Building Of Wave Assimilation Model Based On The Synchronous Observations Of Wind And Wave

Wave data assimilation is an important way to improve the precision of wavesimulation and forecast. Four main factors affected the accuracy of the waveassimilation model are the wave model, the forcing wind field, the observation dataand the assimilation method. In view of the above four factors, based on the wavemodel WAVEWATCH III (WW3), wave simulation and assimilation experiments areprocessed in the three sea areas, the South China Sea, the gulf of Maine and theHawaii. This article evaluates the three input/dissipation schemes of WW3model,and explores the impact mechanism of synchronous wind and wave dataobservations to the assimilation effects. Based on the spectrum partition strategy,Envisat ASAR two-dimensional wave spectra are assimilated using the optimalinterpolation method. The work in this paper could serve as the pre-study ofCFOSAT satellite application and has practical significance to improving the level ofour wave simulation and forecast.First, based on the HY-2altimeter and the significant wave height of the waveobservation radar, this work evaluates WW3’s three input/dissipation schemes inorder to establish high quality wave simulation and forecast model. The threeschemes, WAM3, TC96and WAM4, could simulate the evolution trend of the wavenicely, but in the case of ocean swell dominated, simulation results are not very ideal.The simulation result of TC96scheme is the best which is based on the strategy of"effective wind speed" considered the atmospheric instability. Because the windspeed correction parameter is very sensitive, it should be selected reasonably in orderto obtain high accuracy of the simulation result.Secondly, taking the QSCAT/NCEP and CCMP wind field as the backgroundwind field, this work fuses wind speed and direction of10buoys, analyzes dataassimilation effect of the synchronous wind and wave through several groups ofsignificant wave height assimilation experiments. The two wind fields have highprecision, the root mean square error of the QSCAT/NCEP and CCMP wind speed in March2008are2.93m/s and1.61m/s, respectively. Taking the two original windfields and the wind fields fused wind speed and wind direction of buoys as the forcewind field of wave model, wave assimilation experiments are carried out. Theconclusions are that: the assimilation effect is the best which both fusesobservational wind field and assimilates synchronous wave data; the ratio of waveand wind data effect to the assimilation is about4:1; wave data assimilation canreduce sensitive of the wave model to the force wind field.Thirdly, based on the spectra partition scheme, Envisat ASAR two-dimensionalwave spectral is assimilated with the optimal interpolation method. This workcompares assimilation effect of the significant wave height assimilation and wavespectral assimilation. The conclusions are that: the effect of Envisat ASARtwo-dimensional wave spectral assimilation based on the spectra partition scheme isthe best, compared with the significant wave height assimilation, and the RMSreduces about30%and AI improves about35%; The quality of the data source forassimilation is one of the main factors that determine assimilation effect. Waveheight assimilation of the buoy is better than wave height assimilation of ASAR, thusbeside the data quality, observation density will be a serious impact on assimilationeffect; compared with buoy wave height assimilation, the RMS of ASAR wavespectral assimilation reduces5.6%and AI improves17.7%. It is due to that thetwo-dimensional wave spectral contains not only the significant wave height, whichrepresents total energy of wave, but also other wave information such as wave period,wave propagation direction and so on. Based on the spectrum partition strategy, theoptimal interpolation assimilation method can use those information to correct themodel background spectral.