scholarly journals Towards a merged satellite and in situ fluorescence ocean chlorophyll product

2012 ◽  
Vol 9 (6) ◽  
pp. 2111-2125 ◽  
Author(s):  
H. Lavigne ◽  
F. D'Ortenzio ◽  
H. Claustre ◽  
A. Poteau

Abstract. Understanding the ocean carbon cycle requires a precise assessment of phytoplankton biomass in the oceans. In terms of numbers of observations, satellite data represent the largest available data set. However, as they are limited to surface waters, they have to be merged with in situ observations. Amongst the in situ data, fluorescence profiles constitute the greatest data set available, because fluorometers have operated routinely on oceanographic cruises since the 1970s. Nevertheless, fluorescence is only a proxy of the total chlorophyll a concentration and a data calibration is required. Calibration issues are, however, sources of uncertainty, and they have prevented a systematic and wide range exploitation of the fluorescence data set. In particular, very few attempts to standardize the fluorescence databases have been made. Consequently, merged estimations with other data sources (e.g. satellite) are lacking. We propose a merging method to fill this gap. It consists firstly in adjusting the fluorescence profile to impose a zero chlorophyll a concentration at depth. Secondly, each point of the fluorescence profile is then multiplied by a correction coefficient, which forces the chlorophyll a integrated content measured on the fluorescence profile to be consistent with the concomitant ocean colour observation. The method is close to the approach proposed by Boss et al. (2008) to correct fluorescence data of a profiling float, although important differences do exist. To develop and test our approach, in situ data from three open ocean stations (BATS, HOT and DYFAMED) were used. Comparison of the so-called "satellite-corrected" fluorescence profiles with concomitant bottle-derived estimations of chlorophyll a concentration was performed to evaluate the final error (estimated at 31%). Comparison with the Boss et al. (2008) method, using a subset of the DYFAMED data set, demonstrated that the methods have similar accuracy. The method was applied to two different data sets to demonstrate its utility. Using fluorescence profiles at BATS, we show that the integration of "satellite-corrected" fluorescence profiles in chlorophyll a climatologies could improve both the statistical relevance of chlorophyll a averages and the vertical structure of the chlorophyll a field. We also show that our method could be efficiently used to process, within near-real time, profiles obtained by a fluorometer deployed on autonomous platforms, in our case a bio-optical profiling float. The application of the proposed method should provide a first step towards the generation of a merged satellite/fluorescence chlorophyll a product, as the "satellite-corrected" profiles should then be consistent with satellite observations. Improved climatologies with more consistent satellite and in situ data are likely to enhance the performance of present biogeochemical models.

2011 ◽  
Vol 8 (6) ◽  
pp. 11899-11939
Author(s):  
H. Lavigne ◽  
F. D'Ortenzio ◽  
H. Claustre ◽  
A. Poteau

Abstract. Understanding the ocean carbon cycle requires a precise assessment of phytoplankton biomass in the oceans. In terms of numbers of observations, satellite data represents the largest available data set. However, as they are limited to surface waters, they have to be merged with in situ observations. Amongst the in situ data, fluorescence profiles constitute the greatest data set available, because fluorometers operate routinely on oceanographic cruise since the seventies. Nevertheless, fluorescence is only a proxy of the Total Chlorophyll-a concentration and a data calibration is required. Calibration issues are, however, source of uncertainty and they have prevented a systematic and wide range exploitation of the fluorescence data set. In particular, very few attempts to standardize the fluorescence data bases exist. Consequently, merged estimations with other data sources (i.e. satellite) are lacking. We propose a merging method to fill this gap. It consists firstly, in adjusting the fluorescence profile to impose a zero Chlorophyll-a concentration at depth. Secondly, each point of the fluorescence profile is then multiplied by a correction coefficient which forces the Chlorophyll-a integrated content measured on the fluorescence profile to be consistent with the concomitant ocean color observation. The method is close to the approach proposed by Boss et al. (2008) to calibrate fluorescence data of a profiling float, although important differences do exist. To develop and test our approach, in situ data from three open ocean stations (BATS, HOT and DYFAMED) were used. Comparison of the so-called "satellite-corrected" fluorescence profiles with concomitant bottle derived estimations of Chlorophyll-a concentration was performed to evaluate the final error, which resulted to be of about 31 %. Comparison with the Boss et al. (2008) method, carried out on a subset of the DYFAMED data set simulating a profiling float time series, demonstrated that the methods have similar accuracy. Applications of the method were then explored on two different data sets. Using fluorescence profiles at BATS, we show that the integration of "satellite-corrected" fluorescence profiles in Chlorophyll-a climatologies could improve both the statistical relevance of Chlorophyll-a averages and the vertical structure of the Chlorophyll-a field. We also show that our method could be efficiently used to process, within near-real time, profiles obtained by a fluorometer deployed on autonomous platforms, in our case a bio-optical profiling float. The wide application of the proposed method should provide a first step toward the generation of a merged satellite/fluorescence Chlorophyll-a product, as the "satellite-corrected" profiles should then be consistent with satellite observations. Improved climatologies and more consistent satellite and in situ data (comprising those from autonomous platforms) should strongly enhance the performance of present biogeochemical models.


Author(s):  
A. Manuel ◽  
A. C. Blanco ◽  
A. M. Tamondong ◽  
R. Jalbuena ◽  
O. Cabrera ◽  
...  

Abstract. Laguna Lake, the Philippines’ largest freshwater lake, has always been historically, economically, and ecologically significant to the people living near it. However, as it lies at the center of urban development in Metro Manila, it suffers from water quality degradation. Water quality sampling by current field methods is not enough to assess the spatial and temporal variations of water quality in the lake. Regular water quality monitoring is advised, and remote sensing addresses the need for a synchronized and frequent observation and provides an efficient way to obtain bio-optical water quality parameters. Optimization of bio-optical models is done as local parameters change regionally and seasonally, thus requiring calibration. Field spectral measurements and in-situ water quality data taken during simultaneous satellite overpass were used to calibrate the bio-optical modelling tool WASI-2D to get estimates of chlorophyll-a concentration from the corresponding Landsat-8 images. The initial output values for chlorophyll-a concentration, which ranges from 10–40 μg/L, has an RMSE of up to 10 μg/L when compared with in situ data. Further refinements in the initial and constant parameters of the model resulted in an improved chlorophyll-a concentration retrieval from the Landsat-8 images. The outputs provided a chlorophyll-a concentration range from 5–12 μg/L, well within the usual range of measured values in the lake, with an RMSE of 2.28 μg/L compared to in situ data.


Author(s):  
Alessandro Rhadamek Alves Pereira ◽  
João Batista Lopes ◽  
Giovana Mira de Espindola ◽  
Carlos Ernando da Silva

Recently, the Poti river mouth region has experienced environmental impacts that resulted in a change of landscape in its dry season, highlighting the eutrophication and proliferation of phytoplankton, algae, cyanobacteria and aquatic plants. Considering the aspects related to water-quality monitoring in the semiarid region of Brazil from remote sensing, this study aimed to evaluate the performance of Sentinel-2A satellite data in the retrieval of chlorophyll-a concentration in Poti River in Teresina, Piaui, Brazil. The chlorophyll-a concentration retrieval and mapping methodology involved the study of the water surface reflectance in Sentinel-2A images and their correlation with the chlorophyll-a data collected in situ during the years 2016 and 2017. The results generated by the Chl-1, Ha et al. (2017), Chl-2, Page et al. (2018), and Chl-3, Kuhn et al. (2019) equations show the need for calibrating the algorithms used for the Poti River water components. However, the empirical algorithm Chl-2 shows a correlation has been established to identify the spatiotemporal variation of chlorophyll-a concentration along the Poti River broadly and not punctually. The spatial distribution of this pigment in maps derived from Sentinel-2A is consistent with the pattern of occurrence determined by the in situ data. Therefore, the MSI sensor proved to be a tool suitable for the retrieval and monitoring of chlorophyll-a concentration along the Poti River.


2021 ◽  
Vol 13 (1) ◽  
pp. 85-97
Author(s):  
Ioannis Moutzouris-Sidiris ◽  
Konstantinos Topouzelis

Abstract The objective of this study is to evaluate the efficiency of two well-known algorithms (Ocean Colour 4 for MERIS [OC4Me] and neural net [NN]) used in the calculation of chlorophyll-a (Chl-a) from the Sentinel-3 Ocean and Land Colour Instrument (OLCI) compared to in situ measurements covering the Mediterranean Sea. In situ data set, obtained from the Copernicus Marine Environmental Monitoring Service (CMEMS) and more specifically from the data set with the title INSITU_MED_NRT_OBSERVATIONS_013_035, and Chl-a values at different depths were extracted. The concentration of Chl-a at a penetration depth was calculated. Then, water was classified into two categories, Case-1 and Case-2. For Case-2 waters, the OC4Me presents a moderate correlation with the in situ data for a time window of 0–2 h. In contrast with the NN algorithm, where very weak correlations were calculated, lower values of the statistical index of Bias for Case-1 waters were calculated for the OC4Me algorithm. Higher values of Pearson correlation were calculated (r > 0.5) for OC4Me algorithm than NN. OC4Me performed better than NN.


Author(s):  
Sisir Kumar Dash ◽  
Tasuku Tanaka ◽  
Hiroyuki Hachiya ◽  
Yashuhiro Sugimori

Multi Angle Imaging Spectro Radiometer (MISR) has a capability to observe the ocean surface from different viewing directions. Attempts were made to estimate the ocean surface reflectance and chlorophyll-a concentration using MISR data. The aerosol optical thickness (OAT), available from the MISR archive is compared with the results simulated using the 6S radiation transfer code. It turns out that the AOT values agree with each other up to 85 percent in certain areas in case-1 waters. Substituting the archive values of AOT into the radiative transfer process, we obtain the surface reflectance. This surface reflectance, in turn, is employed together with the in-water algorithm, to obtain the clhorophyll concentration maps for three viewing directions (aft, nadir and forward). The pattern of obtained chlorophyll map is reasonable. It is estimated that an error of about 35 percent is involved in the radiance calibration and AOT , Hence, with best possibility, the surface reflectance is quantified and the chlorophyll maps were generated. When it is compared with the nadir observation, the forward viewing camera overestimates and the aft viewing camera underestimates the chlorophyll-a concentrartion especially in case-1 waters. In case 2 waters, the chlorophyll-a concentration shows similiar patterns for the three different viewing directions. Due to lack of in-situ data, absolute chlorophyll values were ignored but errors were quatified for the surface reflectance and the aerosol optical thickness with the 6S simulated results. Keywords: MISR, 6S, AOT, Surface reflectance, Chlorophyll-a


2013 ◽  
Vol 8 (S300) ◽  
pp. 265-268
Author(s):  
Miho Janvier ◽  
Pascal Démoulin ◽  
Sergio Dasso

AbstractMagnetic clouds (MCs) consist of flux ropes that are ejected from the low solar corona during eruptive flares. Following their ejection, they propagate in the interplanetary medium where they can be detected by in situ instruments and heliospheric imagers onboard spacecraft. Although in situ measurements give a wide range of data, these only depict the nature of the MC along the unidirectional trajectory crossing of a spacecraft. As such, direct 3D measurements of MC characteristics are impossible. From a statistical analysis of a wide range of MCs detected at 1 AU by the Wind spacecraft, we propose different methods to deduce the most probable magnetic cloud axis shape. These methods include the comparison of synthetic distributions with observed distributions of the axis orientation, as well as the direct integration of observed probability distribution to deduce the global MC axis shape. The overall shape given by those two methods is then compared with 2D heliospheric images of a propagating MC and we find similar geometrical features.


2006 ◽  
Vol 27 (19) ◽  
pp. 4267-4276 ◽  
Author(s):  
H. B. Jiao ◽  
Y. Zha ◽  
J. Gao ◽  
Y. M. Li ◽  
Y. C. Wei ◽  
...  

Author(s):  
Eihab M. Fathelrahman ◽  
Khalid A. Hussein ◽  
Safwan Paramban ◽  
Timothy R. Green ◽  
Bruce C. Vandenberg

The United Arab Emirates (UAE) recently witnessed algal/phytoplankton blooms attributed to the high concentrations of Chlorophyll-a associated with the spread and accumulation of a wide range of organisms with toxic effects that influence ecological and fishing economic activities and water desalination along coastal areas.  This research explores the UAE coasts as a case study for the framework presented here. In this research, we argue that advances in satellite remote sensing and imaging of spatial and temporal data offer sufficient information to find the best-fit regression method and relationship between Chlorophyll-a concentration and a set of climatic and biological explanatory variables over time. Three functional forms of regression models were tested and analysed to reveal that the Log-Linear Model found to be the best fit providing the most statistically robust model compared to the Linear and the Generalised Least Square models.  Besides, it is useful to identify the factors Sea Surface temperature, Calcite Concentration, Instantaneous Photosynthetically Available Radiation, Normalized Fluorescence Line Height, and Wind Speed that significantly influence Chlorophyll-a concentration. Research results can be beneficial to aid decision-makers in building a best-fit statistical system and models of algal blooms in the study area. The study found results to be sensitive to the study’s temporal time-period length and the explanatory variables selected for the analysis.


2017 ◽  
Vol 49 (5) ◽  
pp. 1608-1617 ◽  
Author(s):  
Matias Bonansea ◽  
Claudia Rodriguez ◽  
Lucio Pinotti

Abstract Landsat satellites, 5 and 7, have significant potential for estimating several water quality parameters, but to our knowledge, there are few investigations which integrate these earlier sensors with the newest and improved mission of Landsat 8 satellite. Thus, the comparability of water quality assessing across different Landsat sensors needs to be evaluated. The main objective of this study was to assess the feasibility of integrating Landsat sensors to estimate chlorophyll-a concentration (Chl-a) in Río Tercero reservoir (Argentina). A general model to retrieve Chl-a was developed (R2 = 0.88). Using observed versus predicted Chl-a values the model was validated (R2 = 0.89) and applied to Landsat imagery obtaining spatial representations of Chl-a in the reservoir. Results showed that Landsat 8 can be combined with Landsat 5 and 7 to construct an empirical model to estimate water quality characteristics, such as Chl-a in a reservoir. As the number of available and upcoming sensors with open access will increase with time, we expect that this trend will certainly further promote remote sensing applications and serve as a valuable basis for a wide range of water quality assessments.


1990 ◽  
Vol 68 (5) ◽  
pp. 981-985 ◽  
Author(s):  
Neil A. MacKay ◽  
Stephen R. Carpenter ◽  
Patricia A. Soranno ◽  
Michael J. Vanni

The responses of a zooplankton community to Chaoborus predation were studied in large in situ mesocosms in Peter Lake. Chaoborus flavicans, the native chaoborid, significantly reduced the density of the dominant grazer, Daphnia pulex, in relation to controls that lacked Chaoborus. Chaoborus americanus, a species found only in fishless bogs, reduced Da. pulex densities far more than the chaoborid found in Peter Lake, C. flavicans. Chaoborus americanus also significantly reduced the dominant copepod, Diaptomus oregonensis, in relation to both the control and the C. flavicans treatment. Chlorophyll a concentration did not differ among treatments, indicating that herbivore responses could not be explained by changes in food levels. Our results show that Chaoborus predation can greatly affect a zooplankton community, especially daphnids.


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