This paper investigates processing of fast-response data and corrections of turbulent fluxes obtained by using eddy covariance method based on data collected at an offshore observation tower during three Cold-intrusio...This paper investigates processing of fast-response data and corrections of turbulent fluxes obtained by using eddy covariance method based on data collected at an offshore observation tower during three Cold-intrusion(CI)events in the South China Sea in 2010. This study presents the data processing procedure in detail and compares frictional velocities(u*), sensible heat fluxes(H) and latent heat fluxes(LE) yielded by using different averaging periods and different coordinate rotation methods; evaluates the sonic temperature correction for sensible heat flux and the Webb correction for latent heat flux as a function of 10 m wind speed(u10) during the CIs. The results show(1) that the different averaging periods of 30 min and 10 min cause biases of u*(H, LE) within 5%(15%, 62%). The values of u*(H,LE) averaged from 30 mins are mostly larger than those averaged from 10 mins. We suggest that the averaging period of 10 min is not sufficiently long to capture all scale eddies and recommend 30 min averaging period in calculating turbulent fluxes using eddy covariance method during CIs;(2) that the values of u*(H, LE) obtained from double rotation(DR2) and those obtained from planar fit rotation(PF) have good agreements and correlation coefficients between them are larger than 0.99. Because PF method requires unchanged environment and it is easier to apply DR2 method, we suggest DR2 coordinate rotation method in processing fast-response data; and(3) that the median values of frictional velocity(sensible heat flux and latent heat flux) binned according to 2 m s^(-1) intervals of u_(10) increase(decrease,increase) by less than 9%(4%, 10%) by Coriolis corrections(sonic temperature corrections, Webb corrections), which decreases(decreases, increases) with increasing u10 when u10 are 5-17 m s^(-1).展开更多
对传统的消除偏差法进行改进，形成分等级消除偏差法，并使用混合训练期和60d滑动训练期方案分别对2012年6—8月ECMWF（European Centre for Medium-Range Weather Forecasting）模式夏季1～5d的降水预报进行订正试验。为了尽可能符合...对传统的消除偏差法进行改进，形成分等级消除偏差法，并使用混合训练期和60d滑动训练期方案分别对2012年6—8月ECMWF（European Centre for Medium-Range Weather Forecasting）模式夏季1～5d的降水预报进行订正试验。为了尽可能符合中国东部夏季降水具有移动性及多种时间尺度变化的特点，混合训练期以预报期前30d与预报期前一年同日的前后各15d组成。结果表明：在使用分等级消除偏差法的基础上，相比ECMWF模式降水预报，两种训练期方案的订正结果几乎对各个阈值的ETS评分均有一定提高，特别是对25mm以上降水预报评分的提高幅度，混合训练期方案的订正结果明显高于60d滑动训练期方案；在区域性强降水预报的订正中，混合训练期方案优势更为明显。另外，通过分析两种训练期方案的预报偏差发现，分等级订正是此次消除偏差订正试验中提高强降水预报评分的关键，选择合适的训练期可以增加评分提高的幅度。由于上述试验使用的ECMWF模式预报和站点实况均是业务上常用数据，因此，该方法具有一定的业务应用价值。展开更多
基金Science and Technology Program of Guangzhou,China(201510010218)National Key Project for Basic Research(973 project)(2015CB452802)+2 种基金National Natural Science Foundation of China(41675019,41475014,41475061,41675021 and 41475102)Strategic Priority Research Program of the Chinese Academy of Sciences(XDA11010403)Natural Science Foundation of Guangdong Province of China(2016A030310009)
文摘This paper investigates processing of fast-response data and corrections of turbulent fluxes obtained by using eddy covariance method based on data collected at an offshore observation tower during three Cold-intrusion(CI)events in the South China Sea in 2010. This study presents the data processing procedure in detail and compares frictional velocities(u*), sensible heat fluxes(H) and latent heat fluxes(LE) yielded by using different averaging periods and different coordinate rotation methods; evaluates the sonic temperature correction for sensible heat flux and the Webb correction for latent heat flux as a function of 10 m wind speed(u10) during the CIs. The results show(1) that the different averaging periods of 30 min and 10 min cause biases of u*(H, LE) within 5%(15%, 62%). The values of u*(H,LE) averaged from 30 mins are mostly larger than those averaged from 10 mins. We suggest that the averaging period of 10 min is not sufficiently long to capture all scale eddies and recommend 30 min averaging period in calculating turbulent fluxes using eddy covariance method during CIs;(2) that the values of u*(H, LE) obtained from double rotation(DR2) and those obtained from planar fit rotation(PF) have good agreements and correlation coefficients between them are larger than 0.99. Because PF method requires unchanged environment and it is easier to apply DR2 method, we suggest DR2 coordinate rotation method in processing fast-response data; and(3) that the median values of frictional velocity(sensible heat flux and latent heat flux) binned according to 2 m s^(-1) intervals of u_(10) increase(decrease,increase) by less than 9%(4%, 10%) by Coriolis corrections(sonic temperature corrections, Webb corrections), which decreases(decreases, increases) with increasing u10 when u10 are 5-17 m s^(-1).
文摘对传统的消除偏差法进行改进，形成分等级消除偏差法，并使用混合训练期和60d滑动训练期方案分别对2012年6—8月ECMWF（European Centre for Medium-Range Weather Forecasting）模式夏季1～5d的降水预报进行订正试验。为了尽可能符合中国东部夏季降水具有移动性及多种时间尺度变化的特点，混合训练期以预报期前30d与预报期前一年同日的前后各15d组成。结果表明：在使用分等级消除偏差法的基础上，相比ECMWF模式降水预报，两种训练期方案的订正结果几乎对各个阈值的ETS评分均有一定提高，特别是对25mm以上降水预报评分的提高幅度，混合训练期方案的订正结果明显高于60d滑动训练期方案；在区域性强降水预报的订正中，混合训练期方案优势更为明显。另外，通过分析两种训练期方案的预报偏差发现，分等级订正是此次消除偏差订正试验中提高强降水预报评分的关键，选择合适的训练期可以增加评分提高的幅度。由于上述试验使用的ECMWF模式预报和站点实况均是业务上常用数据，因此，该方法具有一定的业务应用价值。
