In recent decades the Arctic surface air temperature(SAT) in autumn has been increasing steadily. In winter, however, instead of a linear trend, the Arctic SAT shows an abrupt change that occurred in 2004. During the ...In recent decades the Arctic surface air temperature(SAT) in autumn has been increasing steadily. In winter, however, instead of a linear trend, the Arctic SAT shows an abrupt change that occurred in 2004. During the years from 1979 to 2003, the first principle component(PC1) of winter Arctic SAT remains stable, and no significant increasing trend is detected. However, the PC1 changes abruptly from negative to positive phase in the winter of 2004. The enhanced Siberian high may have contributed to this abrupt change because the temporal evolution of Arctic temperature correlates significantly with sea level pressure variation in the northern Eurasian continent, and the atmospheric circulation anomaly related to the Siberian high from 2004 to 2013 favors a warmer Arctic. With the help of the meridional wind anomaly around the Siberian high, warmer air is transported to the high latitudes and therefore increases the Arctic temperature.展开更多
This study validates a method for discriminating between daytime clouds and dust aerosol layers over the Sahara Desert that uses a combination of active CALIOP（Cloud-Aerosol Lidar with Orthogonal Polarization） and p...This study validates a method for discriminating between daytime clouds and dust aerosol layers over the Sahara Desert that uses a combination of active CALIOP（Cloud-Aerosol Lidar with Orthogonal Polarization） and passive IIR（Infrared Imaging Radiometer） measurements;hereafter,the CLIM method.The CLIM method reduces misclassification of dense dust aerosol layers in the Sahara region relative to other techniques.When evaluated against a suite of simultaneous measurements from CALIPSO（Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations）,CloudSat,and the MODIS（Moderate-resolution Imaging Spectroradiometer）,the misclassification rate for dust using the CLIM technique is 1.16%during boreal spring 2007.This rate is lower than the misclassification rates for dust using the cloud aerosol discriminations performed for version 2（V2-CAD;16.39%） or version 3（V3-CAD;2.01%） of the CALIPSO data processing algorithm.The total identification errors for data from in spring 2007 are 13.46%for V2-CAD,3.39%for V3-CAD,and 1.99%for CLIM.These results indicate that CLIM and V3-CAD are both significantly better than V2-CAD for discriminating between clouds and dust aerosol layers.Misclassifications by CLIM in this region are mainly limited to mixed cloud-dust aerosol layers.V3-CAD sometimes misidentifies low-level aerosol layers adjacent to the surface as thin clouds,and sometimes fails to detect thin clouds entirely.The CLIM method is both simple and fast,and may be useful as a reference for testing or validating other discrimination techniques and methods.展开更多
基金supported by the National Basic Research Program of China (2013CBA01804 and 2015CB453200)the National Natural Science Foundation of China (41475080 and 41221064)State Oceanic Administration Project (201205007)
文摘In recent decades the Arctic surface air temperature(SAT) in autumn has been increasing steadily. In winter, however, instead of a linear trend, the Arctic SAT shows an abrupt change that occurred in 2004. During the years from 1979 to 2003, the first principle component(PC1) of winter Arctic SAT remains stable, and no significant increasing trend is detected. However, the PC1 changes abruptly from negative to positive phase in the winter of 2004. The enhanced Siberian high may have contributed to this abrupt change because the temporal evolution of Arctic temperature correlates significantly with sea level pressure variation in the northern Eurasian continent, and the atmospheric circulation anomaly related to the Siberian high from 2004 to 2013 favors a warmer Arctic. With the help of the meridional wind anomaly around the Siberian high, warmer air is transported to the high latitudes and therefore increases the Arctic temperature.
基金Supported by the National(Key)Basic Research and Development(973)Program of China(2012CB955301)Fundamental Research Funds for the Central Universities(LZUJBKY-2013-104 and LZUJBKY-2009-k03)+1 种基金Development Program of Changjiang Scholarship and Research Team(IRT1018)China Meteorological Administration Special Public Welfare Research Fund (GYHY201206009)
文摘This study validates a method for discriminating between daytime clouds and dust aerosol layers over the Sahara Desert that uses a combination of active CALIOP（Cloud-Aerosol Lidar with Orthogonal Polarization） and passive IIR（Infrared Imaging Radiometer） measurements;hereafter,the CLIM method.The CLIM method reduces misclassification of dense dust aerosol layers in the Sahara region relative to other techniques.When evaluated against a suite of simultaneous measurements from CALIPSO（Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations）,CloudSat,and the MODIS（Moderate-resolution Imaging Spectroradiometer）,the misclassification rate for dust using the CLIM technique is 1.16%during boreal spring 2007.This rate is lower than the misclassification rates for dust using the cloud aerosol discriminations performed for version 2（V2-CAD;16.39%） or version 3（V3-CAD;2.01%） of the CALIPSO data processing algorithm.The total identification errors for data from in spring 2007 are 13.46%for V2-CAD,3.39%for V3-CAD,and 1.99%for CLIM.These results indicate that CLIM and V3-CAD are both significantly better than V2-CAD for discriminating between clouds and dust aerosol layers.Misclassifications by CLIM in this region are mainly limited to mixed cloud-dust aerosol layers.V3-CAD sometimes misidentifies low-level aerosol layers adjacent to the surface as thin clouds,and sometimes fails to detect thin clouds entirely.The CLIM method is both simple and fast,and may be useful as a reference for testing or validating other discrimination techniques and methods.
