Wave Fusion Methods Based On Multi-source Altimeter Data

Ocean wave is a wave phenomenon occurring in the ocean,and the significant wave height(SWH)is one of the important parameters to reflect the wave condition,which is of great significance for the study of ocean dynamics and climate change.The means of wave observation mainly include field survey and satellite remote sensing survey.The field survey mainly relies on observation stations in the coastal area or sparse offshore platforms and observation buoys.The observation data has high accuracy,but the observation points are not evenly distributed and the observation data is relatively few.Satellite remote sensing survey can provide a wide range of coverage and relatively high aging wave observation results with its features of all-day and large-scale observation.Therefore,it has the advantages of time-space coverage that field measurement cannot match,thus providing the necessary data guarantee for scientific research on wave observation and prediction of the globe ocean.As one of the main remote sensors for wave observation,the satellite altimeter observation obtains the significant wave height of the substellar point through the front slope of the sea surface tracking waveform.However,since the distance between adjacent orbits of single-satellite altimeter in the equatorial region is about 100 kilometers,and the distance between adjacent orbits of different satellite altimeters is tens of kilometers,the significant wave height observation data of different satellite altimeters must be fused in order to obtain the significant wave height information of global uniform distribution.Therefore,data fusion is the main direction of the comprehensive utilization of multi-source altimeter wave data,which can effectively solve the problems such as the lack of timeliness caused by the long repetition periods of satellites and the observation blank caused by the large interval of orbit data,so as to better serve the needs of scientific research.In order to meet the needs of globe wave research and make comprehensive use of the advantages of multi-source altimeters,the fusion of significant wave height is carried out with the data of five major satellite altimeters operating at the same time in this paper,namely,Jason-2,Cryo Sat-2,SARAL/Alti Ka,Jason-3 and Sentinel-3A.Firstly,the quality control of significant wave height data of multi-source altimeters and NDBC buoy is carried out.Then,the accuracy of significant wave height data of the multi-source altimeters is evaluated by using the buoy data,and the altimeter data is corrected by the matching results of the two,so as to obtain the significant wave height data with the same accuracy,which can effectively improve the accuracy of significant wave height data of the multi-source altimeters while ensuring the consistency of the observation data of the multi-source altimeters.Finally,on the basis of the above data processing,the significant wave height data of the corrected multi-source altimeters are fused by using five methods,namely,inverse distance weight(IDW),kriging,successive correction analysis,weighted mean and IDW-based spatiotemporal interpolation,to obtain the wave fusion product with a temporal resolution of 1 day and a spatial resolution of 0.25°×0.25°.In this paper,the data fusion results of 2018 are used to compare different fusion methods.The result show that the fusion results of the first three methods are less different,but significantly different from those of weighted mean method and the IDW-based spatiotemporal interpolation method.Then the fusion results of five methods are verified and evaluated by using NDBC buoy data.The verification results of buoy show that the fusion results obtained by weighted mean method are the most consistent with the buoy data among the five methods,and the standard deviation of the data set matched with the buoy is 0.0413 m,and the root mean square error is 0.3344 m.Moreover,the weighted mean method has more obvious advantages in the coastal region and the low median range of SWH.AVISO wave fusion products are used to compare the globe wave fusion results of five fusion methods.The results also show that the weighted mean method and the IDW-based spatiotemporal interpolation method have good adaptability to the fusion products of the globe ocean.In order to highlight the time weight,the 12 UTC fusion data obtained on each day of September 2018 by IDW-based spatiotemporal interpolation method are matched with the buoy measured data within a specific time period(12UTC±3h).A total of 2228 matching point pairs are obtained,with the standard deviation value of 0.1122 m and the root mean square error value of 0.3011 m.The matching results show that the precision of the IDW-based spatiotemporal interpolation is relatively high and the farther distance from coast is,the higher precision is.It can reproduce the instantaneous change of wave field well.The distribution of globe mixed wave ages in 2018 is calculated by using wave fusion products obtained by weighted mean method and ERA-Interim reanalysis of wind speed data.The distribution of ocean wind wave and swell around the world and their seasonal variation characteristics are preliminarily analyzed.The results show that the globe waves are overwhelmingly dominated by swell.There are three distinct areas with high wave ages in the equatorial tropics and subtropical regions,that is,there is the phenomenon of swell intensification-swell pool.The Equatorial Pacific Ocean is the largest swell pool,and the eastern and western Pacific Ocean are almost interlinked.The Equatorial India Ocean swell pool has the largest change throughout the year,and the sea area represented by the Arabian sea has an obvious decrease of wave age under the action of summer monsoon.The Equatorial Atlantic Ocean swell pool is relatively stable in the middle of the Atlantic Ocean and strengthened in winter and spring.By analyzing the globe wave age index of ENSO years(2015 and 2016)and comparing it with globe wave age index of 2018,it is found that the swell in the equatorial western Pacific Ocean is enhanced in ENSO years.And the trend of strengthening is more obvious in winter and spring.