2013AIP conference proceedingsRequires access

Wind-wave simulation in South China Sea: Preliminary results of model evaluation using different wind forcing

Nurul A. idah Abd Rahim, Liew Juneng, Fredolin Tangang

Open publisher page 3 citations

Abstract

Two different sets of wind data QuikSCAT/NCEP scatterometerwind and Climate Forecast System Reanalysis (CFSR) wind were used to evaluate wind-wave characteristic by using the NOAA WaveWatch III during the northeast monsoon. These two datasets have been widely used. The spatial and temporal resolution for both datasets are 0.5° by 0.5° and 6 hourly, respectively. Statistical analyses such as correlation of wind speed, root mean square error (RMSE), bias and correlation coefficient have been carried out in this study. The wind speed and directionof both winds are almost similar for the whole domain. The wind speed correlation of both winds is 0.94. The correlation of significant wave height between QuikSCAT and AWAC data is 0.80 while for CFSR is 0.97. CFSR wind data shows better results compared to QuikSCAT. The lower correlation for the QuickSCAT could be due to the fact that the scatterometer wind is sensitive to rain hence there could be contamination in the QuikSCAT data as precipitation is high during the northeast monsoon.

About this research paper

What this paper is about

Two different sets of wind data QuikSCAT/NCEP scatterometerwind and Climate Forecast System Reanalysis (CFSR) wind were used to evaluate wind-wave characteristic by using the NOAA WaveWatch III during the northeast monsoon. These two datasets have been widely used. The spatial and temporal resolution for both datasets are 0.5° by 0.5° and 6 hourly, respectively. Statistical analyses such as correlation of wind speed, root mean square error (RMSE), bias and correlation coefficient have been carried out in this study. The wind speed and directionof both winds are almost similar for the whole domain. The wind speed correlation of both winds is 0.94. The correlation of significant wave height between QuikSCAT and AWAC data is 0.80 while for CFSR is 0.97. CFSR wind data shows better results compared to QuikSCAT. The lower correlation for the QuickSCAT could be due to the fact that the scatterometer wind is sensitive to rain hence there could be contamination in the QuikSCAT data as precipitation is high during the northeast monsoon.

Why it matters

OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Two different sets of wind data QuikSCAT/NCEP scatterometerwind and Climate Forecast System Reanalysis (CFSR) wind were used to evaluate wind-wave characteristic by using the NOAA WaveWatch III during the northeast monsoon. These two datasets have been widely used. The spatial and temporal resolution for both datasets are 0.5° by 0.5° and 6 hourly, respectively. Statistical analyses such as correlation of wind speed, root mean square error (RMSE), bias and correlation coefficient have been carried out in this study. The wind speed and directionof both winds are almost similar for the whole domain. The wind speed correlation of both winds is 0.94. The correlation of significant wave height between QuikSCAT and AWAC data is 0.80 while for CFSR is 0.97. CFSR wind data shows better results compared to QuikSCAT. The lower correlation for the QuickSCAT could be due to the fact that the scatterometer wind is sensitive to rain hence there could be contamination in the QuikSCAT data as precipitation is high during the northeast monsoon.

Key concepts: Scatterometer, Environmental science, Wind speed, Climatology, Correlation coefficient, Climate Forecast System, Forcing (mathematics), Meteorology

Related papers

Back to paper searchBrowse research topicsOriginal source
Wind-wave simulation in South China Sea: Preliminary results of model evaluation using different wind forcing — Research Paper | ScholarLens