穆穆

穆穆，1954年8月31日出生于安徽省定远县，大气动力学家，^[1]中国科学院院士、发展中国家科学院院士，中国科学院海洋研究所研究员、博士生导师。^[2]

穆穆主要从事大气-海洋动力学及天气与气候的可预报性研究，^[4]1975年穆穆考入安徽大学数学系，先后获得理学学士学位、理学硕士学位，1985年穆穆在复旦大学毕业后进入上海交通大学应用数学系担任讲师，1987年他进入中国科学院大气物理研究所从事博士后研究工作，^[2]穆穆在大气与海洋运动的非线性稳定性和天气与气候的可预报性研究中，提出了研究可预报性的一种新方法（CNOP），得到国际同行的一致赞同，期间他曾在多伦多大学、剑桥大学牛顿研究所、香港科技大学、法国动力气象实验室与夏威夷大学太平洋研究中心进行过合作研究。^[3][4]1989年-2010年，穆穆博士后出站后，他继续留在中国科学院大气物理研究所工作，先后担任副研究员、研究员、博士生导师，2010年12月到2016年3月，穆穆在中国科学院海洋研究所，担任研究员，2016年穆穆在复旦大学大气科学研究院大气与海洋科学系受邀担任特聘教授。^[2][5]

1994年，穆穆获得国家杰出青年科学基金（首届）资助；2007年，穆穆当选为中国科学院院士；2008年，穆穆当选为发展中国家科学院院士；2010年获得何梁何利基金科学与技术进步奖，同年在中国科学院海洋研究所担任研究员。^[2][4]2024年6月24日，穆穆院士荣获国家自然科学二等奖。^[6]

穆穆1954年8月31日出生于安徽定远，^[1]1975年9月，穆穆考入安徽大学数学系应用数学专业，先后获得理学学士学位（1978年8月）、理学硕士学位（1978年9月-1981年8月）。1981年8月，硕士毕业后留校任教，担任安徽大学数学系助教（至1982年3月）。1982年，穆穆进入复旦大学数学研究所，师从谷超豪与李大潜教授攻读博士学位，并开始从事大气动力学中非线性涡度方程的适定性研究，1985年7月毕业，获得理学博士学位。^[2][7][8]

1985年到1987年，穆穆博士毕业后进入上海交通大学应用数学系，担任讲师。^[2]1987年4月，穆穆进入中国科学院大气物理研究所，师从曾庆存院士进行博士后研究工作，主要从事大气与海洋运动的非线性稳定性和天气与气候的可预报性研究。^[3][2]1989年4月，穆穆博士后出站后，继续留在中国科学院大气物理研究所工作，先后担任副研究员（1989年4月-1992年12月）、研究员（1993年1月-2010年11月）。^[2]1990年，穆穆获得了国家级奖项中国科学技术协会“中国青年科技奖”。1994年，穆穆获得首届国家杰出青年科学基金。^[9]1995年，穆穆获得国家级大奖国家博士后管委会“国氏博士后奖”。^[7]1996年入选国家人事部“百千万”人才工程，2005年获中国科学院优秀研究生导师称号，同年又获得国家人事部“全国优秀博士后”称号。2006年获中国科学院研究生“优秀教师”称号和中国科学院“宝洁优秀研究生导师”称号。^[10]2007年，穆穆当选为中国科学院院士，2008年，穆穆当选为发展中国家科学院（TWAS，原第三世界科学院）院士。^[9]2010年，穆穆获得何梁何利基金科学与技术进步奖，^[7]2010年12月到2016年3月，穆穆在中国科学院海洋研究所，担任研究员。2016年3月，在复旦大学大气科学研究院大气与海洋科学系受邀担任特聘教授。^[2][5]2023年2月14日，在大气所举办2023年第一期名家讲坛上，穆院士做了题为《昔日风雨化皓首，未来大气倚少年》的报告，在讲坛互动环节，穆院士还对研究生们感兴趣的问题进行了耐心地解答。^[11]2024年5月6日，穆穆在上海中学为学子带来“大气科学与宜居地球”的讲座，讲座中穆穆着重强调了海洋对天气和气候的影响。^[12]

2024年6月24日，穆穆院士和段晚锁研究员领衔的“减小高影响海气事件预报不确定性的非线性新理论和新技术”项目荣膺国家自然科学二等奖。^[6]

在穆穆主要从事大气与海洋动力学及天气与气候的可预报性研究。穆穆在可预报性和资料同化方面提出了研究可预报性的一种新方法（CNOP），这一创新成果得到国际同行的一致赞同。穆穆等建立的湿饱和大气的非线性稳定性判据，被国外杂志评价为“极大地推动了对地球流体运动稳定性机制的理解”。^[3]之后穆穆在大气与海洋运动的非线性（不）稳定性方面，对于两维正压、多层斜压和三维连续层结准地转模式，建立了Arnold第二非线性稳定性判据。在天气、气候的可预报性研究方面，穆穆用条件非线性最优扰动(CNOP)方法研究了厄尔尼诺春季预报障碍，海洋热盐环流对淡水通量扰动的敏感性等问题，展示了使用CNOP方法考察非线性过程的重要性。^[4]

以上参考：^[2]

穆穆多次在国际重要学术会议上做特邀报告，他多次在国际学术会议上作特邀报告如EGS（欧洲地球物理学会），IUGG（国际大地测量与地球物理学联盟大会），IAMAS-IAPSO（国际气象和大气科学协会与国际海洋协会会议）。在AOGS和IAMAS等重要的国际会议上担任分会共同主席。曾在多伦多大学、剑桥大学牛顿研究所、香港科技大学、法国动力气象实验室与夏威夷大学太平洋研究中心进行过合作研究。^[13][14][4]

截止2024年7月，穆穆一共有200多篇论著^[2]，以下是主要论文：

时间论文名称作者期刊信息2023年Improving the Forecasting of El Niño Amplitude Based on an Ensemble Forecast Strategy for Westerly Wind BurstsJi, C., Mu, M., Fang, X., & Tao, LJournal of Climate, 36(24), 8675-86942023年Influence of Physically Constrained Initial Perturbations on the Predictability of Mei-Yu Heavy PrecipitationKe, J., Mu, M., & Fang, XMonthly Weather Review, 151(8), 2115-21382023年Targeted observations on Arctic sea ice concentration for improving extended-range prediction of Ural Blocking Gao, Y., Mu, M., & Dai, GJournal of Geophysical Research: Atmospheres, 128(22), e2023JD0396302023年 A new sensitivity analysis approach using conditional nonlinear optimal perturbations and its preliminary applicationRen, Q. J., M. Mu, G. D. Sun, and Q. WangAdv. Atmos. Sci2023年A statistical review on the optimal fingerprinting approach in climate change studies Chen, H., Chen, S. X., & Mu, M C. Climate Dynamics2023年Optimal Arctic sea ice concentration perturbation in triggering Ural blocking formationDai, G., Ma, X., Mu, M., Han, Z., Li, C., Jiang, Z., & Zhu, MAtmospheric Research, 2892023年 The Influence of Arctic Sea Ice Concentration Perturbations on Subseasonal Predictions of North Atlantic Oscillation Events Dai, G., Mu, M., Han, Z., Li, C., Jiang, Z., Zhu, M., & Ma, X. Advances in Atmospheric Sciences, 40(12), 2242-22612023年Recent Advances in China on the Predictability of Weather and ClimateDuan, W., Yang, L., Mu, M., Wang, B., Shen, X., Meng, Z., & Ding, R. Advances in Atmospheric Sciences, 40(8), 1521-15472023年Extent of the Impact of Arctic Atmospheric Uncertainty on Extended‐Range Forecasting of Cold Events in East AsiaHan, Z., Dai, G., Mu, M., Li, C., Li, S., Ma, X., & Zhu, M.Journal of Geophysical Research: Atmospheres, 128(9)2023年Influence of Arctic Sea-ice Concentration on Extended-range Forecasting of Cold Events in East AsiaLi, C., Dai, G., Mu, M., Han, Z., Ma, X., Jiang, Z., . . . Zhu, M.Advances in Atmospheric Sciences, 40(12), 2224-22412023年Preface to the Special Issue on the National Report to the 28th IUGG General Assembly by CNC-IAMAS (2019–2022)Mu, M., & Wang, LAdvances in Atmospheric Sciences, 40(8), 1337-13382023年Applications of CNOP-P Method to Predictability Studies of Terrestrial Ecosystems Sun, G., & Mu, MAtmosphere, 14(4)2023年Application of the CNOP‐P Ensemble Prediction (CNOP‐PEP) Method in Evapotranspiration Forecasting Over the Tibet Plateau to Model Parameter UncertaintiesSun, G., Mu, M., Zhang, Q., Ren, Q., & You, QJournal of Advances in Modeling Earth Systems, 15(3)2023年 Application of the Observation‐Oriented CNOP‐P Sensitivity Analysis Method in Evapotranspiration Simulation and Prediction Over the Tibet PlateauSun, G., Mu, M., Zhang, Q., Ren, Q., & You, QWater Resources Research, 59(8)2023年Impacts of Initial Zonal Current Errors on the Predictions of Two Types of El Niño EventsTao, L., Mu, M., Wang, L., Fang, X., Duan, W., & Zhang, R. H. ournal of Geophysical Research: Oceans, 128(6)2022年Optimally growing initial error for predicting the sudden shift in the Antarctic Circumpolar Current transport and its application to targeted observationZhou L., Zhang K., Wang Q. Mu MOcean Dynamics (2022)2022年Recent progress in applications of the conditional nonlinear optimal perturbation approach to atmosphere-ocean sciencesMu Mu; Zhang Kun; Wang QiangChinese Annals of Mathematics, Series B, 43(6), 1033-10482022年Local energetics mechanism for the short-term shift between Kuroshio Extension bimodalityZhang, H., Wang, Q., Mu, M., & Liu, XJournal of Geophysical Research: Oceans, 127, e2022JC0187942022年Impact of Optimally Growing Initial Errors on the Mesoscale Predictability of Heavy Precipitation Events along the Mei-Yu Front in ChinaKe, J., M. Mu, and X. Fang Mon. Wea. Rev., 150, 2399–24212022年Determinants of physical processes and their contributions for uncertainties in simulated evapotranspiration over the Tibet PlateauSun, G., Mu, M., Ren, Q., Zhang, Q., & You, QJournal of Geophysical Research: Atmospheres, 127, e2021JD0357562022年 Role of hydrological parameters in the uncertainty in modeled soil organic carbon using a coupled water-carbon cycle modelSun, G., and M. MuEcological Complexity,50,1009862022年The IAMAS-CNC Early Career Scientists Nobel Prize Online Interpretation WorkshopLi, J., Jiang, Z., Dong, Y., Zhang, L., Ying, T., Zhang, Z., and Mu Mu.Adv. Atmos. Sci2022年Influence of Arctic sea ice concentration on extended-range prediction of strong and long-lasting Ural blocking events in winterMa, X., Mu, M., Dai, G., Han, Z., Li, C., & Jiang, Z Journal of Geophysical Research: Atmospheres, 127, e2021JD0362822022年 A nonlinear representation of model uncertainty in a convective-scale ensemble prediction systemXu, Z. Z., J. Chen, M. Mu, G. K. Dai, and Y. N. MAAdv. Atmos. Sci2022年A stochastic and nonlinear representation of model uncertainty in a convective-scale ensemble prediction systemXu, Z., Chen, J., Mu, M. et al Quart. J. Royal Meteor. Soc2022年Preface to the Special Issue on Extreme Cold Events from East Asia to North America in Winter 2020/21Mu, M., Luo, D., & Zheng, FAdvances in Atmospheric Sciences, 39(4), 543-5452022年Identifying the sensitive areas in targeted observation for predicting the Kuroshio large meander path in a regional ocean modelLiu, X., Wang, Q., & Mu, M Acta Oceanologica Sinica, 41(2), 3-142022年A New Sensitivity Analysis Approach Using Conditional Nonlinear Optimal Perturbations and Its Preliminary ApplicationRen, Q., Mu, M., Sun, G., & Wang, QAdvances in Atmospheric Sciences, 40(2), 285-3042021年Evaluation of the Forecast Performance for Extreme Cold Events in East Asia with Subseasonal-to-Seasonal Datasets from ECMWFDai, G., Mu, M., Li, C., Han, Z., & Wang, LJournal of Geophysical Research: Atmospheres, 126(1), e2020JD0338602021年The Influence of Sudden Arctic Sea-Ice Thinning on North Atlantic Oscillation EventsDai, G., Mu, M, & Wang, L Atmosphere-Ocean, 59(1), 39-522021年 Impacts of two types of errors on the predictability of terrestrial carbon cycleSun, G., and M. MuEcosphere, 12(1): e033152021年Uncertainty range of projected soil carbon responses to climate warming in ChinaSun, G., and M. MuMeteorological Applications,28(3),e19932021年Optimal precursors triggering sudden shifts in the Antarctic circumpolar current transport through Drake PassageZhou, L., Wang, Q., Mu, M., & Zhang, K Journal of Geophysical Research: Oceans, 1262021年数值模式在海洋观测设计中的重要作用:回顾与展望张坤, 穆穆& 王强Sci. Sin. Terrae 51, 653–6652021年Juanzhen Sun and Mu Mu: Lessons Learned from the Tragedy during the 100 km Ultramarathon Race in Baiyin, Gansu Province on 22 May 2021Zhang, Q., Ng, CP., Dai, K.Jun Xu, Jian TangAdv. Atmos. Sci.38,1803–18102021年气候系统和气候变化研究获2021年诺贝尔物理学奖的启示 张人禾,刘哲,穆穆,等中国科学基金, 2021, 35(6):42020年 Arctic Influence on the Eastern Asian Cold Surge Forecast: A Case Study of January 2016Dai, G., & Mu, MJournal of Geophysical Research: Atmospheres, 125(23), e2020JD0332982020年Influence of the Arctic on the Predictability of Eurasian Winter Extreme Weather EventsDai G-K, and Mu MAdvances in Atmospheric Sciences, 37: 307-3172020年Nonlinear optimal moisture perturbations as excitation of primary MJO events in a hybrid coupled climate modelWei Y-T, Ren H-L, Mu M, and Fu J-XClimate Dynamics, 54: 675-6992020年New Indices for Better Understanding ENSO by Incorporating Convection Sensitivity to Sea Surface TemperatureXie R-H, Mu M, and Fang X-H Journal of Climate, 33: 7045-70612020年The Optimal Precursor of El Niño in the GFDL CM2p1 ModelYang Z-Y, Fang X-H, and Mu MJournal of Geophysical Research: Oceans, 125: e2019JC0157972020年The fastest growing initial error in prediction of the Kuroshio Extension state transition processes and its growthWang Q, Mu M, and Pierini SClimate Dynamics, 2020, 54(3): 1953-19712020年 Predictability and error growth dynamics of the Kuroshio Extension state transition process in an eddy-resolving regional ocean modelGeng Y, Wang Q, Mu M, and Zhang KOcean Modelling, 2020, 153: 1016592020年Application of targeted observation in model physical parameters for simulation and forecast of heat flux with a land surface modelSun, G. D., F. Peng, and M. MuMeteorological Applications, 27(1): e18832020年Evaluations of Uncertainty and Sensitivity in Soil Moisture Modeling on the Tibet PlateauFei Peng, Mu Mu and Guodong SunTellus A: Dynamic Meteorology and Oceanography, 72:1, 1-162020年 Increasingly important role of numerical modeling in oceanic observation design strategy: A reviewZhang K, Mu M, Wang Q Science China Earth Sciences, 632020年Fingerprints of anthropogenic influences on vegetation change over the Tibet Plateau from an ecohydrological diagnosisJin, Z., You, Q., Mu, M., Sun, G., and Pepin, NGeophysical Research Letters, 47, e2020GL0878422020年Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approachGao, Y., Mu, M. and Zhang, KJ.Ocean. Limnol. 38, 1382–1392020年A useful approach to sensitivity and predictability studies in geophysical fluid dynamics: conditional non-linear optimal perturbationWang Q, Mu M, and Sun G-DNational Science Review: 1-102020年Identification of Key Physical Processes and Improvements for Simulating and Predicting Net Primary Production Over the Tibet PlateauSun, G., Mu, M., & You, QJournal of Geophysical Research: Atmospheres, 125(23)2020年Hydrodynamics-driven uncertainty study in simulating terrestrial carbon cycle with a coupled water-carbon cycle model[J]Sun G,Mu M 2020.DOI:10.21203/rs.3.rs-108448/v12020年Evaluation of the Forecast Performance for Extreme Cold Events in East Asia With Subseasonal‐to‐Seasonal Data Sets From ECMWFDai, G., Mu, M., Li, C., Han, Z., & Wang, LJournal of Geophysical Research: Atmospheres2019年Conditional nonlinear optimal perturbations of moisture triggering primary MJO initiationWei Y-T, Mu M, Ren H-L, and Fu J-XGeophysical Research Letters, 46: 3492-35012019年Evaluation of the forecast performance for North Atlantic Oscillation onsetDai G-K, Mu M, and Jiang Z-NAdvances in Atmospheric Sciences, 36: 753–7652019年Targeted observations for improving predictions of the NAO event onsetDai G-K, Mu M, and Jiang Z-NJournal of Meteorological Research, 33: 1-162019年CNOP-based adaptive observation network designed for improving upstream Kuroshio transport predictionZhang K, Mu M, Wang Q, Yin B, and Liu SJournal of Geophysical Research: Oceans, 124: 4350-43642019年Ensemble Methods for Meteorological Predictions. Handbook of Hydrometeorological Ensemble ForecastingDu J, Berner J, Buizza R, Charron M, Houtetamer P, Hou D, Jankov I, Mu M, Wang X, Wei M, and Yuan H Qea Duan, Ed., Springer,1-522019年The Initial Condition Errors Occurring in the Indian Ocean Temperature That Cause “Spring Predictability Barrier” for El Niño in the Pacific Ocean Zhou Q, Mu M, and Duan W-SJournal of Geophysical Research: Oceans, 124: 1244-12612019年Optimal Precursors Triggering the Kuroshio Intrusion Into the South China Sea Obtained by the Conditional Nonlinear Optimal Perturbation ApproachLiang P, Mu M, Wang Q, and Yang LJournal of Geophysical Research: Oceans, 124: 3941-39622019年 Parameter Modulation of Madden-Julian Oscillation Behaviors in BCC_CSM1.2: The Key Role of Moisture-Shallow Convection Feedback AtmosphereHuang K, Ren H-L, Liu X, Ren P, Wei Y-T, and Mu M10: 1-262019年Nonlinear optimal moisture perturbations as excitation of primary MJO events in a hybrid coupled climate modelWei Y-T, Ren H-L, Mu M, and Fu J-XClimate Dynamics54:675-6992018年Predictability of El Niño-Southern Oscillation eventsDuan, W.-S., and M. MuOxfordResearch Encyclopedia of Climate Science, 1-412018年Both air-sea components are crucial for El Niño forecast from boreal springFang, X.-H., and M. MuScientific Reports, 8(10501), 1-82018年A three-region conceptual model for central Pacific El Niño including zonal advective feedbackFang, X.-H., and M. MuJournal of Climate, 31(13),4965-49792018年The Nonlinear Optimal Triggering Perturbation of the Kuroshio Large Meander and Its Evolution in a Regional OceanLiu, X., M. Mu, and Q. WangJournal of Physical Oceanography, 48(8), 1771-17862018年Optimal initial error growth in the prediction of the Kuroshio large meander based on a high-resolution regional ocean modelLiu, X., Q. Wang, andM. MuAdvances in Atmospheric Sciences, 35(11), 1362-13712018年Assessing the characteristics of net primary production due to future climate change and CO2 under RCP4.5 in ChinaSun, G.-D., and M. MuEcological Complexity, 34, 58-682018年Progress in ENSO prediction and predictability studyTang, 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. MuNational Science Review, nwy1052018年Planetary scale selection of the Madden-Julian Oscillation in an air-sea coupled dynamic moisture modelWei, Y.-T., F. Liu,M. Mu, and H.-L. RenClimate Dynamics, 50, 3441-34562018年条件非线性最优扰动方法在黑潮目标观测研究中的应用张星,穆穆,王强,张坤海洋气象学报, 38(1), 1-92017年大气-海洋运动的可预报性:思考与展望穆穆，段晚锁，唐佑民中国科学：地球科学2017年The predictability of atmospheric and oceanic motions: Retrospect and prospectsMu, M., W.-S. Duan, and Y.-m. TangScience China: Earth Sciences,60:2001-20122017年Estimating observing locations for advancing beyond the winter predictability barrier of Indian Ocean dipole event predictionsFeng, R., W.-S. Duan, and M. MuClimate Dynamics, 48(3-4), 1173-11852017年Multi-pollutant emissions from the burning of major agricultural residues in China and the related health-economic effectsLi, 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. MelloukiAtmospheric Chemistry and Physics, 17(8), 4957-49882017年Relationship between optimal precursors for Indian Ocean Dipole events and optimally growing initial errors in its predictionMu, M., R. Feng, and W.-S. DuanJournal of Geophysical Research: Oceans, 122(2), 1141-11532017年非线性最优化方法在大气-海洋科学研究中的若干应用穆穆, 王强中国科学：数学, 47(10), 1-162017年Enlightenments from researches and predictions of 2014-2016 super El Niño eventMu, M., and H.-L. RenScience China: Earth Sciences, 60(9), 1569-15712017年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 ChinaPeng, F., M. Mu, and G.-D. SunJournal of Hydro-environment Research, 14, 105-1182017年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 exampleSun, G.-D., and M. MuTheor. Appl. Climatol., 128(3-4), 587-6012017年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. KSun, G.-D., and M. MuPark and L. Xu, pp. 527-547, Springer International Publishing, Switzerland2017年Variations in soil moisture over the 'Huang-Huai-Hai Plain' in China due to temperature change using the CNOP-P method and outputs from CMIP5Sun, G.-D., F. Peng, and M. MuScience China: Earth Sciences2017年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. KWang, Q., and M. MuPark and L. Xu, pp. 513-526, Springer International Publishing, Switzerland2017年A WRF-based tool for forecast sensitivity to the initial perturbation: the conditional nonlinear optimal perturbations versus the first singular vector method and comparison to MM5Yu, H.-Z., H.-L. Wang, Z.-Y. Meng, M. Mu, X.-Y. Huang, and X. ZhangJournal of Atmospheric and Oceanic technology, 34(1), 187-2062017年Identifying the sensitive area in adaptive observation for predicting the upstream Kuroshio transport variation in a 3-D ocean modelZhang, K., M. Mu, and Q. WangScience China: Earth Sciences, 60(5), 866-8752017年Optimal precursors triggering the Kuroshio extension state transition obtained by the conditional nonlinear optimal perturbation approachZhang, X., M. Mu, Q. Wang, and S. PieriniAdvances in Atmospheric Sciences, 34(6), 685-6992017年The impact of global warming on Kuroshio Extension and its southern recirculation using CMIP5 experiments with a high-resolution climate model MIROC4hZhang, X., Q. Wang, and M. MuTheor. Appl. Climatol., 127(3-4), 815-8272016年Effects of optimal initial errors on predicting the seasonal reduction of the upstream Kuroshio transportZhang, K., Q. Wang, M. Mu and P. LiangDeep-Sea Research I, 116: 220-2352016年Optimal Initial Excitations of Decadal Modification of the Atlantic Meridional Overturning Circulation under the Prescribed Heat and Freshwater Flux Boundary ConditionsZu, Z., M. Mu, H. A. DijkstraJ. Phys. Oceanogr., 46(7):2029-20472016年Identifying sensitive areas of adaptive observations for prediction of the Kuroshio large meander using a shallow-water modelZou, G., Q. Wang and M. MuChin. J. Ocean. Limnol., 34: 1122-11332016年Relationships between Optimal Precursors Triggering NAO Onset and Optimally Growing Initial Errors during NAO PredictionDai, G., M. Mu and Z. JiangJ. Atmos. Sci., 73(1): 293-3172016年Impacts of climate change on the environment, economy, and society of ChinaDing, Y., Mu, M., Zhang, J., Jiang, T., Zhang, T., Wang, C., ... & Zhang, SIn Climate and Environmental Change in China: 1951–2012 (pp. 69-92). Springer, Berlin, Heidelberg2015年Influence of positive and negative Indian Ocean dipoles on ENSO via the Indonesian Throughflow: Results from sensitivity experimentsZhou, Q., W. S. Duan, M. Mu, and R. FengAdv. Atmos. Sci., 32(6), 783–7932015年A new application of conditional nonlinear optimal perturbation approach to boundary condition uncertaintyWang Qiang, and Mu MuJournal of Geophysical Research: Oceans2015年Target observations for improving initialization of high-impact ocean-atmospheric environmental events forecastingMu Mu, Wansuo Duan, Dake Chen, and Weidong YuNational Science Review, 2(2), 226–2362015年基于CNOP方法的台风目标观测研究进展穆穆，周菲凡气象科技进展，5, 6-172015年混沌理论之父——1983 年 Crafoord 奖获得者洛伦茨教授成就解读罗德海, & 穆穆中国科学: 地球科学, (001), 1-72014年The analyses of the net primary production due to regional and seasonal temperature differences in eastern China using the LPJ modelGuodong Sun , Mu MuEcological Modelling，289,66-762014年Responses of the ocean planktonic ecosystem to finite-amplitude perturbationsWang, Q., and M. MuJ. Geophys. Res. Oceans, 1192014年The ‘‘winter predictability barrier’’ for IOD events and its error growth dynamics: Results from a fully coupled GCMFeng, R., W. Duan , and M. MuJ. Geophys. Res. Oceans, 1192014年Similarities between optimal precursors for ENSO events and optimally growing initial errors in El Niño predictionsMu Mu , Yanshan Yu , Hui Xu and Tingting GongTheor．Appl．Climatol．,115:461–4692014年Study on the “winter persistence barrier”of Indian Ocean dipole events using observation data and CMIP5 model outputsRong Feng, Mu Mu ,Wansuo DuanTheor Appl. Climatol., 118(3),523-5342014年Can adaptive observations improve tropical cyclone intensity forecasts?Qin, X. H., and M. Mudv. Atmos.Sci., 31(2), 252–2622014年Role of parameter errors in the spring predictability barrier for ENSO events in the Zebiak–Cane modelYu, L., M. Mu, and Y. S. YuAdv. Atmos. Sci., 31(3), 647–6562014年Intrinsic low-frequency variability and predictability of the Kuroshio Current and of its extensionStefano Pierini, Henk A. Dijkstra and Mu MuAdvances in Oceanography and Limnology2014年Application of Conditional Nonlinear Optimal Perturbation to Targeted Observation Studies of the Atmosphere and OceanMu Mu , Wang Qiang , Duan Wansuo , Jiang ZhinaJournal of Meteorological Research,28(5),923-9332014年Addressing the issue of fog and haze: A promising perspective from meteorological science and technologyMu, M., & Zhang, RScience China. Earth Sciences, 57(1), 12014年应对雾霾天气: 气象科学与技术大有可为穆穆, & 张人禾中国科学: 地球科学, 44(1), 1-22014年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穆穆, 王强, 段晚锁, & 姜智娜气象学报, 72(5), 1001-10112013年Methods, current status, and prospect of targeted observationMu MuScience China (Earth Sciences), 56, 1997-20052013年Effects of nonlinear physical processes on optimal error growth in predictability experiments of the Kuroshio Large MeanderWang, Q., M. Mu, and H. A. DijkstraJ. Geophys. Res., 118, 6425-64362013年The similarity between optimal precursor and optimally growing initial error in prediction of Kuroshio large meander and its application to targeted observationWang, Q., M. Mu, and H. A. DijkstraJ. Geophys. Res., 118(2), 869-8842012年Contribution of the location and spatial pattern of initial error to uncertainties in El Niño predictionsYu, Y., M. Mu, W. Duan, and T. GongJ. Geophys. Res., 1172012年Does Model Parameter Error Cause a Significant “Spring Predictability Barrier” for El Niño Events in the Zebiak–Cane Model?Yu, Y., Mu M.,and W. DuanJ.Climate,25,1263-12772011年Similarities between Optimal Precursors that Trigger the Onset of Blocking Events and Optimally Growing Initial Errors in Onset PredictionMu, Mu, Zhina JiangJ. Atmos. Sci., 68, 2860-28772010年An extension of conditional nonlinear optimal perturbation approach and its applicationsMu, M., W. Duan, Q. Wang, and R. ZhangNonlin. Processes Geophys., 17, 211-2202009年A Method for Identifying the Sensitive Areas in Targeted Observations for Tropical Cyclone Prediction: Conditional Nonlinear Optimal PerturbationMu, M., F. F. Zhou, and H. L. WangMon. Wea. Rev., 137, 1623-16392008年A method to find perturbations that trigger blocking onset: Conditional nonlinear optimal perturbationsMu, M., and Z. N. JiangJ. Atmos. Sci., 65, 3935-39462008年A new approach to the generation of initial perturbations for ensemble prediction: Conditional nonlinear optimal perturbationMu, M., and Z. N. JiangChinese Science Bulletin, 53, 2062-20682007年A kind of initial errors related to "spring predictability barrier" for El Nino events in Zebiak-Cane modelMu, M., H. Xu, and W. S. DuanGeophysics Research Letters，34， L037092007年Nonlinear instability and sensitivity of a theoretical grassland ecosystem to finite-amplitude perturbationsMu, M. and B. WangNonlin. Processes Geophys., 14, 409-4232006年Conditional nonlinear optimal perturbations of a two-dimensional quasigeostrophic modelMu, M., and Z. Y. ZhangJ.Atmos.Sci.，63, 1587-16042005年Zigzag Oscillations in Variational Data Assimilation with Physical "On-Off" ProcessesMu, M. and Q. ZhengMonth Weather Review, 133, 2711-27202004年The sensitivity and stability of thermohaline circulation of ocean to finite amplitude perturbationsMu, M., L. Sun and H. A. DijkstraJournal of Physical Oceanography，34，2305-23152003年A method to adjoint variational data assimilation with physical "on-off" processesMu, M., and J. F. WangJ.Atmos.Sci.，60，2010-20182003年Conditional nonlinear optimal perturbation and its applicationsMu, M., W. S. Duan, and B. WangNonlinear Processes in Geophysics, 10， 493-5012002年Theoretical research on the predictability of climate systemMu Mu , Jianping Li, Jifan Chou, Wansuo Duan and Jiacheng WangClimate and Environmental Research, Vol.7, 2002, 227-235 (in Chinese)2001年Weak solutions to a model of climate dynamicsWu Yonghui, Mu Mu , Zeng Qingcun and Li YangNonlinear Analysis: Real World Applications, Vol.2, 2001, 507-5212000年The impact of nonlinear stability and instability on the validity of the tangent linear modelMu Mu , Guo Huan, Wang Jiafeng and Li YongAdv. Atmos. Sci., Vol.17, 2000, 375-3901999年Symmetric stability problems in the atmospheric dynamics, Nonlinear Evolution Equations and Their ApplicationsMu Mu and Wu YonghuiWorld Scientific, Singapore, 1999, 163-1761998年Energy-Casimir method in the study of nonlinear stability of the atmospheric motionsMu MuAdvances in Mechanics, Vol.28, 1998, 235-249 (in Chinese)1994年Nonlinear stability of Eady's modelMu Mu and Shepherd T. GJ. Atmos. Sci., Vol. 51, 1994, 3427-34361992年Nonlinear stability of two-dimensional quasigeostrphic motions, Geophys. and AstrophysMu MuFluid Dynamics, Vol.65, 1992, 57-76

以上参考：^[2][7]

从1993年穆穆被批准为博士生以来，^[16]穆穆培养了一大批博士和硕士研究生，^[7]穆穆培养的博士曾于2006年荣获“全国百篇优秀博士论文奖”与“中科院优秀博士论文奖”。^[3]2016年穆穆担任复旦大学特约教授之后，多次参与各类讲座，为学生播种了科学的种子。^[2][11][12]

担任职务地球科学部2018年度创新研究群体项目评审 中国科学院知识创新工程重要方向项目首席科学家国际气象学和大气科学协会（IAMAS）动力气象委员会（ICDM）委员英国皇家气象学会季刊（QJRMS）编委会成员美国气象学会"每月天气评论"associate editor行星大气及其演变委员会（ICPAE）委员国务院学位委员会大气科学评议组召集人中国气象学会动力气象专业委员会非线性动力学专业组组长北京气象学会理事美国《数学评论》特约评论员《中国科学：地球科学》副主编《自然科学进展》（中，英文版）《大气科学》编委《Adv.Atmos.Sci.》编委《海洋科学进展》编委

以上参考：^[1][2][7]

穆穆等建立的湿饱和大气的非线性稳定性判据，极大地推动了对地球流体运动稳定性机制的理解。——国外杂志评^[3]