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 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

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 ofbefore 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 typeHlm. 25-3

Analisis Penerapan Metode Gap Filling Untuk Optimalisasi Perolehan Data Suhu Permukaan Laut Bebas Awan Di Selat Bali = Analysis Of The Application Gap Filling Method For Optimization Cloud Free Sea Surface Temperature Data In Bali Strait

Hlm. 55-6