Numerical sea ice forecasting products during the ninth Chinese National Arctic Research Expedition(9th CHINARE-Arctic)from Arctic Ice Ocean Prediction System(ArcIOPS)of National Marine Environmental Forecasting Cente...Numerical sea ice forecasting products during the ninth Chinese National Arctic Research Expedition(9th CHINARE-Arctic)from Arctic Ice Ocean Prediction System(ArcIOPS)of National Marine Environmental Forecasting Center of China are evaluated against satellite-retrieved sea ice concentration data,in-situ sea ice thickness observations,and sea ice products from Pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS).The results show that ArcIOPS forecasts reliable sea ice concentration and thickness evolution.Deviations of the 168 h sea ice concentration and thickness forecasts with respect to the observations are less than 0.2 and 0.36 m.Comparison between outputs of the latest version of ArcIOPS and that of its previous version shows that the latest version has a substantial improvement on sea ice concentration forecasts due to data assimilation of new observational component,the sea surface temperature.Meanwhile,the sea ice volume product of the latest version is more close to the PIOMAS product.In the future,with more and more kinds of observations to be assimilated,the high-resolution version of ArcIOPS will be put into operational running and benefit Chinese scientific and commercial activities in the Arctic Ocean.展开更多
基金This paper is a contribution to the Year of Polar Prediction(YOPP),a flagship activity of the Polar Prediction Project(PPP),initiated by the World Weather Research Programme(WWRP)of the World Meteorological Organization(WMO)The authors thank the University of Bremen for the AMSR2 data,the University of Hamburg for the SMOS data,the Alfred-Wegener-Institut,Helmholtz Zentrum für Polar-und Meeresforschung for the CryoSat-2 data,the Copernicus Marine Environment Monitoring Service for the GMPE SST data,the Norwegian Meteorological Institute for the OSISAF data,the Polar Research Institute of China for the EM31 data,and the University of Washington for the PIOMAS data+2 种基金The authors thank the two anonymous reviewers for the constructive commentsThis work is supported by the National Key R&D Program of China(Grant nos.2016YFC1402700,2017YFE0111700)the National Natural Science Foundation of China(Grant no.41506224).
文摘Numerical sea ice forecasting products during the ninth Chinese National Arctic Research Expedition(9th CHINARE-Arctic)from Arctic Ice Ocean Prediction System(ArcIOPS)of National Marine Environmental Forecasting Center of China are evaluated against satellite-retrieved sea ice concentration data,in-situ sea ice thickness observations,and sea ice products from Pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS).The results show that ArcIOPS forecasts reliable sea ice concentration and thickness evolution.Deviations of the 168 h sea ice concentration and thickness forecasts with respect to the observations are less than 0.2 and 0.36 m.Comparison between outputs of the latest version of ArcIOPS and that of its previous version shows that the latest version has a substantial improvement on sea ice concentration forecasts due to data assimilation of new observational component,the sea surface temperature.Meanwhile,the sea ice volume product of the latest version is more close to the PIOMAS product.In the future,with more and more kinds of observations to be assimilated,the high-resolution version of ArcIOPS will be put into operational running and benefit Chinese scientific and commercial activities in the Arctic Ocean.
