利用欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,简称ECMWF)细网格10m风预报场和海南岛国家气象站地面风观测资料,基于天气学误差统计等方法对2019—2021年10m极大风速预报结果进行评估,以期为预报员更...利用欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,简称ECMWF)细网格10m风预报场和海南岛国家气象站地面风观测资料,基于天气学误差统计等方法对2019—2021年10m极大风速预报结果进行评估,以期为预报员更好地应用模式产品提供依据。结果表明:(1)海南岛四周地区10 m极大风速预报效果优于中部地区;预报误差与海拔高度密切相关,海拔较低站点与实况观测一致性更高;模式对海拔低且开阔地区的极大风速具有较好可预报性。(2)10 m极大风速预报误差随时效略有增长,昼夜误差呈现波峰特征,具有一定日变化。(3)海南岛6级风速预报效果最佳,5级及以下风速预报次之,7级及以上风速预报效果则最差;对于大风预报,ECMWF细网格预报量级具有偏小的特征。(4)基于机器学习方法,选取ECMWF细网格预报场,对海南岛极大风速预报进行订正,独立样本预报模型表明,该方法可以有效减小预报误差,改善效果显著,为海南岛大风预报的准确性提供可靠方法。展开更多
Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been...Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.展开更多
利用新疆及周边地区2012 年11 月1 日-2013 年10 月31 日的地面2 m 温度和10 m风场的逐6 h 观测和预报资料,通过预报的均方根误差和平均误差的分析,对基于WRFv3.5 和WRFDAv3.4.1 的新疆快速更新循环数值预报同化系统（DOGRAFS）的预报...利用新疆及周边地区2012 年11 月1 日-2013 年10 月31 日的地面2 m 温度和10 m风场的逐6 h 观测和预报资料,通过预报的均方根误差和平均误差的分析,对基于WRFv3.5 和WRFDAv3.4.1 的新疆快速更新循环数值预报同化系统（DOGRAFS）的预报效果进行检验评估.结果表明：DOGRAFS系统对地面2 m温度和10 m风速的预报具有较好的参考价值,二者的预报偏差均呈周期性变化,对2 m 温度预报整体呈“低温偏高,高温偏低”特点,采用12 UTC 初值场起报的预报结果对冬、春、夏季的高温预报冷偏差最小,采用06 UTC 初值场起报的预报结果对秋季的预报冷偏差最小,采用18 UTC 初值场起报的预报结果对冬、春、夏季的低温预报偏差最小,采用00 UTC 初值场起报的预报结果则对秋季的最低温预报偏差最小,各时次对18 UTC 的预报偏差均接近0 .偏差的空间分布上,大部分站点在不同季节、不同时次的偏差都在-2-2 益之间.对10 m风场的预报在秋季效果最好,冬季最差,预报平均误差整体从冬到秋逐季递减,夜间大于白天,四季中,采用18 UTC 初值场起报的预报效果最好.展开更多
文摘利用欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,简称ECMWF)细网格10m风预报场和海南岛国家气象站地面风观测资料,基于天气学误差统计等方法对2019—2021年10m极大风速预报结果进行评估,以期为预报员更好地应用模式产品提供依据。结果表明:(1)海南岛四周地区10 m极大风速预报效果优于中部地区;预报误差与海拔高度密切相关,海拔较低站点与实况观测一致性更高;模式对海拔低且开阔地区的极大风速具有较好可预报性。(2)10 m极大风速预报误差随时效略有增长,昼夜误差呈现波峰特征,具有一定日变化。(3)海南岛6级风速预报效果最佳,5级及以下风速预报次之,7级及以上风速预报效果则最差;对于大风预报,ECMWF细网格预报量级具有偏小的特征。(4)基于机器学习方法,选取ECMWF细网格预报场,对海南岛极大风速预报进行订正,独立样本预报模型表明,该方法可以有效减小预报误差,改善效果显著,为海南岛大风预报的准确性提供可靠方法。
基金This work was supported by the National Natural Science Foundation of China(72221002,42271375)the Strategic Priority Research Program(XDA28060100)the Informatization Plan Project(CAS-WX2021PY-0109)of the Chinese Academy of Sciences.
文摘Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.
文摘利用新疆及周边地区2012 年11 月1 日-2013 年10 月31 日的地面2 m 温度和10 m风场的逐6 h 观测和预报资料,通过预报的均方根误差和平均误差的分析,对基于WRFv3.5 和WRFDAv3.4.1 的新疆快速更新循环数值预报同化系统（DOGRAFS）的预报效果进行检验评估.结果表明：DOGRAFS系统对地面2 m温度和10 m风速的预报具有较好的参考价值,二者的预报偏差均呈周期性变化,对2 m 温度预报整体呈“低温偏高,高温偏低”特点,采用12 UTC 初值场起报的预报结果对冬、春、夏季的高温预报冷偏差最小,采用06 UTC 初值场起报的预报结果对秋季的预报冷偏差最小,采用18 UTC 初值场起报的预报结果对冬、春、夏季的低温预报偏差最小,采用00 UTC 初值场起报的预报结果则对秋季的最低温预报偏差最小,各时次对18 UTC 的预报偏差均接近0 .偏差的空间分布上,大部分站点在不同季节、不同时次的偏差都在-2-2 益之间.对10 m风场的预报在秋季效果最好,冬季最差,预报平均误差整体从冬到秋逐季递减,夜间大于白天,四季中,采用18 UTC 初值场起报的预报效果最好.
