Total Cloud Cover （TCC） over China deter- mined from four climate datasets including the Interna- tional Satellite Cloud Climatology Project （ISCCP）, the 40-year Re-Analysis Project of the European Centre for Medi...Total Cloud Cover （TCC） over China deter- mined from four climate datasets including the Interna- tional Satellite Cloud Climatology Project （ISCCP）, the 40-year Re-Analysis Project of the European Centre for Medium-Range Weather Forecasts （ERA-40）, Climate Research Unit Time Series 3.0 （CRU3）, and ground sta- tion datasets are used to show spatial and temporal varia- tion of TCC and their differences. It is demonstrated that the four datasets show similar spatial pattern and seasonal variation. The maximum value is derived from ISCCE TCC value in North China derived from ERA-40 is 50% larger than that from the station dataset; however, the value is 50% less than that in South China. The annual TCC of ISCCP, ERA-40, and ground station datasets shows a decreasing trend during 1984-2002; however, an increasing trend is derived from CRU3. The results of this study imply remarkable differences of TCC derived from surface and satellite observations as well as model simu- lations. The potential effects of these differences on cloud climatology and associated climatic issues should be carefully considered.展开更多
This study attempts to investigate the interaction between lower and upper atmosphere, employing daily data of Total Ozone Column (TOC) and atmospheric parameter (cloud cover) over Nigeria from 1998-2012;in order to s...This study attempts to investigate the interaction between lower and upper atmosphere, employing daily data of Total Ozone Column (TOC) and atmospheric parameter (cloud cover) over Nigeria from 1998-2012;in order to study the dynamic effect of ozone on climate and vice versa. This is due to the fact that ozone and climate influence each other and the understanding of the dynamic effect of the interconnectivity is still an open research area. Monthly mean daily TOC and cloud cover data were obtained from the Earth Probe Total Ozone Mass Spectroscopy (EPTOMS) and the International Satellite Cloud Climatology Project (ISCCP)-D2 datasets respectively. Bivariate analysis and Mann Kendall trend tests were used in data analysis. MATLAB and ArcGIS software were employed in analyzing the data. Results reveal that TOC increased spatially from the coastal region to the north eastern region of the country. Seasonally, the highest value of TOC was observed at the peak of rainy season when cloud activity is very high, while the lowest value was recorded in dry season. These variations were attributed to rain producing mechanisms and atmospheric phenomena which influence the transport and distribution of ozone. Furthermore, the statistical analysis reveals significant relationship between TOC and low and middle cloud covers in contrast to high cloud cover. This relationship is consistent with previous studies using other atmospheric variables. This study has given scientific insight which is useful in understanding the coupling of the lower and upper atmosphere.展开更多
利用2007—2016年国际卫星云气候计划(International Satellite Cloud Climatology Project,ISCCP)、云和地球辐射能量系统(Clouds and the Earth s Radiant Energy System,CERES)和中分辨率成像光谱仪(Moderate Resolution Imaging Spe...利用2007—2016年国际卫星云气候计划(International Satellite Cloud Climatology Project,ISCCP)、云和地球辐射能量系统(Clouds and the Earth s Radiant Energy System,CERES)和中分辨率成像光谱仪(Moderate Resolution Imaging Spectroradiometer,MODIS)卫星反演云产品,对比分析了不同数据反演的中国地区云系结构的宏微观特征,并采用复合评价指标定量评估了不同数据之间时间和空间上的一致性。结果表明:三套卫星数据都能较好地反演出中国地区总云量呈南高北低、东高西低、夏高冬低的分布特征,但通过比较时间技巧(Temporal Skill,S_(T))及空间技巧(Spatial Skill,S_(S))复合评价指标及其各项分量发现,与MODIS相比,CERES与ISCCP数据反演的总云量时间序列演变特征明显更为一致,且其评分均有南方优于北方,夏季优于冬季的特征;进一步分析不同高度云量的S_(T)评分发现,CERES和ISCCP两套数据在南方地区的总云量差异主要来自于低云量的绝对偏差,而北方地区的偏差则同时存在于低云和中云;对比分析MODIS和CERES反演的云滴有效半径发现,高云对应的冰相云一致性较高,而中低云相对应的液相云的偏差则有夏季高于冬季的规律。针对夏季液相和冰相云滴粒径及概率密度分析则表明,相比CERES数据,MODIS对夏季液水和冰水粒子的有效半径在不同地区均有不同程度的高估,液(冰)水谱宽则更宽(窄)。展开更多
基金supported by the "Strategic Priority Research Program" of the Chinese Academy of Sciences(XDA05100300)the National Basic Research Program of China(2013CB955801)the National Natural Science Foundation of China(41175030)
文摘Total Cloud Cover （TCC） over China deter- mined from four climate datasets including the Interna- tional Satellite Cloud Climatology Project （ISCCP）, the 40-year Re-Analysis Project of the European Centre for Medium-Range Weather Forecasts （ERA-40）, Climate Research Unit Time Series 3.0 （CRU3）, and ground sta- tion datasets are used to show spatial and temporal varia- tion of TCC and their differences. It is demonstrated that the four datasets show similar spatial pattern and seasonal variation. The maximum value is derived from ISCCE TCC value in North China derived from ERA-40 is 50% larger than that from the station dataset; however, the value is 50% less than that in South China. The annual TCC of ISCCP, ERA-40, and ground station datasets shows a decreasing trend during 1984-2002; however, an increasing trend is derived from CRU3. The results of this study imply remarkable differences of TCC derived from surface and satellite observations as well as model simu- lations. The potential effects of these differences on cloud climatology and associated climatic issues should be carefully considered.
文摘This study attempts to investigate the interaction between lower and upper atmosphere, employing daily data of Total Ozone Column (TOC) and atmospheric parameter (cloud cover) over Nigeria from 1998-2012;in order to study the dynamic effect of ozone on climate and vice versa. This is due to the fact that ozone and climate influence each other and the understanding of the dynamic effect of the interconnectivity is still an open research area. Monthly mean daily TOC and cloud cover data were obtained from the Earth Probe Total Ozone Mass Spectroscopy (EPTOMS) and the International Satellite Cloud Climatology Project (ISCCP)-D2 datasets respectively. Bivariate analysis and Mann Kendall trend tests were used in data analysis. MATLAB and ArcGIS software were employed in analyzing the data. Results reveal that TOC increased spatially from the coastal region to the north eastern region of the country. Seasonally, the highest value of TOC was observed at the peak of rainy season when cloud activity is very high, while the lowest value was recorded in dry season. These variations were attributed to rain producing mechanisms and atmospheric phenomena which influence the transport and distribution of ozone. Furthermore, the statistical analysis reveals significant relationship between TOC and low and middle cloud covers in contrast to high cloud cover. This relationship is consistent with previous studies using other atmospheric variables. This study has given scientific insight which is useful in understanding the coupling of the lower and upper atmosphere.
文摘利用2007—2016年国际卫星云气候计划(International Satellite Cloud Climatology Project,ISCCP)、云和地球辐射能量系统(Clouds and the Earth s Radiant Energy System,CERES)和中分辨率成像光谱仪(Moderate Resolution Imaging Spectroradiometer,MODIS)卫星反演云产品,对比分析了不同数据反演的中国地区云系结构的宏微观特征,并采用复合评价指标定量评估了不同数据之间时间和空间上的一致性。结果表明:三套卫星数据都能较好地反演出中国地区总云量呈南高北低、东高西低、夏高冬低的分布特征,但通过比较时间技巧(Temporal Skill,S_(T))及空间技巧(Spatial Skill,S_(S))复合评价指标及其各项分量发现,与MODIS相比,CERES与ISCCP数据反演的总云量时间序列演变特征明显更为一致,且其评分均有南方优于北方,夏季优于冬季的特征;进一步分析不同高度云量的S_(T)评分发现,CERES和ISCCP两套数据在南方地区的总云量差异主要来自于低云量的绝对偏差,而北方地区的偏差则同时存在于低云和中云;对比分析MODIS和CERES反演的云滴有效半径发现,高云对应的冰相云一致性较高,而中低云相对应的液相云的偏差则有夏季高于冬季的规律。针对夏季液相和冰相云滴粒径及概率密度分析则表明,相比CERES数据,MODIS对夏季液水和冰水粒子的有效半径在不同地区均有不同程度的高估,液(冰)水谱宽则更宽(窄)。
