穆穆(Mu Mu)


穆穆

特聘教授/中国科学院院士/博士生导师

mumu@fudan.edu.cn

电话:021-31248899  传真:021-3124888



研究兴趣  

天气与气候可预报性、大气海洋动力学、气候预测与资料同化、集合预报、目标观测、地球流体动力学


教育背景

学士学位(1975.9 - 1978.8),应用数学,安徽大学

硕士学位(1978.9 - 1981.8),应用数学,安徽大学

博士学位(1982.3 - 1985.7),基础数学,复旦大学


研究经历

2016.3-至今, 特聘教授, 复旦大学

2010.12-2016.3, 研究员, 中国科学院海洋研究所

1993.1-2010.11, 研究员, 中国科学院大气物理研究所

1989.4-1992.12, 副研究员, 中国科学院大气物理研究所

1987.4-1989.3, 博士后, 中国科学院大气物理研究所

1985.8-1987.3, 讲师, 上海交通大学应用数学系


承担课题

2018.01.01-2022.12.31  北极海-冰-气系统对欧亚大陆冬季极端天气事件可预报性的影响,41790475,国家自然科学基金重大项目,基金委,主持,322万   

2015.01.01-2019.12.31  黑潮及延伸体海域海气相互作用机制及其气候效应,41490644,国家自然科学基金重大项目,基金委,参与(张荣华),90万   

2015.01.01-2020.12.31  西太平洋海洋环流动力过程,41421005,国家自然科学基金创新群体,基金委,参与(袁东亮),60万

2013.01.01-2017.12.31  可预报性研究中最优前期征兆与增长最快初始误差的相似性及其在目标观测中的应用,41230420,国家自然科学基金重点项目,基金委,主持,335万   

2013.11.01-2017.12.31  NEC和STCC的变异对黑潮上游段及其可预报性的影响,XDA11010303,中科院先导性专项,中科院,参与(王凡),245.49万   

2012.11.01-2016.08.31  EI Nino可预报性、模式及同化技术改进,国家重点基础项目研究发展计划(973计划),参与,144万

  

学术兼职

国际气象学和大气科学协会(IAMAS)动力气象委员会(ICDM)和行星大气及其演变委员会(ICPAE)委员   

美国气象学会'每月天气评论'associate editor'   

英国皇家气象学会季刊(QJRMS)编委   

国务院学位委员会大气科学评议组召集人   

《中国科学:地球科学》与《Science   China: Earth Sciences》副主编   

《气候与环境研究》副主编   

   

获奖情况

1994   国家杰出青年科学基金   

2001   中国科学院自然科学一等奖(第一完成人)   

2005   国家人事部“全国优秀博士后”称号   

2006   中国科学院宝洁优秀研究生导师奖   

2006   中国科学院研究生院“优秀教师”称号   

2010   何梁何利基金科学与技术进步奖


发表论文(本人名称加粗,通讯作者加*号)

1.Wei, Y.-T., M.   Mu, H.-L. Ren, and J.-X. Fu (2019), Conditional nonlinear optimal   perturbations of moisture triggering primary MJO initiation, Geophysical   Research Letters, doi:10.1029/2018GL081755.

2.Duan, W.-S., and   M. Mu (2018), Predictability of El Niño-Southern Oscillation events, Oxford   Research Encyclopedia of Climate Science, 1-41,   doi:10.1093/acrefore/9780190228620.013.80.

3.Fang, X.-H., and   M. Mu (2018), Both air-sea components are crucial for El Niño forecast   from boreal spring, Scientific Reports, 8(10501), 1-8,   doi:10.1038/s41598-018-28964-z.

4.Fang, X.-H., and   M. Mu (2018), A three-region conceptual model for central Pacific El   Niño including zonal advective feedback, Journal of Climate, 31(13),   4965-4979, doi:10.1175/JCLI-D-17-0633.1.

5.Liu, X., M.   Mu, and Q. Wang (2018), The Nonlinear Optimal Triggering Perturbation of   the Kuroshio Large Meander and Its Evolution in a Regional Ocean Journal   of Physical Oceanography, 48(8), 1771-1786, doi:10.1175/JPO-D-17-0246.1.

6.Liu, X., Q.   Wang, and M. Mu (2018), Optimal initial error growth in the prediction   of the Kuroshio large meander based on a high-resolution regional ocean   model, Advances in Atmospheric Sciences, 35(11), 1362-1371,   doi:10.1007/s00376-018-8003-z.

7.Sun, G.-D., and M.   Mu (2018),   Assessing the characteristics of net primary production due to future climate change and CO2 under RCP4.5 in China,   Ecological Complexity, 34, 58-68, doi:10.1016/j.ecocom.2018.04.001.

8.Tang, Y.-M.,   R.-H. Zhang, T. Liu, W.-S. Duan, D.-J. Yang, F. Zheng, H.-L. Ren, T. Lian, C.   Gao, D.-K. Chen and M. Mu (2018), Progress in ENSO prediction and   predictability study, National Science Review, nwy105,   doi:10.1093/nsr/nwy105.

9.Wei, Y.-T., F.   Liu, M. Mu, and H.-L. Ren (2018), Planetary scale selection of the   Madden-Julian Oscillation in an air-sea coupled dynamic moisture model, Climate   Dynamics, 50, 3441-3456, doi:10.1007/s00382-017-3816-5.

10.张星穆穆王强张坤 (2018), 条件非线性最优扰动方法在黑潮目标观测研究中的应用海洋气象学报, 38(1), 1-9,   doi:10.19513/j.cnki.issn2096-3599.2018.01.001.

11.Feng, R., W.-S.   Duan, and M. Mu (2017), Estimating observing locations for advancing   beyond the winter predictability barrier of Indian Ocean dipole event   predictions, Climate Dynamics, 48(3-4), 1173-1185,   doi:10.1007/s00382-016-3134-3.

12.Li, C., Y. Hu,   F. Zhang, J. Chen, Z. Ma, X. Ye, X. Yang, L. Wang, X. Tang, R. Zhang, M.   Mu, G. Wang, H. Kan, X. Wang, and A. Mellouki (2017), Multi-pollutant   emissions from the burning of major agricultural residues in China and the   related health-economic effects. Atmospheric Chemistry and Physics17(8),   4957-4988, doi:10.5194/acp-17-4957-2017.

13.Luo, D.-H.,   Y.-N. Chen, A.-G. Dai, M. Mu, R.-H. Zhang, and I. Simmonds (2017),   Winter Eurasian cooling linked with the Atlantic Multidecadal Oscillation, Environmental   Research Letters, 12(12), 125002, doi:10.1088/1748-9326/aa8de8.

14.Mu, M., W.-S. Duan,   and Y.-m. Tang (2017), The predictability of atmospheric and oceanic motions:   Retrospect and prospects, Science China: Earth Sciences60(11),   2001-2012, doi:10.1007/s11430-016-9101-x.

穆穆,段晚锁,唐佑民 (2017), 大气-海洋运动的可预报性思考与展望中国科学:地球科学47(10),   1166-1178, doi:10.1360/N072016-00420.

15.Mu, M., R. Feng, and   W.-S. Duan (2017), Relationship between optimal precursors for Indian Ocean   Dipole events and optimally growing initial errors in its prediction, Journal   of Geophysical Research: Oceans122(2), 1141-1153,   doi:10.1002/2016JC012527.

16.Mu, M., and H.-L. Ren   (2017), Enlightenments from researches and predictions of 2014-2016 super El   Niño event, Science China: Earth Sciences60(9), 1569-1571,   doi:10.1007/s11430-017-9094-5.

穆穆,任宏利 (2017),   2014~2016 年超强厄尔尼诺事件研究及其预测给予我们的启示中国科学:地球科学47(9), 993-995,   doi:10.1360/N072017-00245.

17.Mu, M., and Q. Wang   (2017), Applications of nonlinear optimization approach to atmospheric and   oceanic sciences (in Chinese), Scientia Sinica Mathematica, 47(10),   1-16, doi:10.1360/N012016-00200.

18.Peng, F., M.   Mu, and G.-D. Sun (2017), Responses of soil moisture to climate change   based on projections by the end of the 21st century under the high emission   scenario in the 'Huang-Huai-Hai Plain' region of China, Journal of   Hydro-environment Research, 14, 105-118, doi:10.1016/j.jher.2016.10.003.

19.Sun, G.-D., and M.   Mu (2017), A flexible method to determine the sensitive physical   parameter combination for soil carbon under five plant types, Ecosphere,   8(8), doi:10.1002/ecs2.1920.

20.Sun, G.-D., and M.   Mu (2017), A new approach to identify the sensitivity and importance of   physical parameters combination within numerical models using the   Lund-Potsdam-Jena (LPJ) model as an example, Theor. Appl. Climatol.,   128(3-4), 587-601, doi:10.1007/s00704-015-1690-9.

21.Sun, G.-D., and M.   Mu (2017), Projections of soil carbon using the combination of the CNOP-P   method and GCMs from CMIP5 under RCP4.5 in north-south transect of eastern   China, Plant Soil, 413(1-2), 243-260, doi:10.1007/s11104-016-3098-4.

22.Sun, G.-D., and M.   Mu (2017), Responses of terrestrial ecosystem to climate change: results   from approach of conditional nonlinear optimal perturbation of parameters, in   Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications,   edited by S. K. Park and L. Xu, pp. 527-547, Springer International   Publishing, Switzerland, doi:10.1007/978-3-319-43415-5_24.

23.Sun, G.-D., F.   Peng, and M. Mu (2017), Uncertainty assessment and sensitivity   analysis of soil moisture based on model parameter errors - Results from four   regions in China, Journal of Hydrology, 555, 347-360,   doi:10.1016/j.jhydrol.2017.09.059.

24.Sun, G.-D., F.   Peng, and M. Mu (2017), Variations in soil moisture over the   'Huang-Huai-Hai Plain' in China due to temperature change using the CNOP-P   method and outputs from CMIP5, Science China: Earth Sciences,   doi:10.1007/s11430-016-9061-3.

25.Wang, Q., and M.   Mu (2017), Application of conditional nonlinear optimal perturbation to   target observations for high-impact ocean-atmospheric environmental events,   in Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications,   edited by S. K. Park and L. Xu, pp. 513-526, Springer International   Publishing, Switzerland, doi:10.1007/978-3-319-43415-5_23.

26.Wang, Q., Y.-M.   Tang, S. Pierini, and M. Mu (2017), Effects of singular-vector-type   initial errors on the short-range prediction of Kuroshio Extension transition   processes, Journal of Climate, 30(15), 5961-5983,   doi:10.1175/JCLI-D-16-0305.1.

27.Yu, H.-Z., H.-L.   Wang, Z.-Y. Meng, M. Mu, X.-Y. Huang, and X. Zhang (2017), A WRF-based   tool for forecast sensitivity to the initial perturbation: the conditional   nonlinear optimal perturbations versus the first singular vector method   andcomparison to MM5, Journal of   Atmospheric and Oceanic technology, 34(1), 187-206,   doi:10.1175/JTECH-D-15-0183.1.

28.Zhang, K., M.   Mu, and Q. Wang (2017), Identifying the sensitive area in adaptive   observation for predicting the upstream Kuroshio transport variation in a 3-D   ocean model, Science China: Earth Sciences, 60(5), 866-875,   doi:10.1007/s11430-016-9020-8.

29.Zhang, X., M.   Mu, Q. Wang, and S. Pierini (2017), Optimal precursors triggering the   Kuroshio extension state transition obtained by the conditional nonlinear   optimal perturbation approach, Advances in Atmospheric Sciences,   34(6), 685-699, doi:10.1007/s00376-017-6263-7.

30.Zhang, X., Q.   Wang, and M. Mu (2017), The impact of global warming on Kuroshio   Extension and its southern recirculation using CMIP5 experiments with a   high-resolution climate model MIROC4h, Theor. Appl. Climatol.,   127(3-4), 815-827, doi: 10.1007/s00704-015-1672-y.

31.穆穆王强 (2017), 非线性最优化方法在大气-海洋科学研究中的若干应用中国科学:数学47(10),   1-16, doi:10.1360/N012016-00200.

32.Dai, G.-K., M.   Mu, and Z.-N. Jiang (2016), Relationships between optimal precursors   triggering NAO onset and optimally growing initial errors during NAO   prediction, Journal of the Atmospheric Sciences73(1),   293-317, doi:10.1175/JAS-D-15-0109.1.

33.Ding, Y.-J., M.   Mu, J.-Y. Zhang, T. Jiang, T.-J. Zhang, C.-Y. Wang, L.-X. Wu, B.-S. Ye,   M.-Z. Bao, and S.-Q. Zhang (2016), Impacts of Climate Change on the   Environment, Economy, and Society of China, in Climate and Environmental   Change in China: 1951-2012, edited by D.-H. Qin, Y.-J. Ding and M. Mu,   pp. 69-92, Springer-Verlag, Berlin Heidelberg,   doi:10.1007/978-3-662-48482-1_4.

34.Zhang, K., Q.   Wang, M. Mu, and P. Liang (2016), Effects of optimal initial errors on   predicting the seasonal reduction of the upstream Kuroshio transport, Deep-Sea   Research I116(19), 220-235, doi:10.1016/j.dsr.2016.08.008.

35.Zou, G.-A., Q.   Wang, and M. Mu (2016), Identifying sensitive areas of adaptive   observations for prediction of the Kuroshio large meander using a   shallow-water model, Chinese journal of Oceanology and Limnology34(5),   1122-1133, doi:10.1007/s00343-016-4264-5.

36.Zu, Z.-Q., M.   Mu, and H. A. Dijkstra (2016), Optimal initial excitations of decadal   modification of the Atlantic meridional overturning circulation under the   prescribed heat and freshwater flux boundary conditions, Journal of   Physical Oceanography46(7), 2029-2047, doi:10.1175/JPO-D-15-0100.1.

37.Mu, M., W.-S. Duan,   D.-K. Chen, and W.-D. Yu (2015), Target observations for improving   initialization of high-impact ocean-atmospheric environmental events   forecasting, National Science Review2(2), 226-236, doi:   10.1093/nsr/nwv021.

38.Wang, Q., and M.   Mu (2015), A new application of conditional nonlinear optimal   perturbation approach to boundary condition uncertainty, Journal of   Geophysical Research: Oceans120(12), 7979-7996,   doi:10.1002/2015JC011095.

39.Zhou, Q., W.-S.   Duan, M. Mu, and R. Feng (2015), Influence of positive and negative   Indian Ocean Dipoles on ENSO via the Indonesian Throughflow: results from   sensitivity experiments, Advances in Atmospheric Sciences32(6),   783-793, doi:10.1007/s00376-014-4141-0.

40.罗德海穆穆 (2015), 混沌理论之父——1983  Crafoord 奖获得者洛伦茨教授成就解读中国科学:地球科学45(1), 1-7.

41.穆穆周菲凡 (2015), 基于CNOP方法的台风目标观测研究进展气象科技进展5(3),   6-17, doi:10.3969/j.issn.2095-1973.2015.03.001.

42.Feng, R., W.-S.   Duan, and M. Mu (2014), The winter predictability barrier   for IOD events and its error growth dynamics: Results from a fully coupled   GCM, Journal of Geophysical Research: Oceans119(12),   8688-8708, doi:10.1002/2014JC010473.

43.Feng, R., M.   Mu, and W.-S. Duan (2014), Study on the winter persistence   barrier of Indian Ocean dipole events using observation data and CMIP5   model outputs, Theor. Appl. Climatol.118(3), 523-534,   doi:10.1007/s00704-013-1083-x.

44.Mu, M., Q. Wang, W.-S.   Duan, and Z.-N. Jiang (2014), Application of conditional nonlinear optimal   perturbation to targeted observation studies of the atmosphere and ocean, Journal   of Meteorological Research28(5), 923-933,   doi:10.1007/s13351-014-4057-8.

穆穆王强段晚锁姜智娜 (2014), 条件非线性最优扰动法在大气与海洋目标观测研究中的应用,气象学报72(5), 1001-1011, doi:10.11676/qxxb2014.081.

45.Mu, M., Y.-S. Yu, H.   Xu, and T.-T. Gong (2014), Similarities between optimal precursors for ENSO   events and optimally growing initial errors in El Niño predictions, Theor.   Appl. Climatol.115(3-4), 461-469, doi:10.1007/s00704-013-0909-x.

46.Pierini, S., H.   A. Dijkstra, and M. Mu (2014), Intrinsic low-frequency variability and   predictability of the Kuroshio Current and of its extension, Advances in   Oceanography and Limnology5(2), 79-122, doi:10.1080/19475721.2014.962091.

47.Qin, X.-H., and M.   Mu (2014), Can adaptive observations improve tropical cyclone intensity   forecasts?, Advances in Atmospheric Sciences31(2), 252-262,   doi:10.1007/s00376-013-3008-0.

48.Sun, G.-D., and M.   Mu (2014), The analyses of the net primary production due to regional and   seasonal temperature differences in eastern China using the LPJ model, Ecological   Modelling289(7), 66-76, doi:10.1016/j.ecolmodel.2014.06.021.

49.Wang, Q., and M.   Mu (2014), Responses of the ocean planktonic ecosystem to   finite-amplitude perturbations, Journal of Geophysical Research: Oceans,   119(12), 8454-8471, doi:10.1002/2014JC010339.

50.Yu, L., M. Mu,   and Y.-S. Yu (2014), Role of parameter errors in the spring predictability   barrier for ENSO events in the Zebiak-Cane model, Advances in Atmospheric   Sciences31(3), 647-656, doi:10.1007/s00376-013-3058-3.

51.Mu, M., and R.-H.   Zhang (2014), Addressing the issue of fog and haze: A promising perspective   from meteorological science and technology, Science China: Earth Sciences,   57(1), 1-2, doi:10.1007/s11430-013-4791-2.

穆穆张人禾 (2014), 应对雾霾天气气象科学与技术大有可为中国科学地球科学44(1), 1-2, doi:10.1360/zd-2014-44-1-1.

52.Chen, B.-Y., M.   Mu, and X.-H. Qin (2013), The impact of assimilating dropwindsonde data   deployed at different sites on typhoon track forecasts, Monthly Weather   Review141(8), 2669-2682, doi:10.1175/MWR-D-12-00142.1.

53.Jiang, Z.-N., M.   Mu, and D.-H. Luo (2013), A study of the north Atlantic oscillation using   conditional nonlinear optimal perturbation, Journal of the Atmospheric   Sciences70(3), 855-875, doi:10.1175/JAS-D-12-0148.1.

54.Mu, M. (2013),   Methods, current status, and prospect of targeted observation, Science   China: Earth Sciences56(12), 1997-2005,   doi:10.1007/s11430-013-4727-x.

穆穆 (2013), 目标观测的方法、现状与发展展望中国科学:地球科学43(11), 1717-1725, doi:   10.1007/s11430-013-4727-x.

55.Qin, X.-H.,   W.-S. Duan, and M. Mu (2013), Conditions under which CNOP sensitivity   is valid for tropical cyclone adaptive observations, Quarterly Journal of   the Royal Meteorological Society139(675), 1544-1554,   doi:10.1002/qj.2109.

56.Sun, G.-D., and M.   Mu (2013), Understanding variations and seasonal characteristics of net   primary production under two types of climate change scenarios in China using   the LPJ model, Climate Change120(4), 755-769,   doi:10.1007/s10584-013-0833-1.

57.Sun, G.-D., and M.   Mu (2013), Using the Lund-Potsdam-Jena model to understand the different   responses of three woody plants to land use in China, Advances in   Atmospheric Sciences30(2), 515-524,   doi:10.1007/s00376-012-2011-1.

58.Wang, C.-Z.,   C.-X. Li, M. Mu, and W.-S. Duan (2013), Seasonal modulations of   different impacts of two types of ENSO events on tropical cyclone activity in   the western North Pacific, Climate Dynamics40(11-12),   2887-2902, doi:10.1007/s00382-012-1434-9.

59.Wang, Q., M.   Mu, and H. A. Dijkstra (2013), The similarity between optimal precursor   and optimally growing initial error in prediction of Kuroshio large meander   and its application to targeted observation, Journal of Geophysical   Research: Oceans118(2), 869-884, doi:10.1002/jgrc.20084.

60.Zu, Z.-Q., M.   Mu, and H. A. Dijkstra (2013), Optimal nonlinear excitation of decadal   variability of the North Atlantic thermohaline circulation, Chinese   journal of Oceanology and Limnology31(6), 1356-1362,   doi:10.1007/s00343-014-3051-4.

61.Zu, Z.-Q., M.   Mu, and H. A. Dijkstra (2013), Three-dimensional structure of optimal   nonlinear excitation for decadal variability of the thermocline circulation, Atmospheric   and Oceanic Science Letters6(6), 410-416,   doi:10.3878/j.issn.1674-2834.13.0023.

62.穆穆段晚锁 (2013), 条件非线性最优扰动在可预报性问题研究中的应用大气科学37(2), 281-296,   doi:10.3878/j.issn.1006-9895.2012.12319.

63.谢东东孙国栋邵爱梅穆穆 (2013), 草原生态系统模式中参数不确定性导致的模拟结果不确定性研究气候与环境研究18(3), 375-386,   doi:10.3878/j.issn.1006-9585.2012.11179.

64.Chen, B.-Y., and   M. Mu (2012), The roles of spatial locations and patterns of initial   errors in the uncertainties of tropical cyclone forecasts, Advances in   Atmospheric Sciences29(1), 63-78, doi:10.1007/s00376-011-0201-x.

65.Qin, X.-H., and M.   Mu (2012), Influence of conditional nonlinear optimal perturbations   sensitivity on typhoon track forecasts, Quarterly Journal of the Royal   Meteorological Society138(662), 185-197, doi:10.1002/qj.902.

66.Yu, Y.-S., M.   Mu, and W.-S. Duan (2012), Does model parameter error cause a significant   Spring Predictability Barrier for El Niño events in the   Zebiak-Cane model?, Journal of Climate25(4), 1263-1277,   doi:10.1175/2011JCLI4022.1.

67.Yu, Y.-S., M.   Mu, W.-S. Duan, and T.-T. Gong (2012), Contribution of the location and   spatial pattern of initial error to uncertainties in El Niño predictions, Journal   of Geophysical Research: Oceans117(C6), C06018,   doi:10.1029/2011JC007758.

68.Zhou, F.-F., and   M. Mu (2012), The impact of horizontal resolution on the CNOP and on   its identified sensitive areas for tropical cyclone predictions, Advances   in Atmospheric Sciences29(1), 36-46,   doi:10.1007/s00376-011-1003-x.

69.Zhou, F.-F., and   M. Mu (2012), The time and regime dependencies of sensitive areas for   tropical cyclone prediction using the CNOP method, Advances in Atmospheric   Sciences29(4), 705-716, doi:10.1007/s00376-012-1174-0.

70.穆穆秦晓昊周菲凡陈博宇 (2012), 加强目标观测服务防灾减灾成都信息工程学院学报27(1), 20-26.

71.王凡胡敦欣穆穆王启何金海朱江刘志宇 (2012), 热带太平洋海洋环流与暖池的结构特征、变异机理和气候效应地球科学进展27(6), 595-602.

72.Mu, M., and Z.-N.   Jiang (2011), Similarities between optimal precursors that trigger the onset   of blocking events and optimally growing initial errors in onset prediction, Journal   of the Atmospheric Sciences68(12), 2860-2877, doi:   10.1175/JAS-D-11-037.1.

73.Qin, X.-H., and M.   Mu (2011), A study on the reduction of forecast error variance by three   adaptive observation approaches for tropical cyclone prediction, Monthly   Weather Review139(7), 2218-2232, doi: 10.1175/2010MWR3327.1.

74.Sun, G.-D., and M.   Mu (2011), Nonlinearly combined impacts of initial perturbation from   human activities and parameter perturbation from climate change on the   grassland ecosystem, Nonlin. Processes Geophys.18(6),   883-893, doi:10.5194/npg-18-883-2011.

75.Sun, G.-D., and M.   Mu (2011), Response of a grassland ecosystem to climate change in a   theoretical model, Advances in Atmospheric Sciences28(6),   1266-1278, doi:10.1007/s00376-011-0169-6.

76.Wang, H.-L., M.   Mu, and X.-Y. Huang (2011), Application of conditional non-linear optimal   perturbations to tropical cyclone adaptive observation using the Weather   Research Forecasting (WRF) model, Tellus63(5), 939-957,   doi:10.1111/j.1600-0870.2011.00536.x.

77.Zhou, F.-F., and   M. Mu (2011), The impact of verification area design on tropical   cyclone targeted observations based on the CNOP method, Advances in   Atmospheric Sciences28(5), 997-1010,   doi:10.1007/s00376-011-0120-x.

78.穆穆陈博宇周菲凡余堰山 (2011), 气象预报的方法与不确定性气象37(1),   1-13.

79.Mu, M., W.-S. Duan, Q.   Wang, and R. Zhang (2010), An extension of conditional nonlinear optimal   perturbation approach and its applications, Nonlin. Processes Geophys.,   17(2), 211-220.

80.Sun, G.-D., M.   Mu, and Y.-L. Zhang (2010), Algorithm studies on how to obtain a   conditional nonlinear optimal perturbation (CNOP), Advances in Atmospheric   Sciences27(6), 1311-1321, doi:10.1007/s00376-010-9088-1.

81.Duan, W.-S.,   X.-C. Liu, K.-Y. Zhu, and M. Mu (2009), Exploring the initial errors   that cause a significant spring predictability barrier for El   Niño events, Journal of Geophysical Research: Oceans114(C4),   C04022, doi:10.1029/2008JC004925.

82.Duan, W.-S., and   M. Mu (2009), Conditional nonlinear optimal perturbation: Applications   to stability, sensitivity, and predictability, Science in China Series D:   Earth Sciences52(7), 883-906, doi:10.1007/s11430-009-0090-3.

83.Duan, W.-S., F.   Xue, and M. Mu (2009), Investigating a nonlinear characteristic of El   Niño events by conditional nonlinear optimal perturbation, Atmospheric   Research94(1), 10-18, doi:10.1016/j.atmosres.2008.09.003.

84.Jiang, Z.-N.,   and M. Mu (2009), A comparison study of the methods of conditional   nonlinear optimal perturbations and singular vectors in ensemble prediction, Advances   in Atmospheric Sciences26(3), 465-470.

85.Jiang, Z.-N., M.   Mu, and D.-H. Wang (2009), Ensemble prediction experiments using   conditional nonlinear optimal perturbation, Science in China Series D:   Earth Sciences52(4), 511-518.

姜智娜穆穆王东海 (2008), 基于条件非线性最优扰动方法的集合预报试验中国科学 D辑:地球科学38(11), 1444-1451.

86.Jiang, Z.-N.,   H.-L. Wang, F.-F. Zhou, and M. Mu (2009), Applications of Conditional   Nonlinear Optimal Perturbations to Ensemble Prediction and Adaptive   Observation, in Data Assimilation for Atmospheric, Oceanic and Hydrologic   Applications, edited by S. K. Park and L. Xu, pp. 231-252,   Springer-Verlag Berlin Heidelberg, doi: 10.1007/978-3-540-71056-1 12.

87.Mu, M., F.-F. Zhou,   and H.-L. Wang (2009), A method for identifying the sensitive areas in   targeted observations for tropical cyclone prediction: Conditional nonlinear   optimal perturbation, Monthly Weather Review137(5),   1623-1639, doi: 10.1175/2008MWR2640.1.

88.Sun, G.-D., and M.   Mu (2009), Nonlinear feature of the abrupt transitions between multiple   equilibria states of an ecosystem model, Advances in Atmospheric Sciences,   26(2), 293-304.

89.Wu, X.-G., and M.   Mu (2009), Impact of horizontal diffusion on the nonlinear stability of   thermohaline circulation in a modified box mode, Journal of Physical   Oceanography39(3), 798-805, doi:10.1175/2008JPO3910.1.

90.Yu, Y.-S., W.-S.   Duan, H. Xu, and M. Mu (2009), Dynamics of nonlinear error growth and   season-dependent predictability of El Nino events in the Zebiak-Cane model, Quarterly   Journal of the Royal Meteorological Society135(645), 2146-2160,   doi: 10.1002/qj.526.

91.Duan, W.-S., H.   Xu, and M. Mu (2008), Decisive role of nonlinear temperature advection   in El Niño and La Niña amplitude asymmetry, Journal of Geophysical   Research: Oceans113(C1), C01014, doi:10.1029/2006JC003974.

92.Jiang, Z.-N., M.   Mu, and D.-H. Wang (2008), Conditional nonlinear optimal perturbation of   a T21L3 quasi-geostrophic model, Quarterly Journal of the Royal   Meteorological Society134(633), 1027-1038, doi: 10.1002/qj.256.

93.Mu, M., and Z.-N.   Jiang (2008), A method to find perturbations that trigger blocking onset:   conditional nonlinear optimal perturbations, Journal of the Atmospheric   Sciences65(12), 3935-3946, doi: 10.1175/2008JAS2621.1.

94.Mu, M., and Z.-N.   Jiang (2008), A new approach to the generation of initial perturbations for   ensemble prediction: Conditional nonlinear optimal perturbation, Chinese   Science Bulletin53(13), 2062-2068.

穆穆姜智娜 (2007), 集合预报初始扰动产生的一个新方法条件非线性最优扰动科学通报52(12), 1457-1465,   doi:10.1360/csb2007-52-12-1457.

95.李崇银穆穆周广庆杨辉 (2008), ENSO机理及其预测研究大气科学32(4), 761-781.

96.王铁穆穆 (2008), REM模式伴随系统的建立及其四维变分资料同化初步试验气象学报66(6), 955-967.

97.吴晓刚穆穆 (2008), 风生涡旋对热盐环流年代际变率的影响———基于盒子模型的分析海洋科学进展26(4), 411-417.

98.Mu, M., and W.-S. Duan   (2007), Conditional nonlinear optimal perturbation: a new approach to the   stability and sensitivity studies in geophysical fluid dynamics, in 16th   Australasian Fluid Mechanics Conference (AFMC), edited by J. Peter, M.   Tim, C. Matthew, B. David, M. David, C. Rose, M. Richard and L. Charles, pp.   225-232, School of Engineering, The University of Queensland, Gold Coast,   Queensland, Australia.

99.Mu, M., W.-S. Duan,   and B. Wang (2007), Season-dependent dynamics of nonlinear optimal error growth   and El Niño-Southern Oscillation predictability in a theoretical model, Journal   of Geophysical Research: Atmospheres112(D10), D10113,   doi:10.1029/2005JD006981.

100.Mu, M., and B. Wang (2007), Nonlinear   instability and sensitivity of a theoretical grassland ecosystem to   finite-amplitude perturbations, Nonlin. Processes Geophys.14(4),   409-423.

101.Mu, M., H. Xu, and W.-S. Duan   (2007), A kind of initial errors related to spring predictability barrier   for El Niño events in Zebiak-Cane model, Geophysical Research Letters,   34(3), L03709, doi:10.1029/2006GL027412.

102.穆穆王洪利周菲凡 (2007), 条件非线性最优扰动方法在适应性观测研究中的初步应用大气科学31(6), 1102-1112.

103.王铁穆穆 (2007), 伴随系统及非线性优化方法在REM模式可预报性研究中的实际个例应用大气科学31(5),   987-998.

104.Duan, W.-S., and M. Mu   (2006), Investigating decadal variability of El Nino-Southern Oscillation   asymmetry by conditional nonlinear optimal perturbation, Journal of   Geophysical Research111(C7), C07015, doi:10.1029/2005JC003458.

105.Mu, M., W.-S. Duan, H. Xu,   and B. Wang (2006), Applications of conditional nonlinear optimal   perturbation in predictability study and sensitivity analysis of weather and   climate, Advances in Atmospheric Sciences23(6), 992-1002.

106.Mu, M., and Z.-Y. Zhang   (2006), Conditional nonlinear optimal perturbations of a two-dimensional   quasigeostrophic model, Journal of the Atmospheric Sciences63(6),   1587-1604.

107.Zheng, Q., and M. Mu (2006),   The effects of the model errors generated by discretization of on-off   processes on VDA, Nonlin. Processes Geophys.13(3), 309-320.

108.段晚锁穆穆 (2006), 用非线性最优化方法研究El Niño可预报性的进展与前瞻大气科学30(5),   759-766.

109.Duan, W.-S., and M. Mu   (2005), Applications of nonlinear optimization method to numerical studies of   atmospheric and oceanic sciences, Applied Mathematics and Mechanics26(5),   636-646.

110.Duan, W.-S., and M. Mu   (2005), Applications of nonlinear optimization methods to quantifying the   predictability of a numerical model for El Nino-Southern Oscillation, Progress   in Natural Science15(10), 915-921.

111.Mu, M., and W.-S. Duan   (2005), Conditional nonlinear optimal perturbation and its applications to   the studies of weather and climate predictability, Chinese Science   Bulletin50(21), 2401-2407.

112.Mu, M., and Q. Zheng (2005),   Zigzag oscillations in variational data assimilation with physical   on–off processes, Monthly Weather Review133(9),   2711-2720.

113.Sun, L., M. Mu, D.-J. Sun,   and X.-Y. Yin (2005), Passive mechanism of decadal variation of thermohaline   circulation, Journal of Geophysical Research: Oceans110(C7),   C07025, doi:10.1029/2005JC002897.

114.Wang, J.-F., M. Mu, and Q.   Zheng (2005), Initial condition and parameter estimation in physical 'on–off'   processes by variational data assimilation, Tellus57(5),   736-741.

115.Dimet, F.-S. L., V. P. Shutyaev,   J.-F. Wang, and M. Mu (2004), The problem of data assimilation for   soil water movement, ESAIM: Control, Optimisation and Calculus of   Variations10(3), 331-345, doi:10.1051/cocv:2004009.

116.Duan, W.-S., and M. Mu   (2004), Conditional nonlinear optimal perturbations as the optimal precursors   for El Nino-Southern Oscillation events, Journal of Geophysical Research:   Atmospheres109(D23), D23105, doi:10.1029/2004JD004756.

117.Mu, M., W.-S. Duan, and J.-F.   Chou (2004), Recent advances in predictability studies in China (1999-2002), Advances   in Atmospheric Sciences21(3), 437-443.

118.Mu, M., L. Sun, and H. A.   Dijkstra (2004), The sensitivity and stability of the ocean's thermohaline   circulation to finite amplitude perturbations, Journal of Physical   Oceanography34(10), 2305-2315.

119.Xu, H., M. Mu, and D.-H. Luo   (2004), Application of nonlinear optimization method to sensitivity analysis   of numerical model, Progress in Natural Science14(6),   546-549.

120.卢萍郑琴宇如聪穆穆 (2004), 最优化方法在确定对流混合层顶夹卷率中的应用大气科学28(1), 112-124.

121.Mu, M., and W.-S. Duan   (2003), A new approach to studying ENSO predictability: Conditional nonlinear   optimal perturbation, Chinese Science Bulletin48(10), 1045-1047.

122.Mu, M., W.-S. Duan, and B.   Wang (2003), Conditional nonlinear optimal perturbation and its applications,   Nonlinear Processes in Geophysics10(6), 493-501.

123.Mu, M., and J.-F. Wang   (2003), A method for adjoint variational data assimilation with physical   on-off processes, Journal of the Atmospheric Sciences60(16),   2010-2018.

124.刘永明穆穆邱令存 (2003), 纬向对称的连续层结准地转流的非线性稳定性自然科学进展13(4), 378-382.

125.穆穆季仲贞王斌李扬 (2003), 地球流体力学的研究与进展大气科学27(4), 689-711.

126.孙亮穆穆 (2003), 温盐环流稳定性以及年代际变率的研究进展海洋学报25(4), 111-118.

127.Mu, M., W.-S. Duan, and J.-C.   Wang (2002), The predictability problems in numerical weather and climate   prediction, Advances in Atmospheric Sciences19(2), 191-204.

128.Mu, M., W.-S. Duan, and J.-F.   Wang (2002), Nonlinear optimization problems in atmospheric and oceanic   sciences, Computational Mathematics and Modeling155, 155-164.

129.Wang, J.-F., M. Mu, and Q.   Zheng (2002), Adjoint approach to VDA of on-off processes based   on nonlinear perturbation equation, Progress in Natural Science12(11),   869-873.

130.穆穆李建平丑纪范段晚锁王家城 (2002), 气候系统可预报性理论研究气候与环境研究7(2), 227-235.

131.Liu, Y.-M., and M. Mu (2001),   Nonlinear stability of the generalized Eady model, Journal of the   Atmospheric Sciences58(8), 821-827.

132.Mu, M., and H. Guo (2001),   Effect of four-dimensional variatinal data assimilation in case of nonlinear   instability, Progress in Natural Science11(11), 825-832.

133.Mu, M., and J.-C. Wang (2001),   Nonlinear fastest growing perturbation and the first kind of predictability, Science   in China44(12), 1128-1139.

134.Mu, M., and Y.-H. Wu (2001),   Arnol'd Nonlinear stability theorems and their application to the atmosphere   and oceans, Surveys in Geophysics22(4), 383-426.

135.Wu, Y.-H., M. Mu, Q.-C. Zeng,   and Y. Li (2001), Weak solutions to a model of climate dynamics, Nonlinear   Analysis: Real World Applications2(4), 507-521.

136.穆穆郭欢王佳峰, Y. Li (2001), 非线性稳定性与奇异值关系.自然科学进展11(4), 418-422.

137.Li, Y., M. Mu, and Y.-H. Wu   (2000), A study on the nonlinear stability of fronts in the ocean on a   sloping continental shelf, Advances in Atmospheric Sciences17(2),   275-284.

138.Mu, M. (2000), Nonlinear   singular vectors and nonlinear singular values, Science in China43(4),   375-385.

139.Mu, M., H. Guo, and J.-F.   Wang (2000), The impact of nonlinear stability and instability on the   validity of the tangent linear model. Advances in Atmospheric Sciences,   17(3), 375-390.

140.王必正曾庆存穆穆 (2000), 伴随方程在水汽资料四维同化中的应用I. 理论气候与环境研究5(3), 273-278.

141.Mu, M., V. A. Vladimirov, and   Y.-H. Wu (1999), Energy-Casimir and energy-Lagrange methods in the study of   nonlinear symmetric stability problems, Journal of the Atmospheric   Sciences56(3), 400-411.

142.Mu, M., and Y.-H. Wu (1999),   Symmetric stability problems in the atmospheric dynamics, in Nonlinear   Evolution Equations and Their Applications: Proceedings of the Luso-Chinese   Symposium, edited, pp. 165-175, World Scientific.

143.Mu, M., Y.-H. Wu, and M.-Z.   Tang (1999), Nonlinear stability analysis of the zonal flows at middle and   high latitudes, Advances in Atmospheric Sciences16(4),   569-580.

144.Vladimirov, V. A., M. Mu,   Y.-H. Wu, and K. I. Ilin (1999), On nonlinear stability of baroclinic fronts,   Geophys. Astrophys. Fluid Dynamics91(1-2), 65-84.

145.Wu, Y.-H., and M. Mu (1999),   Maximal energy isolated vortices in a uniform shear flow, Nonlinear   Analysis38(1), 123-135.

146.Wu, Y.-H., and M. Mu (1999),   Nonlinear instability of dipole vortices and the atmospheric blocking, Progress   in Natural Science9(3), 234-237.

吴永辉穆穆 (1999), 偶极涡的Liapunov意义下非线性不稳定性及大气阻塞现象探讨自然科学进展9(4), 369-372.

147.Li, Y., M. Mu, S.-E. Moon,   C.-S. Ryu, and B.-J. Kim (1998), Baroclinic instability in the three-layer   generalized Phillips' model part II: nonlinear stability theory, Korean   Journal of Atmospheric Sciences2(1), 9-13.

148.Li, Y., M. Mu, S.-E. Moon,   and K.-T. Sohn (1998), On the linear and nonlinear stability of generalized   Eady model part I: normal mode method, Korean Journal of Atmospheric   Sciences1(2), 113-118.

149.Mu, M. (1998), Optimality of   a nonlinear stability criterion of two-layer Phillips model, Chinese   Science Bulletin43(8), 656-659.

穆穆(1998), 二层Phillips模型的非线性稳定性判据的最优性之讨论科学通报43(7),   43-46.

150.Mu, M., and J. Xiang (1998),   On the evolution of finite-amplitude disturbance to the barotropic and   baroclinic quasigeostrophic flows, Advances in Atmospheric Sciences15(1),   113-123.

151.Wu, Y.-H., and M. Mu (1998),   A remark on the nonlinearly symmetric stability criteria, Chinese Science   Bulletin43(12), 1050-1053.

152.穆穆 (1998), 大气运动非线性稳定性研究中的能量-Casimir方法力学进展28(2), 235-249.

153.穆穆 (1998), 行星大气对称稳定性的一个判据/中国科学院大气物理所编.东亚季风和中国暴雨——庆贺陶诗言院士八十华诞北京:气象出版社, 476-482.

154.Xiang, J., and M. Mu (1997),   Saturation of nonlinear instability of parallel shear flow, Progress in   Natural Science7(2), 239-243.

项杰穆穆 (1997), 平行切变流的非线性不稳定的饱和问题自然科学进展7(4),   486-490.

155.Li, Y., and M. Mu (1996),   Baroclinic instability in the generalized Phillips' model part I: two-layer   model, Advances in Atmospheric Sciences13(1), 33-42.

156.Li, Y., and M. Mu (1996), On   the nonlinear stability of three-dimensional quasigeostrophic motions in   spherical geometry, Advances in Atmospheric Sciences13(2),   203-216.

157.Liu, Y.-M., and M. Mu (1996),   Nonlinear stability theorem for Eady's model of quasigeostrophic barolinic   flow, Journal of the Atmospheric Sciences53(10), 1459-1463.

158.Liu, Y.-M., M. Mu, and T. G.   Shepherd (1996), Nonlinear stability of continuously stratified   quasi-geostrophic flow, J. Fluid Mech.325(8), 419-439.

159.Mu, M., T. G. Shepherd, and   K. Swanson (1996), On nonlinear symmetric stability and the nonlinear   saturation of symmetric instability, Journal of the Atmospheric Sciences,   53(20), 2918-2923.

160.Mu, M. (1995), Some advances   in the study of nonlinear instability of the atmospheric motions, Chinese   Journal of Atmospheric Sciences19(3), 318-334.

穆穆 (1995), 大气运动非线性不稳定性研究的若干新进展大气科学19(4), 494-509.

161.Liu, Y.-M., and M. Mu (1994),   Arnol'd's second nonlinear stability theorem for general muitilayer   quasi-geostrophic model, Advances in Atmospheric Sciences11(1),   36-42.

162.Mu, M., and T. G. Shepherd   (1994), Nonlinear stability of Eady's model, Journal of the Atmospheric   Sciences51(23), 3427-3436.

163.Mu, M., and T. G. Shepherd   (1994), On Arnol'd's second nonlinear stability theorem for two-dimensional   quasi-geostrophic flow, Geophys. Astrophys. Fluid Dynamics75(1),   21-37.

164.Mu, M., Q.-C. Zeng, T. G.   Shepherd, and Y.-M. Liu (1994), Nonlinear stability of multilayer   quasi-geostrophic flow, J. Fluid Mech.264(264), 165-184.

165.Mu, M., and J. Simon (1993),   A remark on nonlinear stability of three-dimensional quasigeostrophic   motions, Chinese Science Bulletin38(23), 1978-1984.

穆穆, J. Simon (1993), 三维准地转运动的非线性稳定性研究的一个注记Chinese   Science Bulletin38(22), 2057-2062.

166.Liu, Y.-M., and M. Mu (1992),   A problem related to nonlinear stability criteria for multi-layer   quasi-geostrophie flow, Advances in Atmospheric Sciences9(3),   337-345.

167.Mu, M. (1992), Nonlinear   stability of two-dimensional quasigeostrophic motions, Geophys. Astrophys.   Fluid Dynamics65(1-4), 57-76.

168.Mu, M., and X.-Y. Wang   (1992), Nonlinear stability criteria for motions of three-dimensional   quasi-geostrophic flow on β-plane, Progress in Natural Science2(1),   48-53.

169.Mu, M., and X.-Y. Wang   (1992), Nonlinear stability criteria for the motion of three-dimensional   quasigeostrophic flow on a beta-plane, Nonlinearity5(5),   353-371.

170.Mu, M. (1991), Nonlinear   stability criteria for motions of multilayer quasi-geostrophic flow, Science   in China34(12), 1516-1528.

穆穆 (1991), 多层准地转流体运动的稳定性中国科学8(16), 888-897.

171.Mu, M., and Q.-C. Zeng   (1991), Criteria for the nonlinear stability of three-dimensional   quasi-geostrophic motions, Advances in Atmospheric Sciences8(1),   1-10.

172.Mu, M., and Q.-C. Zeng   (1991), New developments on existence and uniqueness of solutions to some   models in atmospheric dynamics, Advances in Atmospheric Sciences8(4),   383-398.

173.穆穆(1990), Global smooth solutions of two-dimensional   Euler equations, Chinese Science Bulletin35(22), 1895-1900.

穆穆 (1990), 二维Euler方程的整体光滑解科学通报35(9),   680-683.

174.Mu, M. (1989), Global   classical solutions to initial-boundary value problems for the potential   vorticity equation, Journal of Computational and Applied Mathematics28(1),   327-338.

175.穆穆 (1989), 椭圆-抛物复合型方程的一类边值问题数学年刊10A(3), 351-358.

176.穆穆 (1989), 一个退缩椭圆型方程的边值问题应用数学与计算数学学报3(1),   26-30.

177.Mu, M. (1988), Classical   solution to 3-dimensional balanced model in numerical weather prediction, KEXUE   TONGBAO33(19), 1628-1631.

178.Mu, M. (1988), Necessary and   sufficient conditions for existence of global classical solutions of   two-dimensional Euler equations in time dependent domain, KEXUE TONGBAO,   33(15), 1295-1299.

穆穆(1988), 两维Euler方程在随时间变化区域中存在整体光滑解的充分必要条件科学通报33(14),   1111-1114.

179.Mu, M., and Q.-C. Zeng   (1988), On wellposedness of an initial-boundary value problem for a   three-dimensional balanced model, Chinese Journal of Atmospheric Sciences,   12(2), 189-199.

180.穆穆 (1988), 一类复合型算子的奇性传播定理复旦学报(自然科学版)27(2),   127-130.

181.穆穆, and 曾庆存 (1988), 关于三维平衡模式初边值问题适定性的研究大气科学12(2), 153-161.

182.Mu, M. (1987), Global   classical solutions of initial-boundary value problems for generalized   vorticity equations, Scientia Sinica30(4), 359-371.

穆穆 (1986), 广义涡度方程初边值问题的整体光滑解及其应用中国科学11A(4), 1153-1163.

183.Mu, M. (1987), Global   classical solutions of the Cauchy problems for nonlinear vorticity equations   and its applications, Chin. Ann.of Math.8B(2), 199-207.

184.穆穆 (1987), 数值天气预报中三维平衡模式的古典解科学通报32(7),   533-536.

185.Mu, M. (1986), Existence and   uniqueness of global strong solutions of two models in atmospheric dynamics, Applied   Mathematics and Mechanics7(10), 965-970.

穆穆 (1986), 两个大气动力学模式整体强解的存在唯一性应用数学和力学7(10), 907-912.

186.穆穆 (1986), 非线性涡度方程初边值问题的整体光滑解及其应用数学物理学报6(2),   201-218.

187.穆穆 (1986), 斜压准地转-准无辐散模式初边值问题古典解的存在唯一性大气科学10(2), 113-120.

188.穆穆 (1986), 一阶线性偏微分方程组抽象齐次定解问题强解与弱解的一致性复旦学报(自然科学版)25(1),   25-33.

  

邀请报告

[1]Mu Mu, How to explore   the extreme impact of climate change on terrestrial ecosystem? WMO/IOC/ICSU   Joint Scientific Committee for the World Climate Research Programme (WCRP),   Nanjing University of Information Science and Technology, April 16-20, 2018,Nanjing, China.

[2]Mu Mu, Conditional   Nonlinear Optimal Perturbation and its Applications to the Studies of the   Atmosphere and Oceans, Understanding Nature from Computation, December 16,   2018, Shanghai, China.

[3]Mu Mu, Similarities   Between optimal Precursors and Optimally Growing Initial Errors and targeted   Observations in Weather and Climate Predictions, IAPSO-IAMAS-IAGA JOINT   ASSEMBLY 2017, August 27-September 1, 2017, Cape Town, South Africa.

[4]Mu Mu, A nonlinear   optimization approach to uncertainties of simulation and prediction of   terrestrial ecosystem under global changes, 5th China-Thailand   Joint Conference on Climate Change, November 27-29, 2017,Chiang Mai,   Thailand.

[5]Mu Mu, Some   Progresses in the studies of Target observations, 7th   International Conference on Atmosphere, Ocean and Climate Change,   Chinese-American Oceanic and Atmospheric Association (COAA), July 27-30,   2016, Beijing, China.

[6]Mu Mu, Winter   Predictability Barrier of Indian Ocean Dipole Event Predictions: The Role of   Initial Errors and Targeted Observations, Asia Oceania Geosciences Society   (AOGS), August 1-5, 2016, Beijing, China.

[7]Mu Mu, Applications   of Nonlinear Optimization Approaches to ENSO Predictability Studies, Asia   Oceania Geosciences Society (AOGS), August 1-5, 2016, Beijing, China.

[8]Mu Mu, Targeted   observation studies of oceans, the Institute of Oceanology of the Chinese   Academy of Sciences (IOCAS) and Research Center for Oceanography, Indonesian   Institute of Sciences (RCO-LIPI), December 5-6, 2016, Bali, Indonesia.

[9]Mu Mu, Applications   of Climate System Models, Target Observations for High-impact   Ocean-Atmospheric Environmental Events, Second International Symposium on   Climate and Earth System Modeling, Earth System Modeling Center, Nanjing   University of Information Science and Technology, October 15-16, 2015,   Nanjing, China.

[10]Mu Mu, Optimal precursor and optimally   growing initial error in the predictability studies of Kuroshio large meander   and their nonlinear evolution mechanism, EGU General Assembly 2014, April   27-May 2, 2014, Vienna, Austria.

[11]Mu Mu, Application of conditional nonlinear   optimal perturbation to the predictability studies of Kuroshio large meander,   AOGS 11th Annual Meeting, Jul.28-Aug.1, 2014, Sapporo, Japan.

[12]Mu Mu, Similarities between precursors for El   Niño events and   initial errors in the predictions and implications in targeted observation,   Davos Atmosphere and Cryosphere Assembly, IAMAS, IACS and IUGG, August 8-12,   2013, Davos, Switzerland.

[13]Mu Mu, Dynamics of nonlinear optimal error   growth in the studies of predictability, the RIMS International Conference on   Theoretical Aspects of Variability and Predictability in Weather and Climate   Systems, Kyoto University, October 22-25, 2013, Kyoto, Japan.

[14]Mu Mu, Similarities between optimal   precursors and optimally growing initial errors in onset predictionENSO, Blocking   and Kuroshio Current, EGU 2012 General Assembly, EGU, April 22-27, 2012,   Vienna, Austria.

[15]Mu Mu, Applications of Conditional nonlinear   optimal perturbations to the studies of ENSO and THC, NTU International   Science Conference on Climate Change: Multidecadal and Beyond, Taiwan   University, September 17-21, 2012, Taiwan University, Taipei.

[16]Mu Mu, A Similarity problem between signals and noises in   thepredictability studies of ENSOblocking and kuroshio current, 7th   International symposium on atmospheric physics, climate and environment,   Institute of atmospheric physics, Russian academy of sciences, July 19-21,   2012, Moscow, Russia.

[17]Mu Mu, Similarities between precursors of   weather and climate events and optimally growing initial errors in their   onset predictions, IUGG 2011, June 28-July 7, 2011, Melbourne, Australia.

[18]Mu Mu, Duan Wansuo, and Yu Yanshan, The error   growth dynamics and spring predictability barrier of El Nino prediction,   International Symposium on Boundary Current Dynamics: Its Connection with   Open-ocean and Coastal Processes and Responses to Global Climate Change,   Ocean University of China, May 31-June 2, 2010, Qingdao, China.

[19]Mu Mu, and Qin XiaohaoA comparison   study on adaptive observation approaches, Singular vector, conditional   nonlinear optimal perturbation and ensemble transform Kalman filter, The   Third International Workshop on Prevention and Mitigation of Meteorological   Disasters in Southeast Asia, Kyoto UniversityUniversity Consortium Oita and Japan Meteorological   Agency March 1-4, 2010,Ritsumeikan Asia Pacific University, Beppu,   Japan.

[20]Mu Mu, Conditional nonlinear optimal   perturbation and its applications to predictability, stability and   sensitivity studies, EGU General Assembly 2010, 2-7 May, 2010, Vienna,   Austria.

[21]Mu Mu, Duan Wansuo, and Yu Yanshan, Dynamics   of Nonlinear Error Growth and Spring Predictability Barrier for El Nino Predictions, 9th CTWF   International Workshop Climate and Environmental Change: Challenges for   Developing Countries, CAS-TWAS-WMO, November 17-19, 2010, Beijing, China.

[22]Mu Mu, Approaches to Adaptive Observation for   Improving High Impact Weather Prediction: CNOP and SV, The Second   International Workshop on Prevention and Mitigation of Meteorological   Disasters in Southeast Asia, March 2-5, 2009, Bandung, Indonesia.

[23]Mu Mu, Progresses in the study of spring   predictability barrier for El Nino events, 2009 LASG International Summer   Symposium, August 19-21, 2009, Yinchuan, China.

[24]Mu Mu, Zhou Feifan, and Wang Hongli, An   Investigation on the Applicability of Conditional Nonlinear Optimal   Perturbations to Targeting Observations, Asia Oceanic Geosciences Society   (AOGS), June 16-20, 2008, Busan, Korea.

[25]Mu Mu, Zhou Feifan, Wang Hongli, and Wu   Xiaogang, Some new progresses in the applications of conditional nonlinear   optimal perturbations, JSPS 5th university allied workshop on climate and   environment studies for global sustainability, June 30-July 4, 2008, Tokyo,   Japan.

[26]Mu Mu, Applications of Conditional nonlinear   optimal perturbations to adaptive observations, EGU General Assembly 2008, April 13-18,   2008, Vienna,   Austria.

[27]Mu Mu, Duan Wansuo, and Xu Hui, Study of spring   predictability barrier for ENSO in Zebiak-Cane model, IUGG2007, July 2-13, 2007,   Perugia, Italy.

[28]Mu Mu, Conditional nonlinear optimal   perturbation and its applications, IUGG2007, July 2-13, 2007, Perugia, Italy.

[29]Mu Mu, and Duan Wansuo, Conditional nonlinear   optimal perturbation, a new approach to the stability and sensitivity studies   in geophysical fluid dynamics, 16th Australasian Fluid Mechanics   Conference,University of Queensland, December 2-7, 2007, Brisbane,   Australia.

[30]Mu Mu, and Wang Bo, The transition between   grassland and desert in a theoretical grassland ecosystem, International   Geographical Union (IGU), July 3-7, 2006, Brisbane, Australia.

[31]Mu Mu, and Sun Liang, Passive mechanism of   decadal variation of thermohaline circulation, EGU General Assembly, April   24-29, 2005, Vienna, Austria.

[32]Mu Mu, and Zheng Qin, Removing zigzag   oscillations in VDA with physical on-off processes, The fourth WMO International   symposium on assimilation of observations in meteorology and oceanography,   April 18-22, 2005, Prague, Czech.

[33]Mu Mu, Duan Wansuo, and Wang Bin, A possible   mechanism of spring   predictability barrier for El Nino-Southern Oscillation events, EGU General   Assembly, April 24-29, 2005, Vienna, Austria.

[34]Mu Mu, and Duan Wansuo, A possible mechanism   of spring   predictability barrier for ENSO events, 1st Alexander Von Humboldt   International Conference on The El Niño Phenomenon and its global impact,   Centro International para la Investigación del Fenómeno de El Niño (CIIFEN) and EGU, May 16-20, 2005,   Guayaquil, Ecuador.

[35]Mu Mu, Sun Liang, and D. A. Henk,   Applications of conditional nonlinear optimal perturbation to the study of   oceans thermohaline   circulation, 1st EGU General Assembly, April 25-30, 2004, Nice,   France.

[36]Mu Mu, Zheng Qin and Wang Jiafeng, Approaches   to adjoint variational data assimilation with physical on-off processes, 1st   EGU General Assembly, April 25-30, 2004, Nice, France.

[37]Mu Mu, and Duan Wansuo, Applications of   conditional nonlinear optimal perturbation to the study of climte   predictability, The Fourth METRI-IAP Joint Research Workshop, October 9-11,   2004, Jeju, Korea.

[38]Mu Mu, and Duan Wansuo, A possible mechanism of   the spring predictability barrier on ENSO events, International symposium on   tropical weather and climate, LASG, November 7-11, 2004, Guangzhou, China.

[39]Mu Mu, Duan Wansuo, and Sun Liang,   Applications of conditional nonlinear optimal perturbations to predictability   of ENSO and sensitivity analysis of oceans THC, CAS-TWAS-WMO Forum, International   Symposium on extreme weather and climate events, their dynamics and   predictions, CAS-TWAS-WMO, October 12-16, 2004, Beijing, China.

[40]Mu Mu, Zheng Qin, and Wang Jiafeng, A method for adjoint   variational data assimulation, 1st annual meeting of AOGS, July   5-9, 2004, Sigapore.

[41]Mu Mu, and Wang Jiafeng, A new adjoint method   for variational data assimilation with physical on-off processes, European Geophysical Society   27th General Assembly, EGS, April 21-26, 2002, Nice, France.

[42]Mu Mu, Duan Wansuo, and Wang Jiacheng,   Predictability problems in numerical weather and climate prediction, European   Geophysical Society 27th General Assembly, EGS, April 21-26, 2002,   Nice, France.

[43]Mu Mu, and Wang Jiachen, The first kind of   predictability and nonlinear fastest growing perturbation, European   Geophysical Society 26th General Assembly, EGS,March 25-30,   2001, Nice, France.

[44]Mu Mu, and Wang Jiacheng, Nonlinear optimal   perturbations, predictability and sensitivity analysis, International   Conference on Climate and Environment Variability and Predictability (CEVP),   August 7-11, 2000, Shanghai, China.

[45]Mu Mu, Arnolds stability theorems, the Eliassen-Palm   flux theorem, and applications to atmosphere dynamics, EGS XXV General   Assembly, April 25-292000,   Nice, France.

[46]Mu Mu, Nonlinear stability and instabililty   of zonal wind in the atmosphere, 23th General assembly of European Geophysics   Society, April 20-24, 1998, Nice, France.

[47]Mu Mu, Numerical investigation of the   nonlinear stability and instability of quasigeostrophic motions, 23th General   assembly of European Geophysics Society, April 20-24, 1998, Nice, France.

[48]Mu Mu, Nonlinear symmetric instability and   its saturations in the atmosphere, The tenth conference on atmospheric and   oceanic waves and stability, June 5-9, 1995, Big Sky, Montana, USA.

[49]Mu Mu, Some new results on nonlinear   instability in geophysical fluid dynamics, International conference on   nonlinear evolution equations and infinite-dimensional dynamical system,   1994, Beijing, China.

[50]Mu Mu, Nonlinear stability criteria for the   motion of quasigeostrophic flow, 19th General assembly of European Geophysics   Society, April 25-29, 1994, Grenoble, France

[51]Mu Mu, Nonlinear Arnolds second stability criteria of atmospheric motions,   International Symposium on Methods and Applications of Analysis, 1994, Hong   Kong.

[52]Mu Mu, Nonlinear stability problem of modified   quasigeostrophic flow, The ninth conference on atmospheric and oceanic waves   and stability, 1993, San Antonio, Texas, USA.

[53]Mu Mu, Nonlinear stability criteria relevant   to Arnolds second theorem   in geophysical fluid dynamics, Thirteen Annual conference of Canadian applied   methematics society, Wave phenomena, Modern Theory and applications, 1992,   Edmonton, Alberta, Canada.

[54]Mu Mu, and T. G. Shepherd, Nonlinear stability criteria for   quasigeostrophic motion, Climate, Environment and geophysical fluid dynamics,   1992, Beijing, China.

[55]Mu Mu, Well posedness and stability of   initial-boundary value problems in atmospheric dynamics, School on   qualitative aspects and applications of nonlinear evolution equations,   International center for theoretical Physics, 1990, Trieste, Italy.

[56]Mu Mu, Arnolds second nonlinear stability criteria of   atmospheric motions, The eleventh congress on ordinary and partial   differential equations, 1990, University of Dundee, UK.

[57]Mu Mu, Existence and uniqueness of   initial-boundary value problems for quasigeostrophic equation, Theory and   numerical methods for initial-boundary value problems, 1989, Oberwolfach,   Germany

[58]Mu Mu, and Zeng Qingcun, Stability of   quasigeostrophic motions in atmosphere, Fourth Asian Congress of Fluid Mech.,   1989Hong Kong.

[59]Mu Mu, Global classical solutions of   initial-boundary value problems for potential vorticity equation, The third   International congress on computational and applied mathematics, 1988, University   of Leuven, Belgium.

[60]Mu Mu, On the boundary value problem for a   degenerate elliptic equations, The seventh international symposium on   differential geometry and differential equations, Nankai Institute of   Mathematics, 1986, Tianjing, China.

[61]Mu Mu, Global classical   solutions of nonlinear generalized vorticity equations and its application,   International workshop on applied differential equations, Tsinghua   University, 1985, Beijing, China.

  

会议组织

[1]Mu Mu, 2018, EGU General Assembly, Inverse problem, data assimilation,and predictability studies in geophysics. (Co-convener), Vienna, Austria.

[2]Mu Mu, 2017, EGU General Assembly, Initial error dynamics and model error physics in predictability studies of weather and climate. (Co-convener), Vienna, Austria.

[3]Mu Mu, 2016, EGU General Assembly, Inverse problem of data assimilation, Initial error and model error. (Co-convener), Vienna, Austria.

[4]Mu Mu, 2015, EGU General Assembly, Inverse Problems, Data Assimilation, Coupled Initialization, and Impact of initial and model Errors and Predictability. (Co-convener), Vienna, Austria.

[5]Mu Mu, 2015, EGU General Assembly, Initial error dynamics and model error physics in weather and climate predictability studies. (Co-convener), Vienna, Austria.

[6]Mu Mu, 2014, AOGS 11th Annual Meeting, Western Boundary Currents, Transport, Path Variability, Eddies and Continental Shelf Processes. (Co-convener), Sapporo, Japan.

[7]Mu Mu, 2014, EGU General Assembly, Initial Error dynamics and model error physics in predictability studies of weather and climate. (Co-convener), Vienna, Austria.

[8]Mu Mu, 2013, EGU General Assembly, Error growth dynamics and related predictability problems.(Co-Convener), Vienna, Austria.

[9]Mu Mu, 2012, EGU General Assembly, Nonlinear optimal modes and their applications in predictability, sensitivity and stability studies. (Co-convener), Vienna, Austria.

[10]Mu Mu, 2011, IUGG, Data assimilation and ensemble forecasting for weather and climate. (Co-convener), Melbourne, Australia.

[11]Mu Mu, 2011, EGU General Assembly, Nonlinear instabilities and predictability. (Co-convener), Vienna, Austria.

[12]Mu Mu, 2010, EGU General Assembly, Nonlinear optimal modes and their applications in predictability, sensitivity and stability studies. (Convener), Vienna, Austria.

[13]Mu Mu, 2009, Advances in Data Assimilation for Earth System Science. (Co-convener), IMMAS, Montréal, Canada.

[14]Mu Mu, 2008, AOGS2008, Predictability of weather and climate: theory and methodology, (Convener), Busan, Korea.

[15]Mu Mu, 2007, IUGG XXIV General Assembly, Data Assimilation for the Atmosphere, Ocean and Land Surface. (Co-convener), Perugia, Italy.

[16]Mu Mu, 2006, AGU Western Pacific Geophysics Meeting, Uncertainty in Numerical Weather Prediction and its Application I, (Convener), Beijing, China.

[17]Mu Mu, 2006, EGU General Assembly,Uncertainty, Random Dynamical Systems and Stochastic Modeling in Geophysics, (Co-convener), Vienna, Austria

[18]Mu Mu, 2005IAMASAeronomy of Planetary Atmospheres: Comparative Planetology, (Co-Convener),Beijing, China.

[19]Mu Mu, 2005, IAMAS, Advances in Data Assimilation, (Convener), Beijing China

[20]Mu Mu, 2005, AOGS, Joint NL4/OA10 Session - AOGS 2004. (Co-Organizer), Singapore.

  


#以上信息由本人提供,更新时间:2019/03/05