基本信息
郭振海 男 博导 中国科学院大气物理研究所
电子邮件： gzh@lasg.iap.ac.cn
通信地址： 北京9804信箱
邮政编码： 100029
电子邮件： gzh@lasg.iap.ac.cn
通信地址： 北京9804信箱
邮政编码： 100029
招生信息
招生专业
070602-大气物理学与大气环境
070620-地球流体力学
070620-地球流体力学
招生方向
风(光)能数值预报方法
大气边界层物理
中尺度气象
大气边界层物理
中尺度气象
教育背景
1994-09--1997-07 北京大学地球物理系 博士
1989-09--1992-07 兰州大学大气科学系 硕士
1982-09--1986-07 河北师范学院物理系 本科
1989-09--1992-07 兰州大学大气科学系 硕士
1982-09--1986-07 河北师范学院物理系 本科
学历
-- 研究生
学位
-- 博士
工作经历
工作简历
2012-04~现在, 中国科学院大气物理研究所, 研究员
2010-06~现在, 中国科学院大气物理研究所LASG, 副主任
2001-04~2012-04,中国科学院大气物理研究所, 副研究员
1999-07~2001-04,北海道大学低温科学研究所, 客座教授
1997-07~1999-07,北京大学环境科学中心, 博士后
1992-07~1994-09,兰州高原大气物理研究所, **
2010-06~现在, 中国科学院大气物理研究所LASG, 副主任
2001-04~2012-04,中国科学院大气物理研究所, 副研究员
1999-07~2001-04,北海道大学低温科学研究所, 客座教授
1997-07~1999-07,北京大学环境科学中心, 博士后
1992-07~1994-09,兰州高原大气物理研究所, **
出版信息
发表论文
[1] 张文煜, 马可可, 郭振海, 赵晶, 邱文智. 基于灰狼算法和极限学习机的风速多步预测. 郑州大学学报(工学版)[J]. 2024, 45(2): 89-96,
[2] zhao, jing, Guo Yiyi, lin yihua, Zhao Zhiyuan, zhenhai guo. A novel dynamic ensemble of Numerical Weather Prediction for multi-step wind speed forecasting with deep reinforcement learning and error sequence modeling. Energy[J]. 2024, 131787, https://www.sciencedirect.com/science/article/pii/S0360544224015603.
[3] 张超, 胡俊, 沈辉, 郭振海, 段安民. 中国北部近海超级赤潮与西北太平洋海气相互作用的关联分析. 厦门大学学报:自然科学版[J]. 2023, 62(3): 406-412, http://lib.cqvip.com/Qikan/Article/Detail?id=7109811783.
[4] Zhao, Jing, Guo, Zhenhai, Guo, Yanling, Lin, Wantao, Zhu, Wenjin. A self-organizing forecast of day-ahead wind speed: Selective ensemble strategy based on numerical weather predictions. ENERGY[J]. 2021, 218: http://dx.doi.org/10.1016/j.energy.2020.119509.
[5] 戴秋丹, 郭振海, 孙菽芬, 肖霞. 安徽省淮南森林冠层辐射传输过程的特征. 大气科学[J]. 2021, 45(1): 205-216, http://lib.cqvip.com/Qikan/Article/Detail?id=7103884222.
[6] Zhao, Jing, Wang, Jianzhou, Guo, Zhenhai, Guo, Yanling, Lin, Wantao, Lin, Yihua. Multi-step wind speed forecasting based on numerical simulations and an optimized stochastic ensemble method. APPLIED ENERGY[J]. 2019, 255: http://dx.doi.org/10.1016/j.apenergy.2019.113833.
[7] Zhang, Shenghui, Wang, Jiyang, Guo, Zhenhai. Research on combined model based on multi-objective optimization and application in time series forecast. SOFT COMPUTING[J]. 2019, 23(22): 11493-11521, https://www.webofscience.com/wos/woscc/full-record/WOS:000490958700012.
[8] Zhao, Jing, Guo, Zhenhai, Guo, Yanling, Zhang, Ye, Lin, Wantao, Hu, Jianming. Wind resource assessment based on numerical simulations and an optimized ensemble system. ENERGY CONVERSION AND MANAGEMENT[J]. 2019, 201: http://dx.doi.org/10.1016/j.enconman.2019.112164.
[9] Mangara Rajabu J, Guo Zhenhai, Li Shuanglin. Performance of the Wind Farm Parameterization Scheme Coupled with the Weather Research and Forecasting Model under Multiple Resolution Regimes for Simulating an Onshore Wind Farm. ADVANCES IN ATMOSPHERIC SCIENCES[J]. 2019, 36(2): 119-132, http://sciencechina.cn/gw.jsp?action=detail.jsp&internal_id=6409651&detailType=1.
[10] Ye ZHANG, Shiping YANG, Zhenhai GUO, Yanling GUO, Jing ZHAO. Wind speed forecasting based on wavelet decomposition and wavelet neural networks optimized by the Cuckoo search algorithm. ATMOSPHERIC AND OCEANIC SCIENCE LETTERS[J]. 2019, 12(2): 107-115, http://lib.cqvip.com/Qikan/Article/Detail?id=65798376504849574850484853.
[11] Dong, Yunxuan, Wang, Jianzhou, Guo, Zhenhai. Research and application of local perceptron neural network in highway rectifier for time series forecasting. APPLIED SOFT COMPUTING[J]. 2018, 64: 656-673, http://dx.doi.org/10.1016/j.asoc.2017.12.022.
[12] 张君霞, 黄倩, 田文寿, 郭振海, 田红瑛, 吴稀稀. 对流冷池对黑风暴沙尘抬升和传输影响的大涡模拟研究. 高原气象[J]. 2018, 37(3): 850-862, http://lib.cqvip.com/Qikan/Article/Detail?id=675537296.
[13] Wang, Jianzhou, Niu, Tong, Lu, Haiyan, Guo, Zhenhai, Yang, Wendong, Du, Pei. An analysis-forecast system for uncertainty modeling of wind speed: A case study of large-scale wind farms. APPLIED ENERGY[J]. 2018, 211: 492-512, http://dx.doi.org/10.1016/j.apenergy.2017.11.071.
[14] Dong, Yunxuan, Wang, Jianzhou, Guo, Zhenhai. Research and application of local perceptron neural network in highway rectifier for time series forecasting. APPLIED SOFT COMPUTING[J]. 2018, 64: 656-673, http://dx.doi.org/10.1016/j.asoc.2017.12.022.
[15] Li, Hongmin, Wang, Jianzhou, Lu, Haiyan, Guo, Zhenhai. Research and application of a combined model based on variable weight for short term wind speed forecasting. RENEWABLE ENERGY[J]. 2018, 116: 669-684, http://dx.doi.org/10.1016/j.renene.2017.09.089.
[16] Zhao, Jing, Guo, Yanling, Xiao, Xia, Wang, Jianzhou, Chi, Dezhong, Guo, Zhenhai. Multi-step wind speed and power forecasts based on a WRF simulation and an optimized association method. APPLIED ENERGY[J]. 2017, 197: 183-202, http://dx.doi.org/10.1016/j.apenergy.2017.04.017.
[17] Wang, Jianzhou, Dong, Yunxuan, Zhang, Kequan, Guo, Zhenhai. A numerical model based on prior distribution fuzzy inference and neural networks. RENEWABLE ENERGY[J]. 2017, 112: 486-497, http://dx.doi.org/10.1016/j.renene.2017.05.053.
[18] Wang, Jianzhou, Zhang, Xiaobo, Guo, Zhenhai, Lu, Haiyan. Developing an early-warning system for air quality prediction and assessment of cities in China. EXPERT SYSTEMS WITH APPLICATIONS[J]. 2017, 84: 102-116, http://dx.doi.org/10.1016/j.eswa.2017.04.059.
[19] 郭燕玲, 赵晶, 周林, 张文煜, 郭振海. 山东半岛风电爬坡事件的识别与天气分析研究. 气候与环境研究[J]. 2017, 22(1): 97-107, http://lib.cqvip.com/Qikan/Article/Detail?id=671297052.
[20] Dong, Yunxuan, Wang, Jianzhou, Wang, Chen, Guo, Zhenhai. Research and Application of Hybrid Forecasting Model Based on an Optimal Feature Selection System-A Case Study on Electrical Load Forecasting. ENERGIES[J]. 2017, 10(4): https://doaj.org/article/5aac0e32e1384c14a84552f5473d1ab6.
[21] 夏芸洁, 武云飞, 郭振海, 张井贝, 肖霞, 宋磊, 张仁健. 华东乡村站点气溶胶吸收特性的观测研究. 中国粉体技术[J]. 2017, 23(6): 17-23, http://lib.cqvip.com/Qikan/Article/Detail?id=674167769.
[22] Du, Pei, Wang, Jianzhou, Guo, Zhenhai, Yang, Wendong. Research and application of a novel hybrid forecasting system based on multi-objective optimization for wind speed forecasting. ENERGY CONVERSION AND MANAGEMENT[J]. 2017, 150: 90-107, http://dx.doi.org/10.1016/j.enconman.2017.07.065.
[23] 薛巍, 郭振海, 胡江凯, 付昊桓, 刘勇, 车喜龙, 陈文光. 地球系统模式公共软件平台研发. 中国基础科学[J]. 2017, 19(6): 9-13, http://lib.cqvip.com/Qikan/Article/Detail?id=674390028.
[24] Zhao, Jing, Guo, ZhenHai, Su, ZhongYue, Zhao, ZhiYuan, Xiao, Xia, Liu, Feng. An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed. APPLIED ENERGY[J]. 2016, 162: 808-826, http://dx.doi.org/10.1016/j.apenergy.2015.10.145.
[25] Guo, Zhenhai, Xiao, Xia. Wind Power Assessment Based on a WRF Wind Simulation with Developed Power Curve Modeling Methods. ABSTRACT AND APPLIED ANALYSIS[J]. 2014, 2014:
[26] Guo, Zhenhai, Chi, Dezhong, Wu, Jie, Zhang, Wenyu. A new wind speed forecasting strategy based on the chaotic time series modelling technique and the Apriori algorithm. ENERGY CONVERSION AND MANAGEMENT[J]. 2014, 84: 140-151, http://dx.doi.org/10.1016/j.enconman.2014.04.028.
[27] Li Jihang, Guo Zhenhai, Wang Huijun. Analysis of Wind Power Assessment Based on the WRF Model. 大气和海洋科学快报：英文版[J]. 2014, 126-131, http://lib.cqvip.com/Qikan/Article/Detail?id=49709035.
[28] 张宇, 郭振海, 林一骅, 迟德中. 中尺度模式风电场风速短期预报能力研究. 大气科学[J]. 2013, 37(4): 955-962, http://lib.cqvip.com/Qikan/Article/Detail?id=47737894.
[29] Guo, Zhenhai, Zhao, Weigang, Lu, Haiyan, Wang, Jianzhou. Multi-step forecasting for wind speed using a modified EMD-based artificial neural network model. RENEWABLE ENERGY[J]. 2012, 37(1): 241-249, http://dx.doi.org/10.1016/j.renene.2011.06.023.
[30] 林万涛, 王建州, 张文煜, 郭振海, 迟德中, 张宇. 基于数值模拟和统计分析及智能优化的风速预报系统. 气候与环境研究[J]. 2012, 17(5): 646-658, http://lib.cqvip.com/Qikan/Article/Detail?id=43236318.
[31] Guo, Zhenhai, Zhao, Jing, Zhang, Wenyu, Wang, Jianzhou. A corrected hybrid approach for wind speed prediction in Hexi Corridor of China. ENERGY[J]. 2011, 36(3): 1668-1679, http://dx.doi.org/10.1016/j.energy.2010.12.063.
[32] Guo, Zhenhai, Wu, Jie, Lu, Haiyan, Wang, Jianzhou. A case study on a hybrid wind speed forecasting method using BP neural network. KNOWLEDGE-BASED SYSTEMS[J]. 2011, 24(7): 1048-1056, http://dx.doi.org/10.1016/j.knosys.2011.04.019.
[33] Huang He, Guo ZhenHai, You XiaoBao. A study of atmospheric boundary layer spatial changes over heterogeneous surface in Baiyangdian area. CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION[J]. 2010, 53(9): 2023-2031, https://www.webofscience.com/wos/woscc/full-record/WOS:000282294600002.
[34] Guo, Zhenhai, Dong, Yao, Wang, Jianzhou, Lu, Haiyan. The Forecasting Procedure for Long-Term Wind Speed in the Zhangye Area. MATHEMATICAL PROBLEMS IN ENGINEERING[J]. 2010, 2010: https://doaj.org/article/24939256358c4af2a797e00029b146bb.
[35] 黄鹤, 郭振海, 游小宝. 白洋淀水陆下垫面上行星边界层空间变动研究. 地球物理学报[J]. 2010, 53(9): 2023-2031, http://lib.cqvip.com/Qikan/Article/Detail?id=35559499.
[36] 张宇, 郭振海, 张文煜, 黄鹤. 中尺度模式不同分辨率下大气多尺度特征模拟能力分析. 大气科学[J]. 2010, 34(3): 653-660, http://lib.cqvip.com/Qikan/Article/Detail?id=34056903.
[37] 胡文超, 张文煜, 张宇, 郭振海, 刘欣. 河西走廊下垫面粗糙度实测值与模拟值的差异性分析. 高原气象[J]. 2010, 29(1): 51-55, http://lib.cqvip.com/Qikan/Article/Detail?id=33035335.
[38] 胡文超, 张文煜, 郭振海, 宋嘉尧, 王晓妍. 甘肃半干旱区城乡气溶胶光学特性的观测与分析. 兰州大学学报：自然科学版[J]. 2009, 45(6): 46-50, http://lib.cqvip.com/Qikan/Article/Detail?id=32453078.
[39] 肖霞, 郭振海, 张文煜, 郑飞, 李万彪. NCAR分析资料在大气边界层内误差的初步分析. 气候与环境研究[J]. 2009, 475-483, http://lib.cqvip.com/Qikan/Article/Detail?id=1001286158.
[40] 张文煜, 张宇, 陆晓静, 郭振海, 王晓妍. 黄土高原半干旱区非均一下垫面粗糙度分析. 高原气象[J]. 2009, 28(4): 763-768, http://lib.cqvip.com/Qikan/Article/Detail?id=31893200.
[41] 郭振海. 南水北调华北受水区植被与降水的关系研究. 气候与环境研究[J]. 2006, 11(3): 380-386, http://lib.cqvip.com/Qikan/Article/Detail?id=22454705.
[42] 赵海英, 郭振海, 张宏昇, 何金海. 农牧交错带陆面过程的数值模拟研究. 气候与环境研究[J]. 2006, 11(4): 535-545, https://d.wanfangdata.com.cn/periodical/qhyhjyj200604010.
[43] Tian, WS, Guo, ZH, Yu, RC. Treatment of LBCs in 2D simulation of convection over hills. ADVANCES IN ATMOSPHERIC SCIENCES[J]. 2004, 21(4): 573-586, http://lib.cqvip.com/Qikan/Article/Detail?id=11194904.
[44] 黄伟, 郭振海, 宇如聪. CLM在淮河流域数值模拟试验. 气象学报[J]. 2004, 62(6): 764-775, http://lib.cqvip.com/Qikan/Article/Detail?id=12033501.
[45] 张霭琛, 张宏升, 郭振海, 陈家宜, 陈重. 一维大气边界层二阶闭合的有限元数值模式：I.对流边界层模拟. 大气科学[J]. 1999, 23(6): 733, http://lib.cqvip.com/Qikan/Article/Detail?id=3691710.
[2] zhao, jing, Guo Yiyi, lin yihua, Zhao Zhiyuan, zhenhai guo. A novel dynamic ensemble of Numerical Weather Prediction for multi-step wind speed forecasting with deep reinforcement learning and error sequence modeling. Energy[J]. 2024, 131787, https://www.sciencedirect.com/science/article/pii/S0360544224015603.
[3] 张超, 胡俊, 沈辉, 郭振海, 段安民. 中国北部近海超级赤潮与西北太平洋海气相互作用的关联分析. 厦门大学学报:自然科学版[J]. 2023, 62(3): 406-412, http://lib.cqvip.com/Qikan/Article/Detail?id=7109811783.
[4] Zhao, Jing, Guo, Zhenhai, Guo, Yanling, Lin, Wantao, Zhu, Wenjin. A self-organizing forecast of day-ahead wind speed: Selective ensemble strategy based on numerical weather predictions. ENERGY[J]. 2021, 218: http://dx.doi.org/10.1016/j.energy.2020.119509.
[5] 戴秋丹, 郭振海, 孙菽芬, 肖霞. 安徽省淮南森林冠层辐射传输过程的特征. 大气科学[J]. 2021, 45(1): 205-216, http://lib.cqvip.com/Qikan/Article/Detail?id=7103884222.
[6] Zhao, Jing, Wang, Jianzhou, Guo, Zhenhai, Guo, Yanling, Lin, Wantao, Lin, Yihua. Multi-step wind speed forecasting based on numerical simulations and an optimized stochastic ensemble method. APPLIED ENERGY[J]. 2019, 255: http://dx.doi.org/10.1016/j.apenergy.2019.113833.
[7] Zhang, Shenghui, Wang, Jiyang, Guo, Zhenhai. Research on combined model based on multi-objective optimization and application in time series forecast. SOFT COMPUTING[J]. 2019, 23(22): 11493-11521, https://www.webofscience.com/wos/woscc/full-record/WOS:000490958700012.
[8] Zhao, Jing, Guo, Zhenhai, Guo, Yanling, Zhang, Ye, Lin, Wantao, Hu, Jianming. Wind resource assessment based on numerical simulations and an optimized ensemble system. ENERGY CONVERSION AND MANAGEMENT[J]. 2019, 201: http://dx.doi.org/10.1016/j.enconman.2019.112164.
[9] Mangara Rajabu J, Guo Zhenhai, Li Shuanglin. Performance of the Wind Farm Parameterization Scheme Coupled with the Weather Research and Forecasting Model under Multiple Resolution Regimes for Simulating an Onshore Wind Farm. ADVANCES IN ATMOSPHERIC SCIENCES[J]. 2019, 36(2): 119-132, http://sciencechina.cn/gw.jsp?action=detail.jsp&internal_id=6409651&detailType=1.
[10] Ye ZHANG, Shiping YANG, Zhenhai GUO, Yanling GUO, Jing ZHAO. Wind speed forecasting based on wavelet decomposition and wavelet neural networks optimized by the Cuckoo search algorithm. ATMOSPHERIC AND OCEANIC SCIENCE LETTERS[J]. 2019, 12(2): 107-115, http://lib.cqvip.com/Qikan/Article/Detail?id=65798376504849574850484853.
[11] Dong, Yunxuan, Wang, Jianzhou, Guo, Zhenhai. Research and application of local perceptron neural network in highway rectifier for time series forecasting. APPLIED SOFT COMPUTING[J]. 2018, 64: 656-673, http://dx.doi.org/10.1016/j.asoc.2017.12.022.
[12] 张君霞, 黄倩, 田文寿, 郭振海, 田红瑛, 吴稀稀. 对流冷池对黑风暴沙尘抬升和传输影响的大涡模拟研究. 高原气象[J]. 2018, 37(3): 850-862, http://lib.cqvip.com/Qikan/Article/Detail?id=675537296.
[13] Wang, Jianzhou, Niu, Tong, Lu, Haiyan, Guo, Zhenhai, Yang, Wendong, Du, Pei. An analysis-forecast system for uncertainty modeling of wind speed: A case study of large-scale wind farms. APPLIED ENERGY[J]. 2018, 211: 492-512, http://dx.doi.org/10.1016/j.apenergy.2017.11.071.
[14] Dong, Yunxuan, Wang, Jianzhou, Guo, Zhenhai. Research and application of local perceptron neural network in highway rectifier for time series forecasting. APPLIED SOFT COMPUTING[J]. 2018, 64: 656-673, http://dx.doi.org/10.1016/j.asoc.2017.12.022.
[15] Li, Hongmin, Wang, Jianzhou, Lu, Haiyan, Guo, Zhenhai. Research and application of a combined model based on variable weight for short term wind speed forecasting. RENEWABLE ENERGY[J]. 2018, 116: 669-684, http://dx.doi.org/10.1016/j.renene.2017.09.089.
[16] Zhao, Jing, Guo, Yanling, Xiao, Xia, Wang, Jianzhou, Chi, Dezhong, Guo, Zhenhai. Multi-step wind speed and power forecasts based on a WRF simulation and an optimized association method. APPLIED ENERGY[J]. 2017, 197: 183-202, http://dx.doi.org/10.1016/j.apenergy.2017.04.017.
[17] Wang, Jianzhou, Dong, Yunxuan, Zhang, Kequan, Guo, Zhenhai. A numerical model based on prior distribution fuzzy inference and neural networks. RENEWABLE ENERGY[J]. 2017, 112: 486-497, http://dx.doi.org/10.1016/j.renene.2017.05.053.
[18] Wang, Jianzhou, Zhang, Xiaobo, Guo, Zhenhai, Lu, Haiyan. Developing an early-warning system for air quality prediction and assessment of cities in China. EXPERT SYSTEMS WITH APPLICATIONS[J]. 2017, 84: 102-116, http://dx.doi.org/10.1016/j.eswa.2017.04.059.
[19] 郭燕玲, 赵晶, 周林, 张文煜, 郭振海. 山东半岛风电爬坡事件的识别与天气分析研究. 气候与环境研究[J]. 2017, 22(1): 97-107, http://lib.cqvip.com/Qikan/Article/Detail?id=671297052.
[20] Dong, Yunxuan, Wang, Jianzhou, Wang, Chen, Guo, Zhenhai. Research and Application of Hybrid Forecasting Model Based on an Optimal Feature Selection System-A Case Study on Electrical Load Forecasting. ENERGIES[J]. 2017, 10(4): https://doaj.org/article/5aac0e32e1384c14a84552f5473d1ab6.
[21] 夏芸洁, 武云飞, 郭振海, 张井贝, 肖霞, 宋磊, 张仁健. 华东乡村站点气溶胶吸收特性的观测研究. 中国粉体技术[J]. 2017, 23(6): 17-23, http://lib.cqvip.com/Qikan/Article/Detail?id=674167769.
[22] Du, Pei, Wang, Jianzhou, Guo, Zhenhai, Yang, Wendong. Research and application of a novel hybrid forecasting system based on multi-objective optimization for wind speed forecasting. ENERGY CONVERSION AND MANAGEMENT[J]. 2017, 150: 90-107, http://dx.doi.org/10.1016/j.enconman.2017.07.065.
[23] 薛巍, 郭振海, 胡江凯, 付昊桓, 刘勇, 车喜龙, 陈文光. 地球系统模式公共软件平台研发. 中国基础科学[J]. 2017, 19(6): 9-13, http://lib.cqvip.com/Qikan/Article/Detail?id=674390028.
[24] Zhao, Jing, Guo, ZhenHai, Su, ZhongYue, Zhao, ZhiYuan, Xiao, Xia, Liu, Feng. An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed. APPLIED ENERGY[J]. 2016, 162: 808-826, http://dx.doi.org/10.1016/j.apenergy.2015.10.145.
[25] Guo, Zhenhai, Xiao, Xia. Wind Power Assessment Based on a WRF Wind Simulation with Developed Power Curve Modeling Methods. ABSTRACT AND APPLIED ANALYSIS[J]. 2014, 2014:
[26] Guo, Zhenhai, Chi, Dezhong, Wu, Jie, Zhang, Wenyu. A new wind speed forecasting strategy based on the chaotic time series modelling technique and the Apriori algorithm. ENERGY CONVERSION AND MANAGEMENT[J]. 2014, 84: 140-151, http://dx.doi.org/10.1016/j.enconman.2014.04.028.
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