scholarly journals Spatio-Temporal Complexity analysis of the Sea Surface Temperature in the Philippines

Ocean Science ◽  
2010 ◽  
Vol 6 (4) ◽  
pp. 933-947
Author(s):  
Z. T. Botin ◽  
L. T. David ◽  
R. C. H. del Rosario ◽  
L. Parrott

Abstract. A spatio-temporal complexity (STC) measure which has been previously used to analyze data from terrestrial ecosystems is employed to analyse 21 years of remotely sensed sea-surface temperature (SST) data from the Philippines. STC on the Philippine wide SST showed the monsoonal variability of the Philippine waters. STC is correlated with the SST mean (R2 ≈ 0.7), and inversely correlated with the SST standard deviation (R2 ≈ 0.9). Both STC and SST are highest during the middle of the year, which coincides with the Southwest Monsoon, but with the STC values being higher towards the end of the monsoon until the start of the inter-monsoon. In order to determine if STC has the potential to define limits of bio-regions, the spatial domain was subsequently divided into six thermal regions computed via clustering of temperature means. STC and EOF of the STC values were computed for each thermal region. Our STC analysis of the SST data, and comparisons with SST values suggest that the STC measure may be useful for characterising environmental heterogeneity over space and time for many long-term remotely sensed data.

2009 ◽  
Vol 6 (3) ◽  
pp. 2831-2859
Author(s):  
Z. T. Botin ◽  
L. T. David ◽  
R. C. H. del Rosario ◽  
L. Parrott

Abstract. A spatio-temporal complexity (STC) measure which has been previously used to analyze data from terrestrial ecosystems is employed to analyse 21 years of remotely sensed sea-surface temperature (SST) data from the Philippines. STC on the Philippine wide SST showed the monsoonal variability of the Philippine waters but did not show significant differences between El Niño, La Niña and normal years. The spatial domain was subsequently divided into six thermal regions computed via clustering of temperature means. The STC values of each thermal region showed variations corresponding to the monsoonal shifts – as well as – to ENSO events. STC characterized environmental heterogeneity over space and time has the potential to define limits of bio-regions. The same approach can be utilized for many long-term remotely sensed data.


Author(s):  
Mukti Zainuddin

Skipjack tuna is an important species targeting by pole and line fishery in Bone Bay. The distribution and abundance of this species tended to aggregate to the preferred bio-physical environments. To describe the short term relationship between skipjack tuna and oceanographic conditions and to visualize the predicted high catch areas, remotely sensed satellite based-oceanographic sea surface temperature (SST) and chlorophyll-a together fisheries data were used. Results indicated that the highest skipjack CPUEs were mainly found in coastal areas of Palopo and Kolaka both in 2007 and in 2009 during the period of study. The high tuna concentrations corresponded well with chlorophyll-a of 0.15-0.40 mg mg-3 and SST of 29.0-31.5 °C. The preferred ranges provide a good indicator for initially detecting potential skipjack fishing grounds. This study suggested that thermal and chlorophyll fronts as well as upwelling may important mechanisms in explaining the temporal and spatial dynamics of skipjack tuna distribution and abundance in Bone Bay.Keywords: skipjack tuna, potential fishing grounds, satellite images and fronts


2020 ◽  
Author(s):  
Getachew Bayable Tiruneh ◽  
Gedamu Amare ◽  
Getnet Alemu ◽  
Temesgen Gashaw

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.


2005 ◽  
Vol 62 (3) ◽  
pp. 319-327 ◽  
Author(s):  
Jeffrey J. Polovina ◽  
Evan A. Howell

Abstract Satellite remotely sensed oceanographic data provide reliable global ocean coverage of sea surface temperature, sea surface height, surface winds, and ocean colour, with relatively high spatial and temporal resolution. We illustrate approaches to use these data to construct indicators that describe aspects of ecosystem dynamics in the North Pacific. Specifically, altimetry data are used to construct regional indicators of the ocean vertical structure, ocean colour data to describe the temporal chlorophyll dynamics of the coastal zone, ocean colour, sea surface temperature, and altimetry data to develop indices of biologically important ocean features, and finally altimetry data to drive a larval transport model and develop an index of larval retention. Recent changes in the North Pacific based on these indices are discussed.


Oceanologia ◽  
2016 ◽  
Vol 58 (3) ◽  
pp. 187-195 ◽  
Author(s):  
Jorge O. Pierini ◽  
Michele Lovallo ◽  
Eduardo A. Gómez ◽  
Luciano Telesca

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