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Li X, Zheng H, Mao Z, Du P, Zhang W. Change in water column total chlorophyll-a in the Mediterranean revealed by satellite observation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 945:174076. [PMID: 38908583 DOI: 10.1016/j.scitotenv.2024.174076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 05/25/2024] [Accepted: 06/15/2024] [Indexed: 06/24/2024]
Abstract
Chlorophyll-a (Chl-a) is a crucial pigment in algae and macrophytes, which makes the concentration of total Chl-a in the water column (total Chl-a) an essential indicator for estimating the primary productivity and carbon cycle of the ocean. Integrating the Chl-a concentration at different depths (Chl-a profile) is an important way to obtain the total Chl-a. However, due to limited cost and technology, it is difficult to measure Chl-a profiles directly in a spatially continuous and high-resolution way. In this study, we proposed an integrated strategy model that combines three different machine learning methods (PSO-BP, random forest and gradient boosting) to predict the Chl-a profile in the Mediterranean by using several sea surface variables (photosynthetically active radiation, spectral irradiance, sea surface temperature, wind speed, euphotic depth and KD490) and subsurface variables (mixed layer depth) observed by or estimated from satellite and BGC-Argo float observations. After accuracy estimation, the integrated model was utilized to generate the time series total Chl-a in the Mediterranean from 2003 to 2021. By analysing the time series results, it was found that seasonal fluctuation contributed the most to the variation in total Chl-a. In addition, there was an overall decreasing trend in the Mediterranean phytoplankton biomass, with the total Chl- decreasing at a rate of 0.048 mg/m2 per year, which was inferred to be related to global warming and precipitation reduction based on comprehensive analysis with sea surface temperature and precipitation data.
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Affiliation(s)
- Xiaojuan Li
- School of Geographical Sciences, China West Normal University, Nanchong 637001, China; Sichuan Provincial Engineering Laboratory of Monitoring and Control for Soil Erosion in Dry Valleys, China West Normal University, Nanchong 637001, China
| | - Hongrui Zheng
- School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China; Xizang Autonomous Region Key Laboratory of Satellite Remote Sensing and Application, Lhasa 851400, China.
| | - Zhihua Mao
- States Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou 310012, China; School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210033, China
| | - Peijun Du
- School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing 210033, China
| | - Wei Zhang
- National Key Laboratory of Water Disaster Prevention, Nanjing Hydraulic Research Institute, Nanjing 210024, China
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2
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Comparing dormancy in two distantly related tunicates reveals morphological, molecular, and ecological convergences and repeated co-option. Sci Rep 2022; 12:12620. [PMID: 35871255 PMCID: PMC9308810 DOI: 10.1038/s41598-022-16656-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 07/13/2022] [Indexed: 11/08/2022] Open
Abstract
AbstractMany asexually-propagating marine invertebrates can survive extreme environmental conditions by developing dormant structures, i.e., morphologically simplified bodies that retain the capacity to completely regenerate a functional adult when conditions return to normal. Here, we examine the environmental, morphological, and molecular characteristics of dormancy in two distantly related clonal tunicate species: Polyandrocarpa zorritensis and Clavelina lepadiformis. In both species, we report that the dormant structures are able to withstand harsher temperature and salinity conditions compared to the adults. The dormant structures are the dominant forms these species employ to survive adverse conditions when the zooids themselves cannot survive. While previous work shows C. lepadiformis dormant stage is present in winters in the Atlantic Ocean and summers in the Mediterranean, this study is the first to show a year-round presence of P. zorritensis dormant forms in NW Italy, even in the late winter when all zooids have disappeared. By finely controlling the entry and exit of dormancy in laboratory-reared individuals, we were able to select and characterize the morphology of dormant structures associated with their transcriptome dynamics. In both species, we identified putative stem and nutritive cells in structures that resemble the earliest stages of asexual propagation. By characterizing gene expression during dormancy and regeneration into the adult body plan (i.e., germination), we observed that genes which control dormancy and environmental sensing in other metazoans, notably HIF-α and insulin signaling genes, are also expressed in tunicate dormancy. Germination-related genes in these two species, such as the retinoic acid pathway, are also found in other unrelated clonal tunicates during asexual development. These results are suggestive of repeated co-option of conserved eco-physiological and regeneration programs for the origin of novel dormancy-germination processes across distantly related animal taxa.
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3
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Butt MA, Voronkov GS, Grakhova EP, Kutluyarov RV, Kazanskiy NL, Khonina SN. Environmental Monitoring: A Comprehensive Review on Optical Waveguide and Fiber-Based Sensors. BIOSENSORS 2022; 12:bios12111038. [PMID: 36421155 PMCID: PMC9688474 DOI: 10.3390/bios12111038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 11/15/2022] [Accepted: 11/15/2022] [Indexed: 05/31/2023]
Abstract
Globally, there is active development of photonic sensors incorporating multidisciplinary research. The ultimate objective is to develop small, low-cost, sensitive, selective, quick, durable, remote-controllable sensors that are resistant to electromagnetic interference. Different photonic sensor designs and advances in photonic frameworks have shown the possibility to realize these capabilities. In this review paper, the latest developments in the field of optical waveguide and fiber-based sensors which can serve for environmental monitoring are discussed. Several important topics such as toxic gas, water quality, indoor environment, and natural disaster monitoring are reviewed.
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Affiliation(s)
| | - Grigory S Voronkov
- Ufa University of Science and Technology, Z. Validi St. 32, 450076 Ufa, Russia
| | | | - Ruslan V Kutluyarov
- Ufa University of Science and Technology, Z. Validi St. 32, 450076 Ufa, Russia
| | - Nikolay L Kazanskiy
- Samara National Research University, 443086 Samara, Russia
- IPSI RAS-Branch of the FSRC "Crystallography and Photonics" RAS, 443001 Samara, Russia
| | - Svetlana N Khonina
- Samara National Research University, 443086 Samara, Russia
- IPSI RAS-Branch of the FSRC "Crystallography and Photonics" RAS, 443001 Samara, Russia
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4
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Mohseni F, Saba F, Mirmazloumi SM, Amani M, Mokhtarzade M, Jamali S, Mahdavi S. Ocean water quality monitoring using remote sensing techniques: A review. MARINE ENVIRONMENTAL RESEARCH 2022; 180:105701. [PMID: 35939895 DOI: 10.1016/j.marenvres.2022.105701] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 07/09/2022] [Accepted: 07/10/2022] [Indexed: 06/15/2023]
Abstract
Ocean Water Quality (OWQ) monitoring provides insights into the quality of water in marine and near-shore environments. OWQ measurements can contain the physical, chemical, and biological characteristics of oceanic waters, where low OWQ values indicate an unhealthy ecosystem. Many parameters of water can be estimated from Remote Sensing (RS) data. Thus, RS offers significant opportunities for monitoring water quality in estuaries, coastal waterways, and the ocean. This paper reviews various RS systems and techniques for OWQ monitoring. It first introduces the common OWQ parameters, followed by the definition of the parameters and techniques of OWQ monitoring with RS techniques. In this study, the following OWQ parameters were reviewed: chlorophyll-a, colored dissolved organic matter, turbidity or total suspended matter/solid, dissolved organic carbon, Secchi disk depth, suspended sediment concentration, and sea surface temperature. This study presents a systematic analysis of the capabilities and types of spaceborne systems (e.g., optical and thermal sensors, passive microwave radiometers, active microwave scatterometers, and altimeters) which are commonly applied to OWQ assessment. The paper also provides a summary of the opportunities and limitations of RS data for spatial and temporal estimation of OWQ. Overall, it was observed that chlorophyll-a and colored dissolved organic matter are the dominant parameters applied to OWQ monitoring. It was also concluded that the data from optical and passive microwave sensors could effectively be applied to estimate OWQ parameters. From a methodological perspective, semi-empirical algorithms generally outperform the other empirical, analytical, and semi-analytical methods for OWQ monitoring.
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Affiliation(s)
- Farzane Mohseni
- Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran; Department of Technology and Society, Faculty of Engineering, Lund University, P.O. Box 118, 221 00, Lund, Sweden.
| | - Fatemeh Saba
- Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran.
| | - S Mohammad Mirmazloumi
- Centre Tecnològic de Telecommunications de Catalunya (CTTC/CERCA), Geomatics Research Unit, Av. Gauss 7, E-08860, Castelldefels, Barcelona, Spain.
| | - Meisam Amani
- Wood Environment and Infrastructure Solutions, Ottawa, ON, K2E 7L5, Canada.
| | - Mehdi Mokhtarzade
- Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran.
| | - Sadegh Jamali
- Department of Technology and Society, Faculty of Engineering, Lund University, P.O. Box 118, 221 00, Lund, Sweden.
| | - Sahel Mahdavi
- Wood Environment and Infrastructure Solutions, Ottawa, ON, K2E 7L5, Canada.
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5
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Liang H, Wang J, Zhang L, Liu J, Wang S. Review of Optical Fiber Sensors for Temperature, Salinity, and Pressure Sensing and Measurement in Seawater. SENSORS 2022; 22:s22145363. [PMID: 35891043 PMCID: PMC9325297 DOI: 10.3390/s22145363] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 07/02/2022] [Accepted: 07/15/2022] [Indexed: 02/04/2023]
Abstract
Temperature, salinity, and pressure (TSP) are essential parameters for the ocean. Optical fiber sensors (OFSs) have rapidly come into focus as an ocean detection technology in recent years due to their advantages of electromagnetic interference, light weight, low cost, and no waterproof requirement. In this paper, the most recently developed TSP sensors for single parameter and multi-parameter TSP sensing and measurement based on different OFSs are reviewed. In addition, from the practical point of view, encapsulation methods that protect fibers and maintain the normal operation of OFSs in seawater, and the response time of the OFS, are addressed. Finally, we discuss the prospects and challenges of OFSs used in marine environments and provide some clues for future work.
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AVHRR GAC Sea Surface Temperature Reanalysis Version 2. REMOTE SENSING 2022. [DOI: 10.3390/rs14133165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The 40+ years-long sea surface temperature (SST) dataset from 4 km Global Area Coverage (GAC) data of the Advanced Very High-Resolution Radiometers (AVHRR/2s and/3s) flown onboard ten NOAA satellites (N07/09/11/12/14/15/16/17/18/19) has been created under the NOAA AVHRR GAC SST Reanalysis 2 (RAN2) Project. The data were reprocessed with the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) enterprise SST system. Two SST products are reported in the full ~3000 km AVHRR swath: ‘subskin’ (highly sensitive to true skin SST, but debiased with respect to in situ SST) and ‘depth’ (a closer proxy for in situ data, but with reduced sensitivity). The reprocessing methodology aims at close consistency of satellite SSTs with in situ SSTs, in an optimal retrieval domain. Long-term orbital and calibration trends were compensated by daily recalculation of regression coefficients using matchups with drifters and tropical moored buoys (supplemented by ships for N07/09), collected within limited time windows centered at the processed day. The nighttime Sun impingements on the sensor black body were mitigated by correcting the L1b calibration coefficients. The Earth view pixels contaminated with a stray light were excluded. Massive cold SST outliers caused by volcanic aerosols following three major eruptions were filtered out by a modified, more conservative ACSPO clear-sky mask. The RAN2 SSTs are available in three formats: swath L2P (144 10-min granules per 24 h interval) and two 0.02° gridded (uncollated L3U, also 144 granules/24 h; and collated L3C, two global maps per 24 h, one for day and one for the night). This paper evaluates the RAN2 SST dataset, with a focus on the L3C product and compares it with two other available AVHRR GAC L3C SST datasets, NOAA Pathfinder v5.3 and ESA Climate Change Initiative v2.1. Among the three datasets, the RAN2 covers the global ocean more completely and shows reduced regional and temporal biases, improved stability and consistency between different satellites, and in situ SSTs.
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Machine-Learning Classification of SAR Remotely-Sensed Sea-Surface Petroleum Signatures—Part 1: Training and Testing Cross Validation. REMOTE SENSING 2022. [DOI: 10.3390/rs14133027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Sea-surface petroleum pollution is observed as “oil slicks” (i.e., “oil spills” or “oil seeps”) and can be confused with “look-alike slicks” (i.e., environmental phenomena, such as low-wind speed, upwelling conditions, chlorophyll, etc.) in synthetic aperture radar (SAR) measurements, the most proficient satellite sensor to detect mineral oil on the sea surface. Even though machine learning (ML) has become widely used to classify remotely-sensed petroleum signatures, few papers have been published comparing various ML methods to distinguish spills from look-alikes. Our research fills this gap by comparing and evaluating six traditional techniques: simple (naive Bayes (NB), K-nearest neighbor (KNN), decision trees (DT)) and advanced (random forest (RF), support vector machine (SVM), artificial neural network (ANN)) applied to different combinations of satellite-retrieved attributes. 36 ML algorithms were used to discriminate “ocean-slick signatures” (spills versus look-alikes) with ten-times repeated random subsampling cross validation (70-30 train-test partition). Our results found that the best algorithm (ANN: 90%) was >20% more effective than the least accurate one (DT: ~68%). Our empirical ML observations contribute to both scientific ocean remote-sensing research and to oil and gas industry activities, in that: (i) most techniques were superior when morphological information and Meteorological and Oceanographic (MetOc) parameters were included together, and less accurate when these variables were used separately; (ii) the algorithms with the better performance used more variables (without feature selection), while lower accuracy algorithms were those that used fewer variables (with feature selection); (iii) we created algorithms more effective than those of benchmark-past studies that used linear discriminant analysis (LDA: ~85%) on the same dataset; and (iv) accurate algorithms can assist in finding new offshore fossil fuel discoveries (i.e., misclassification reduction).
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Zhang F, Zhang Y, Zhang Z, Ding J. Validation and Improvement of COCTS/HY-1C Sea Surface Temperature Products. SENSORS (BASEL, SWITZERLAND) 2022; 22:3726. [PMID: 35632132 PMCID: PMC9145735 DOI: 10.3390/s22103726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/09/2022] [Accepted: 05/12/2022] [Indexed: 06/15/2023]
Abstract
In oceanographic study, satellite-based sea surface temperature (SST) retrieval has always been the focus of researchers. This paper investigates several multi-channel SST retrieval algorithms for the thermal infrared band, and evaluates the accuracy of the COCTS/HY-1C SST products. NEAR-GOOS in situ SST data are utilized for validation and improvement, and a three-step matching procedure including geographic location screening, cloud masking, and homogeneity check is conducted to match in situ SST data with satellite SST data. Two improvement schemes, including nonlinear regression and regularization iteration, are proposed to improve the accuracy of the COCTS/HY-1C SST products and the typical application scenarios and the algorithm characteristics of these two schemes are discussed. The standard deviation of residual between retrieved SST and measured SST for these two data improvement algorithms, which are considered as the main indexes for assessment, result in an improvement of 13.245% and 14.096%, respectively. In addition, the generalization ability of the SST models under two data improvement methods is quantitatively compared, and the factors affecting the model accuracy are also carefully evaluated, including the in situ data acquisition method and measurement time (day/night). Finally, future works about SST retrieval with COCTS/HY-1C satellite data are summarized.
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Affiliation(s)
- Feizhou Zhang
- Beijing Key Lab of Spatial Information Integration and 3S Application, Institute of Remote Sensing and Geographic Information System, School of Earth and Space Science, Peking University, Beijing 100871, China; (F.Z.); (Y.Z.); (Z.Z.)
| | - Yulin Zhang
- Beijing Key Lab of Spatial Information Integration and 3S Application, Institute of Remote Sensing and Geographic Information System, School of Earth and Space Science, Peking University, Beijing 100871, China; (F.Z.); (Y.Z.); (Z.Z.)
| | - Zihan Zhang
- Beijing Key Lab of Spatial Information Integration and 3S Application, Institute of Remote Sensing and Geographic Information System, School of Earth and Space Science, Peking University, Beijing 100871, China; (F.Z.); (Y.Z.); (Z.Z.)
| | - Jing Ding
- Key Laboratory of Space Ocean Remote Sensing and Application, National Satellite Ocean Application Service, Ministry of Natural Resources, Beijing 100081, China
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9
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Relative Merits of Optimal Estimation and Non-Linear Retrievals of Sea-Surface Temperature from MODIS. REMOTE SENSING 2022. [DOI: 10.3390/rs14092249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
We compared the results of an Optimal Estimation (OE) based approach for the retrieval of the skin sea surface temperature (SSTskin) with those of the traditional non-linear sea surface temperature (NLSST) algorithm. The retrievals were from radiance measurements in two infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA satellite Aqua. The OE used a reduced state vector of SST and total column water vapor (TCWV). The SST and atmospheric profiles of temperature and humidity from ERA5 provided prior knowledge, and we made reasonable assumptions about the variance of these fields. An atmospheric radiative transfer model was used as the forward model to simulate the MODIS measurements. The performances of the retrieval approaches were assessed by comparison with in situ measurements. We found that the OESST reduces the satellite–in situ bias, but mostly for retrievals with an already small bias between in situ and the prior SST. The OE approach generally fails to improve the SST retrieval when that difference is large. In such cases, the NLSST often provides a better estimate of the SST than the OE. The OESST also underperforms NLSST in areas that include large horizontal SST gradients.
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10
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Castaneda-Guzman M, Mantilla-Saltos G, Murray KA, Settlage R, Escobar LE. A database of global coastal conditions. Sci Data 2021; 8:304. [PMID: 34836949 PMCID: PMC8626420 DOI: 10.1038/s41597-021-01081-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 10/29/2021] [Indexed: 11/08/2022] Open
Abstract
Remote sensing satellite imagery has the potential to monitor and understand dynamic environmental phenomena by retrieving information about Earth's surface. Marine ecosystems, however, have been studied with less intensity than terrestrial ecosystems due, in part, to data limitations. Data on sea surface temperature (SST) and Chlorophyll-a (Chlo-a) can provide quantitative information of environmental conditions in coastal regions at a high spatial and temporal resolutions. Using the exclusive economic zone of coastal regions as the study area, we compiled monthly and annual statistics of SST and Chlo-a globally for 2003 to 2020. This ready-to-use dataset aims to reduce the computational time and costs for local-, regional-, continental-, and global-level studies of coastal areas. Data may be of interest to researchers in the areas of ecology, oceanography, biogeography, fisheries, and global change. Target applications of the database include environmental monitoring of biodiversity and marine microorganisms, and environmental anomalies.
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Affiliation(s)
- Mariana Castaneda-Guzman
- Department of Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 24061, USA
| | - Gabriel Mantilla-Saltos
- Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ciencias Naturales y Matemáticas, Guayaquil, Ecuador
| | - Kris A Murray
- MRC Unit The Gambia at London School of Hygiene and Tropical Medicine, Fajara, The Gambia
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK
| | - Robert Settlage
- Advanced Research Computing at Virginia Tech Carilion, Roanoke, Virginia, USA
| | - Luis E Escobar
- Department of Fish and Wildlife Conservation, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 24061, USA.
- Global Change Center, Virginia Tech, Blacksburg, VA, USA.
- Center for Emerging Zoonotic and Arthropod-borne Pathogens, Virginia Tech, Blacksburg, VA, USA.
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Abstract
The first full-mission global AVHRR FRAC sea surface temperature (SST) dataset with a nominal 1.1 km resolution at nadir was produced from three Metop First Generation (FG) satellites: Metop-A (2006-on), -B (2012-on) and -C (2018-on), using the NOAA Advanced Clear Sky Processor for Ocean (ACSPO) SST enterprise system. Historical reprocessing (‘Reanalysis-1’, RAN1) starts at the beginning of each mission and continues into near-real time (NRT). ACSPO generates two SST products, one with global regression (GR; highly sensitive to skin SST), and another one with piecewise regression (PWR; proxy for depth SST) algorithms. Small residual effects of orbital and sensor instabilities on SST retrievals are mitigated by retraining the regression coefficients daily, using matchups with drifting and tropical moored buoys within moving time windows. In RAN, the training windows are centered at the processed day. In NRT, the same size windows are employed but delayed in time, ending four to ten days prior to the processed day. Delayed-mode RAN reprocessing follows the NRT with a two-month lag, resulting in a higher quality and a more consistent SST record. In addition to its completeness, the newly created Metop-FG RAN1 SST dataset shows very close agreement with in situ data (including the fully independent Argo floats), well within the NOAA specifications for accuracy (global mean bias; ±0.2 K) and precision (global standard deviation; 0.6 K) in a ~20% clear-sky domain (percent of clear-sky SST pixels to the total of ice-free ocean). All performance statistics are stable in time, and consistent across the three platforms. The Metop-FG RAN1 data set is archived at the NASA JPL PO.DAAC and NOAA NCEI. This paper documents the newly created dataset and evaluates its performance.
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12
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Oil Spills or Look-Alikes? Classification Rank of Surface Ocean Slick Signatures in Satellite Data. REMOTE SENSING 2021. [DOI: 10.3390/rs13173466] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Linear discriminant analysis (LDA) is a mathematically robust multivariate data analysis approach that is sometimes used for surface oil slick signature classification. Our goal is to rank the effectiveness of LDAs to differentiate oil spills from look-alike slicks. We explored multiple combinations of (i) variables (size information, Meteorological-Oceanographic (metoc), geo-location parameters) and (ii) data transformations (non-transformed, cube root, log10). Active and passive satellite-based measurements of RADARSAT, QuikSCAT, AVHRR, SeaWiFS, and MODIS were used. Results from two experiments are reported and discussed: (i) an investigation of 60 combinations of several attributes subjected to the same data transformation and (ii) a survey of 54 other data combinations of three selected variables subjected to different data transformations. In Experiment 1, the best discrimination was reached using ten cube-transformed attributes: ~85% overall accuracy using six pieces of size information, three metoc variables, and one geo-location parameter. In Experiment 2, two combinations of three variables tied as the most effective: ~81% of overall accuracy using area (log transformed), length-to-width ratio (log- or cube-transformed), and number of feature parts (non-transformed). After verifying the classification accuracy of 114 algorithms by comparing with expert interpretations, we concluded that applying different data transformations and accounting for metoc and geo-location attributes optimizes the accuracies of binary classifiers (oil spill vs. look-alike slicks) using the simple LDA technique.
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Abstract
Fengyun-3C (FY-3C) is a second-generation meteorological satellite of China that was launched on 23 September 2013. The on board Visible and Infrared Radiometer (VIRR) can be used to observe global sea surface temperature (SST). In this paper, the VIRR SST products are compared with MODIS SST products and buoy measurements from 2015 to 2019. The collocations of VIRR, MODIS, and buoy SST are generated separately during the day and night with the spatial window of 0.05° × 0.05°. The comparison results show that the biases of VIRR SST minus buoy SST during the day and night are −0.21 and −0.13 °C with a corresponding robust standard deviation (RSD) of 0.58 and 0.59 °C, respectively. The mean differences between VIRR and MODIS are −0.10 and 0.08 °C with RSDs of 0.53 and 0.58 °C for the daytime and nighttime, respectively. The consistency of VIRR SST accuracy from 2015 to 2019 and the dependence of VIRR SST error on SST and latitude are also investigated.
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Abrahams A, Schlegel RW, Smit AJ. A novel approach to quantify metrics of upwelling intensity, frequency, and duration. PLoS One 2021; 16:e0254026. [PMID: 34237084 PMCID: PMC8266120 DOI: 10.1371/journal.pone.0254026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 06/17/2021] [Indexed: 11/19/2022] Open
Abstract
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. Our findings promote the viability of using SST and wind time series data to detect upwelling signals within coastal upwelling systems. We highlight the importance of high-resolution data products to improve the reliability of such estimates. This study represents an important step towards the development of an objective method for describing the behavior of coastal upwelling systems.
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Affiliation(s)
- Amieroh Abrahams
- Department of Biodiversity and Conservation Biology, University of the Western Cape, Cape Town, South Africa
- * E-mail:
| | | | - Albertus J. Smit
- Department of Biodiversity and Conservation Biology, University of the Western Cape, Cape Town, South Africa
- South African Environmental Observation Network, Elwandle Coastal Node, Port Elizabeth, South Africa
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15
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Tsimara E, Vasilakopoulos P, Koutsidi M, Raitsos DE, Lazaris A, Tzanatos E. An Integrated Traits Resilience Assessment of Mediterranean fisheries landings. J Anim Ecol 2021; 90:2122-2134. [PMID: 34013517 DOI: 10.1111/1365-2656.13533] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 05/14/2021] [Indexed: 11/28/2022]
Abstract
An increasing number of studies have been examining the functional configuration of biological communities or ecosystems using biological traits. Here, we investigated the temporal dynamics and resilience of the traits composition in Mediterranean fisheries landings over 31 years (1985-2015). We transcribed the FAO Mediterranean landings dataset for 101 marine species into a dataset of 23 traits related to the life cycle, distribution, ecology and behaviour. Mediterranean mean Sea Surface Temperature (SST) was evaluated as a potential driver of the traits composition. Trait dynamics were evaluated both individually and holistically by developing an Integrated Traits Resilience Assessment (ITRA). ITRA is a variation of the Integrated Resilience Assessment (IRA), a method to infer resilience dynamics and build stability landscapes of complex natural systems. Changes in landings trait dynamics were documented both for individual traits and for the entire traits 'system', and a relevant regime shift was detected in the second half of the 1990s. The traits system switched to higher optimal temperature, more summer spawning, shorter life span, smaller maximum size, shallower optimal depth and planktivorous diet. This shift was found to be a lagged discontinuous response to sea warming, which gradually eroded the resilience of the original state of the traits system, leading it into a new basin of attraction. The inclusion of ecological/response traits (related to environmental preferences) in our analyses indicates potential mechanisms that explain the observed shift, while changes in functional/effect traits indicate potential impacts on ecosystem functioning. Our findings suggest that changes in the Mediterranean ecosystems are evidently larger than previously thought, with profound implications for the management of this highly impacted sea. .
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Affiliation(s)
- Eleni Tsimara
- Department of Biology, University of Patras, Patras, Greece
| | | | | | - Dionysios E Raitsos
- Department of Biology, National and Kapodistrian University of Athens, Athens, Greece
| | - Alexis Lazaris
- Department of Biology, University of Patras, Patras, Greece
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16
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Parracho AC, Safieddine S, Lezeaux O, Clarisse L, Whitburn S, George M, Prunet P, Clerbaux C. IASI-Derived Sea Surface Temperature Data Set for Climate Studies. EARTH AND SPACE SCIENCE (HOBOKEN, N.J.) 2021; 8:e2020EA001427. [PMID: 34222560 PMCID: PMC8243959 DOI: 10.1029/2020ea001427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 03/10/2021] [Accepted: 03/22/2021] [Indexed: 06/13/2023]
Abstract
Sea surface temperature (SST) is an essential climate variable, that is directly used in climate monitoring. Although satellite measurements can offer continuous global coverage, obtaining a long-term homogeneous satellite-derived SST data set suitable for climate studies based on a single instrument is still a challenge. In this work, we assess a homogeneous SST data set derived from reprocessed Infrared Atmospheric Sounding Interferometer (IASI) level-1 (L1C) radiance data. The SST is computed using Planck's Law and simple atmospheric corrections. We assess the data set using the ERA5 reanalysis and the EUMETSAT-released IASI level-2 SST product. Over the entire period, the reprocessed IASI SST shows a mean global difference with ERA5 close to zero, a mean absolute bias under 0.5°C, with a SD of difference around 0.3°C and a correlation coefficient over 0.99. In addition, the reprocessed data set shows a stable bias and SD, which is an advantage for climate studies. The interannual variability and trends were compared with other SST data sets: ERA5, Hadley Centre's SST (HadISST), and NOAA's Optimal Interpolation SST Analysis (OISSTv2). We found that the reprocessed SST data set is able to capture the patterns of interannual variability well, showing the same areas of high interannual variability (>1.5°C), including over the tropical Pacific in January corresponding to the El Niño Southern Oscillation. Although the period studied is relatively short, we demonstrate that the IASI data set reproduces the same trend patterns found in the other data sets (i.e., cooling trend in the North Atlantic, warming trend over the Mediterranean).
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Affiliation(s)
| | | | | | - Lieven Clarisse
- Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES)Université Libre de Bruxelles (ULB)BrusselsBelgium
| | - Simon Whitburn
- Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES)Université Libre de Bruxelles (ULB)BrusselsBelgium
| | - Maya George
- LATMOS/IPSLUVSQCNRSSorbonne UniversitéParisFrance
| | | | - Cathy Clerbaux
- LATMOS/IPSLUVSQCNRSSorbonne UniversitéParisFrance
- Spectroscopy, Quantum Chemistry and Atmospheric Remote Sensing (SQUARES)Université Libre de Bruxelles (ULB)BrusselsBelgium
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17
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Evaluation of the ABI/GOES-16 SST Product in the Tropical and Southwestern Atlantic Ocean. REMOTE SENSING 2021. [DOI: 10.3390/rs13020192] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Sea surface temperature (SST) is an essential climate variable used for ocean and weather monitoring and forecasting. The NOAA’s next generation geostationary satellite GOES-16 was declared operational at the east position (75°W) in December 2017, carrying onboard an Advanced Baseline Imager (ABI). The hyperspectral ABI sensor now allows SST estimates every 10–15 min at both day and nighttime, with advanced options for cloud screening and water vapor correction. In the present work, we compare the first operational ABI SST product (OSI SAF, 2018) with an in situ match-up database (MDB) across the Tropical and Southwestern Atlantic Ocean, off the Brazilian coast, throughout the year of 2018. The MDB was obtained from two long-term programs, i.e., PIRATA moored buoys (FOLTZ et al., 2016) and PNBoia moored and drifting buoys (MARINHA DO BRASIL, 2017). Separate comparisons were made for each data set, analyzing the uncertainties according to the program (i.e., buoy type and region), satellite SST quality level and influence of diurnal heating. We also compare the ABI product with the OSTIA analysis L4 SST (DONLON et al., 2012) to increment our analyses on the spatio-temporal biases within the study region. The results show that the OSI SAF ABI SST L3C has a mean bias (0.1 °C) and error (RMSE, 0.5 °C) within the GHRSST standards, with an exception being coastal waters off the southeast Brazilian coast (RMSE, 0.65 °C), which are subjected to sharp thermal fronts. The highest biases are for regions/seasons subjected to persistent cloud coverage and high water-vapor content, i.e., the Intertropical and South Atlantic Convergence Zones, as well as highly dynamic frontal zones, i.e., the Brazil Malvinas Confluence Zone, the Subtropical Front and coastal waters. The ABI SST product is suitable for operational use, and applications should explore more deeply the new set of information provided.
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18
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Validation of Satellite Sea Surface Temperatures and Long-Term Trends in Korean Coastal Regions over Past Decades (1982–2018). REMOTE SENSING 2020. [DOI: 10.3390/rs12223742] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Validation of daily Optimum Interpolation Sea Surface Temperature (OISST) data from 1982 to 2018 was performed by comparison with quality-controlled in situ water temperature data from Korea Meteorological Administration moored buoys and Korea Oceanographic Data Center observations in the coastal regions around the Korean Peninsula. In contrast to the relatively high accuracy of the SSTs in the open ocean, the SSTs of the coastal regions exhibited large root-mean-square errors (RMSE) ranging from 0.75 K to 1.99 K and a bias ranging from −0.51 K to 1.27 K, which tended to be amplified towards the coastal lines. The coastal SSTs in the Yellow Sea presented much higher RMSE and bias due to the appearance of cold water on the surface induced by vigorous tidal mixing over shallow bathymetry. The long-term trends of OISSTs were also compared with those of in situ water temperatures over decades. Although the trends of OISSTs deviated from those of in situ temperatures in coastal regions, the spatial patterns of the OISST trends revealed a similar structure to those of in situ temperature trends. The trends of SSTs using satellite data explained about 99% of the trends in in situ temperatures in offshore regions (>25 km from the shoreline). This study discusses the limitations and potential of global SSTs as well as long-term SST trends, especially in Korean coastal regions, considering diverse applications of satellite SSTs and increasing vulnerability to climate change.
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Skin Sea-Surface Temperature from VIIRS on Suomi-NPP—NASA Continuity Retrievals. REMOTE SENSING 2020. [DOI: 10.3390/rs12203369] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Retrievals of skin Sea-Surface Temperature (SSTskin) from the measurements of the Visible Infrared Imaging Radiometer Suite on the Suomi-National Polar-orbiting Partnership satellite are presented and discussed. The algorithms used to derive the SSTskin from the radiometric measurements are given in detail. A number of approaches to assess the accuracy and stability of the Visible Infrared Imaging Radiometer Suite (VIIRS) SSTskin retrievals are reported, and factors including latitude and season, and physical processes in the atmosphere and at the surface are discussed. We conclude that the Suomi National Polar-orbiting Partnership (S-NPP) VIIRS is capable of matching and improving upon the accuracies of SSTskin from the MODISs on Terra and Aqua, and that the VIIRS SSTskin fields have the potential to contribute to the extension of the satellite-derived Climate Data Records of SST into the future.
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20
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High-Resolution Sea Surface Temperatures Derived from Landsat 8: A Study of Submesoscale Frontal Structures on the Pacific Shelf off the Hokkaido Coast, Japan. REMOTE SENSING 2020. [DOI: 10.3390/rs12203326] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Coastal and offshore waters are generally separated by a barrier or “ocean front” on the continental shelf. A basic question arises as to what the representative spatial scale across the front may be. To answer this question, we simply corrected skin sea surface temperatures (SSTs) estimated from Landsat 8 imagery with a resolution of 100 m using skin SSTs estimated from geostationary meteorological satellite Himawari 8 with a resolution of 2 km. We analyzed snapshot images of skin SSTs on 13 October 2016, when we performed a simultaneous ship survey. We focused in particular on submesoscale thermal fronts on the Pacific shelf off the southeastern coast of Hokkaido, Japan. The overall spatial distribution of skin SSTs was consistent between Landsat 8 and Himawari 8; however, the spatial distribution of horizontal gradients of skin SSTs differed greatly between the two datasets. Some parts of strong fronts on the order of 1 °C km−1 were underestimated with Himawari 8, mainly because of low resolution, whereas weak fronts on the order of 0.1 °C km−1 were obscured in the Landsat 8 imagery because the signal-to-noise ratios were low. The widths of the strong fronts were estimated to be 114–461 m via Landsat 8 imagery and 539–1050 m via in situ ship survey. The difference was probably attributable to the difference in measurement depth of the SST, i.e., about 10-μm skin layer by satellite and a few dozen centimeters below the sea surface by the in situ survey. Our results indicated that an ocean model with a grid size of no more than ≤100–200 m is essential for realistic simulation of the frontal structure on the shelf.
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Sarker S, Yadav AK, Akter M, Shahadat Hossain M, Chowdhury SR, Kabir MA, Sharifuzzaman S. Rising temperature and marine plankton community dynamics: Is warming bad? ECOLOGICAL COMPLEXITY 2020. [DOI: 10.1016/j.ecocom.2020.100857] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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22
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SST Comparison of AVHRR and MODIS Time Series in the Western Mediterranean Sea. REMOTE SENSING 2020. [DOI: 10.3390/rs12142241] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Sea Surface Temperature (SST) is a key parameter for understanding atmospheric and oceanic processes. Since the late 1980s, infrared satellite images have been used to complement in situ records for studying the temporal and spatial variability of SST. The Advanced Very High Resolution Radiometer (AVHRR) of the National Oceanic and Atmospheric Administration (NOAA)’s satellite was the first sensor successfully used to compute SST following the development and validation of the atmospheric correction algorithm known as “split-window”. More recently, the MODerate-resolution Imaging Spectroradiometer (MODIS) on board the National Aeronautics and Space Administration (NASA)’s Terra and Aqua satellites, launched in 1999 and 2002, respectively, also provides SST products which can be combined with AVHRR series to complete the analysis of time series. This paper presents a comparison of the monthly SST data derived from both sensors, AVHRR and MODIS, in a series of ten years (2000–2009) in the Western Mediterranean basins. The results showed a high correlation (R2 = 0.99) between the sensors when averaged values at the regional scale were compared. SST obtained from AVHRR were slightly higher (+0.18 °C ± 0.2 °C, on average) than SST from MODIS. The series were most similar during winter and spring (+0.09 °C ± 0.1 °C for January to May) with a greater difference from June to December (+0.24 °C ± 0.2 °C). The comparative analysis showed that the two sensors can be used jointly to estimate long-term trends at the regional scale.
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23
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Inter-Comparisons of Daily Sea Surface Temperatures and In-Situ Temperatures in the Coastal Regions. REMOTE SENSING 2020. [DOI: 10.3390/rs12101592] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
In this study, seven, global, blended, sea surface temperature (SST) analyses, including Operational SST and Sea Ice Analysis (OSTIA), Canadian Meteorological Centre (CMC) analysis, Optimum Interpolation SST (OISST), Remote Sensing System (REMSS) analysis, Multi-scale Ultra-high Resolution SST (MURSST), Merged Satellite and In situ Data Global Daily SST (MGDSST), and Geo-Polar Blended SST (Blended SST) were conducted. In-situ temperature measurements were used for the years 2014–2018, from 35 narrowly-spaced buoys distributed along the Korean Peninsula coast, to investigate how well the SST analyses represent the temperatures at the coastal regions. Contrary to the overall accuracy of the SSTs in the global ocean and offshore regions, the root-mean-square errors for the analyses were relatively large over 1.27 K. Specifically, all SST analyses resulted in warm biases over 0.31 K, which became quite distinctive in the western and the southwestern coastal regions. Investigation of the errors identified relationships with the coastal zones of vigorous tidal mixing, shallow bathymetry, and absence of microwave measurements. Overall, temporal wavelet coherency between in-situ measurements and SST products revealed high coherency of greater than 0.8 in periods longer than 180 days, however, low coherency (<0.5) in the period shorter than 10 days was observed. Inter-comparisons between the SST analyses illustrated clear spatial differences in the correlations at both the coastal regions, along the southwestern coast of the Korean Peninsula and in the frontal regions, and in the marginal seas of the Northwest Pacific. Overall, the results emphasized on the importance of using real-time in-situ measurements as much as possible, to overcome the increasing SST errors in coastal regions.
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24
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High-Resolution Sea Surface Temperature Retrieval from Landsat 8 OLI/TIRS Data at Coastal Regions. REMOTE SENSING 2019. [DOI: 10.3390/rs11222687] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
High-resolution sea surface temperature (SST) images are essential to study the highly variable small-scale oceanic phenomena in a coastal region. Most previous SST algorithms are focused on the low or medium resolution SST from the near polar orbiting or geostationary satellites. The Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) makes it possible to obtain high-resolution SST images of coastal regions. This study performed a matchup procedure between 276 Landsat 8 images and in-situ temperature measurements of buoys off the coast of the Korean Peninsula from April 2013 to August 2017. Using the matchup database, we investigated SST errors for each formulation of the Multi-Channel SST (MCSST) and the Non-Linear SST (NLSST) by considering the satellite zenith angle (SZA) and the first-guess SST. The retrieved SST equations showed a root-mean-square error (RMSE) from 0.59 to 0.72 °C. The smallest errors were found for the NLSST equation that considers the SZA and uses the first-guess SST, compared with the MCSST equations. The SST errors showed characteristic dependences on the atmospheric water vapor, the SZA, and the wind speed. In spite of the narrow swath width of the Landsat 8, the effect of the SZA on the errors was estimated to be significant and considerable for all the formations. Although the coefficients were calculated in the coastal regions around the Korean Peninsula, these coefficients are expected to be feasible for SST retrieval applied to any other parts of the global ocean. This study also addressed the need for high-resolution coastal SST, by emphasizing the usefulness of the high-resolution Landsat 8 OLI/TIRS data for monitoring the small-scale oceanic phenomena in coastal regions.
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Abstract
Coastal upwelling has a significant local impact on marine coastal environment and on marine biology, namely fisheries. This study aims to evaluate climate and environmental changes in upwelling trends between 1950 and 2010. Annual, seasonal and monthly upwelling trends were studied in three different oceanographic areas of the Portuguese coast (northwestern—NW, southwestern—SW, and south—S). Two sea surface temperature datasets, remote sensing (RS: 1985–2009) and International Comprehensive Ocean—Atmosphere Data Set (ICOADS: 1950–2010), were used to estimate an upwelling index (UPWI) based on the difference between offshore and coastal sea surface temperature. Time series analyses reveal similar yearly and monthly trends between datasets A decrease of the UPWI was observed, extending longer than 20 years in the NW (1956–1979) and SW (1956–1994), and 30 years in the S (1956–1994). Analyses of sudden shifts reveal long term weakening and intensification periods of up to 30 years. This means that in the past 60 years a normal climate UPWI occurred along the Portuguese coast. An intensification of UPWI was recorded in recent decades regardless of the areas (RS: 1985–2009). Such an intensification rate (linear increase in UPWI) is only significant in S in recent decades (increase rate: ICOADS = 0.02 °C decade-1; RS = 0.11 °C decade-1) while in NW and SW the increase rate is meaningless. In NW more stable UPWI conditions were recorded, however average UPWI values increased in autumn and winter in NW in recently decades (RS: 1985–2009). An intensification rate of UPWI was recorded during summer (July, August and September) in SW and S in latter decades (RS: 1985–2009). The average UPWI values increased in recent decades in autumn in S. Marked phenological changes were observed in S in summer (before downwelling conditions prevail whilst recently when UPWI regimes prevail) with UPWI seasonal regime in S in recent decades becoming similar to those found in SW and NW. Results of this work can contribute to a better understanding of how upwelling dynamics affect/are correlated with biological data.
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26
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Sea Surface Temperature Retrieval from the First Korean Geostationary Satellite COMS Data: Validation and Error Assessment. REMOTE SENSING 2018. [DOI: 10.3390/rs10121916] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Korea’s first geostationary satellite, the “Communication, Ocean, and Meteorological Satellite” (COMS), has been operating since 2010. The Meteorological Imager (MI), an sensor on-board the COMS, has observed sea-surface radiances for the estimation of sea surface temperature (SST) in the western Pacific Ocean and eastern Indian Ocean. To derive the SST coefficients of COMS, quality-controlled surface drifting buoy data were collected for the period of April 2011 to March 2015. A collocation procedure between COMS/MI data and the surface drifter data produced a matchup database for 4 years from 2011 to 2015. The coefficients for the COMS/MI SST were derived by applying appropriate algorithms, i.e., the Multi-channel SST (MCSST) and Non-linear SST (NLSST) algorithms, for daytime and nighttime data using a regression method. Validation results suggest the possibility of the continuous use of the coefficients as representative SST coefficients of COMS. The estimated SSTs near the edge of a full disk with high satellite zenith angles over 60° revealed relatively large errors compared to drifter temperatures. Most of NLSST formulations exhibited overestimation of SSTs at low SSTs (<10 °C). This study suggests an approach by which SST can be measured accurately in order to contribute to tracking climate change.
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Sea Surface Temperature (SST) Variability of the Eastern Coastal Zone of the Gulf of California. REMOTE SENSING 2018. [DOI: 10.3390/rs10091434] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The coastal zones are areas with a high flow of energy and materials where diverse ecosystems are developed. The study of coastal oceanography is important to understand the variability of these ecosystems and determine their role in biogeochemical cycles and climate change. Sea surface temperature (SST) analysis is indispensable for the characterization of physical and biological processes, and it is affected by processes at diverse timescales. The purpose of this work is to analyze the oceanographic variability of the Eastern Coastal Zone of the Gulf of California through the study of the SST from time series analysis of monthly data obtained from remote sensors (AVHRR-Pathfinder Version 5.1 and Version 5 resolution of 4 km, MODIS-Aqua, resolution of 4 km) for the period 1981 to 2016. The descriptive analysis of SST series showed that the values decrease from south to north, as well as the amplitude of the warm period decrease from south to north (cold period increase from south to north). The minimum values occurred during January and February, and ranged between 18 and 20 °C; and maximum values, of about 32 °C, arose in August and September. Cluster analysis allowed to group the data in four regions (south, center, midriff islands and north), the spectral analysis in each region showed frequencies of variation in scales: Annual (the main), seasonal, semiannual, and interannual. The latter is associated with the El Niño and La Niña climatological phenomena.
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The Effect of Arctic Dust on the Retrieval of Satellite Derived Sea and Ice Surface Temperatures. Sci Rep 2018; 8:9727. [PMID: 29950618 PMCID: PMC6021454 DOI: 10.1038/s41598-018-28024-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 06/08/2018] [Indexed: 11/27/2022] Open
Abstract
Large quantities of dust are transported annually to the Arctic, primarily from Asian deserts. The influx of dust into the polar environment changes the radiative properties of clouds while the deposition of dust onto ice and snow decreases the surface albedo. Atmospheric and surface dust may be identified with space borne radiometers by comparing infrared energy in the 11 μm and 12 μm regime. Between 2007 and 2017 satellite infrared data revealed persistent low-level dust clouds in the vicinity of Amundsen Gulf in the Western Canadian Arctic during the melting season. Evidence suggests that the subsequent deposition of atmospheric dust in the region affected the surface emissivity in the thermal infrared regime. As a result, satellite derived sea and ice surface temperature algorithms were rendered inaccurate in these areas. Moreover, the ubiquitous nature of dust in the region may play a role in the rapidly vanishing cryosphere.
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Schaeffer BA, Iiames J, Dwyer J, Urquhart E, Salls W, Rover J, Seegers B. An initial validation of Landsat 5 and 7 derived surface water temperature for U.S. lakes, reservoirs, and estuaries. INTERNATIONAL JOURNAL OF REMOTE SENSING 2018; 39:7789-7805. [PMID: 36419964 PMCID: PMC9680865 DOI: 10.1080/01431161.2018.1471545] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Accepted: 04/24/2018] [Indexed: 05/28/2023]
Abstract
The United States Harmful Algal Bloom and Hypoxia Research Control Act of 2014 identified the need for forecasting and monitoring harmful algal blooms (HAB) in lakes, reservoirs, and estuaries across the nation. Temperature is a driver in HAB forecasting models that affects both HAB growth rates and toxin production. Therefore, temperature data derived from the U.S. Geological Survey Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus thermal band products were validated across 35 lakes and reservoirs, and 24 estuaries. In situ data from the Water Quality Portal (WQP) were used for validation. The WQP serves data collected by state, federal, and tribal groups. Discrete in situ temperature data included measurements at 11,910 U.S. lakes and reservoirs from 1980 through 2015. Landsat temperature measurements could include 170,240 lakes and reservoirs once an operational product is achieved. The Landsat-derived temperature mean absolute error was 1.34°C in lake pixels >180 m from land, 4.89°C at the land-water boundary, and 1.11°C in estuaries based on comparison against discrete surface in situ measurements. This is the first study to quantify Landsat resolvable U.S. lakes and reservoirs, and large-scale validation of an operational satellite provisional temperature climate data record algorithm. Due to the high performance of open water pixels, Landsat satellite data may supplement traditional in situ sampling by providing data for most U.S. lakes, reservoirs, and estuaries over consistent seasonal intervals (even with cloud cover) for an extended period of record of more than 35 years.
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Affiliation(s)
- Blake A. Schaeffer
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - John Iiames
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - John Dwyer
- U.S. Geological Survey, Center for Earth Resources Observation and Science, Garretson, SD, USA
| | - Erin Urquhart
- Office of Research and Development, Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Wilson Salls
- Office of Research and Development, Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Jennifer Rover
- U.S. Geological Survey, Center for Earth Resources Observation and Science, Garretson, SD, USA
| | - Bridget Seegers
- Goddard Space Flight Center, National Aeronautics Space Administration, Greenbelt, MD, USA
- Goddard Earth Sciences Technology and Research, Universities Space Research Association, Columbia, MD, USA
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An Assessment of Atmospheric and Meteorological Factors Regulating Red Sea Phytoplankton Growth. REMOTE SENSING 2018. [DOI: 10.3390/rs10050673] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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31
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Wedding LM, Lecky J, Gove JM, Walecka HR, Donovan MK, Williams GJ, Jouffray JB, Crowder LB, Erickson A, Falinski K, Friedlander AM, Kappel CV, Kittinger JN, McCoy K, Norström A, Nyström M, Oleson KLL, Stamoulis KA, White C, Selkoe KA. Advancing the integration of spatial data to map human and natural drivers on coral reefs. PLoS One 2018; 13:e0189792. [PMID: 29494613 PMCID: PMC5832214 DOI: 10.1371/journal.pone.0189792] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Accepted: 12/03/2017] [Indexed: 11/18/2022] Open
Abstract
A major challenge for coral reef conservation and management is understanding how a wide range of interacting human and natural drivers cumulatively impact and shape these ecosystems. Despite the importance of understanding these interactions, a methodological framework to synthesize spatially explicit data of such drivers is lacking. To fill this gap, we established a transferable data synthesis methodology to integrate spatial data on environmental and anthropogenic drivers of coral reefs, and applied this methodology to a case study location-the Main Hawaiian Islands (MHI). Environmental drivers were derived from time series (2002-2013) of climatological ranges and anomalies of remotely sensed sea surface temperature, chlorophyll-a, irradiance, and wave power. Anthropogenic drivers were characterized using empirically derived and modeled datasets of spatial fisheries catch, sedimentation, nutrient input, new development, habitat modification, and invasive species. Within our case study system, resulting driver maps showed high spatial heterogeneity across the MHI, with anthropogenic drivers generally greatest and most widespread on O'ahu, where 70% of the state's population resides, while sedimentation and nutrients were dominant in less populated islands. Together, the spatial integration of environmental and anthropogenic driver data described here provides a first-ever synthetic approach to visualize how the drivers of coral reef state vary in space and demonstrates a methodological framework for implementation of this approach in other regions of the world. By quantifying and synthesizing spatial drivers of change on coral reefs, we provide an avenue for further research to understand how drivers determine reef diversity and resilience, which can ultimately inform policies to protect coral reefs.
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Affiliation(s)
- Lisa M. Wedding
- Center for Ocean Solutions, Stanford University, Palo Alto, California, United States of America
| | - Joey Lecky
- Department of Natural Resources and Environmental Management, University of Hawai‘i at Mānoa, Honolulu, Hawai‘i, United States of America
- Ecosystem Sciences Division, NOAA Pacific Islands Fisheries Science Center, Honolulu, Hawai‘i, United States of America
| | - Jamison M. Gove
- Ecosystem Sciences Division, NOAA Pacific Islands Fisheries Science Center, Honolulu, Hawai‘i, United States of America
| | - Hilary R. Walecka
- Center for Ocean Solutions, Stanford University, Palo Alto, California, United States of America
- Bren School of Environmental Science and Management, University of California, Santa Barbara, Santa Barbara, California, United States of America
| | - Mary K. Donovan
- Fisheries Ecology Research Lab, Department of Biology, University of Hawai‘i at Mānoa, Honolulu, Hawai‘i, United States of America
| | | | | | - Larry B. Crowder
- Center for Ocean Solutions, Stanford University, Palo Alto, California, United States of America
| | - Ashley Erickson
- Center for Ocean Solutions, Stanford University, Palo Alto, California, United States of America
| | - Kim Falinski
- Department of Natural Resources and Environmental Management, University of Hawai‘i at Mānoa, Honolulu, Hawai‘i, United States of America
| | - Alan M. Friedlander
- Fisheries Ecology Research Lab, Department of Biology, University of Hawai‘i at Mānoa, Honolulu, Hawai‘i, United States of America
- Pristine Seas, National Geographic Society, Washington, DC, United States of America
| | - Carrie V. Kappel
- National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, Santa Barbara, California, United States of America
| | - John N. Kittinger
- Conservation International, Center for Oceans, Honolulu, Hawai‘i, United States of America
- Arizona State University, Center for Biodiversity Outcomes, Julie Ann Wrigley Global Institute of Sustainability, Tempe, Arizona, United States of America
| | - Kaylyn McCoy
- Fisheries Ecology Research Lab, Department of Biology, University of Hawai‘i at Mānoa, Honolulu, Hawai‘i, United States of America
| | - Albert Norström
- Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden
- Global Economic Dynamics and the Biosphere Academy Programme, Royal Swedish Academy of Sciences, Stockholm, Sweden
| | - Magnus Nyström
- Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden
- Global Economic Dynamics and the Biosphere Academy Programme, Royal Swedish Academy of Sciences, Stockholm, Sweden
| | - Kirsten L. L. Oleson
- Department of Natural Resources and Environmental Management, University of Hawai‘i at Mānoa, Honolulu, Hawai‘i, United States of America
| | - Kostantinos A. Stamoulis
- Fisheries Ecology Research Lab, Department of Biology, University of Hawai‘i at Mānoa, Honolulu, Hawai‘i, United States of America
- Curtin University, Department of Environment and Agriculture, Perth, Australia
| | - Crow White
- Biological Sciences Department, California Polytechnic State University, San Luis Obispo, California, United States of America
| | - Kimberly A. Selkoe
- Bren School of Environmental Science and Management, University of California, Santa Barbara, Santa Barbara, California, United States of America
- National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara, Santa Barbara, California, United States of America
- Hawai‘i Institute of Marine Biology, University of Hawai‘i at Mānoa, Kāne‘ohe, Hawai‘i, United States of America
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Role of El Niño Southern Oscillation (ENSO) Events on Temperature and Salinity Variability in the Agulhas Leakage Region. REMOTE SENSING 2018. [DOI: 10.3390/rs10010127] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
This study explores the relationship between the Agulhas Current system and El Niño Southern Oscillation (ENSO) events. Specifically, it addresses monthly to yearly variations in Agulhas leakage where the Agulhas Current sheds waters into the Atlantic Ocean, in turn affecting meridional overturning circulation (MOC). Sea surface temperature (SST) data from the National Oceanic and Atmospheric Administration’s (NOAA) Advanced Very High Resolution Radiometer (AVHRR) combined with sea surface salinity (SSS) from Soil Moisture Ocean Salinity (SMOS) and Simple Ocean Data Assimilation (SODA) reanalysis are used to explore changes in Agulhas leakage dynamics. Agulhas leakage is anomalously warm in response to El Niño and anomalously cool in response to La Niña. The corresponding SSS signal shows both a primary and secondary signal response. At first, the SSS signal of Agulhas leakage is anomalously fresh in response to El Niño, but this primary signal is replaced by a secondary anomalously saline signal. In response to La Niña, the primary SSS signal of Agulhas leakage is anomalously saline, while the secondary SSS signal is anomalously fresh. The lag between the peak of ENSO and the response in SST and the corresponding primary SSS signal of Agulhas leakage is about 20 months, followed by the secondary SSS signal at a lag of about 26 months. In general, increasing ENSO strength increases the extremes of the resulting anomalous SST and SSS signal and impacts the Agulhas leakage region earlier during El Niño and slightly later during La Niña.
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33
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The Role of Advanced Microwave Scanning Radiometer 2 Channels within an Optimal Estimation Scheme for Sea Surface Temperature. REMOTE SENSING 2018. [DOI: 10.3390/rs10010090] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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34
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Climate Variability and Change: Monitoring Data and Evidence for Increased Coral Bleaching Stress. ECOLOGICAL STUDIES 2018. [DOI: 10.1007/978-3-319-75393-5_4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
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35
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Werdell PJ, McKinna LI, Boss E, Ackleson SG, Craig SE, Gregg WW, Lee Z, Maritorena S, Roesler CS, Rousseaux CS, Stramski D, Sullivan JM, Twardowski MS, Tzortziou M, Zhang X. An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing. PROGRESS IN OCEANOGRAPHY 2018; 160:186-212. [PMID: 30573929 PMCID: PMC6296493 DOI: 10.1016/j.pocean.2018.01.001] [Citation(s) in RCA: 82] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Ocean color measured from satellites provides daily global, synoptic views of spectral waterleaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches.
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Affiliation(s)
| | - Lachlan I.W. McKinna
- NASA Goddard Space Flight Center, Code 616, Greenbelt, MD, USA
- Go2Q Pty Ltd, Sunshine Coast, QLD, Australia
| | - Emmanuel Boss
- School of Marine Sciences, University of Maine, Orono, Maine, USA
| | | | - Susanne E. Craig
- NASA Goddard Space Flight Center, Code 616, Greenbelt, MD, USA
- Universities Space Research Association, Columbia, MD, USA
| | - Watson W. Gregg
- NASA Global Modeling and Assimilation Office, Greenbelt, MD, USA
| | - Zhongping Lee
- School for the Environment, University of Massachusetts Boston, Boston, MA, USA
| | | | - Collin S. Roesler
- Department of Earth and Oceanographic Science, Bowdoin College, Brunswick, ME, USA
| | - Cécile S. Rousseaux
- Universities Space Research Association, Columbia, MD, USA
- NASA Global Modeling and Assimilation Office, Greenbelt, MD, USA
| | - Dariusz Stramski
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA
| | - James M. Sullivan
- Harbor Branch Oceanographic Institute, Florida Atlantic University, Fort Pierce, FL, USA
| | - Michael S. Twardowski
- Harbor Branch Oceanographic Institute, Florida Atlantic University, Fort Pierce, FL, USA
| | - Maria Tzortziou
- Department of Earth and Atmospheric Science, The City College of New York, New York, NY, USA
- NASA Goddard Space Flight Center, Code 614, Greenbelt, MD, USA
| | - Xiaodong Zhang
- Department of Earth System Science and Policy, University of North Dakota, Grand Forks, ND, USA
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36
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Performance Assessment of Tailored Split-Window Coefficients for the Retrieval of Lake Surface Water Temperature from AVHRR Satellite Data. REMOTE SENSING 2017. [DOI: 10.3390/rs9121334] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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37
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Retrieval of Sea Surface Temperature from MODIS Data in Coastal Waters. SUSTAINABILITY 2017. [DOI: 10.3390/su9112032] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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38
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Wang J, Deng Z. Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters. ENVIRONMENTAL MONITORING AND ASSESSMENT 2017; 189:286. [PMID: 28536910 DOI: 10.1007/s10661-017-6010-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2016] [Accepted: 05/15/2017] [Indexed: 06/07/2023]
Abstract
A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.
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Affiliation(s)
- Jiao Wang
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA
| | - Zhiqiang Deng
- Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA.
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39
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Pareeth S, Bresciani M, Buzzi F, Leoni B, Lepori F, Ludovisi A, Morabito G, Adrian R, Neteler M, Salmaso N. Warming trends of perialpine lakes from homogenised time series of historical satellite and in-situ data. THE SCIENCE OF THE TOTAL ENVIRONMENT 2017; 578:417-426. [PMID: 27839756 DOI: 10.1016/j.scitotenv.2016.10.199] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2016] [Revised: 10/25/2016] [Accepted: 10/25/2016] [Indexed: 06/06/2023]
Abstract
The availability of more than thirty years of historical satellite data is a valuable source which could be used as an alternative to the sparse in-situ data. We developed a new homogenised time series of daily day time Lake Surface Water Temperature (LSWT) over the last thirty years (1986-2015) at a spatial resolution of 1km from thirteen polar orbiting satellites. The new homogenisation procedure implemented in this study corrects for the different acquisition times of the satellites standardizing the derived LSWT to 12:00 UTC. In this study, we developed new time series of LSWT for five large lakes in Italy and evaluated the product with in-situ data from the respective lakes. Furthermore, we estimated the long-term annual and summer trends, the temporal coherence of mean LSWT between the lakes, and studied the intra-annual variations and long-term trends from the newly developed LSWT time series. We found a regional warming trend at a rate of 0.017°Cyr-1 annually and 0.032°Cyr-1 during summer. Mean annual and summer LSWT temporal patterns in these lakes were found to be highly coherent. Amidst the reported rapid warming of lakes globally, it is important to understand the long-term variations of surface temperature at a regional scale. This study contributes a new method to derive long-term accurate LSWT for lakes with sparse in-situ data thereby facilitating understanding of regional level changes in lake's surface temperature.
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Affiliation(s)
- Sajid Pareeth
- Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach (FEM), S. Michele all'Adige (Trento), Italy; Department of Biology, Chemistry and Pharmacy, Free University, Berlin, Germany.
| | - Mariano Bresciani
- Optical Remote Sensing-Water group, Istituto per il Rilevamento Elettromagnetico dell'Ambiente IREA - CNR, Milan, Italy
| | | | - Barbara Leoni
- Department of Earth and Environmental Sciences, University of Milan-Bicocca, Milan, Italy
| | - Fabio Lepori
- Institute of Earth Sciences, University of Applied Sciences and Arts of Southern Switzerland, Canobbio, Switzerland
| | - Alessandro Ludovisi
- Dipartimento di Chimica, Biologia e Biotecnologie, Università degli Studi di Perugia, Perugia, Italy
| | | | - Rita Adrian
- Department of Biology, Chemistry and Pharmacy, Free University, Berlin, Germany; Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Berlin, Germany
| | | | - Nico Salmaso
- Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Centre, Fondazione Edmund Mach (FEM), S. Michele all'Adige (Trento), Italy
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40
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A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques. SENSORS 2016; 16:s16081298. [PMID: 27537896 PMCID: PMC5017463 DOI: 10.3390/s16081298] [Citation(s) in RCA: 220] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Revised: 08/01/2016] [Accepted: 08/08/2016] [Indexed: 11/25/2022]
Abstract
Remotely sensed data can reinforce the abilities of water resources researchers and decision makers to monitor waterbodies more effectively. Remote sensing techniques have been widely used to measure the qualitative parameters of waterbodies (i.e., suspended sediments, colored dissolved organic matter (CDOM), chlorophyll-a, and pollutants). A large number of different sensors on board various satellites and other platforms, such as airplanes, are currently used to measure the amount of radiation at different wavelengths reflected from the water’s surface. In this review paper, various properties (spectral, spatial and temporal, etc.) of the more commonly employed spaceborne and airborne sensors are tabulated to be used as a sensor selection guide. Furthermore, this paper investigates the commonly used approaches and sensors employed in evaluating and quantifying the eleven water quality parameters. The parameters include: chlorophyll-a (chl-a), colored dissolved organic matters (CDOM), Secchi disk depth (SDD), turbidity, total suspended sediments (TSS), water temperature (WT), total phosphorus (TP), sea surface salinity (SSS), dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD).
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41
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Homogenised daily lake surface water temperature data generated from multiple satellite sensors: A long-term case study of a large sub-Alpine lake. Sci Rep 2016; 6:31251. [PMID: 27502177 PMCID: PMC4977524 DOI: 10.1038/srep31251] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2016] [Accepted: 07/15/2016] [Indexed: 11/09/2022] Open
Abstract
Availability of remotely sensed multi-spectral images since the 1980’s, which cover three decades of voluminous data could help researchers to study the changing dynamics of bio-physical characteristics of land and water. In this study, we introduce a new methodology to develop homogenised Lake Surface Water Temperature (LSWT) from multiple polar orbiting satellites. Precisely, we developed homogenised 1 km daily LSWT maps covering the last 30 years (1986 to 2015) combining data from 13 satellites. We used a split-window technique to derive LSWT from brightness temperatures and a modified diurnal temperature cycle model to homogenise data which were acquired between 8:00 to 17:00 UTC. Gaps in the temporal LSWT data due to the presence of clouds were filled by applying Harmonic ANalysis of Time Series (HANTS). The satellite derived LSWT maps were validated based on long-term monthly in-situ bulk temperature measurements in Lake Garda, the largest lake in Italy. We found the satellite derived homogenised LSWT being significantly correlated to in-situ data. The new LSWT time series showed a significant annual rate of increase of 0.020 °C yr−1 (*P < 0.05), and of 0.036 °C yr−1 (***P < 0.001) during summer.
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42
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Atwood EC, Englhart S, Lorenz E, Halle W, Wiedemann W, Siegert F. Detection and Characterization of Low Temperature Peat Fires during the 2015 Fire Catastrophe in Indonesia Using a New High-Sensitivity Fire Monitoring Satellite Sensor (FireBird). PLoS One 2016; 11:e0159410. [PMID: 27486664 PMCID: PMC4972419 DOI: 10.1371/journal.pone.0159410] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Accepted: 07/02/2016] [Indexed: 11/18/2022] Open
Abstract
Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2-3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future.
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Affiliation(s)
- Elizabeth C. Atwood
- GeoBio Center, Department of Biology II, Ludwig-Maximilians-Universität Munich, Planegg-Martinsried, Germany
- RSS Remote Sensing Solutions GmbH, Baierbrunn, Germany
| | | | - Eckehard Lorenz
- Institute of Optical Sensor Systems, German Aerospace Center (DLR e.V.), Berlin-Adlershof, Germany
| | - Winfried Halle
- Institute of Optical Sensor Systems, German Aerospace Center (DLR e.V.), Berlin-Adlershof, Germany
| | | | - Florian Siegert
- GeoBio Center, Department of Biology II, Ludwig-Maximilians-Universität Munich, Planegg-Martinsried, Germany
- RSS Remote Sensing Solutions GmbH, Baierbrunn, Germany
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43
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Sensor Stability for SST (3S): Toward Improved Long-Term Characterization of AVHRR Thermal Bands. REMOTE SENSING 2016. [DOI: 10.3390/rs8040346] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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44
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45
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Gove JM, McManus MA, Neuheimer AB, Polovina JJ, Drazen JC, Smith CR, Merrifield MA, Friedlander AM, Ehses JS, Young CW, Dillon AK, Williams GJ. Near-island biological hotspots in barren ocean basins. Nat Commun 2016; 7:10581. [PMID: 26881874 PMCID: PMC4757766 DOI: 10.1038/ncomms10581] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2015] [Accepted: 12/30/2015] [Indexed: 11/09/2022] Open
Abstract
Phytoplankton production drives marine ecosystem trophic-structure and global fisheries yields. Phytoplankton biomass is particularly influential near coral reef islands and atolls that span the oligotrophic tropical oceans. The paradoxical enhancement in phytoplankton near an island-reef ecosystem--Island Mass Effect (IME)--was first documented 60 years ago, yet much remains unknown about the prevalence and drivers of this ecologically important phenomenon. Here we provide the first basin-scale investigation of IME. We show that IME is a near-ubiquitous feature among a majority (91%) of coral reef ecosystems surveyed, creating near-island 'hotspots' of phytoplankton biomass throughout the upper water column. Variations in IME strength are governed by geomorphic type (atoll vs island), bathymetric slope, reef area and local human impacts (for example, human-derived nutrient input). These ocean oases increase nearshore phytoplankton biomass by up to 86% over oceanic conditions, providing basal energetic resources to higher trophic levels that support subsistence-based human populations.
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Affiliation(s)
- Jamison M Gove
- Ecosystems and Oceanography Program, Pacific Islands Fisheries Science Center, 1845 Wasp Blvd Building 176, Honolulu, 96818 Hawaii, USA
| | - Margaret A McManus
- Department of Oceanography, University of Hawai'i at Mānoa, 1000 Pope Road, Marine Sciences Building, Honolulu, 96822 Hawaii, USA
| | - Anna B Neuheimer
- Department of Oceanography, University of Hawai'i at Mānoa, 1000 Pope Road, Marine Sciences Building, Honolulu, 96822 Hawaii, USA
| | - Jeffrey J Polovina
- Ecosystems and Oceanography Program, Pacific Islands Fisheries Science Center, 1845 Wasp Blvd Building 176, Honolulu, 96818 Hawaii, USA
| | - Jeffrey C Drazen
- Department of Oceanography, University of Hawai'i at Mānoa, 1000 Pope Road, Marine Sciences Building, Honolulu, 96822 Hawaii, USA
| | - Craig R Smith
- Department of Oceanography, University of Hawai'i at Mānoa, 1000 Pope Road, Marine Sciences Building, Honolulu, 96822 Hawaii, USA
| | - Mark A Merrifield
- Department of Oceanography, University of Hawai'i at Mānoa, 1000 Pope Road, Marine Sciences Building, Honolulu, 96822 Hawaii, USA.,Joint Institute for Marine and Atmospheric Research, University of Hawai'i at Mānoa, 1000 Pope Road, Marine Sciences Building, Honolulu, 96822 Hawaii, USA
| | - Alan M Friedlander
- Fisheries Ecology Research Laboratory, Department of Biology, University of Hawai'i at Mānoa, 2538 McCarthy Mall, Honolulu, 96822 Hawaii, USA.,Pristine Seas, National Geographic Society, 1145 17th St NW, Washington, DC 20036, USA
| | - Julia S Ehses
- Joint Institute for Marine and Atmospheric Research, University of Hawai'i at Mānoa, 1000 Pope Road, Marine Sciences Building, Honolulu, 96822 Hawaii, USA.,Coral Reef Ecosystem Program, Pacific Islands Fisheries Science Center, 1845 Wasp Blvd Building 176, Honolulu, 96818 Hawaii, USA
| | - Charles W Young
- Joint Institute for Marine and Atmospheric Research, University of Hawai'i at Mānoa, 1000 Pope Road, Marine Sciences Building, Honolulu, 96822 Hawaii, USA.,Coral Reef Ecosystem Program, Pacific Islands Fisheries Science Center, 1845 Wasp Blvd Building 176, Honolulu, 96818 Hawaii, USA
| | - Amanda K Dillon
- Joint Institute for Marine and Atmospheric Research, University of Hawai'i at Mānoa, 1000 Pope Road, Marine Sciences Building, Honolulu, 96822 Hawaii, USA.,Coral Reef Ecosystem Program, Pacific Islands Fisheries Science Center, 1845 Wasp Blvd Building 176, Honolulu, 96818 Hawaii, USA
| | - Gareth J Williams
- Center for Marine Biodiversity and Conservation, Scripps Institution of Oceanography, UC San Diego, 9500 Gilman Drive, La Jolla, 92093 California, USA.,School of Ocean Sciences, Bangor University, Menai Bridge, LL59 5AB Anglesey, UK
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46
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D’Agostini A, Gherardi DFM, Pezzi LP. Connectivity of Marine Protected Areas and Its Relation with Total Kinetic Energy. PLoS One 2015; 10:e0139601. [PMID: 26448650 PMCID: PMC4598093 DOI: 10.1371/journal.pone.0139601] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Accepted: 09/15/2015] [Indexed: 11/18/2022] Open
Abstract
The East Continental Shelf (ECS) of Brazil is a hotspot of endemism and biodiversity of reef biota in the South Atlantic, hosting a number of Marine Protected Areas (MPAs). Connectivity of MPAs through larval dispersal influences recruitment, population dynamics, genetic structure and biogeography in coral reef ecosystems. Connectivity of protected reef ecosystem in the ECS was investigated with a hydrodynamic model (ROMS) forcing an Individual Based Model (IBM—Ichthyop), and used groupers (genus Mycteroperca) as functional group. The hydrodynamic output from ROMS was compared with satellite data and showed good agreement with observed surface fields. Eggs were released, in IBM experiments, from April to September along six years (2002–2007) in five MPAs along the ECS. Intrannual variability in recruitment and self-recruitment of grouper larvae was observed, as well as a negative correlation of these population parameters with total Kinetic Energy (KE) used as a metric of the physical environment. Higher KE leads to increased offshore advection of larvae, reduced total recruitment and connectivity of MPAs. Our results indicate high and uni-directional connectivity between MPAs from north to south influenced by the Brazil Current flowing in the same direction. Results also showed that some MPAs act predominantly as “sink” while others are mainly “source” areas.
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Affiliation(s)
- Andressa D’Agostini
- Remote Sensing Department (DSR), National Institute for Space Research (INPE), São José dos Campos, São Paulo, Brazil
- * E-mail:
| | | | - Luciano Ponzi Pezzi
- Remote Sensing Department (DSR), National Institute for Space Research (INPE), São José dos Campos, São Paulo, Brazil
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47
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Puerta P, Hunsicker ME, Quetglas A, Álvarez-Berastegui D, Esteban A, González M, Hidalgo M. Spatially Explicit Modeling Reveals Cephalopod Distributions Match Contrasting Trophic Pathways in the Western Mediterranean Sea. PLoS One 2015; 10:e0133439. [PMID: 26201075 PMCID: PMC4511516 DOI: 10.1371/journal.pone.0133439] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2015] [Accepted: 06/26/2015] [Indexed: 11/27/2022] Open
Abstract
Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla) and sea surface temperature (SST), and trophic (prey density) conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid) across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents a valuable approach for understanding the spatially variant ecology of cephalopod populations, which is important for fisheries and ecosystem management.
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Affiliation(s)
- Patricia Puerta
- Instituto Español de Oceanografía, Centro Oceanográfico de Baleares, Palma de Mallorca, Islas Baleares, Spain
| | - Mary E. Hunsicker
- National Center for Ecological Analysis and Synthesis, University of California Santa Barbara, Santa Barbara, California, United States of America
| | - Antoni Quetglas
- Instituto Español de Oceanografía, Centro Oceanográfico de Baleares, Palma de Mallorca, Islas Baleares, Spain
| | - Diego Álvarez-Berastegui
- Balearic Islands Coastal Observing and Forecasting System, Palma de Mallorca, Islas Baleares, Spain
| | - Antonio Esteban
- Instituto Español de Oceanografía, Centro Oceanográfico de Murcia, San Pedro del Pinatar, Murcia, Spain
| | - María González
- Instituto Español de Oceanografía, Centro Oceanográfico de Málaga, Fuengirola, Málaga, Spain
| | - Manuel Hidalgo
- Instituto Español de Oceanografía, Centro Oceanográfico de Baleares, Palma de Mallorca, Islas Baleares, Spain
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A global database of lake surface temperatures collected by in situ and satellite methods from 1985-2009. Sci Data 2015; 2:150008. [PMID: 25977814 PMCID: PMC4423389 DOI: 10.1038/sdata.2015.8] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2014] [Accepted: 02/13/2015] [Indexed: 11/25/2022] Open
Abstract
Global environmental change has influenced lake surface temperatures, a key driver of ecosystem structure and function. Recent studies have suggested significant warming of water temperatures in individual lakes across many different regions around the world. However, the spatial and temporal coherence associated with the magnitude of these trends remains unclear. Thus, a global data set of water temperature is required to understand and synthesize global, long-term trends in surface water temperatures of inland bodies of water. We assembled a database of summer lake surface temperatures for 291 lakes collected in situ and/or by satellites for the period 1985–2009. In addition, corresponding climatic drivers (air temperatures, solar radiation, and cloud cover) and geomorphometric characteristics (latitude, longitude, elevation, lake surface area, maximum depth, mean depth, and volume) that influence lake surface temperatures were compiled for each lake. This unique dataset offers an invaluable baseline perspective on global-scale lake thermal conditions as environmental change continues.
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49
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Reef-Scale Thermal Stress Monitoring of Coral Ecosystems: New 5-km Global Products from NOAA Coral Reef Watch. REMOTE SENSING 2014. [DOI: 10.3390/rs61111579] [Citation(s) in RCA: 99] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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50
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Chollett I, Enríquez S, Mumby PJ. Redefining thermal regimes to design reserves for coral reefs in the face of climate change. PLoS One 2014; 9:e110634. [PMID: 25333380 PMCID: PMC4204933 DOI: 10.1371/journal.pone.0110634] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2014] [Accepted: 09/13/2014] [Indexed: 11/18/2022] Open
Abstract
Reef managers cannot fight global warming through mitigation at local scale, but they can use information on thermal patterns to plan for reserve networks that maximize the probability of persistence of their reef system. Here we assess previous methods for the design of reserves for climate change and present a new approach to prioritize areas for conservation that leverages the most desirable properties of previous approaches. The new method moves the science of reserve design for climate change a step forwards by: (1) recognizing the role of seasonal acclimation in increasing the limits of environmental tolerance of corals and ameliorating the bleaching response; (2) using the best proxy for acclimatization currently available; (3) including information from several bleaching events, which frequency is likely to increase in the future; (4) assessing relevant variability at country scales, where most management plans are carried out. We demonstrate the method in Honduras, where a reassessment of the marine spatial plan is in progress.
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Affiliation(s)
- Iliana Chollett
- Marine Spatial Ecology Lab, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
- Marine Spatial Ecology Lab, School of Biological Sciences, Goddard Building, University of Queensland, Brisbane, Australia
- * E-mail:
| | - Susana Enríquez
- Instituto de Ciencias del Mar y Limnología, Universidad Nacional Autónoma de México, Puerto Morelos, México
| | - Peter J. Mumby
- Marine Spatial Ecology Lab, College of Life and Environmental Sciences, University of Exeter, Exeter, United Kingdom
- Marine Spatial Ecology Lab, School of Biological Sciences, Goddard Building, University of Queensland, Brisbane, Australia
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