Validation of Sea Surface Temperature from GCOM-C Satellite Using iQuam Datasets and MUR-SST in Indonesian Waters

Sea surface temperature (SST) is an important variable in oceanography. One of the SST data can be obtained from the Global Observation Mission-Climate (GCOM-C) satellite. Therefore, this data needs to be validated before being applied in various fields. This study aimed to validate SST data from the GCOM-C satellite in the Indonesian Seas. Validation was performed using the data of Multi-sensor Ultra-high Resolution sea surface temperature (MUR-SST) and in situ sea surface temperature Quality Monitor (iQuam). The data used are the daily GCOM-C SST dataset from January to December 2018, as well as the daily dataset from MUR-SST and iQuam in the same period. The validation process was carried out using the three-way error analysis method. The results showed that the accuracy of the GCOM-C SST was 0.37oC

Empirical Cumulative Distribution Function (ECDF) Analysis of Thunnus.sp Using ARGO Float Sub-surface Multilayer Temperature Data in Indian Ocean South of Java

AbstractSpatial distribution of tuna (Thunnus.sp) in Indian Ocean south of Java has been investigated. Tuna was scientifically known as thermo-conformer species, thus their distribution were strongly influenced by sub-surface temperature. Tuna species in this study comprise of bigeye tuna (Thunnus obesus), albacore tuna (Thunnus alalunga), yellowfin tuna (Thunnus albacares) and southern bluefin tuna (Thunnus maccoyii). The study was conducted in the area between 100oE – 127oE and 7oS – 20oS during 2013 covering of southeast monsoon (April – September) and northwest monsoon (October – March) data. About 1200 coordinate of ARGO Float data and actual catch of tuna from fishing fleet in the same day were processed to obtain the polynomial equation and correlation coefficient. ARGO Float data were processed using kriging method. Correlation coefficient method that used in the study was Empirical Cumulative Distribution Function (ECDF), while spatial distribution equation was developed by polynomial regression equation. Sub-surface temperature in Indian Ocean south of Java fluctuates seasonally. Temporal distribution of dataset indicates that sub-surface temperature was warmer in northwest monsoon than in southeast monsoon. Seasonal fluctuation of sub-surface temperature may vary due to occurrence of upwelling. T. alalunga, T. Albacares and T. Obesus were found to be more favour in the depth around 150m with optimum temperature between 16oC – 21oC, while T. maccoyii were found in the dept around 250m with optimum temperature between 13oC – 16oC. Potential fishing zone for Thunnus.sp in southeast monsoon was wider than in northwest monsoon. This condition was according to seasonal variability of sub-surface temperature

Bali Strait‘s Potential Fishing Zone of Sardinella lemuru

Catch fluctuation of Sardinella lemuru in the Bali Strait in the period 2007 - 2019 shows a significant decrease. The fishermen of this area demanded information on the Potential Fishing Zone (PFZ) specifically targeted for Sardinella lemuru beyond their traditional. PFZ will be very helpful, especially during the famine years. Identification of a Potential Fishing Zone (PFZ) is highly important for increased fishing yields and also reduced fishing time for fishermen. Bali strait is dominated by Sardinella lemuru and contributes 16,2% of the total small pelagic fishery production in Fisheries Management Area (FMA) 573. Bali Strait also supports the fishing industry in Muncar (Banyuwangi-East Java) and Pengambengan (Jembrana-Bali). This study will produce a special PFZ for Sardinella lemuru that is not yet available in Indonesia by using remotely sensed and observer data. Here, we apply the Empirical Cumulative Distribution Function (ECDF) algorithm approach for Sardinella lemuru detection. ECDF was developed using Sea Surface Temperature (SST) and Chlorophyll-a (Chl-a) data from Aqua MODIS and extracted according to observer data during 2011-2014. PFZ for Sardinella lemuru in Bali strait was affected by 72,8 % Chl-a conditions and 27,2% by SST conditions. The maximum suitable preference for Sardinella lemuru in Bali Strait is Chl-a condition at 0,2 mg/m3 and SST condition at 28,38°C in northwest monsoon, while in southeast monsoon are 0,97 mg/m3 for Chl-a and 25,61°C for SST. ECDF model result has 69,33% accuracy, which shows the result of Sardinella lemuru PFZ has good accuracy

THREE-WAY ERROR ANALYSIS OF SEA SURFACE TEMPERATURE (SST) BETWEEN HIMAWARI-8, BUOY, AND MUR SST IN SAVU SEA

Variance errors of Himawari-8, buoy, and Multi-scale Ultra-high Resolution (MUR) SST in Savu Sea have been investigated. This research used level 3 Himawari-8 hourly SST, in situ measurement of buoy, and daily MUR SST in the period of December 2016 to July 2017. The data were separated into day time data and night time. Skin temperature of Himawari-8 and subskin tempertaure of MUR SST were corrected with the value of 15∆Tdept">  before compared with buoy data. Hourly SST of Himawari-8 and buoy data were converted to daily format by averaging process before collocated with MUR SST data. The number of 2,264 matchup data are obtained. Differences average between Himawari-8, buoy and MUR SST were calculated to get the value of variance (Vij).  Using three-way error analysis, variance errors of each observation type can be known. From the analysis results can be seen that the variance error of Himawari-8, buoy and MUR SST are 2.5 oC, 0.28oC and 1.21oC respectively. The accuracy of buoy data was better than the other. With a small variance errors, thus buoy data can be used as a reference data for validation of SST from different observation type

ANALISIS MULTILAYER VARIABILITAS UPWELLING DI PERAIRAN SELATAN JAWA

 Variabilitas upwelling di perairan selatan Jawa telah diidentifikasi. Analisis multilayer dilakukan dengan menggunakan data ARGO Float. Variabilitas suhu permukaan laut (SPL) dan klorofil-a (klor-a) dianalisis dengan menggunakan data satelit MODIS Aqua. Pengaruh El Nino Southern Oscillation (ENSO) terhadap upwelling dilakukan dengan menggunakan indeks Oceanic Nino Index (ONI), sedangkan pengaruh Indian Ocean Dipole (IOD) direpresentasikan dengan menggunakan indeks Dipole Mode Index (DMI). Dari hasil penelitian diketahui bahwa ENSO mempengaruhi intensitas upwelling. Pada periode el nino intensitas upwelling mengalami peningkatan yang diikuti oleh penurunan SPL dan naiknya konsentrasi klor-a, sebaliknya pada periode la nina terjadi penurunan intensitas upwelling yang diikuti naiknya SPL dan turunnya konsentrasi klor-a. Peningkatan intensitas upwelling juga terdeteksi pada saat terjadi periode IOD positif, sedangkan penurunan intensitas upwelling terjadi pada periode IOD negatif.

ANALISIS PENERAPAN METODE GAP FILLING UNTUK OPTIMALISASI PEROLEHAN DATA SUHU PERMUKAAN LAUT BEBAS AWAN DI SELAT BALI

Sea Surface Temperature (SST) sensed from infrared satellite sensors has a limitation caused by clouds cover. This limitation affects SST data to be not optimal because there are many empty areas without SST information. Gap Filling is a simple method for combining multitemporal satellite data to generate cloud free data. This research will apply Gap Filling method from two SST data, namely Himawari-8 and Multiscale Ultrahigh Resolution Sea Surface Temperature (MUR-SST). Cloud free daily SST data generated by this method has ~2 Km spatial resolution and daily temporal resolution. Validation of cloud-free SST data using in situ measurement data shows Mean Absolute Deviation (MAD) value 0.29 is smaller than MAD value from MUR-SST and Himawari-8 data. High correlation between cloud free SST data and insitu data is reflected from Kendall's Tau correlation value of 0.7966 or 79.66% and R2 with 0.93 value. These results indicate that the cloud free daily SST data can be used as valid estimation of SST condition in Bali Strait

Karakteristik Oseanografis Teluk Senggrong Banyuwangi

Penelitian ini ditujukan untuk mengetahui karakteristik oseanografis teluk Senggrong.  Data yang digunakan meliputi suhu permukaan laut, konsentrasi klorofil-a,  salinitas dan pH baik musim barat maupun musim timur.  Data time series suhu permukaan laut dan klorofil-a menggunakan data dari satelit Aqua dan Terra dengan sensor Moderate Resolution Imaging Spectroradiometer (MODIS) tahun 2007 hingga 2018. Data insitu teluk Senggrong diperoleh dari pengukuran langsung yang dilakukan pada bulan April  dan bulan September  dengan menggunakan water quality checker (WQC). Untuk menampilkan distribusi spasial masing-masing variabel dilakukan interpolasi Krigging. Hasil penelitian menunjukan bahwa karakteristik oseanografis teluk Senggrong dipengaruhi oleh perubahan musim baik musim barat maupun musim timur.  Suhu permukaan laut pada musim barat relatif lebih tinggi dibandingkan pada musim timur. Konsentrasi klorofil-a pada musim barat lebih rendah daripada musim timur. Salinitas pada musim barat lebih rendah dibandingkan pada musim timur, sedangkan pH pada musim barat lebih tinggi daripada musim timur. Pada musim barat teluk Senggrong memiliki suhu permukaan laut antara 28,1 ℃ – 31,6 ℃, konsentrasi klorofil-a sekitar 0,2 mg/m3– 0,5 mg/m3, salinitas sebesar 32 ppm – 33 ppm dan pH berkisar 8,4 – 8,7. Sedangkan pada musim timur suhu permukaan laut berkisar antara 24,9 ℃ – 30,7℃, konsentrasi klorofil-a sebesar 0,1 mg/m3 – 3,5 mg/m3, salinitas antara 34 ppm – 35 ppm dan pH sekitar 7,5 – 8,3.