Ocean Chlorophyll Studies from a U-2 Aircraft Platform

Chlorophyll gradient maps of large ocean areas were generated from U-2 ocean color scanner data obtained over test sites in the Pacific and Atlantic Oceans. The delineation of oceanic features using the upward radiant intensity relies on an analysis method which presupposes that radiation backscattered from the atmosphere and ocean surface can be properly modeled using a measurement made at 778 nm. An estimation of the chlorophyll concentration was performed by properly ratioing radiances measured at 472 nm and 548 nm after removing the atmospheric effects. The correlation between the remotely sensed data and in-situ surface chlorophyll measurements was validated in two sets of data. The results show that the correlation between the in-situ measured chlorophyll and the derived quantity is a negative exponential function and the correlation coefficient was calculated to be -0.965

Ocean Chlorophyll Studies From a U-2 Aircraft Platform

Chlorophyll gradient maps of large ocean areas were generated from U-2/OCS data obtained over test sites in the Pacific and the Atlantic Oceans. The delineation of oceanic features using the upward radiant intensity relies on an analysis method which presupposes that radiation backscattered from the atmosphere and the ocean surface can be properly modeled by using a measurement made at 778 nm. The calculation of atmospheric radiance was performed by using a method developed by J.V. Dave. An estimation of the chlorophyll concentration is performed by properly ratioing radiances measured at 472 and 548 nm after removing the atmospheric effects. The correlation between the remotely sensed data and the in situ surface chlorophyll measurements has been validated in two sets of data. The results show that the correlation between the in situ measured chlorophyll and the derived quantity is a negative exponential function, and the correlation coefficient was calculated to be -0.965

Robust Detection of the North-West African Upwelling From SST Images

International audienceAnalysis and study of coastal upwelling using sea surface temperature (SST) satellite images is a common procedure because of its coast effectiveness (economic, time, frequency, and manpower). Developing on the Ekman theory, we propose a robust method to identify the upwelling regions along the northwest African margin. The proposed method comes to overcome the issues encountered in a recent method devoted for the same purpose and for the same upwelling system. Afterward, we show how our method can serve as a framework to study and monitor the spatio-temporal variability of the upwelling phenomenon in the studied region

Remote Sensing Applications in Coastal Environment

Coastal regions are susceptible to rapid changes, as they constitute the boundary between the land and the sea. The resilience of a particular segment of coast depends on many factors, including climate change, sea-level changes, natural and technological hazards, extraction of natural resources, population growth, and tourism. Recent research highlights the strong capabilities for remote sensing applications to monitor, inventory, and analyze the coastal environment. This book contains 12 high-quality and innovative scientific papers that explore, evaluate, and implement the use of remote sensing sensors within both natural and built coastal environments

A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans

The need for more effective environmental monitoring of the open and coastal ocean has recently led to notable advances in satellite ocean color technology and algorithm research. Satellite ocean color sensors' data are widely used for the detection, mapping and monitoring of phytoplankton blooms because earth observation provides a synoptic view of the ocean, both spatially and temporally. Algal blooms are indicators of marine ecosystem health; thus, their monitoring is a key component of effective management of coastal and oceanic resources. Since the late 1970s, a wide variety of operational ocean color satellite sensors and algorithms have been developed. The comprehensive review presented in this article captures the details of the progress and discusses the advantages and limitations of the algorithms used with the multi-spectral ocean color sensors CZCS, SeaWiFS, MODIS and MERIS. Present challenges include overcoming the severe limitation of these algorithms in coastal waters and refining detection limits in various oceanic and coastal environments. To understand the spatio-temporal patterns of algal blooms and their triggering factors, it is essential to consider the possible effects of environmental parameters, such as water temperature, turbidity, solar radiation and bathymetry. Hence, this review will also discuss the use of statistical techniques and additional datasets derived from ecosystem models or other satellite sensors to characterize further the factors triggering or limiting the development of algal blooms in coastal and open ocean waters

Factors affecting the identification of phytoplankton groups by means of remote sensing

A literature review was conducted on the state of the art as to whether or not information about communities and populations of phytoplankton in aquatic environments can be derived by remote sensing. In order to arrive at this goal, the spectral characteristics of various types of phytoplankton were compared to determine first, whether there are characteristic differences in pigmentation among the types and second, whether such differences can be detected remotely. In addition to the literature review, an extensive, but not exhaustive, annotated bibliography of the literature that bears on these questions is included as an appendix, since it constitutes a convenient resource for anyone wishing an overview of the field of ocean color. The review found some progress has already been made in remote sensing of assemblages such as coccolithophorid blooms, mats of cyanobacteria, and red tides. Much more information about the composition of algal groups is potentially available by remote sensing particularly in water bodies having higher phytoplankton concentrations, but it will be necessary to develop the remote sensing techniques required for working in so-called Case 2 waters. It is also clear that none of the satellite sensors presently available or soon to be launched is ideal from the point of view of what we might wish to know; it would seem wise to pursue instruments with the planned characteristics of the Moderate Resolution Imaging Spectrometer-Tilt (MODIS-T) or Medium Resolution Imaging Spectrometer (MERIS)

Estimation of CDOM in Inland Waters via Water Bio-Optical Properties Using a Remote Sensing Approach

Monitoring of Colored dissolved organic matter (CDOM) in inland waters provides important information for tracing carbon cycle at the land-water interface and studying aquatic ecosystem. Remote sensing estimation of CDOM in the inland waters offers an alternative approach to field samplings in examining CDOM spatial-temporal dynamics. However, CDOM retrieval is a challenge due to the lack of algorithm for resolving bottom effect in shallow inland waters. Moreover, an effective approach based on multi-spectral, high spatial resolution and global coverage satellite images is in urgent need. To resolve these challenges, shallow water bio-optical properties (SBOP) algorithm was developed to overcome bottom reflectance effect on the total water leaving reflectance in shallow inland water. SBOP algorithm included the bottom reflectance in building underwater light transfer model. It was designed based on the field spectral data from four cruises in Lake Huron. SBOP algorithm had an obviously advantage over previous deep water CDOM algorithm (e.g. QAA-CDOM). In this study, Landsat-8 multi-spectral satellite imagery was selected to derive CDOM spatial-temporal dynamics in lake and river waters. The coastal blue band (443 nm), global coverage and high spatial resolution (30 m) of Landsat-8 images offered suitable data for inland water CDOM mapping. The SBOP algorithm was applied on Landsat-8 images in broad ranges of inland waters with high accuracy (Lake Huron (R2 = 0.87), 14 northeastern freshwater lakes (R2 = 0.80), and 6 large Arctic Rivers (R2 = 0.87)). Both the spatial patterns and seasonal dynamics were derived to study the multiple factors’ impact on terrestrially derived CDOM input to the rivers and lakes, including river discharge, watershed landcover, and temperature. This new satellite approach of CDOM estimation in inland waters provided high accuracy spatial-temporal information for studying land-water carbon cycle and aquatic environment

Variabilité interannuelle et intrasaisonnière de l'Upwelling du Sud Vietnam : le rôle du forçage atmosphérique haute fréquence, de la dynamique océanique hauturière et côtière et de la variabilité intrinsèque océanique

L'Upwelling du Sud Vietnam (SVU) se développe en été au large de la côte vietnamienne (mer de Chine du Sud, SCS) sous l'influence des vents de mousson du sud-ouest. Une configuration haute résolution (1 km à la côte) du modèle SYMPHONIE a été développée pour étudier le fonctionnement, la variabilité et l'influence du SVU. Une simulation a d'abord été réalisée sur la période 2009-2018. Le réalisme de cette simulation en termes de représentation de la dynamique océanique et des masses d'eau, des échelles journalière à interannuelle, et côtière à régionale, a été évalué en détail par comparaison avec les données satellitaires disponibles et quatre jeux d'observations in-situ. Cette simulation a ensuite été utilisée pour examiner la variabilité interannuelle du SVU sur ses principales zones de développement : les zones côtières sud (BoxSC) et nord (BoxNC), et la zone offshore (BoxOF). Pour BoxSC et BoxOF, nos résultats confirment que l'intensité moyenne estivale du vent dans la région et de la circulation induite pilotent au premier ordre cette variabilité . Ils révèlent de plus qu'elle est modulée par l'organisation spatiale et temporelle des structures océaniques de méso-échelle et du forçage atmosphérique de haute fréquence. Pour BoxNC, la variabilité interannuelle de l'upwelling est principalement déterminée par la circulation côtière et les structures de méso-échelle : des conditions de vent estivales similaires peuvent être associées à des intensités d'upwelling très contrastées, et vice versa, en fonction de la circulation dans la zone. Nous avons ensuite réalisé un ensemble de 10 simulations jumelles avec des conditions initiales perturbées pour examiner les mécanismes impliqués dans la variabilité journalière à intrasaisonnière de l'upwelling. Cet ensemble révèle le rôle de la chronologie quotidienne à intrasaisonnière du vent, mais aussi la forte influence de la variabilité intrinsèque de l'océan (OIV), liée à l'influence de la circulation côtière et de mésoéchelle.The South Vietnam Upwelling (SVU) develops off the Vietnamese coast (South China Sea, SCS) under the influence of southwest summer monsoon winds. A high resolution configuration (1 km at the coast) of the SYMPHONIE model was developed to study the functioning, variability and influence of the SVU. A simulation was first performed over the period 2009-2018. The realism of the simulation in terms of representation of ocean dynamics and water masses, from daily to interannual, and coastal to regional scales, was assessed in detail by comparison with available satellite data and four sets of in-situ observations. The interannual variability of the SVU is examined over its main areas of development: the southern (BoxSC) and northern (BoxNC) coasts, and the offshore area (BoxOF). For BoxSC and BoxOF, our results confirm the driving role of the summer regional mean wind and induced circulation. They moreover reveal that the spatial and temporal organization of mesoscale ocean structures and high frequency atmospheric forcing modulate this interannual variability. For BoxNC, the upwelling interannual variability is mainly determined by coastal circulation and mesoscale structures: similar summer wind conditions can be associated with very contrasting upwelling intensities, and vice versa, depending on the circulation in the BoxNC area. We then perform an ensemble of 10 twin simulations with perturbed initial conditions to examine the mechanisms involved in the daily to intraseasonal variability of upwelling. This ensemble reveals the role of the daily to intraseasonal chronology of wind forcing, but also the strong influence of Ocean Intrinsic Variability (OIV), related to the influence of coastal and mesoscale circulation

Shrunken Locally Linear Embedding for Passive Microwave Retrieval of Precipitation

This paper introduces a new Bayesian approach to the inverse problem of passive microwave rainfall retrieval. The proposed methodology relies on a regularization technique and makes use of two joint dictionaries of coincidental rainfall profiles and their corresponding upwelling spectral radiative fluxes. A sequential detection-estimation strategy is adopted, which basically assumes that similar rainfall intensity values and their spectral radiances live close to some sufficiently smooth manifolds with analogous local geometry. The detection step employs a nearest neighborhood classification rule, while the estimation scheme is equipped with a constrained shrinkage estimator to ensure stability of retrieval and some physical consistency. The algorithm is examined using coincidental observations of the active precipitation radar (PR) and passive microwave imager (TMI) on board the Tropical Rainfall Measuring Mission (TRMM) satellite. We present promising results of instantaneous rainfall retrieval for some tropical storms and mesoscale convective systems over ocean, land, and coastal zones. We provide evidence that the algorithm is capable of properly capturing different storm morphologies including high intensity rain-cells and trailing light rainfall, especially over land and coastal areas. The algorithm is also validated at an annual scale for calendar year 2013 versus the standard (version 7) radar (2A25) and radiometer (2A12) rainfall products of the TRMM satellite

A novel approach to quantify metrics of upwelling intensity, frequency, and duration

The importance of coastal upwelling systems is widely recognized. However, several aspects of the current and future behaviors of these systems remain uncertain. Fluctuations in temperature because of anthropogenic climate change are hypothesized to affect upwelling-favorable winds and coastal upwelling is expected to intensify across all Eastern Boundary Upwelling Systems. To better understand how upwelling may change in the future, it is necessary to develop a more rigorous method of quantifying this phenomenon. In this paper, we use SST data and wind data in a novel method of detecting upwelling signals and quantifying metrics of upwelling intensity, duration, and frequency at four sites within the Benguela Upwelling System. We found that indicators of upwelling are uniformly detected across five SST products for each of the four sites and that the duration of those signals is longer in SST products with higher spatial resolutions. Moreover, the high-resolution SST products are significantly more likely to display upwelling signals at 25 km away from the coast when signals were also detected at the coast