Marine forecasting is critical for navigation safety and disaster prevention.However,traditional ocean numerical forecasting models are often limited by substantial errors and inadequate capture of temporal-spatial fe...Marine forecasting is critical for navigation safety and disaster prevention.However,traditional ocean numerical forecasting models are often limited by substantial errors and inadequate capture of temporal-spatial features.To address the limitations,the paper proposes a TimeXer-based numerical forecast correction model optimized by an exogenous-variable attention mechanism.The model treats target forecast values as internal variables,and incorporates historical temporal-spatial data and seven-day numerical forecast results from traditional models as external variables based on the embedding strategy of TimeXer.Using a self-attention structure,the model captures correlations between exogenous variables and target sequences,explores intrinsic multi-dimensional relationships,and subsequently corrects endogenous variables with the mined exogenous features.The model’s performance is evaluated using metrics including MSE(Mean Squared Error),MAE(Mean Absolute Error),RMSE(Root Mean Square Error),MAPE(Mean Absolute Percentage Error),MSPE(Mean Square Percentage Error),and computational time,with TimeXer and PatchTST models serving as benchmarks.Experiment results show that the proposed model achieves lower errors and higher correction accuracy for both one-day and seven-day forecasts.展开更多
This research evaluates the performance of an eddy-resolving forecast system(LFS)in simulating mesoscale eddies over the South China Sea(SCs)through a comparative analysis with satellite observations and the reanalysi...This research evaluates the performance of an eddy-resolving forecast system(LFS)in simulating mesoscale eddies over the South China Sea(SCs)through a comparative analysis with satellite observations and the reanalysis dataset from the Global Ocean Physics Reanalysis product(CMEMS).The findings indicate that the spatial characteristics of eddy kinetic energy,number,and amplitude of coherent mesoscale eddies simulated by LFS exhibit a reasonable agreement with satellite observations.The reproduced seasonal variations are also comparable to outputs from the CMEMS reanalysis dataset.Nevertheless,certain systematic biases have also been identified.In the SCS,LFS generates approximately 17%fewer eddies than observed.Such biases are also evident in the CMEMS reanalysis dataset.Similar to the statistics shown in the CMEMS reanalysis dataset,both cyclonic and anticyclonic eddies are significantly weaker in LFS compared to the observations.Additionally,the composite three-dimensional structures of mesoscale eddies simulated by LFS exhibit a remarkable similarity to those identified in the CMEMS reanalysis datasets.This work lays the foundation for further studies using LFS to investigate the predictability of mesoscale eddies and enhance the accuracy of simulations.展开更多
Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike sc...Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike scatterometers and al-timeters,space-borne SAR offers high-resolution images of the ocean,regardless of weather conditions or time of day.SAR imagery provides rich information about the sea surface,capturing complicated dynamic processes in the upper layers of the ocean,particular-ly in relation to tropical cyclones.Over the past four decades,the advantages of SAR have been increasingly recognized,leading to notable marine applications,especially in the development of algorithms for retrieving wind and wave data from SAR images.This study reviews the history,progress,and future outlook of SAR-based monitoring of sea surface wind and waves.In particular,the ap-plicability of various SAR wind and wave algorithms is systematically investigated,with a particular focus on their performance un-der extreme sea conditions.展开更多
基金supported by the National Key Research and Development Program Project(2023YFC3107804)Planning Fund Project of Humanities and Social Sciences Research of the Ministry of Education(24YJA880097)the Graduate Education Reform Project in North China University of Technology(217051360025XN095-17)。
文摘Marine forecasting is critical for navigation safety and disaster prevention.However,traditional ocean numerical forecasting models are often limited by substantial errors and inadequate capture of temporal-spatial features.To address the limitations,the paper proposes a TimeXer-based numerical forecast correction model optimized by an exogenous-variable attention mechanism.The model treats target forecast values as internal variables,and incorporates historical temporal-spatial data and seven-day numerical forecast results from traditional models as external variables based on the embedding strategy of TimeXer.Using a self-attention structure,the model captures correlations between exogenous variables and target sequences,explores intrinsic multi-dimensional relationships,and subsequently corrects endogenous variables with the mined exogenous features.The model’s performance is evaluated using metrics including MSE(Mean Squared Error),MAE(Mean Absolute Error),RMSE(Root Mean Square Error),MAPE(Mean Absolute Percentage Error),MSPE(Mean Square Percentage Error),and computational time,with TimeXer and PatchTST models serving as benchmarks.Experiment results show that the proposed model achieves lower errors and higher correction accuracy for both one-day and seven-day forecasts.
基金supported by the National Key R&D Program for Developing Basic Sciences [grant number 2022YFC3104805]the National Natural Science Foundation of China [grant numbers 92358302 and 42306219]+1 种基金supported by the Tai Shan Scholar Program [grant number tstp20231237]Laoshan Laboratory project [grant number LSKJ202300301]。
文摘This research evaluates the performance of an eddy-resolving forecast system(LFS)in simulating mesoscale eddies over the South China Sea(SCs)through a comparative analysis with satellite observations and the reanalysis dataset from the Global Ocean Physics Reanalysis product(CMEMS).The findings indicate that the spatial characteristics of eddy kinetic energy,number,and amplitude of coherent mesoscale eddies simulated by LFS exhibit a reasonable agreement with satellite observations.The reproduced seasonal variations are also comparable to outputs from the CMEMS reanalysis dataset.Nevertheless,certain systematic biases have also been identified.In the SCS,LFS generates approximately 17%fewer eddies than observed.Such biases are also evident in the CMEMS reanalysis dataset.Similar to the statistics shown in the CMEMS reanalysis dataset,both cyclonic and anticyclonic eddies are significantly weaker in LFS compared to the observations.Additionally,the composite three-dimensional structures of mesoscale eddies simulated by LFS exhibit a remarkable similarity to those identified in the CMEMS reanalysis datasets.This work lays the foundation for further studies using LFS to investigate the predictability of mesoscale eddies and enhance the accuracy of simulations.
基金supported by the National Nat-ural Science Foundation of China(No.42376174)the Natural Science Foundation of Shanghai(No.23ZR 1426900).
文摘Synthetic aperture radar(SAR)aboard SEASAT was first launched in 1978.At the beginning of the 21st century,the Chinese remote sensing community recognized the urgent need to develop domestic SAR capabilities.Unlike scatterometers and al-timeters,space-borne SAR offers high-resolution images of the ocean,regardless of weather conditions or time of day.SAR imagery provides rich information about the sea surface,capturing complicated dynamic processes in the upper layers of the ocean,particular-ly in relation to tropical cyclones.Over the past four decades,the advantages of SAR have been increasingly recognized,leading to notable marine applications,especially in the development of algorithms for retrieving wind and wave data from SAR images.This study reviews the history,progress,and future outlook of SAR-based monitoring of sea surface wind and waves.In particular,the ap-plicability of various SAR wind and wave algorithms is systematically investigated,with a particular focus on their performance un-der extreme sea conditions.
