Comparative analysis of significant wave height between a new Southern Ocean buoy and satellite altimeter

In-situ observation is restricted by the strong wind and waves in the Southern Ocean.A Westerlies EnvironmentalMonitoring Buoy(WEMB)was firstly deployed in the Southern Ocean during China’s 35th Antarctic Expedition,facilitating further understanding of the oceanic environmental characteristics of this region.With the develop-ment of technology and the improvement of data processing methods,the accuracy of satellite altimeter productsis constantly improved,thus making it possible to inspect and evaluate the in-situ observation data.Based on theL3 products of multiple satellite altimeters,this paper analyzes and corrects the significant wave height(SWH)data of WEMB by means of data matching,error statistics,and linear least-squares fitting.Through this study,the authors obtained the following results.The effect of gravitational acceleration changes with latitude on SWHaccuracy is fairly small.Due to the low response of WEMB to high-frequency waves,there is a systematic devia-tion.A feasible correction method is therefore proposed to improve the SWH accuracy of WEMB.The temporalvariation of the corrected SWH is highly consistent with that of the 10 m wind during the observation period,and its average value reaches 3.8 m.

A variational successive corrections approach for the sea ice concentration analysis

The sea ice concentration observation from satellite remote sensing includes the spatial multi-scale information.However,traditional data assimilation methods cannot better extract the valuable information due to the complicated variability of the sea ice concentration in the marginal ice zone.A successive corrections analysis using variational optimization method,called spatial multi-scale recursive filter(SMRF),has been designed in this paper to extract multi-scale information resolved by sea ice observations.It is a combination of successive correction methods(SCM)and minimization algorithms,in which various observational scales,from longer to shorter wavelengths,can be extracted successively.As a variational objective analysis scheme,it gains the advantage over the conventional approaches that analyze all scales resolved by observations at one time,and also,the specification of parameters is more convenient.Results of single-observation experiment demonstrate that the SMRF scheme possesses a good ability in propagating observational signals.Further,it shows a superior performance in extracting multi-scale information in a two-dimensional sea ice concentration(SIC)experiment with the real observations from Special Sensor Microwave/Imager SIC(SSMI).

A multi-scale high-order recursive filter approach for the sea ice concentration analysis

With the development and deployment of observation systems in the ocean,more precise passive and active microwave data are becoming available for the weather forecasting and the climate monitoring.Due to the complicated variability of the sea ice concentration(SIC)in the marginal ice zone and the scarcity of high-precision sea ice data,how to use less data to accurately reconstruct the sea ice field has become an urgent problem to be solved.A reconstruction method for gridding observations using the variational optimization technique,called the multi-scale high-order recursive filter(MHRF),which is a combination of Van Vliet fourth-order recursive filter and the three-dimensional variational(3D-VAR)analysis,has been designed in this study to reproduce the refined structure of sea ice field.Compared with the existing spatial multi-scale first-order recursive filter(SMRF)in which left and right filter iterative processes are executed many times,the MHRF scheme only executes the same filter process once to reduce the analysis errors caused by multiple filters and improve the filter precision.Furthermore,the series connected transfer function in the high-order recursive filter is equivalently replaced by the paralleled one,which can carry out the independent filter process in every direction in order to improve the filter efficiency.Experimental results demonstrate that this method possesses a good potential in extracting the observation information to successfully reconstruct the SIC field in computational efficiency.

China Ocean ReAnalysis(CORA)version 1.0 products and validation for 2009-18

China Ocean ReAnalysis(CORA) version 1.0 products for the period 2009-18 have been developed and validated.The model configuration and assimilation algorithm have both been updated compared to those of the 51-year(1958-2008) products.The assimilated observations include temperature and salinity field data,satellite remote sensing sea surface temperature,and merged sea surface height(SSH) anomaly data.The validation includes the following three aspects:(1) Temperature,salinity,and SSH anomaly root-mean-square errors(RMSEs) are computed as a primary evaluation of the reanalysis quality.The 0-2000 m domain-averaged RMSEs of temperature and salinity are 0.61℃ and 0.08 psu,respectively.The SSH anomaly RMSE is less than 0.2 m in most regions.(2) The 35°N temperature section is used to evaluate the ability to reproduce the thermocline,mixing layer,and Yellow Sea cold water mass.In summer,the thermocline is reinforced,with the gradient changing from 3℃ in May to 10℃ in August.The mixing-layer depth reproduced by CORA is consistent with that computed from the observed climatology.The Yellow Sea cold water mass forms at a depth of 50 m.(3) The reanalysis current is examined against the tracks of some drifting buoys.The results show that the reanalysis current can capture the mesoscale eddies near the Kuroshio,which are similar to those described by the drifting buoys.Overall,the 2009-18 CORA reanalysis products are capable of reproducing major oceanic phenomena and processes in the coastal waters of China and adjacent seas.