穆穆(Mu Mu)


穆穆

特聘教授/中国科学院院士/发展中国家科学院院士/博士生导师

mumu@fudan.edu.cn

电话:021-31248899  传真:021-31248888



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

2020.09.01-2023.08.31 基于风云卫星智能精准观测针对极端天气事件的长三角航空运行安全应对研究, 20dz1200700,上海市2020年度“科技创新行动计划”社会发展科技攻关项目,上海市科委,主持

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,参与(张人禾)   

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) 

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)

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  

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)   

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

 

学术兼职

现任:

国际气象学和大气科学协会(IAMAS)执委会委员(Member at Large)

IAMAS中国委员会主席

国家自然科学基金委员会地球科学部第八届专家咨询委员会委员

《Advances in Atmospheric Sciences》共同主编

《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   


曾任:

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   

   

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)

1Dai, G.-K., and M. Mu (2020), Arctic influence on the eastern Asian cold surge forecast: A case study of January 2016, Journal of Geophysical Research: Atmospheres, e2020JD033298

2Dai, G.-K., and M. Mu (2020), Influence of the Arctic on the Predictability of Eurasian Winter Extreme Weather Events, Advances in Atmospheric Sciences, 37: 307-317.

3Wei, Y.-T., H.-L. Ren, M. Mu, and J.-X. Fu (2020), Nonlinear optimal moisture perturbations as excitation of primary MJO events in a hybrid coupled climate model, Climate Dynamics, 54: 675-699.

4Xie, R.-H., M. Mu, and X.-H. Fang (2020), New Indices for Better Understanding ENSO by Incorporating Convection Sensitivity to Sea Surface Temperature, Journal of Climate, 33: 7045-7061.

5Yang, Z.-Y., X.-H. Fang, and M. Mu (2020), The Optimal Precursor of El Niño in the GFDL CM2p1 Model, Journal of Geophysical Research: Oceans, 125: e2019JC015797.

6Wang, Q., M. Mu, and S. Pierini (2020), The fastest growing initial error in prediction of the Kuroshio Extension state transition processes and its growth, Climate Dynamics, 54(3): 1953-1971.

7Geng, Y., Q. Wang, M. Mu, and K. Zhang (2020), Predictability and error growth dynamics of the Kuroshio Extension state transition process in an eddy-resolving regional ocean model, Ocean Modelling, 153: 101659.

8Sun, G.-D., F. Peng, and M. Mu (2020), Application of targeted observation in model physical parameters for simulation and forecast of heat flux with a land surface model, Meteorological Applications, 27(1): e1883

9Peng, F., M. Mu, and G.-D. Sun (2020), Evaluations of Uncertainty and Sensitivity in Soil Moisture Modeling on the Tibetan Plateau, Tellus A: Dynamic Meteorology and Oceanography, 72:1, 1-16

10Sun, G.-D. and M. Mu (2020), Impacts of two types of errors on studies of the predictability of terrestrial carbon cycles: initial errors and model parameter errors, Ecosphere

11Zhang, K., M. Mu, Q. Wang (2020), Increasingly important role of numerical modeling in oceanic observation design strategy: A review, Science China: Earth Sciences, 63

12Jin, Z., Q. You, M. Mu, G.-D. Sun, and N. Pepin (2020), Fingerprints of anthropogenic influences on vegetation change over the Tibetan Plateau from an ecohydrological diagnosis, Geophysical Research Letters, 47, e2020GL087842.

13Gao, Y., M. Mu, and K. Zhang (2020), Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach, J. Ocean. Limnol. 38, 13821393.

14Wei, 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, 46: 3492-3501.

15Dai, G.-K., M. Mu, and Z.-N. Jiang (2019), Evaluation of the forecast performance for North Atlantic Oscillation onset, Advances in Atmospheric Sciences, 36: 753–765.

16Dai, G.-K., M. Mu, and Z-N. Jiang (2019), Targeted observations for improving predictions of the NAO event onset, Journal of Meteorological Research, 33: 1-16.

17Zhang, K., M. Mu, Q. Wang, B. Yin, and S. Liu (2019) CNOP-based adaptive observation network designed for improving upstream Kuroshio transport prediction, Journal of Geophysical Research: Oceans, 124: 4350-4364.

18Du, J., J. Berner, R. Buizza, M. Charron, P. Houtetamer, D. Hou, I. Jankov, M. Mu, X. Wang, M. Wei, and H. Yuan (2019), Ensemble Methods for Meteorological Predictions. Handbook of Hydrometeorological Ensemble Forecasting. Qea Duan, Ed., Springer, 1-52.

19Zhou, Q., M. Mu, W.-S. Duan (2019) The Initial Condition Errors Occurring in the Indian Ocean Temperature That Cause “Spring Predictability Barrier” for El Niño in the Pacific Ocean, Journal of Geophysical Research: Oceans, 124: 1244-1261.

20Liang, P., M. Mu, Q. Wang, and L. Yang (2019), Optimal Precursors Triggering the Kuroshio Intrusion Into the South China Sea Obtained by the Conditional Nonlinear Optimal Perturbation Approach, Journal of Geophysical Research: Oceans, 124: 3941-3962.

21Wang, Q., M. Mu, and G.-D. Sun (2019), A useful approach to sensitivity and predictability studies in geophysical fluid dynamics: conditional non-linear optimal perturbation, National Science Review: 1-10.

22Huang, K., H.-L. Ren, X. Liu, P. Ren, Y.-T. Wei, and M. Mu (2019) Parameter Modulation of Madden-Julian Oscillation Behaviors in BCC_CSM1.2: The Key Role of Moisture-Shallow Convection Feedback, Atmosphere, 10: 1-26.

23Duan, 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.

24Fang, 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.

25Fang, 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.

26Liu, 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.

27Liu, 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.

28Sun, 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.

29Tang, 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.

30Wei, 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.

31、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.

32Feng, 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.

33Li, 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 Physics, 17(8), 4957-4988, doi:10.5194/acp-17-4957-2017.

34Luo, 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.

35Mu, M., W.-S. Duan, and Y.-m. Tang (2017), The predictability of atmospheric and oceanic motions: Retrospect and prospects, Science China: Earth Sciences, 60(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.

36Mu, 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: Oceans, 122(2), 1141-1153, doi:10.1002/2016JC012527.

37Mu, M., and H.-L. Ren (2017), Enlightenments from researches and predictions of 2014-2016 super El Niño event, Science China: Earth Sciences, 60(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.

38Mu, 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.

39Peng, 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.

40Sun, 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.

41Sun, 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.

42Sun, 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.

43Sun, 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.

44Sun, 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.

45Sun, 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.

46Wang, 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.

47Wang, 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.

48Yu, 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.

49Zhang, 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.

50Zhang, 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.

51Zhang, 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.

52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.

53Dai, 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 Sciences, 73(1), 293-317, doi:10.1175/JAS-D-15-0109.1.

54Ding, 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.

55Zhang, 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 I, 116(19), 220-235, doi:10.1016/j.dsr.2016.08.008.

56Zou, 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 Limnology, 34(5), 1122-1133, doi:10.1007/s00343-016-4264-5.

57Zu, 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 Oceanography, 46(7), 2029-2047, doi:10.1175/JPO-D-15-0100.1.

58Mu, 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 Review, 2(2), 226-236, doi: 10.1093/nsr/nwv021.

59Wang, Q., and M. Mu (2015), A new application of conditional nonlinear optimal perturbation approach to boundary condition uncertainty, Journal of Geophysical Research: Oceans, 120(12), 7979-7996, doi:10.1002/2015JC011095.

60Zhou, 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 Sciences, 32(6), 783-793, doi:10.1007/s00376-014-4141-0.

61、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.

62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.

63Feng, 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: Oceans, 119(12), 8688-8708, doi:10.1002/2014JC010473.

64Feng, 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.

65Mu, 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 Research, 28(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.

66Mu, 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.

67Pierini, 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 Limnology, 5(2), 79-122, doi:10.1080/19475721.2014.962091.

68Qin, X.-H., and M. Mu (2014), Can adaptive observations improve tropical cyclone intensity forecasts?, Advances in Atmospheric Sciences, 31(2), 252-262, doi:10.1007/s00376-013-3008-0.

69Sun, 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 Modelling, 289(7), 66-76, doi:10.1016/j.ecolmodel.2014.06.021.

70Wang, 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.

71Yu, 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 Sciences, 31(3), 647-656, doi:10.1007/s00376-013-3058-3.

72Mu, 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.

73Chen, 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 Review, 141(8), 2669-2682, doi:10.1175/MWR-D-12-00142.1.

74Jiang, 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 Sciences, 70(3), 855-875, doi:10.1175/JAS-D-12-0148.1.

75Mu, M. (2013), Methods, current status, and prospect of targeted observation, Science China: Earth Sciences, 56(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.

76Qin, 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 Society, 139(675), 1544-1554, doi:10.1002/qj.2109.

77Sun, 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 Change, 120(4), 755-769, doi:10.1007/s10584-013-0833-1.

78Sun, 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 Sciences, 30(2), 515-524, doi:10.1007/s00376-012-2011-1.

79Wang, 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 Dynamics, 40(11-12), 2887-2902, doi:10.1007/s00382-012-1434-9.

80Wang, 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: Oceans, 118(2), 869-884, doi:10.1002/jgrc.20084.

81Zu, 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 Limnology, 31(6), 1356-1362, doi:10.1007/s00343-014-3051-4.

82Zu, 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 Letters, 6(6), 410-416, doi:10.3878/j.issn.1674-2834.13.0023.

83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.

84、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.

85Chen, 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 Sciences, 29(1), 63-78, doi:10.1007/s00376-011-0201-x.

86Qin, X.-H., and M. Mu (2012), Influence of conditional nonlinear optimal perturbations sensitivity on typhoon track forecasts, Quarterly Journal of the Royal Meteorological Society, 138(662), 185-197, doi:10.1002/qj.902.

87Yu, 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 Climate, 25(4), 1263-1277, doi:10.1175/2011JCLI4022.1.

88Yu, 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: Oceans, 117(C6), C06018, doi:10.1029/2011JC007758.

89Zhou, 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 Sciences, 29(1), 36-46, doi:10.1007/s00376-011-1003-x.

90Zhou, 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 Sciences, 29(4), 705-716, doi:10.1007/s00376-012-1174-0.

91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.

92、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.

93Mu, 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 Sciences, 68(12), 2860-2877, doi: 10.1175/JAS-D-11-037.1.

94Qin, 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 Review, 139(7), 2218-2232, doi: 10.1175/2010MWR3327.1.

95Sun, 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.

96Sun, G.-D., and M. Mu (2011), Response of a grassland ecosystem to climate change in a theoretical model, Advances in Atmospheric Sciences, 28(6), 1266-1278, doi:10.1007/s00376-011-0169-6.

97Wang, 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, Tellus, 63(5), 939-957, doi:10.1111/j.1600-0870.2011.00536.x.

98Zhou, 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 Sciences, 28(5), 997-1010, doi:10.1007/s00376-011-0120-x.

99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.

100Mu, 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.

101Sun, G.-D., M. Mu, and Y.-L. Zhang (2010), Algorithm studies on how to obtain a conditional nonlinear optimal perturbation (CNOP), Advances in Atmospheric Sciences, 27(6), 1311-1321, doi:10.1007/s00376-010-9088-1.

102Duan, 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: Oceans, 114(C4), C04022, doi:10.1029/2008JC004925.

103Duan, W.-S., and M. Mu (2009), Conditional nonlinear optimal perturbation: Applications to stability, sensitivity, and predictability, Science in China Series D: Earth Sciences, 52(7), 883-906, doi:10.1007/s11430-009-0090-3.

104Duan, W.-S., F. Xue, and M. Mu (2009), Investigating a nonlinear characteristic of El Niño events by conditional nonlinear optimal perturbation, Atmospheric Research, 94(1), 10-18, doi:10.1016/j.atmosres.2008.09.003.

105Jiang, 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 Sciences, 26(3), 465-470.

106Jiang, Z.-N., M. Mu, and D.-H. Wang (2009), Ensemble prediction experiments using conditional nonlinear optimal perturbation, Science in China Series D: Earth Sciences, 52(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.

107Jiang, 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.

108Mu, 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 Review, 137(5), 1623-1639, doi: 10.1175/2008MWR2640.1.

109Sun, 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.

110Wu, 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 Oceanography, 39(3), 798-805, doi:10.1175/2008JPO3910.1.

111Yu, 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 Society, 135(645), 2146-2160, doi: 10.1002/qj.526.

112Duan, 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: Oceans, 113(C1), C01014, doi:10.1029/2006JC003974.

113Jiang, 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 Society, 134(633), 1027-1038, doi: 10.1002/qj.256.

114Mu, M., and Z.-N. Jiang (2008), A method to find perturbations that trigger blocking onset: conditional nonlinear optimal perturbations, Journal of the Atmospheric Sciences, 65(12), 3935-3946, doi: 10.1175/2008JAS2621.1.

115Mu, M., and Z.-N. Jiang (2008), A new approach to the generation of initial perturbations for ensemble prediction: Conditional nonlinear optimal perturbation, Chinese Science Bulletin, 53(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.

116、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.

117、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.

118、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.

119Mu, 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.

120Mu, 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: Atmospheres, 112(D10), D10113, doi:10.1029/2005JD006981.

121Mu, 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.

122Mu, 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.

123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.

124、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.

125Duan, W.-S., and M. Mu (2006), Investigating decadal variability of El Nino-Southern Oscillation asymmetry by conditional nonlinear optimal perturbation, Journal of Geophysical Research, 111(C7), C07015, doi:10.1029/2005JC003458.

126Mu, 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 Sciences, 23(6), 992-1002.

127Mu, M., and Z.-Y. Zhang (2006), Conditional nonlinear optimal perturbations of a two-dimensional quasigeostrophic model, Journal of the Atmospheric Sciences, 63(6), 1587-1604.

128Zheng, 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.

129、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.

130Duan, W.-S., and M. Mu (2005), Applications of nonlinear optimization method to numerical studies of atmospheric and oceanic sciences, Applied Mathematics and Mechanics, 26(5), 636-646.

131Duan, 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 Science, 15(10), 915-921.

132Mu, M., and W.-S. Duan (2005), Conditional nonlinear optimal perturbation and its applications to the studies of weather and climate predictability, Chinese Science Bulletin, 50(21), 2401-2407.

133Mu, M., and Q. Zheng (2005), Zigzag oscillations in variational data assimilation with physical on–off processes, Monthly Weather Review, 133(9), 2711-2720.

134Sun, L., M. Mu, D.-J. Sun, and X.-Y. Yin (2005), Passive mechanism of decadal variation of thermohaline circulation, Journal of Geophysical Research: Oceans, 110(C7), C07025, doi:10.1029/2005JC002897.

135Wang, J.-F., M. Mu, and Q. Zheng (2005), Initial condition and parameter estimation in physical 'on–off' processes by variational data assimilation, Tellus, 57(5), 736-741.

136Dimet, 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 Variations, 10(3), 331-345, doi:10.1051/cocv:2004009.

137Duan, W.-S., and M. Mu (2004), Conditional nonlinear optimal perturbations as the optimal precursors for El Nino-Southern Oscillation events, Journal of Geophysical Research: Atmospheres, 109(D23), D23105, doi:10.1029/2004JD004756.

138Mu, M., W.-S. Duan, and J.-F. Chou (2004), Recent advances in predictability studies in China (1999-2002), Advances in Atmospheric Sciences, 21(3), 437-443.

139Mu, 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 Oceanography, 34(10), 2305-2315.

140Xu, H., M. Mu, and D.-H. Luo (2004), Application of nonlinear optimization method to sensitivity analysis of numerical model, Progress in Natural Science, 14(6), 546-549.

141、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.

142Mu, M., and W.-S. Duan (2003), A new approach to studying ENSO predictability: Conditional nonlinear optimal perturbation, Chinese Science Bulletin, 48(10), 1045-1047.

143Mu, M., W.-S. Duan, and B. Wang (2003), Conditional nonlinear optimal perturbation and its applications, Nonlinear Processes in Geophysics, 10(6), 493-501.

144Mu, M., and J.-F. Wang (2003), A method for adjoint variational data assimilation with physical on-off processes, Journal of the Atmospheric Sciences, 60(16), 2010-2018.

145、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.

146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.

147、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.

148Mu, M., W.-S. Duan, and J.-C. Wang (2002), The predictability problems in numerical weather and climate prediction, Advances in Atmospheric Sciences, 19(2), 191-204.

149Mu, M., W.-S. Duan, and J.-F. Wang (2002), Nonlinear optimization problems in atmospheric and oceanic sciences, Computational Mathematics and Modeling, 155, 155-164.

150Wang, J.-F., M. Mu, and Q. Zheng (2002), Adjoint approach to VDA of on-off processes based on nonlinear perturbation equation, Progress in Natural Science, 12(11), 869-873.

151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.

152Liu, Y.-M., and M. Mu (2001), Nonlinear stability of the generalized Eady model, Journal of the Atmospheric Sciences, 58(8), 821-827.

153Mu, M., and H. Guo (2001), Effect of four-dimensional variatinal data assimilation in case of nonlinear instability, Progress in Natural Science, 11(11), 825-832.

154Mu, M., and J.-C. Wang (2001), Nonlinear fastest growing perturbation and the first kind of predictability, Science in China, 44(12), 1128-1139.

155Mu, M., and Y.-H. Wu (2001), Arnol'd Nonlinear stability theorems and their application to the atmosphere and oceans, Surveys in Geophysics, 22(4), 383-426.

156Wu, Y.-H., M. Mu, Q.-C. Zeng, and Y. Li (2001), Weak solutions to a model of climate dynamics, Nonlinear Analysis: Real World Applications, 2(4), 507-521.

157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.

158Li, 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 Sciences, 17(2), 275-284.

159Mu, M. (2000), Nonlinear singular vectors and nonlinear singular values, Science in China, 43(4), 375-385.

160Mu, 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.

161、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.

162Mu, 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 Sciences, 56(3), 400-411.

163Mu, 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.

164Mu, M., Y.-H. Wu, and M.-Z. Tang (1999), Nonlinear stability analysis of the zonal flows at middle and high latitudes, Advances in Atmospheric Sciences, 16(4), 569-580.

165Vladimirov, V. A., M. Mu, Y.-H. Wu, and K. I. Ilin (1999), On nonlinear stability of baroclinic fronts, Geophys. Astrophys. Fluid Dynamics, 91(1-2), 65-84.

166Wu, Y.-H., and M. Mu (1999), Maximal energy isolated vortices in a uniform shear flow, Nonlinear Analysis, 38(1), 123-135.

167Wu, Y.-H., and M. Mu (1999), Nonlinear instability of dipole vortices and the atmospheric blocking, Progress in Natural Science, 9(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.

168Li, 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 Sciences, 2(1), 9-13.

169Li, 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 Sciences, 1(2), 113-118.

170Mu, M. (1998), Optimality of a nonlinear stability criterion of two-layer Phillips model, Chinese Science Bulletin, 43(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.

171Mu, M., and J. Xiang (1998), On the evolution of finite-amplitude disturbance to the barotropic and baroclinic quasigeostrophic flows, Advances in Atmospheric Sciences, 15(1), 113-123.

172Wu, Y.-H., and M. Mu (1998), A remark on the nonlinearly symmetric stability criteria, Chinese Science Bulletin, 43(12), 1050-1053.

173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.

174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.

175Xiang, J., and M. Mu (1997), Saturation of nonlinear instability of parallel shear flow, Progress in Natural Science, 7(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.

176Li, Y., and M. Mu (1996), Baroclinic instability in the generalized Phillips' model part I: two-layer model, Advances in Atmospheric Sciences, 13(1), 33-42.

177Li, Y., and M. Mu (1996), On the nonlinear stability of three-dimensional quasigeostrophic motions in spherical geometry, Advances in Atmospheric Sciences, 13(2), 203-216.

178Liu, Y.-M., and M. Mu (1996), Nonlinear stability theorem for Eady's model of quasigeostrophic barolinic flow, Journal of the Atmospheric Sciences, 53(10), 1459-1463.

179Liu, Y.-M., M. Mu, and T. G. Shepherd (1996), Nonlinear stability of continuously stratified quasi-geostrophic flow, J. Fluid Mech., 325(8), 419-439.

180Mu, 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.

181Mu, M. (1995), Some advances in the study of nonlinear instability of the atmospheric motions, Chinese Journal of Atmospheric Sciences, 19(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.

182Liu, Y.-M., and M. Mu (1994), Arnol'd's second nonlinear stability theorem for general muitilayer quasi-geostrophic model, Advances in Atmospheric Sciences, 11(1), 36-42.

183Mu, M., and T. G. Shepherd (1994), Nonlinear stability of Eady's model, Journal of the Atmospheric Sciences, 51(23), 3427-3436.

184Mu, M., and T. G. Shepherd (1994), On Arnol'd's second nonlinear stability theorem for two-dimensional quasi-geostrophic flow, Geophys. Astrophys. Fluid Dynamics, 75(1), 21-37.

185Mu, 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.

186Mu, M., and J. Simon (1993), A remark on nonlinear stability of three-dimensional quasigeostrophic motions, Chinese Science Bulletin, 38(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 Bulletin, 38(22), 2057-2062.

187Liu, Y.-M., and M. Mu (1992), A problem related to nonlinear stability criteria for multi-layer quasi-geostrophie flow, Advances in Atmospheric Sciences, 9(3), 337-345.

188Mu, M. (1992), Nonlinear stability of two-dimensional quasigeostrophic motions, Geophys. Astrophys. Fluid Dynamics, 65(1-4), 57-76.

189Mu, M., and X.-Y. Wang (1992), Nonlinear stability criteria for motions of three-dimensional quasi-geostrophic flow on β-plane, Progress in Natural Science, 2(1), 48-53.

190Mu, M., and X.-Y. Wang (1992), Nonlinear stability criteria for the motion of three-dimensional quasigeostrophic flow on a beta-plane, Nonlinearity, 5(5), 353-371.

191Mu, M. (1991), Nonlinear stability criteria for motions of multilayer quasi-geostrophic flow, Science in China, 34(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.

192Mu, M., and Q.-C. Zeng (1991), Criteria for the nonlinear stability of three-dimensional quasi-geostrophic motions, Advances in Atmospheric Sciences, 8(1), 1-10.

193Mu, M., and Q.-C. Zeng (1991), New developments on existence and uniqueness of solutions to some models in atmospheric dynamics, Advances in Atmospheric Sciences, 8(4), 383-398.

194穆穆 (1990), Global smooth solutions of two-dimensional Euler equations, Chinese Science Bulletin, 35(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.

195Mu, M. (1989), Global classical solutions to initial-boundary value problems for the potential vorticity equation, Journal of Computational and Applied Mathematics, 28(1), 327-338.

196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.

197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.

198Mu, M. (1988), Classical solution to 3-dimensional balanced model in numerical weather prediction, KEXUE TONGBAO, 33(19), 1628-1631.

199Mu, 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.

200Mu, 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.

201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.

202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.

203Mu, M. (1987), Global classical solutions of initial-boundary value problems for generalized vorticity equations, Scientia Sinica, 30(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.

204Mu, M. (1987), Global classical solutions of the Cauchy problems for nonlinear vorticity equations and its applications, Chin. Ann.of Math., 8B(2), 199-207.

205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.

206Mu, M. (1986), Existence and uniqueness of global strong solutions of two models in atmospheric dynamics, Applied Mathematics and Mechanics, 7(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.

207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.

208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.

209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:2020/01/05