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 Assessment of chlorophyll-a and sea surface temperature variability around the Mascarene Plateau, Nazareth Bank (Mauritius) using satellite data

2017 ◽  
Vol 64 (4) ◽  
Author(s):  
V. Ramchandur ◽  
Soonil D. D. V. Rughooputh ◽  
R. Boojawon ◽  
B. A. Motah
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Satellite Data ◽  
Phytoplankton Biomass ◽  
Winter Season ◽  
Sea Surface ◽  
Chl A ◽  
The Past ◽  
Western Side

The Mascarene Plateau is characterised by shallow banks namely Saya de Malha and Nazareth which are known to harbour high phytoplankton biomass along the slope down to the ridge. Correlation between sea surface temperature (SST) and Chlorophyll-a (Chl-a) distribution surrounding the plateau was investigated. Higher Chl-a concentration was observed during the period July to September, indicating higher productivity due to upwelling. The regions east (61-630E) and west (57-590E) of the Mascarene Plateau were also studied along latitudes 130S up to 180S in the exclusive economic zone of Mauritius, where most of the fishing activities are concentrated. In general, 2008 was observed to be less warm during the past 14 years registering a drop with respect to the maximum monthly mean records, whilst 2006 was the most productive during winter season in the region of study. Chl-a bloom was observed after cyclone Imelda in April 2013 showing Chl-a concentration above 0.3 mg m-3 along latitude 130S and longitude 570E. The study reveals that the western side of the plateau is more productive with relatively warmer surface temperature compared to the eastern side of the plateau.

scholarly journals STUDY ON CYCLONE INDUCED PHYTOPLANKTON BLOOM IN THE ARABIAN SEA THROUGH GAP-FREE RECONSTRUCTED CHLOROPHYLL-A DATA

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1391-1396
Author(s):  
R. Shunmugapandi ◽  
S. Gedam ◽  
A. B. Inamdar
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Arabian Sea ◽  
Phytoplankton Bloom ◽  
Suitable Condition ◽  
Sea Surface ◽  
Cyclone Track ◽  
Chl A ◽  
The Impact

Abstract. Ocean surface phytoplankton responses to the tropical cyclone (TC)/storms have been extensively studied using satellite observations by aggregating the data into a weekly or bi-weekly composite. The reason behind is the significant limitations found in the satellite-based observation is the missing of valid data due to cloud cover, especially at the time of cyclone track passage. The data loss during the cyclone is found to be a significant barrier to efficiently investigate the response of chl-a and SST during cyclone track passage. Therefore it is necessary to rectify the above limitation to effectively study the impact of TC on the chlorophyll-a concentration (chl-a) and the sea surface temperature (SST) to achieve a complete understanding of their response to the TC prevailed in the Arabian Sea. Intending to resolve the limitation mentioned above, this study aims to reconstruct the MODIS-Aqua chl-a, and SST data using Data Interpolating Empirical Orthogonal Function (DINEOF) for all the 31 cyclonic events occurred in the Arabian Sea during 2003-2018 (16 years). Reconstructed satellite retrieved data covering all the cyclonic events were further used to investigate the chl-a and SST dynamics during TC. From the results, the exciting fact has been identified that only two TC over the eastern-AS were able to induce phytoplankton bloom. On investigating this scenario using sea surface temperature, it was disclosed that the availability of nutrients decides the suitable condition for the phytoplankton to proliferate in the surface ocean. Relevant to the precedent criterion, the results witnessed that the 2 TC (Phyan and Ockhi cyclone) prevailed in the eastern AS invoked a suitable condition for phytoplankton bloom. Other TC found to be less provocative either due to less intensity, origination region or the unsuitable condition. Thereby, gap-free reconstructed daily satellite-derived data efficiently investigates the response of bio-geophysical parameters during cyclonic events. Moreover, this study sensitised that though several TC strikes the AS, only two could impact phytoplankton productivity and SST found to highly consistent with the chl-a variability during the cyclone passage.

scholarly journals Spatio-Temporal Variability and Trend of Rainfall and Its Association with Pacific Ocean Sea Surface Temperature in West Harerge Zone, Eastern Ethiopia

2020 ◽  
Author(s):  
Getachew Bayable Tiruneh ◽  
Gedamu Amare ◽  
Getnet Alemu ◽  
Temesgen Gashaw
Keyword(s):  
Pacific Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temporal Variability ◽  
Rainfall Variability ◽  
Sea Surface ◽  
Annual Rainfall ◽  
Eastern Ethiopia ◽  
Spatio Temporal ◽  
Annual Time

Abstract Background: Rainfall variability is a common characteristic in Ethiopia and it exceedingly affects agriculture particularly in the eastern parts of the country where rainfall is relatively scarce. Hence, understanding the spatio-temporal variability of rainfall is indispensable for planning mitigation measures during high and low rainfall seasons. This study examined the spatio-temporal variability and trends of rainfall in the West Harerge Zone, eastern Ethiopia.Method: The coefficient of variation (CV) and standardized anomaly index (SAI) was employed to analyze rainfall variability while Mann-Kendall (MK) trend test and Sen’s slop estimator were employed to examine the trend and magnitude of the rainfall changes, respectively. The association between rainfall and Pacific Ocean Sea Surface Temperature (SST) was also evaluated by the Pearson correlation coefficient (r).Results: The annual rainfall CV ranges from 12-19.36% while the seasonal rainfall CV extends from 15-28.49%, 24-35.58%, and 38-75.9% for average Kiremt (June-September), Belg (February-May), and Bega (October-January) seasons, respectively (1983-2019). On the monthly basis, the trends of rainfall decreased in all months except in July, October, and November. However, the trends of rainfall were not statistically significant (α = 0.05), unlike November. The annual rainfall trends showed a non-significant decreasing trend. On a seasonal basis, the trend of mean Kiremt and Belg seasons rainfall was decreased. But, it increased in Bega season although it was not statistically significant. Moreover, the correlation between rainfall and Pacific Ocean SST was negative for Kiremt while positive for Belg and Bega seasons. Besides, the correlation between rainfall and Pacific Ocean SST was negative at annual time scales.Conclusions: High spatial and temporal rainfall variability on monthly, seasonal, and annual time scales was observed in the study area. Seasonal rainfall has high inter-annual variability in the dry season (Bega) than other seasons. The trends in rainfall were decreased in most of the months. Besides, the trend of rainfall was increased annually and in the Bega season rather than other seasons. Generally, the occurrence of droughts in the study area was associated with ENSO events like most other parts of Ethiopia and East Africa.

scholarly journals VARIABILITY OF SEA SURFACE TEMPERATURE (SST) AND CHLOROPHYLL-A (CHL-A) CONCENTRATIONS IN THE EASTERN INDIAN OCEAN DURING THE PERIOD 2002–2017

2019 ◽  
Vol 16 (1) ◽  
pp. 55
Author(s):  
Michelia Mashita ◽  
Jonson Lumban-Gaol
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Sea Surface ◽  
Asia Pacific ◽  
Eastern Indian Ocean ◽  
Positive Anomaly ◽  
Chl A ◽  
Annual Variability

We analysed the variability of sea surface temperature (SST) and chlorophyll-a concentration (Chl-a) in the eastern Indian Ocean (EIO). We used monthly mean Chl-a and SST data with a 4-km spatial resolution derived from Level-3 Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) distributed by the Asia-Pacific Data-Research Center (APDRC) for the period 2002–2017. Wavelet analysis shows the annual and interannual variability of SST and Chl-a concentration in the EIO. The annual variability of SST and Chl-a is influenced by monsoon systems. During a southeast monsoon, SST falls while Chl-a increases due to upwelling. The annual variability of SST and Chl-a is also influenced by the Indian Ocean Dipole (IOD). During positive phases of the IOD (2006, 2012 and 2015), there was more intense upwelling in the EIO caused by the negative anomaly of SST and the positive anomaly of Chl-a concentration.

scholarly journals MONITORING CHLOROPHYLL-A AND SEA SURFACE TEMPERATURE WITH SATELLITE DATA DERIVED FROM MULTIPLE SENSORS

2021 ◽  
Vol XLIII-B3-2021 ◽  
pp. 515-520
Author(s):  
A. Tuzcu Kokal ◽  
N. Musaoğlu
Keyword(s):  
Water Quality ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Temporal Resolution ◽  
Satellite Data ◽  
Sea Surface ◽  
High Temporal Resolution ◽  
Landsat Images ◽  
Combined Data

Abstract. Water is an essential natural source for human being and environment. To conserve water sources, monitoring them by using remote sensing data and technologies is an efficient way. In this study, water quality of the Sea of Marmara (Turkey), which has lots of currents, was examined. The main aim of the study was developing a common model to monitor chlorophyll-a concentration in time by using satellite data. After, the coefficients of the OC2 (ocean chlorophyll 2) model were detected by curve fitting, it was applied to Landsat images. The bias and RMSE (Root Mean Square Error) were found as 0.73 µg/l and 5.80 µg/l, respectively. The high RMSE was stemmed from dynamic structure of the sea. Thus, the temporal resolution has a profound impact on the accuracy of estimations. The developed model was applied to the HLS (Harmonized Landsat Sentinel-2) data, which has high temporal resolution. The results of the HLS and Landsat images were compared, and HLS is found as proper to monitor the water quality. The combined data (SST (Sea Surface Temperature) daily data from 1981 to present derived from satellite observations Level-4 product) was used for the secondary aim of the study which was monitoring SST. The bias and RMSE of the data, which was acquired on 19.07.2017, were found as 0.33 °C and 1.12 °C, respectively. The bias and RMSE of the data, which was acquired on 18.07.2018, were found as −0.02 °C and 1.03 °C, respectively. The combined data is found appropriate to monitor the SST.

Sea surface temperature spatio-temporal variability in the Azores using a new technique to remove invalid pixels

2004 ◽  
Author(s):  
Virginie Lafon ◽  
Ana Martins ◽  
Igor Bashmachnikov ◽  
Margarida Melo-Rodrigues ◽  
Miguel Figueiredo
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Temporal Variability ◽  
Sea Surface ◽  
New Technique ◽  
Spatio Temporal ◽  
A New Technique
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