scholarly journals Effects of Spring–Neap Tidal Cycle on Spatial and Temporal Variability of Satellite Chlorophyll-A in a Macrotidal Embayment, Ariake Sea, Japan

2020 ◽  
Vol 12 (11) ◽  
pp. 1859
Author(s):  
Mengmeng Yang ◽  
Joaquim I. Goes ◽  
Hongzhen Tian ◽  
Elígio de R. Maúre ◽  
Joji Ishizaka
Keyword(s):  
Chlorophyll A ◽  
Temporal Variability ◽  
Tidal Cycle ◽  
Ocean Color ◽  
Spatial And Temporal Variability ◽  
Ariake Sea ◽  
Chl A ◽  
Moderate Resolution ◽  
Spatio Temporal ◽  
Moderate Resolution Imaging Spectroradiometer

We investigated the spatio-temporal variability of chlorophyll-a (Chl-a) and total suspended matter (TSM) associated with spring–neap tidal cycles in the Ariake Sea, Japan. Our study relied on significantly improved, regionally-tuned datasets derived from the ocean color sensor Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua over a 16-year period (2002–2017). The results revealed that spring–neap tidal variations in Chl-a and TSM within this macrotidal embayment (the Ariake Sea) are clearly different regionally and seasonally. Generally, the spring–neap tidal variability of Chl-a in the inner part of the Ariake Sea was controlled by TSM for seasons other than summer, whereas it was controlled by river discharge for summer. On the other hand, the contribution of TSM to the variability of Chl-a was not large for two areas in the middle of Ariake Sea where TSM was not abundant. This study demonstrates that ocean color satellite observations of Chl-a and TSM in the macrotidal embayment offer strong advantages for understanding the variations during the spring–neap tidal cycle.

scholarly journals Spatio-Temporal Variability of Chlorophyll-A and Environmental Variables in the Panama Bight

2020 ◽  
Vol 12 (13) ◽  
pp. 2150
Author(s):  
Andrea Corredor-Acosta ◽  
Náyade Cortés-Chong ◽  
Alberto Acosta ◽  
Matias Pizarro-Koch ◽  
Andrés Vargas ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Satellite Data ◽  
Temporal Variability ◽  
Phytoplankton Growth ◽  
Sea Surface ◽  
Chl A ◽  
Physical Variables ◽  
Spatio Temporal

The analysis of synoptic satellite data of total chlorophyll-a (Chl-a) and the environmental drivers that influence nutrient and light availability for phytoplankton growth allows us to understand the spatio-temporal variability of phytoplankton biomass. In the Panama Bight Tropical region (PB; 1–9°N, 79–84°W), the spatial distribution of Chl-a is mostly related to the seasonal wind patterns and the intensity of localized upwelling centers. However, the association between the Chl-a and different physical variables and nutrient availability is still not fully assessed. In this study, we evaluate the relationship between the Chl-a and multiple physical (wind, Ekman pumping, geostrophic circulation, mixed layer depth, sea level anomalies, river discharges, sea surface temperature, and photosynthetically available radiation) and chemical (nutrients) drivers in order to explain the spatio-temporal Chl-a variability in the PB. We used satellite data of Chl-a and physical variables, and a re-analysis of a biogeochemical product for nutrients (2002–2016). Our results show that at the regional scale, the Chl-a varies seasonally in response to the wind forcing and sea surface temperature. However, in the coastal areas (mainly Gulf of Panama and off central-southern Colombia), the maximum non-seasonal Chl-a values are found in association with the availability of nutrients by river discharges, localized upwelling centers and the geostrophic circulation field. From this study, we infer that the interplay among these physical-chemical drivers is crucial for supporting the phytoplankton growth and the high biodiversity of the PB region.

scholarly journals Spatial and temporal variability of surface chlorophyll-a in the Gulf of Tomini, Sulawesi, Indonesia

2018 ◽  
Vol 19 (3) ◽  
pp. 793-801 ◽  
Author(s):  
QURNIA WULAN SARI ◽  
EKO SISWANTO ◽  
DEDI SETIABUDIDAYA ◽  
INDRA YUSTIAN ◽  
ISKHAQ ISKANDAR
Keyword(s):  
Chlorophyll A ◽  
El Niño ◽  
Temporal Variability ◽  
El Nino ◽  
Southern Oscillation ◽  
Surface Wind ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Spatial And Temporal Variability ◽  
Chl A

Sari QW, Siswanto E, Setiabudidaya D, Yustian I, Iskandar I. 2018. Spatial and temporal variability of surface chlorophyll-a in the Gulf of Tomini, Sulawesi, Indonesia. Biodiversitas 19: 793-801. The Gulf of Tomini (GoT) is mostly influenced by seasonal and interannual events. So, the immensive aim of this study is to explore spatial and temporal variations of chlorophyll-a (chl-a) and oceanographic parameters in the GoT under the influences of monsoonal winds, El Niño Southern Oscillation (ENSO), and Indian Ocean Dipole (IOD). The data were collected from the satellite imaging of chl-a and sea and surface temperature (SST) as well as surface wind from the reanalysis data for a period of January 2003 to December 2015. Monthly variations of the chl-a and SST in the GoT reveal chl-a bloom in the center part to the mouth of the GoT during the southeast monsoon season (boreal summer). The chl-a concentrations were relatively higher (>0.1 mg m-3) and distributed throughout most of the areas near the Maluku Sea. The SST in the middle of the GoT was relatively lower than that near the Maluku Sea (the eastern part of the GoT). On the other hand, during the northwest monsoon (boreal winter), the chl-a concentration decreased (<0.1 mg m-3). During this season, the SST was relatively higher (28-29 °C) than that during the boreal summer (27-26 °C) and distributed uniformly. Meanwhile, on interannual timescale, the ENSO and IOD play important role in regulating chl-a distribution in the GoT. High surface chl-a concentration was observed during El Niño and/or positive IOD events. Enhanced surface chl-a concentration during El Niño and/or positive IOD events was associated with the upward Ekman pumping induced by the southeasterly wind anomalies. The situation was reversed during the Niña and/or negative IOD events.

scholarly journals Chlorophyll a Concentration Distribution on the Mainland Coast of the Gulf of California, Mexico

2020 ◽  
Vol 12 (8) ◽  
pp. 1335
Author(s):  
Carlos Manuel Robles-Tamayo ◽  
Ricardo García-Morales ◽  
José Eduardo Valdez-Holguín ◽  
Gudelia Figueroa-Preciado ◽  
Hugo Herrera-Cervantes ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Gulf Of California ◽  
Concentration Distribution ◽  
Trophic State Index ◽  
Coastal Zones ◽  
Study Region ◽  
Chl A ◽  
Moderate Resolution ◽  
State Index ◽  
Moderate Resolution Imaging Spectroradiometer

Coastal zones are important areas for the development of diverse ecosystems. The analysis of chlorophyll a (Chl a), as an indicator of primary production in these regions, is crucial for the quantification of phytoplankton biomass, which is considered the main food chain base in the oceans and an indicator of the trophic state index. This variable is greatly important for the analysis of the oceanographic variability, and it is crucial for determining the tendencies of change in these areas with the objective of determining the effects on the ecosystem and the population dynamics of marine resources. In this study, we analysed the Chl a concentration distribution on the mainland coast of the Gulf of California based on the monthly data from July 2002 to July 2019, obtained from remote sensing (Moderate-Resolution Imaging Spectroradiometer Aqua (MODIS-Aqua) with a 9 km resolution). The results showed a clear distribution pattern of Chl a observed along this area with the maximum levels in March and minimum levels in August. A four-region characterisation on this area was used to make a comparison of the Chl a concentrations during warm and cold periods. The majority of the results were statistically significant. The spectral analysis in each of the four regions analysed in this study determined the following variation frequencies: annual, semi-annual, seasonal, and inter-annual; the last was related to the macroscale climatological phenomena El Niño-La Niña affecting the variability of the Chl a concentration in the study region.

scholarly journals Analysis of Spatial and Temporal Variability of the PAR/GHI Ratio and PAR Modeling Based on Two Satellite Estimates

2020 ◽  
Vol 12 (8) ◽  
pp. 1262 ◽  
Author(s):  
Francisco Ferrera-Cobos ◽  
Jose M. Vindel ◽  
Rita X. Valenzuela ◽  
José A. González
Keyword(s):  
Temporal Variability ◽  
Spatial And Temporal Variability ◽  
Mean Square ◽  
Clearness Index ◽  
Active Radiation ◽  
Oceanic Climate ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Using Data

The main objectives of this work are to address the analysis of the spatial and temporal variability of the ratio between photosynthetically active radiation (PAR) and global horizontal irradiance (GHI), as well as to develop PAR models. The analysis was carried out using data from three stations located in mainland Spain covering three climates: oceanic, standard Mediterranean, and continental Mediterranean. The results of this analysis showed a clear dependence between the PAR/GHI ratio and the location; the oceanic climate showed higher values of PAR/GHI compared with Mediterranean climates. Further, the temporal variability of PAR/GHI was conditioned by the variability of clearness index, so it was also higher in oceanic than in Mediterranean climates. On the other hand, Climate Monitoring Satellite Facility (CM-SAF) and Moderate-Resolution Imaging Spectroradiometer (MODIS) data were used to estimate PAR as a function of GHI over the whole territory. The validation with ground measurements showed better performance of the MODIS-estimates-derived model for the oceanic climate (root-mean-square error (RMSE) around 5%), while the model obtained from CM-SAF fitted better for Mediterranean climates (RMSEs around 2%).

scholarly journals Spatial Downscaling of MODIS Chlorophyll-a with Genetic Programming in South Korea

2020 ◽  
Vol 12 (9) ◽  
pp. 1412
Author(s):  
Hamid Mohebzadeh ◽  
Junho Yeom ◽  
Taesam Lee
Keyword(s):  
Genetic Programming ◽  
Chlorophyll A ◽  
Spatial Resolution ◽  
Polynomial Regression ◽  
Ocean Color ◽  
Water Quality Assessment ◽  
Global Scale ◽  
Chl A ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Gp Model

Chlorophyll-a (Chl-a) is one of the major indicators for water quality assessment and recent developments in ocean color remote sensing have greatly improved the ability to monitor Chl-a on a global scale. The coarse spatial resolution is one of the major limitations for most ocean color sensors including Moderate Resolution Imaging Spectroradiometer (MODIS), especially in monitoring the Chl-a concentrations in coastal regions. To improve its spatial resolution, downscaling techniques have been suggested with polynomial regression models. Nevertheless, polynomial regression has some restrictions, including sensitivity to outliers and fixed mathematical forms. Therefore, the current study applied genetic programming (GP) for downscaling Chl-a. The proposed GP model in the current study was compared with multiple polynomial regression (MPR) to different degrees (2nd-, 3rd-, and 4th-degree) to illustrate their performances for downscaling MODIS Chl-a. The obtained results indicate that GP with R2 = 0.927 and RMSE = 0.1642 on the winter day and R2 = 0.763 and RMSE = 0.5274 on the summer day provides higher accuracy on both winter and summer days than all the applied MPR models because the GP model can automatically produce appropriate mathematical equations without any restrictions. In addition, the GP model is the least sensitive model to the changes in the input parameters. The improved downscaling data provide better information to monitor the status of oceanic and coastal marine ecosystems that are also critical for fisheries and fishing farming.

scholarly journals Analysis of the Monthly and Spring-Neap Tidal Variability of Satellite Chlorophyll-a and Total Suspended Matter in a Turbid Coastal Ocean Using the DINEOF Method

2021 ◽  
Vol 13 (4) ◽  
pp. 632
Author(s):  
Mengmeng Yang ◽  
Faisal Ahmed Khan ◽  
Hongzhen Tian ◽  
Qinping Liu
Keyword(s):  
Sea Level ◽  
Satellite Data ◽  
Temporal Variability ◽  
Total Suspended Matter ◽  
Empirical Orthogonal Functions ◽  
Spatial And Temporal Variability ◽  
Ariake Sea ◽  
Orthogonal Functions ◽  
Chl A ◽  
Tidal Variability

Missing spatial data is one of the major concerns associated with the application of satellite data. The Data INterpolating Empirical Orthogonal Functions (DINEOF) method has been proven to be an effective tool for filling spatial gaps in various satellite data products. The Ariake Sea, which is a turbid coastal sea, shows the large spatial and temporal variability of chlorophyll-a (Chl-a) and total suspended matter (TSM). However, ocean color satellite data for this region usually have large gaps, which affects the accurate analysis of Chl-a and TSM variability. In this study, we applied the DINEOF method to fill the missing pixels from the regionally tuned Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua (hereafter, MODIS) Chl-a and MODIS-derived TSM datasets for the period 2002–2017. The validation results showed that the DINEOF reconstructed data were accurate and reliable. Furthermore, the Empirical Orthogonal Functions (EOF) analysis based on the reconstructed data was used to quantitatively analyze the spatial and temporal variability of Chl-a and TSM at both monthly and individual events of spring-neap tidal scales. The first three EOF modes of Chl-a showed seasonal variability mainly caused by precipitation, the sea surface temperature (SST), and river discharge for the first EOF mode and the sea level amplitude for the second. The first three EOF modes of TSM exhibited both seasonal and spring-neap tidal variability. The first and second EOF modes of TSM displayed spring-neap tidal variability caused by the sea level amplitude. The second EOF mode of TSM also showed seasonal variability caused by the sea level amplitude. In this study, we first applied the DINEOF method to reconstruct the satellite data and to capture the major spatial and temporal variability of Chl-a and TSM for the Ariake Sea. Our results demonstrate that the DINEOF method can reconstruct patchy oceanic color datasets and improve spatio-temporal variability analysis.

Spatial and temporal variability and size fractionation of chlorophyll a in the tropical and subtropical Pacific Ocean

2012 ◽  
Vol 31 (3) ◽  
pp. 120-131 ◽  
Author(s):  
Dongsheng Zhang ◽  
Chunsheng Wang ◽  
Zhensheng Liu ◽  
Xuewei Xu ◽  
Xiaogu Wang ◽  
...  
Keyword(s):  
Pacific Ocean ◽  
Chlorophyll A ◽  
Temporal Variability ◽  
Spatial And Temporal Variability ◽  
Size Fractionation

MODIS ocean color product downscaling via spatio-temporal fusion and regression: The case of chlorophyll-a in coastal waters

2018 ◽  
Vol 73 ◽  
pp. 340-361 ◽  
Author(s):  
Shanxin Guo ◽  
Bo Sun ◽  
Hankui K. Zhang ◽  
Jing Liu ◽  
Jinsong Chen ◽  
...  
Keyword(s):  
Chlorophyll A ◽  
Coastal Waters ◽  
Ocean Color ◽  
Spatio Temporal
Sign in / Sign up

Export Citation Format

Share Document