Comparison of Remotely Sensed Wind Data over Sulawesi and Maluku Islands Sea Areas


In order to obtain accurate prediction of ocean wind energy, long term data are needed. However, one data sources might not able to provide long duration data. Therefore, the data need to be combined with other sources of data. However, before combining the data, it is important to compare and validate them to confirm their accuracy. In the present study, wind speed data collected by QuikScat and SSM/I (SSMIS) missions are compared and analyzed. QuikScat data were collected by a satellite with the same name, while Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) data are processed and offered by Remote Sensing System (RSS). SSM/I (SSMIS) are passive microwave radiometers carried onboard Defense Meteorological Satellite Program (DMSP). For the comparison, 5 (five) arbitrary positions over Sulawesi and Maluku islands sea areas are chosen for the analyses. For the evaluation purposes, beside time series of daily data from several chosen positions in research location, several statistical parameters are also computed and compared such as mean, standard deviation, root mean square (RMS), correlation coefficient. 

[1] National Institute for Environmental Studies (NIES), Report on research results for sailing type offshore wind turbine, Makuhari Messe, Japan, October 2007.

[2] K. Takagi, K. Yamamoto, M. Kondo, T. Funaki, and Z. Kawazaki, Conceptual design of a very large mobile structure for the renewable energy plant., Proceedings of the Asia Pacific Workshop on Marine Hydrodynamics, 239–244, (2002).

[3] K. Takagi, Hydroelastic behavior of VLMOS in beam seas, Proceeding of 14th International Offshore and Polar Engineering Conference, Vol. 4, 616–621, (2004).

[4] F. Mahmuddin, M. Idrus, and Hamzah, Analysis of Ocean Wind Energy Density around Sulawesi and Maluku Islands with Scatterometer Data, Energy Procedia, 65, 107–115, (2015).

[5] F. Mahmuddin, M. Idrus, and Hamzah, Analysis of Wind Energy Potential with a Mobile Floating Structure around Sulawesi and Maluku Islands of Indonesia, Proceeding of the 34th Conference on Ocean, Offshore, and Arctic Engineering, 9, 64– 73, (2015).

[6] I. R. Young, S. Zieger, and A. V. Babanin, Development and Application of a Global Satellite Database of Wind And Wave Conditions, Proceeding of the 34th Conference on Ocean, Offshore, and Arctic Engineering, 7, 62–71, (2015).

[7] Remote Sensing System, SSMI/SSMIS, URL at ssmi.

[8] J. Winterfelt, in Comparison of Measured and Simulated Wind Speed Data in the North Atlantic, GKSS Report 2008/2, GKSS-Forschungszentrum, Geesthacht, 2008.