we first analysed the seasonal variability of chl-a, and then examine the relationship between surface chl-a, sea surface temperature (SST), and sea surface wind stress in the area. Our results suggest that prevailing southeasterly winds play a fundamental role in generating chl-a blooms in the HS. Particularly on a seasonal timescale, through the mechanism of Ekman mass transport, strengthening of southeasterly wind stress during the Southeast Monsoon season (June – August) produces enhanced chl-a concentrations associated with ocean surface cooling in the area of study. On the other hand, the chl-a bloom completely diminishes during the Northwest Monsoon season (December – February) due to weakening of wind stress and Ekman transport. On an interannual timescale, sea level pressure and wind stress are coherent with ENSO and IOD phases. During El Niño and positive IOD events (La Niña and negative IOD events), both sea level pressure and wind stress greatly increase (decrease) over the HS. These conditions cause an anomaly in southerly (northerly) wind stress, which is favourable to an enhancement (reduction) of the chl-a concentration in the region. This study demonstrates that sea level pressure and wind stress are the critical factors in determining the magnitude of chl-a bloom in the HS.     

Fusion of sea surface wind vector data acquired by multi-source active and passive sensors in China sea

This work is the first to analyse the sea surface wind vector (SSWV) data acquisition capabilities of eight satellites carrying microwave scatterometer (scanning scatterometer carried by Haiyang satellite 2A, advanced scatterometer carried by Metop satellite A, advanced scatterometer carried by Metop satellite B and scanning scatterometer carried by Oceansat satellite 2) or radiometers (Special Sensor Microwave Imager carried by Meteorological Satellite Program satellites F15 and F17, advanced microwave scanning radiometer 2 carried by GCOM-W1 satellite, and windsat polarimetric radiometer carried by Coriolis satellite) and investigate a SSWV fusion algorithm for active and passive remote-sensing data. We found that combining observations of the eight satellites can provide an SSWV data product with spatial resolution of 25 km × 25 km and temporal resolution of 3 h. Sea surface wind speed and direction data were obtained from multi-source active and passive sensors using a spatiotemporally weighted fusion algorithm. An adaptive sliding window was introduced for calculating effective observation data within spatial/temporal radii, which can effectively improve calculation efficiency for wind field fusion. Comparing the fused and buoy observation results, the root-mean-square errors of the wind direction and speed were 20.6° and 1.2 m s^–1, respectively, indicating that the fusion results can meet most application requirements for wind vector. Meanwhile, the space coverage, accuracy of merged wind speed and wind direction can be improved comparing to a single sensor.     

Regional accuracy of QuikSCAT gridded winds

The quality of gridded 00 UTC and 12 UTC QuikSCAT wind speed fields provided by the Florida State University (FSU) and NASA Jet Propulsion Laboratory (JPL) are analysed over the Bay of Bengal during May–August 2001. Additionally, an examination of these fields is performed over the Gulf of Mexico for the May–August period from 2001 to 2003. Both 00 UTC and 12 UTC time almost coincide with QuikSCAT sampling times (twice a day) and correspond to either early morning or late evening local time over these regions. The primary restriction for generating accurate maps with a temporal resolution of 12 hours and less is a lack of adequate sampling. Due to non‐uniform spatial‐temporal sampling of the scatterometer, interpolation procedures cannot provide proper estimates in data gaps over the regions not covered by a swath. Wind speed autocorrelation coefficients for gridded datasets have been compared with that of original QuikSCAT data and buoy winds. It is shown that the spatial and temporal interpolation used to obtain these datasets results in smoothing of the QuikSCAT wind speeds, reducing their original variance. This smoothing is amplified where substantial diurnal wind variability occurs. A comparison with buoy data shows that FSU and JPL gridded fields are unable to reproduce correctly observed low correlations in wind speed between morning and evening breeze flows and diurnal variability of winds, leading to a reduced difference between 00 UTC and 12 UTC values in comparison with buoys and swath QuikSCAT data. Rather, the FSU and JPL maps describe daily mean fields. Another consequence of the spatial‐temporal interpolation is that the winds are distorted at a frequency matching the dominant sampling interval (3–4 days) of QuikSCAT measurements over the Bay of Bengal.     

Remote sensing of the Indo-Pacific region: ocean colour,sea level,winds and sea surface temperatures

The 1997–1998 ENSO (El Niño-Southern Oscillation) was not only the largest event of the century but also the most comprehensively observed. Satellite data were employed for ocean colour, sea level, winds, sea surface temperature (SST), and outgoing longwave radiation (OLR) were used to describe the response of the surface marine ecosystem associated with the ENSO event. Some of the large-scale anomalies in ocean colour include elevated biological activity to the north of the Equator in the Pacific coincident with lower sea levels associated with the classic ENSO-horseshoe pattern ecosystem response to the anomalous upwelling in the eastern Indian Ocean caused by the 1997–1998 dipole event, and the dramatic eastward propagating feature in the Equatorial Pacific in response to the La Niña dynamics. Ocean general circulation model (OGCM) experiments show that capturing the high-frequency wind changes is crucial for simulating the La Niña and the coupled biological–physical model (OBGCM) runs clearly show that higher frequency winds are also important for capturing the mean upwelling and nutrient supply into the euphotic zone. Thus, the QuickSCAT winds are expected to play a major role in ecosystem modelling in the future. This study shows the utility of satellite data for understanding not only ocean circulation but also the coupled ecosystem variability. Morcover, it is also shown that spatio-temporal resolution of the satellite winds will directly affect the accuracy of oceanic and ecosystem simulations.     

RFSCAT散射计数据地理定位与误差分析

星载微波散射计是目前唯一能够同时测量海面风速和风向的传感器,在海洋科学研究中发挥着重要作用。散射计获取的地物后向散射只有经过地理定位才能得到包含地物位置信息的有效物理量。因此,散射计地理定位是数据预处理的重要组成部分,与遥感数据的质量密切相关。扇形波束旋转扫描散射计具备扇形固定波束散射计和笔形波束旋转扫描散射计的优势,目前还没有实现在轨运行。基于其工作方式的特殊性,详细分析了该散射计的扫描方式,给出了一种适用于该散射计的地理定位方法,得到了最终的定位结果。然后分析了影响定位结果的误差源,讨论了卫星姿态对于定位结果的影响情况,最终利用HY\|2卫星产品评价了该地理定位算法的相对精度指标。     

Interannual variability of Ulva prolifera blooms in the Yellow Sea

A massive Ulva prolifera bloom occurred in the Yellow Sea in 2008. Since then, green tide events have occurred every year and two other massive bloom events occurred in 2009 and 2013. In this article, we investigate the spatial and temporal patterns of U. prolifera green tides in the Yellow Sea during 2007–2013 using satellite images from operational MODIS instruments on board the Terra and Aqua satellites. Satellite sea surface temperature (SST) data and sea surface wind products were analysed to study their impacts on the occurrence and evolution of the floating macroalgae. Results show that the U. prolifera blooms were most likely caused by the rapid expansion of coastal Porphyra aquaculture in Jiangsu province, China. The SST was not a controlling factor influencing the size of the algal bloom or determining the blooming time. Surface wind played a significant role on the movement and distribution of the floating macroalgae, which causes an interannual variability in the spatial and temporal patterns of the U. prolifera blooms. The weak connection between the increase in Porphyra aquaculture and the size of the bloom implies that there must have been a nutrient supplier (or suppliers) for the extensive growth of the macroalgae in 2008, 2009, and 2013. The tide-induced upwelling between the Subei Bank and the western-central Yellow Sea seems to be a nutrient source.     

Sea surface temperature variability off north-west Africa: 1981-1989

A temporal and spatial Empirical Orthogonal Function (EOF) analysis has been performed on monthly maximum sea surface temperature (SST) satellite data over eight years (July 1981-August 1989) to examine the SST patterns of variability off north-west Africa. The first temporal EOF mode (75 per cent) represents the cooling and warming cycle over the region. The temporal amplitudes show an interannual variability with 1982 summer temperatures abnormally much colder, immediately preceding the largest El Nino phenomenon of the century. The second temporal mode (9 per cent) distinguishes a large-scale behaviour of the northern and southern areas of the region, the two areas being out of phase presumably related to the variability of the wind field. The first spatial EOF mode (66 per cent), which resembles the mean of all images, is stronger in fall, with a smaller second maximum at the beginning of spring. The second spatial mode (10 per cent) shows the coastal upwelling region where a seaward extension of upwelled water around 300km offshore is observed off Cape Blanc. All the modes show complex eastern boundary dynamics with different regimes north and south of Cape Blanc. The Cape Blanc vicinity must have some interesting dynamics with a sharp boundary evident in all the modes. Only these two first temporal and spatial EOF modes are significantly above the noise level. The EOF method is efficient in compressing monthly SST satellite imagery off north-west Africa, with a great percentage of the total variance being accounted by only two modes.     

Multi-sensor synergistic analysis of mesoscale oceanic features: Campos Basin,south-eastern Brazil

This study presents a combined use of multi-sensor remote sensing and in situ data for the analysis and interpretation of oceanic features observed at the continental shelf and slope of the Campos Basin, south-eastern Brazil. Ocean colour (SeaWiFS), thermal infrared (AVHRR), scatterometer winds (QuikSCAT) and SAR (Radarsat-1) data were integrated to associate the different SAR backscatter patterns with physical and biological oceanic processes. The interpreted SAR features included processes such as oceanic fronts, current meandering and eddies, upwelling plumes, wind variability and algae blooms. The interpretation of these features was only feasible through the use of the multi-sensor synergistic approach complemented by timely field verification.