机译:利用小波和机器学习改进北美地区的多模式合奏(NMME)降水预报
Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China;
Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China|Collaborat Innovat Ctr Geospatial Technol, Wuhan 430079, Hubei, Peoples R China;
Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China|CMA, Key Lab Arid Climat Change & Reducing Disaster CM, Key Lab Arid Climat Change & Reducing Disaster Ga, Inst Arid Meteorol, Lanzhou 730020, Gansu, Peoples R China;
Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China;
China Univ Geosci Wuhan, Fac Informat Engn, Wuhan 430074, Hubei, Peoples R China;
Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Hubei, Peoples R China;
NMME; Precipitation forecast; Bias correction; Wavelet; Machine learning;
机译:使用小波和机器学习改善当地地区的北美多模型集合(NMME)降水预测
机译:对美国大陆上北美多模式集合(NMME)降水预报的有效后处理
机译:评价北美多模型集合(NMME)全球气候模型的技能预测美国大陆平均和极端降水和温度
机译:与单模型集合预报相比,多模型集合预报是否可以提高降水预报的概率?
机译:通过短期整体天气预报系统和降水量校准进行概率定量降水量预报。
机译:基于小波支持向量机和集成学习的全波形LiDAR点云分类
机译:评估北美多模式合奏(NMME)全球气候模型预测美国大陆上平均和极端降水与温度的技能