Surface wind speed(SWS)not only plays a crucial role in regulating the Earth's energy and hydrological cycle,but also is an important source of sustainable renewable energy.This study assesses the credibility of s...Surface wind speed(SWS)not only plays a crucial role in regulating the Earth's energy and hydrological cycle,but also is an important source of sustainable renewable energy.This study assesses the credibility of sws in three reanalyses(ERA5,MERRA2,and JRA-55)in East Asia using both satellite and in-situ observations.Results show all three reanalyses can capture the spatial pattern of swS as in observations,yet there are notable differences in magnitude.On land,ERA5 and MERRA2 overestimate the SWS by about 0.6 and 1.5 m s^(-1),respectively,whereas JRA-55 underestimates it.The biases over the oceans are opposite to those on land and are relatively small due to the assimilation of observations of oceanic surface winds.Overall,JRA-55 and ERA5 offer better estimates of seasonal means and variances of SWS than MERRA2.The observed SWS shows a negative trend of-0.08 m s^(-1)/10 yr on land and a positive trend of 0.09 m s^(-1)/10 yr in the western North Pacific.Only JRA-55 shows similar trends to observations over both land and ocean,while ERA5 and MERRA2 show varying degrees of deviation from the observations.Further investigation shows that there is a strong link between the trend of SWS and that of the large-scale circulation,and that a large part of the SwS trend can be attributed to changes in large-scale circulations.展开更多
To improve retrieval accuracy, this paper studies wave effects on retrieved wind field from a scatterometer. First, the advanced scatterometer （ASCAT） data and buoy data of the National Data Buoy Center （NDBC） are...To improve retrieval accuracy, this paper studies wave effects on retrieved wind field from a scatterometer. First, the advanced scatterometer （ASCAT） data and buoy data of the National Data Buoy Center （NDBC） are collocated. Buoy wind speed is converted into neutral wind at 10 m height. Then, ASCAT data are com- pared with the buoy data for the wind speed and direction. Subsequently, the errors between the ASCAT and the buoy wind as a function of each wave parameter are used to analyze the wave effects. Wave param- eters include dominant wave period （dpd）, significant wave height （swh）, average wave period （apd） and the angle between the dominant wave direction （dwd） and the wind direction. Collocated data are divided into sub-datasets according to the different intervals of each wave parameter. A root mean square error （RMSE） for the wind speed and a mean absolute error （MAE） for the wind direction are calculated from the sub-datasets, which are considered as the function of wave parameters. Finally, optimal wave conditions on wind retrieved from the ASCAT are determined based on the error analyses. The results show the ocean wave parameters have correlative relationships with the RMSE of the retrieved wind speed and the MAE of the retrieved wind direction. The optimal wave conditions are presented in terms of dpd, swh, apd and angle.展开更多
基金supported by the National Natural Science Foundation of China[grant numbers 42361144708,42205041,and 42175165]a scientific research project of the Shanghai Investigation,Design and Research Institute Co.,Ltd.[grant number 2023CN(83)-001]the National Key Scientific and Technological Infrastructure project“Earth System Science Numerical Simulator Facility”(EarthLab).
文摘Surface wind speed(SWS)not only plays a crucial role in regulating the Earth's energy and hydrological cycle,but also is an important source of sustainable renewable energy.This study assesses the credibility of sws in three reanalyses(ERA5,MERRA2,and JRA-55)in East Asia using both satellite and in-situ observations.Results show all three reanalyses can capture the spatial pattern of swS as in observations,yet there are notable differences in magnitude.On land,ERA5 and MERRA2 overestimate the SWS by about 0.6 and 1.5 m s^(-1),respectively,whereas JRA-55 underestimates it.The biases over the oceans are opposite to those on land and are relatively small due to the assimilation of observations of oceanic surface winds.Overall,JRA-55 and ERA5 offer better estimates of seasonal means and variances of SWS than MERRA2.The observed SWS shows a negative trend of-0.08 m s^(-1)/10 yr on land and a positive trend of 0.09 m s^(-1)/10 yr in the western North Pacific.Only JRA-55 shows similar trends to observations over both land and ocean,while ERA5 and MERRA2 show varying degrees of deviation from the observations.Further investigation shows that there is a strong link between the trend of SWS and that of the large-scale circulation,and that a large part of the SwS trend can be attributed to changes in large-scale circulations.
基金The National Natural Science Youth Foundation of China under contract Nos 41306191 and 41306192the National High Tech-nology Development Program(863 Program) of China under contract No.2013AA09A505the Scientific Research Fund of the Second Institute of Oceanography,State Oceanic Administration of China under contract No.JG1317
文摘To improve retrieval accuracy, this paper studies wave effects on retrieved wind field from a scatterometer. First, the advanced scatterometer （ASCAT） data and buoy data of the National Data Buoy Center （NDBC） are collocated. Buoy wind speed is converted into neutral wind at 10 m height. Then, ASCAT data are com- pared with the buoy data for the wind speed and direction. Subsequently, the errors between the ASCAT and the buoy wind as a function of each wave parameter are used to analyze the wave effects. Wave param- eters include dominant wave period （dpd）, significant wave height （swh）, average wave period （apd） and the angle between the dominant wave direction （dwd） and the wind direction. Collocated data are divided into sub-datasets according to the different intervals of each wave parameter. A root mean square error （RMSE） for the wind speed and a mean absolute error （MAE） for the wind direction are calculated from the sub-datasets, which are considered as the function of wave parameters. Finally, optimal wave conditions on wind retrieved from the ASCAT are determined based on the error analyses. The results show the ocean wave parameters have correlative relationships with the RMSE of the retrieved wind speed and the MAE of the retrieved wind direction. The optimal wave conditions are presented in terms of dpd, swh, apd and angle.
