2. Ke, J., Mu, M., & Fang, X. (2023). Influence of Physically Constrained Initial Perturbations on the Predictability of Mei-Yu Heavy Precipitation. Monthly Weather Review, 151(8), 2115-2138. https://doi.org/10.1175/mwr-d-22-0302.1

3. Gao, Y., Mu, M., & Dai, G. (2023). Targeted observations on Arctic sea ice concentration for improving extended-range prediction of Ural Blocking. Journal of Geophysical Research: Atmospheres, 128(22), e2023JD039630. https://doi.org/10.1029/2023JD039630 

4. Ren, Q. J., M. Mu, G. D. Sun, and Q. Wang. 2022: A new sensitivity analysis approach using conditional nonlinear optimal perturbations and its preliminary application. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-022-1445-3.

5. Chen, H., Chen, S. X., & Mu, M. (2023). A statistical review on the optimal fingerprinting approach in climate change studies. Climate Dynamics. https://doi.org/10.1007/s00382-023-06975-5

6. Dai, G., Ma, X., Mu, M., Han, Z., Li, C., Jiang, Z., & Zhu, M. (2023). Optimal Arctic sea ice concentration perturbation in triggering Ural blocking formation. Atmospheric Research, 289. https://doi.org/10.1016/j.atmosres.2023.106775

7. Dai, G., Mu, M., Han, Z., Li, C., Jiang, Z., Zhu, M., & Ma, X. (2023). The Influence of Arctic Sea Ice Concentration Perturbations on Subseasonal Predictions of North Atlantic Oscillation Events. Advances in Atmospheric Sciences, 40(12), 2242-2261. https://doi.org/10.1007/s00376-023-2371-8

8. Duan, W., Yang, L., Mu, M., Wang, B., Shen, X., Meng, Z., & Ding, R. (2023). Recent Advances in China on the Predictability of Weather and Climate. Advances in Atmospheric Sciences, 40(8), 1521-1547. https://doi.org/10.1007/s00376-023-2334-0

9. Han, Z., Dai, G., Mu, M., Li, C., Li, S., Ma, X., & Zhu, M. (2023). Extent of the Impact of Arctic Atmospheric Uncertainty on Extended‐Range Forecasting of Cold Events in East Asia. Journal of Geophysical Research: Atmospheres, 128(9). https://doi.org/10.1029/2022jd037187

10. Li, C., Dai, G., Mu, M., Han, Z., Ma, X., Jiang, Z., . . . Zhu, M. (2023). Influence of Arctic Sea-ice Concentration on Extended-range Forecasting of Cold Events in East Asia. Advances in Atmospheric Sciences, 40(12), 2224-2241. https://doi.org/10.1007/s00376-023-3010-0

11. Mu, M., & Wang, L. (2023). Preface to the Special Issue on the National Report to the 28th IUGG General Assembly by CNC-IAMAS (2019–2022). Advances in Atmospheric Sciences, 40(8), 1337-1338. https://doi.org/10.1007/s00376-023-3003-z

12. Sun, G., & Mu, M. (2023). Applications of CNOP-P Method to Predictability Studies of Terrestrial Ecosystems. Atmosphere, 14(4). https://doi.org/10.3390/atmos14040617

13. Sun, G., Mu, M., Zhang, Q., Ren, Q., & You, Q. (2023). Application of the CNOP‐P Ensemble Prediction (CNOP‐PEP) Method in Evapotranspiration Forecasting Over the Tibetan Plateau to Model Parameter Uncertainties. Journal of Advances in Modeling Earth Systems, 15(3). https://doi.org/10.1029/2022ms003110

14. Sun, G., Mu, M., Zhang, Q., Ren, Q., & You, Q. (2023). Application of the Observation‐Oriented CNOP‐P Sensitivity Analysis Method in Evapotranspiration Simulation and Prediction Over the Tibetan Plateau. Water Resources Research, 59(8). https://doi.org/10.1029/2022wr033216

15. Tao, L., Mu, M., Wang, L., Fang, X., Duan, W., & Zhang, R. H. (2023). Impacts of Initial Zonal Current Errors on the Predictions of Two Types of El Niño Events. Journal of Geophysical Research: Oceans, 128(6). https://doi.org/10.1029/2023jc019833

16. Zhou L., Zhang K., Wang Q. Mu M. Optimally growing initial error for predicting the sudden shift in the Antarctic Circumpolar Current transport and its application to targeted observation. Ocean Dynamics (2022). https://doi.org/10.1007/s10236-022-01531-x

17. Mu Mu; Zhang Kun; Wang Qiang (2022): Recent progress in applications of the conditional nonlinear optimal perturbation approach to atmosphere-ocean sciences. Chinese Annals of Mathematics, Series B, 43(6), 1033-1048.

18. Zhang, H., Wang, Q., Mu, M., & Liu, X. (2022). Local energetics mechanism for the short-term shift between Kuroshio Extension bimodality. Journal of Geophysical Research: Oceans, 127, e2022JC018794. https://doi.org/10.1029/2022JC018794 

19. Ke, J., M. Mu, and X. Fang, 2022: Impact of Optimally Growing Initial Errors on the Mesoscale Predictability of Heavy Precipitation Events along the Mei-Yu Front in China. Mon. Wea. Rev., 150, 2399–2421.

20. Sun, G., Mu, M., Ren, Q., Zhang, Q., & You, Q. (2022). Determinants of physical processes and their contributions for uncertainties in simulated evapotranspiration over the Tibetan Plateau. Journal of Geophysical Research: Atmospheres, 127, e2021JD035756. https://doi.org/10.1029/2021JD035756

21. Sun, G., and M. Mu. 2022. Role of hydrological parameters in the uncertainty in modeled soil organic carbon using a coupled water-carbon cycle model. Ecological Complexity,50,100986,https://doi.org/10.1016/j.ecocom.2022.100986 

22. Li, J., Jiang, Z., Dong, Y., Zhang, L., Ying, T., Zhang, Z., and Mu Mu. (2022) The IAMAS-CNC Early Career Scientists Nobel Prize Online Interpretation Workshop. Adv. Atmos. Sci. https://doi.org/10.1007/s00376-021-1455-6

23. Ma, X., Mu, M., Dai, G., Han, Z., Li, C., & Jiang, Z. (2022). Influence of Arctic sea ice concentration on extended-range prediction of strong and long-lasting Ural blocking events in winter. Journal of Geophysical Research: Atmospheres, 127, e2021JD036282. https://doi.org/10.1029/2021JD036282 

24. Xu, Z. Z., J. Chen, M. Mu, G. K. Dai, and Y. N. MA, (2022). A nonlinear representation of model uncertainty in a convective-scale ensemble prediction system. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-022-1341-x.

25. Xu, Z., Chen, J., Mu, M. et al. A stochastic and nonlinear representation of model uncertainty in a convective-scale ensemble prediction system. Quart. J. Royal Meteor. Soc.(2022). https://doi.org/10.1002/qj.4322

26. Mu, M., Luo, D., & Zheng, F. (2022). Preface to the Special Issue on Extreme Cold Events from East Asia to North America in Winter 2020/21. Advances in Atmospheric Sciences, 39(4), 543-545. https://doi.org/10.1007/s00376-021-1004-3

27. Liu, X., Wang, Q., & Mu, M. (2022). Identifying the sensitive areas in targeted observation for predicting the Kuroshio large meander path in a regional ocean model. Acta Oceanologica Sinica, 41(2), 3-14. https://doi.org/10.1007/s13131-021-1838-7

28. Ren, Q., Mu, M., Sun, G., & Wang, Q. (2022). A New Sensitivity Analysis Approach Using Conditional Nonlinear Optimal Perturbations and Its Preliminary Application. Advances in Atmospheric Sciences, 40(2), 285-304. https://doi.org/10.1007/s00376-022-1445-3

29. Dai, G., Mu, M., Li, C., Han, Z., & Wang, L. (2021). Evaluation of the Forecast Performance for Extreme Cold Events in East Asia with Subseasonal-to-Seasonal Datasets from ECMWF. Journal of Geophysical Research: Atmospheres, 126(1), e2020JD033860.

30. Dai, G., Mu, M, & Wang, L. (2021). The Influence of Sudden Arctic Sea-Ice Thinning on North Atlantic Oscillation Events. Atmosphere-Ocean, 59(1), 39-52.

31. Sun, G., and M. Mu. 2021. Impacts of two types of errors on the predictability of terrestrial carbon cycle. Ecosphere, 12(1): e03315.

32. Sun, G., and M. Mu. 2021. Uncertainty range of projected soil carbon responses to climate warming in China. Meteorological Applications,28(3),e1993.https://doi.org/10.1002/met.1993

33. Zhou, L., Wang, Q., Mu, M., & Zhang, K. (2021). Optimal precursors triggering sudden shifts in the Antarctic circumpolar current transport through Drake Passage. Journal of Geophysical Research: Oceans, 126, e2021JC017899.

34. 張坤, 穆穆& 王強. 數值模式在海洋觀測設計中的重要作用:回顧與展望. Sci. Sin. Terrae 51, 653–665 (2021)

35. Zhang, Q., Ng, CP., Dai, K.Jun Xu, Jian Tang, Juanzhen Sun and Mu Mu: Lessons Learned from the Tragedy during the 100 km Ultramarathon Race in Baiyin, Gansu Province on 22 May 2021. Adv. Atmos. Sci.38,1803–1810 (2021). https://doi.org/10.1007/s00376-021-1246-0 

36. 張人禾,劉哲,穆穆,等.氣候系統和氣候變化研究獲2021年諾貝爾物理學獎的啟示[J].中國科學基金, 2021, 35(6):4.

37. Dai, G., & Mu, M. (2020). Arctic Influence on the Eastern Asian Cold Surge Forecast: A Case Study of January 2016. Journal of Geophysical Research: Atmospheres, 125(23), e2020JD033298.

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

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

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

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

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

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

44. Sun, 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

45. Fei Peng, Mu Mu and Guodong 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

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

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

48. Gao, Y., Mu, M. and Zhang, K. 2020. Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach. J.Ocean. Limnol. 38, 1382–1393.

49. Wang Q, Mu M, and Sun G-D. 2020. A useful approach to sensitivity and predictability studies in geophysical fluid dynamics: conditional non-linear optimal perturbation. National Science Review: 1-10

50. Sun, G., Mu, M., & You, Q. (2020). Identification of Key Physical Processes and Improvements for Simulating and Predicting Net Primary Production Over the Tibetan Plateau. Journal of Geophysical Research: Atmospheres, 125(23). https://doi.org/10.1029/2020jd033128

51. Sun G,Mu M .Hydrodynamics-driven uncertainty study in simulating terrestrial carbon cycle with a coupled water-carbon cycle model[J]. 2020.DOI:10.21203/rs.3.rs-108448/v1

52. Dai, G., Mu, M., Li, C., Han, Z., & Wang, L. (2021). Evaluation of the Forecast Performance for Extreme Cold Events in East Asia With Subseasonal‐to‐Seasonal Data Sets From ECMWF. Journal of Geophysical Research: Atmospheres, 126(1). https://doi.org/10.1029/2020jd033860

53. Wei Y-T, Mu M, Ren H-L, and Fu J-X. 2019. Conditional nonlinear optimal perturbations of moisture triggering primary MJO initiation. Geophysical Research Letters, 46: 3492-3501.

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

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

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

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

58. Zhou Q, Mu M, and Duan W-S. 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

59. Liang P, Mu M, Wang Q, and Yang L. 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

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

61. Wei Y-T, Ren H-L, Mu M, and Fu J-X. 2019. Nonlinear optimal moisture perturbations as excitation of primary MJO events in a hybrid coupled climate model. Climate Dynamics54:675-699

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

63. 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

64. 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.

65. 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.

66. Liu, X., Q. Wang, andM. 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.

67. 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 

68. 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 

69. 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.

70. 張星,穆穆,王強,張坤(2018),條件非線性最優擾動方法在黑潮目標觀測研究中的應用,海洋氣象學報, 38(1), 1-9, doi:10.19513/j.cnki.issn2096-3599.2018.01.001.

71. 穆穆👩‍👩‍👦，段晚鎖，唐佑民 (2017), 大氣-海洋運動的可預報性:思考與展望, 中國科學🚉：地球科學, doi: 10.1360/N072016-00420.

https://doi.org/10.1007/s00376-012-1174-0

129. 穆穆,秦曉昊,周菲凡,等.加強目標觀測,服務防災減災[J].成都信息工程學院學報, 2012, 27(1):7.DOI:10.3969/j.issn.1671-1742.2012.01.002.

130. 王凡,胡敦欣,穆穆,et al.熱帶太平洋海洋環流與暖池的結構特征🤽🧛🏼‍♂️、變異機理和氣候效應[J].地球科學進展, 2012, 27(6):8.DOI:CNKI:SUN:DXJZ.0.2012-06-000.

131. Mu, Mu, Zhina Jiang, 2011: Similarities between Optimal Precursors that Trigger the Onset of Blocking Events and Optimally Growing Initial Errors in Onset Prediction. J. Atmos. Sci., 68, 2860–2877.

132. Qin, Xiaohao, Mu Mu, A Study on the Reduction of Forecast Error Variance by Three Adaptive Observation Approaches for Tropical Cyclone Prediction. Mon. Wea. Rev., 2011，139：2218–2232.

133. HONGLI WANG, Mu Mu, XIANG-YU 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.

134. Sun, G. D., and M. Mu, 2011: Response of a grassland ecosystem to climate change in a theoretical model. Adv. Atmos. Sci., 28(6), 1266-1278. SCI A5

135. Mu Mu，Boyu Chen, Feifan Zhou and Yu, Y., 2011: Methods and Uncertainties of Meteorological Forecasts. Meteorological Monthly, 37(1): 1-13.(in Chinese)

136. 穆穆,陳博宇,周菲凡,等.氣象預報的方法與不確定性[J].氣象, 2011, 37(1):13.DOI:10.7519/j.issn.1000-0526.2011.1.001.

137. Zhou, F., & Mu, M. (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. https://doi.org/10.1007/s00376-011-0120-x

138. Sun, Guodong, Mu Mu, Y. Zhang, 2010: Algorithm studies on how to obtain a conditional nonlinear optimal perturbation (CNOP). Adv. Atmos. Sci., 27(6), 1311-1321.

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

140. Jiang Zhina and Mu Mu, A comparison study of the methods of conditional nonlinear optimal perturbations and singular vectors in ensemble prediction. Adv. Atmos. Sci., 2009, 26, 465-470.

141. Sun, Guodong and Mu Mu, Nonlinear feature of the abrupt transitions between multiple equilibria states of an ecosystem model. Adv. Atmos. Sci., 2009, 26, 293–304.

142. Mu Mu，Zhou Feifan, Wang Hongli🐞， A method to identify the sensitive areas in targeting for tropical cyclone prediction: conditional nonlinear optimal perturbation. Mon. Wea. Rev., 2009, 137🧑‍🍳，1623-1639.

143. Wu Xiaogang, Mu Mu, Impact of Wind-driven Ocean Gyres on the Nonlinear Stability of Thermohaline Circulation in a Modified Box Model, J. Phys. Oceanogr., 2009⚡️👂🏿，39，798-805.

144. Wansuo Duan, Xinchao Liu, Keyun Zhu, and Mu Mu, Exploring the initial error that causes a significant spring predictability barrier for El Nino events, J. Geophysical Research. 2009👨‍🦯，114, C04022, doi:10.1029/2008JC004925.

145. Wansuo Duan🦹🏼，Mu Mu, Conditional nonlinear optimal perturbation: applications to stability, sensitivity, and predictability, Science in China(D), 2009, 52，884-906.

146. Yu Yanshan, Wansuo Duan, Hui Xu, Mu Mu, Dynamics of nonlinear error growth and season-dependent predictability of El Nino events in the Zebiak-Cane model, Quarterly Journal of Royal Meteorological Society, 2009, DOI: 10.1002/qj.526.

147. Zhina Jiang, Mu Mu👱🏿‍♀️🚋，Donghai Wang, Experiments of ensemble forecast by conditional nonlinear optimal perturbation, Science in China（D），2009: 52（4）😞☄️，511-518.

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

149. Mu Mu, Zhina Jiang, A Method to Determine Perturbations That Trigger Blocking Onset: Conditional Nonlinear Optimal Perturbations. J. Atmos. Sci., 2008, 65, 3935-3946.

150. Zhina Jiang, Mu Mu, Donghai Wang ,Conditional nonlinear optimal perturbation of a T21L3 quasi-geostrophic model, The Quarterly Journal of the Royal Meteorological Society, 2008🎳，134（633）👨🏼‍🚒：1027

1038.

151. Wansuo Duan, Hui Xu, Mu Mu, Decisive role of nonlinear temperature advection in El Nino and La Nina amplitude asymmetry, J. Geophysical Research, 2008, VOL. 113, C01014, doi:10.1029/2006JC003974.

152. Wansuo Duan, Xue Feng, and Mu Mu, Investigating a nonlinear characteristic of ENSO events by conditional nonlinear optimal perturbation, Atmosphere Research, 2008, doi:10.1016/j.atmosres.2008.09.003.

153. Mu Mu, Jiang Zhina, A new approach to the generation of initial perturbations for ensemble prediction: Conditional nonlinear optimal perturbation, Chinese Science Bulletin, 2008，53（13）: 2062-2068.

154. Xiaogang Wu, Mu Mu, Impact of wind-driven ocean gyres on the decadal variability of THC----Analysis by box-models, Advance in Marine Science, 2008, 26（4），411-417 (in Chinese).

155. 李崇銀,穆穆,周廣慶,et al.ENSO機理及其預測研究[J].大氣科學, 2008, 32(4):21.DOI:CNKI:SUN:DQXK.0.2008-04-005.

156. 吳曉剛,穆穆.風生渦旋對熱鹽環流年代際變率的影響——基於盒子模型的分析[J].海洋科學進展, 2008, 26(4):7.DOI:10.3969/j.issn.1671-6647.2008.04.001.

157. 王鐵,穆穆.REM模式伴隨系統的建立及其四維變分資料同化初步試驗[J].氣象學報, 2008, 66(6):13.DOI:10.3321/j.issn:0577-6619.2008.06.010.

158. 姜智娜,穆穆,王東海.基於條件非線性最優擾動方法的集合預報試驗[J].中國科學:D輯, 2008, 038(011):1444-1451.DOI:CNKI:SUN:JDXK.0.2008-11-013.

159. Mu Mu , Xu Hui, Duan Wansuo, A kind of initial errors related to “spring predictability barrier“ for El Nino event in Zebiak-Cane model. Geophysical Research Letters, 2007, Vol. 34, L03709, doi:10.1029/2006GL027412.

160. Mu Mu, Duan Wansuo,Wang Bin, Season-dependent dynamics of nonlinear optimal error growth and ENSO predictability in a theoretical model. Journal of Geophysical Research, 2007,Vol. 112,D10113,doi:10.1029/2005JD006981.

161. Mu Mu , B.Wang, Nonlinear instability and sensitivity of a theoretical grassland ecosystem to finite-amplitude perturbations. Nonlinear Processes in Geophysics, Vol. 14, 409-423, 2007,

162. Mu Mu , Jiang Zhina, A new approach to the generation of initial perturbations for ensemble prediction: conditional nonlinear optimal perturbation, Chin. Sci. Bull., 2007,1457-1462.

163. Wang Tie, Mu Mu, The application of the adjoint modeling system and nonlinear optimization method in the study of predictability of the REM with observational data, Chinese J. Atmos. Sci., 2007,Vol 31, 987-998. (in Chinese)

164. Mu Mu, Wang Hongli, Zhou Feifan, A preliminary application of conditional nonlinear optimal perturbation to adaptive observation, Chinese J. Atmos. Sci., 2007, Vol. 31, 1102-1112. (in Chinese)

165. Mu Mu, Zhang Zhiyue, Conditional nonlinear optimal perturbations of a two-dimensional quasigeostrophic model, Journal of the Atmospheric Sciences, Vol.63, 2006, 1587-1604.

166. Duan Wansuo, Mu Mu , Investigating decadal variability of El Nino Southern Oscillation events by conditional nonlinear optimal perturbation, Journal of Geophysical Research, 2006, Vol.111, C07015, doi:10.1029/2005JC003458.

167. Duan Wansuo, Mu Mu, Advance and prospect of the studies of El Nino predictability by nonlinear optimization method, Chinese J. Atmos. Sci., Vol.30, 2006, 759-766. (in Chinese)

168. 王鐵,穆穆.伴隨系統及非線性優化方法在REM模式可預報性研究中的實際個例應用[J].大氣科學, 2007, 31(5):12.DOI:10.3878/j.issn.1006-9895.2007.05.21.

169. 穆穆,姜智娜.集合預報初始擾動產生的一個新方法: 條件非線性最優擾動[J].科學通報, 2007, 52(12):6.DOI:10.3321/j.issn:0023-074X.2007.12.016.

170. Mu Mu , Duan Wansuo, Xu Hui, Wang Bo, Applications of conditional nonlinear optimal perturbation in weather and climate predictability and sensitivity, Advance in Atmospheric Sciences, Vol.23, 2006, 992-1002.

171. Zheng Qin and Mu Mu , The effects of the model errors generated by discretization of “on-off” processes on VDA, Nonlinear Process in Geophysics, Vol.13, 2006, 309–320.

172. 段晚鎖,穆穆.用非線性最優化方法研究El Niño可預報性的進展與前瞻[J].大氣科學, 2006, 30(5):8.DOI:10.3878/j.issn.1006-9895.2006.05.05.

173. Duan, W., & Mu, M. (2006). Investigating decadal variability of El Nino–Southern Oscillation asymmetry by conditional nonlinear optimal perturbation. Journal of Geophysical Research: Oceans, 111(C7). https://doi.org/10.1029/2005jc003458

174. Mu, M., and Z. Zhang, 2006: Conditional Nonlinear Optimal Perturbations of a Two-Dimensional Quasigeostrophic Model. J. Atmos. Sci.,63, 1587–1604,https://doi.org/10.1175/JAS3703.1.

175. Jiafeng Wang, Mu Mu and Qin Zheng, Initial condition and parameter estimation in physical “On-Off” processes by variational data assimilation, Tellus, Vol.57A, 2005, 736-741

176. Mu Mu and Qin Zheng, Zigzag oscillations in variational data assimilation with physics “On-off” processes, Mon. Wea. Rev., Vol.133, 2005, 2711-2720.

177. Duan Wansuo, Mu Mu , Applications of nonlinear optimization method to numerical studies of atmospheric and oceanic sciences, Applied Mathematics and Mechanics, Vol.26, 2005, 636-646.

178. Sun Liang, Mu Mu , Dejun Sun, and Xieyuan Yin, Passive mechanism of decadal variation of thermohaline circulation, Journal of Geophysical Research-Ocean, 2005, Vol. 110, C07025, doi:10.1029/2005JC002897.

179. Duan Wansuo, Mu Mu , Applications of nonlinear optimization methods to quantifying the predictability of a numerical model for El Nino-Southern Oscillation, Progress in Natural Science, 15, 2005, 915-921.

180. Duan Wansuo, Conditional nonlinear optimal perturbation and its applications in weather and climate predictability, Chinese Sci. Bull., Vol.50, 2005, 2401-2407

181. Wansuo, Mu Mu and Bin Wang, Conditional nonlinear optimal perturbations as the optimal precursors for El Nino-Southern Oscillation events, J. Geophysical Research, D23105, 2004,1029-1041.

182. Wansuo Duan and Jifan Chou, Recent advances in predictability studies in China (1999-2002), Adv. Atmos. Sci., Vol.21, 2004, 437-443.

183. Ping, Zheng Qin, Ru Rucong and Mu Mu, Application of the optimization arithmetic to aseertain the entrainment velocity in the top of the well-mixed layer, Chinese Journal of Atmospheric Sciences, Vol.28, 2004, 112-123.

184. 段晚鎖,穆穆.非線性優化方法在大氣和海洋科學數值研究中的若幹應用[J].應用數學和力學, 2005, 26(5):10.DOI:10.3321/j.issn:1000-0887.2005.05.012.

185. Xu Hui, Mu Mu and Luo Dehai, Application of nonlinear optimization method to sensitivity analysis of numerical model, Progress in Natural Science, Vol.14, 2004, 546-549.

186. Mu Mu , Liang Sun and H. A. Dijkstra, Sensitivity and stability of thermolhaline circulation of ocean to finite amplitude perturbations, J. Physical Oceanography, Vol.34, 2004, 2305-2315.

187. Le Dimet, F. X., Shutyaev, V. P., Wang, J. and Mu, M., The problem of data assimilation for soil water movement, ESAIM: Control, Optimization and Calculus of Variations (COCV), Vol.10, 2004, 331-345.

188. Mu, M., Wansuo, D. & Jifan, C. Recent advances in predictability studies in China (1999–2002).Adv. Atmos. Sci.21, 437–443 (2004). https://doi.org/10.1007/BF02915570

189. Ping L , Qin Z , Rucong Y ,et al.Application of the Optimization Arithmetic to Ascertain the Entrainment Velocity in the Top of the Well-Mixed Layer[J].Chinese Journal of Atmospheric Sciences, 2004.DOI:10.1117/12.528072.

190. Duan, W. , Mu, M. , & Wang, B. . (2004). Conditional nonlinear optimal perturbations as the optimal precursors for el nino–southern oscillation events. Journal of Geophysical Research: Atmospheres, 109.

191. Mu Mu and Wang Jiafeng, A method to adjoint variational data assimilation with physical "on-off" processes, J. Atmos. Sci., Vol.60, 2003, 2010-2018.

192. Mu Mu and Duan Wansuo, A new approach to study ENSO predictability: Conditional nonlinear optimal perturbation, Chinese Science Bulletin, Vol.48, 2003, 1045-1047.

193. Mu Mu , Wansuo Duan and Bin Wang, Conditional nonlinear optimal perturbation and its applications, Nonlinear Processes in Geophysics, Vol.10, 2003, 493-501.

194. Liu Yongming, Mu Mu and Qiu Lincun, Nonlinear stability of zonally symmetric continuously stratified quasigeostrophic flows, Progress in Natural Science, Vol.13, 2003, 378-382 (in Chinese).

195. Sun Liang and Mu Mu, Advances in the research of thermohaline circulation and its decadal variability, Acta Oceanologica Sinica, Vol.25, 2003, 111-118 (in Chinese).

196. Mu Mu , Ji Zhongzhen, Wang Bin and Li Yang, Achievments in geophysical fluid dynamics, Chinese Journal of Atmospheric Sciences, Vol.27, 2003, 689-711 (in Chinese).

197. 孫亮,穆穆.溫鹽環流穩定性以及年代際變率的研究進展[J].海洋學報, 2003, 25(4):8.DOI:10.3321/j.issn:0253-4193.2003.04.014.

198. 劉永明,穆穆,邱令存.緯向對稱的連續層結準地轉流的非線性穩定性[J].自然科學進展, 2003(4):378-382.DOI:10.3321/j.issn:1002-008X.2003.04.008.

199. 徐輝,穆穆,羅德海.非線性優化方法在數值模式敏感性分析中的應用[J].自然科學進展, 2003, 13(11):4.DOI:10.1007/BF02873153.

200. 穆穆,段晚鎖.ENSO可預報性研究的一個新方法:條件非線性最優擾動[J].科學通報, 2003, 48(7):3.DOI:CNKI:SUN:KXTB.0.2003-07-023.

201. Wang Jiafeng, Mu Mu and Zheng Qin, Adjoint approach to VAD of "on-off" processes based on nonlinear perturbation equation, Progress in Natural Science, Vol.12, 2002, 869-873. (SCI) A8

202. Mu Mu , Wansuo Duan and Jiafeng Wang, Nonlinear optimization problems in atmospheric and oceanic sciences, East-west Journal of Mathematics, Thailand, Special Volume, 2002, 155-164.

203. Mu Mu , Jianping Li, Jifan Chou, Wansuo Duan and Jiacheng Wang, Theoretical research on the predictability of climate system, Climate and Environmental Research, Vol.7, 2002, 227-235 (in Chinese).

204. Mu Mu , Wansuo Duan and Jiacheng Wang, The Predictability problems in numerical weather and climate prediction, Adv. Atmos. Sci., Vol.19, 2002, 191-204.

205. Mu Mu and Yonghui Wu, Armold Nonlinear stability theorems and their application to the atmosphere and oceans, Surveys in Geophysics, Vol.22, 2002, 383-426.

206. Mu Mu , Guo Huan , Wang Jiafeng and Li Yong, Relationship between the magnitude of singular value and nonlinear stability，Progress in Natural Science, Vol.11, 2001, 476-480.

207. Mu Mu and Wang Jiacheng, Nonlinear fastest growing perturbation and the first kind of predictability, Science in China (D), Vol.44, 2001, 1128-1139.

208. Liu Yongming and Mu Mu, Nonlinear stability of generalized Eady’s Model, J. Atmos. Sci. Vol.58, 2001, 821-827.

209. Mu Mu and Guo Huan, Effect of four-dimensional variational data assimilation in case of nonlinear instability, Progress in Natural Science, Vol.11, 2001, 825-832.

210. Wu Yonghui, Mu Mu , Zeng Qingcun and Li Yang, Weak solutions to a model of climate dynamics, Nonlinear Analysis: Real World Applications, Vol.2, 2001, 507-521.

211. Mu Mu , Guo Huan, Wang Jiafeng and Li Yong, The impact of nonlinear stability and instability on the validity of the tangent linear model, Adv. Atmos. Sci., Vol.17, 2000, 375-390.

212. Mu Mu , Nonlinear singular vectors and nonlinear singular values, Science in China (D), Vol.43, 2000, 375-385.

213. Wang Bizheng, Zeng Qingcun and Mu Mu, The four-dimensional problem of vapour by means of the adjoint equation, Part I: Theory, Climate and Environment Research, Vol.5, 2000, 273-278 (in Chinese).

214. Li Yang, Mu Mu and Wu Yonghui, A study on the nonlinear stability of fronts in the Ocean on a sloping continental shelf, Adv. Atmos. Sci., Vol.17, 2000, 275-284 .

215. Mu Mu, Wu Yonghui, Tang Mozhi and Liu Haiyan, Nonlinear stability analysis of the zonal flows at middle and high latitudes, Adv. Atmos. Sci., Vol.16, 1999, 569-580.

216. V. A. Vladimirov, Mu Mu , Yonghui Wu and K. I. Ilin, On nonlinear stability of baroclinic fronts, Geophys. Astrophys. Fluid Dynamics, Vol.91, 1999, 65-84.

217. Wu Y. H. and Mu Mu, Maximal energy isolated vortices in a uniform shear flow, Nonlinear Analysis, Vol.38, 1999, 23-135.

218. Wu Y. H. and Mu Mu , Nonlinear instability of dipole vortices and the atmospheric blocking, Progress in Natural Science, Vol.9, 1999, 234-237.

219. Mu Mu and Wu Yonghui, Symmetric stability problems in the atmospheric dynamics, Nonlinear Evolution Equations and Their Applications, World Scientific, Singapore, 1999, 163-176.

220. Mu Mu, V. Vladimirov and Wu Y. H., Energy-Casimir and energy-Lagrange methods in the study of nonlinear symmetric stability problems, J. Atmos. Sci., Vol.56, 1999, 400-411.

221. Li Y , Mu M , Moon S E ,et al.Baroclinic Instability in the Three-Layer Generalized Phillips' Model :Part Ⅱ: Nonlinear Stability Theory[J]. Korean Journal of the Atmospheric Sciences, 1999, 2.

222. Mu Mu, A criterion of symmetric stability of planetary atmospheres, East Asian Monsoon and Torrential Rain in China, Meteorological Press, 1999, 476-482 (in Chinese).

223. Mu Mu and Xiang Jie, On the evolution of finite-amplitude disturbances to the barotropic and baroclinic quasigeostrophic flows, Adv. Atmos. Sci., Vol.5, 1998, 113-123.

224. Mu Mu, Energy-Casimir method in the study of nonlinear stability of the atmospheric motions, Advances in Mechanics, Vol.28, 1998, 235-249 (in Chinese).

225. Mu Mu, Optimality of a nonlinear stability criterion of two-layer Phillips model, Chinese Science Bulletin, Vol.43, 1998, 656-659.

226. Xiang Jie and Mu Mu, The lower bound on the evolution of disturbances to the nonlinear unstable basic flow in the Phillips model, Proceedings of the Third International Conferences on Nonlinear Mechanics, Shanghai University Press, 1998, 548-553.

227. Li Y., Mu Mu, S. E. Moon and K. T. Sohn, On the linear and nonlinear stability of generalized Eady model, Part I: Linear instability theorem. Kor. J. Atmos.Sci., 1998, Vol.1, 113-118.

228. Li Y., Mu Mu, S. E. Moon and K. T. Sohn, On the linear and nonlinear stability of generalized Eady model, Part II: Nonlinear stability theorem. Kor. J. Atmos. Sci., 1998, Vol.1, 119-125.

229. Yonghui W , Mu M .A remark on the nonlinearly symmetric stability criteria[J].科學通報：英文版, 1998, 43(12):4.DOI:10.1007/BF02884648.

230. Wu Y. H. and Mu Mu, A remark on the nonlinear symmetric stability criteria, Chinese Science Bulletin, Vol.43, 1998, 1050-1052.

231. Xiang Jie and Mu Mu, Saturation of nonlinear instability to parallel flow, Progress in Natural Science, Vol.7, 1997, 239-243.

232. 項傑,穆穆.平行切變流的非線性不穩定的飽和問題[J].自然科學進展：國家重點實驗室通訊, 1997, 7(4):5.DOI:10.1007/s00376-997-0061-6.

233. Li Yang and Mu Mu, Baroclinic instability in the generalized Phillips model. Part I: two-layer model, Adv. Atmos. Sci. Vol.13, 1996, 33-42.

234. Li Y. and Mu Mu, On the nonlinear stability of Three-dimensional quasigeostrophic motions in spherical geometry, Adv. Atmos. Sci., Vol.13, 1996, 203-216.

235. Mu Mu , T. G. Shepherd and K. Swanson, On nonlinear symmetric stability and the nonlinear saturation of symmetric instability, J. Atmos. Sci., Vol.53, 1996, 2918-2923.

236. Liu Y. M. and Mu Mu and T. G. Shepherd, Nonlinear stability of continuously stratified quasigeostrophic flow, J. Fluid Mech., Vol.325, 1996, 419-439.

237. Liu, Y. M. and Mu Mu, Nonlinear stability theorem for Eady's model of quasigeostropic baroclinic flow, J. Atmos. Sci., Vol.53, 1996, 1459-1463.

238. Mu Mu, Some advances in the study of nonlinear instability of the atmospheric motions, Chinese Journal of Atmospheric Sciences, Vol.19, 1995, 318-334.

239. Mu Mu, On the nonlinear symmetric stability in the atmosphere, Proceedings of Sixth Asian Congress of Fluid Mechanics, Editors: Y. T. Chew and C. P. Tso, Singapore, Vol.1, 1995, 232-235.

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

241. Liu Y. M. and Mu Mu, Arnol'd's second nonlinear stability theorem for general multilayer quasi-geostrophic model, Adv. Atmos. Sci., Vol.11, 1994, 36-42.

242. Mu Mu and Shepherd T. G., On Arnold's second nonlinear stability theorem for two-dimensional quasigeostrophic flow, Geophys. Astrophys. Fluid Dynamics, Vol.75, 1994, 21-37.

243. Mu Mu and Shepherd T. G., Nonlinear stability of Eady's model, J. Atmos. Sci., Vol. 51, 1994, 3427-3436.

244. Mu Mu and T. G. Shepherd, Nonlinear stability criteria for quasigeostrophic motion, Climate, Environment and Geophysical Fluid Dynamics, Editors: Ye Duzheng, Zeng Qingcun, Wu guoxiong and Zhang Zuojun, China Meteorological Press, 1993, 463-474.

2445 Mu Mu and Simon J., A remark on nonlinear stability of three-dimensional quasigeostrophic motions, Chinese Science Bulletin, Vol.38, 1993, 1978-1984.

246. Liu Y. M. and Mu Mu, A problem related to nonlinear stability criteria for multi-layer quasigeostrophic flow, Adv. Atmos. Sci., Vol.9, 1992, 337-345.

247. Mu Mu, Nonlinear stability of two-dimensional quasigeostrphic motions, Geophys. and Astrophys. Fluid Dynamics, Vol.65, 1992, 57-76.

248. Mu Mu and Wang Xiyong, Nonlinear stability criteria for motions of three-dimensional quasi-geostrophic flow on a beta-plane, Nonlinearity, Vol.5, 1992, 353-371.

249. Mu Mu and Zeng Qingcun, New development on existence and uniqueness of solutions to some models in atmospheric dynamics, Adv. Atmos. Sci., Vol.8, 1991, 383-398.

250. Mu Mu, Nonlinear stability criteria for motions of multilayer quasi-geostrophic flow, Science in China, Ser. B, Vol.34, 1991, 1516-1528.

251. Mu Mu and Zeng Qingcun, Criteria for the nonlinear stability of three-dimensional quasigeostrophic motions, Adv. Atmos. Sci., Vol.8, 1991, 1-10.

221. Mu Mu, Global smooth solutions of two-dimensional Euler equations, Chinese Sciences Bulletin, Vol.35, 1990, 1895-1900

253. Mu Mu and Zeng Qingcun, Stability of quasigeostrophic motions in atmosphere, Proceedings of Fourth Asian Congress of Fluid Mech., Editors: N. W. M. Ko and S. C. Kot, Vol.1.E16-E18, 1989, 21-25, Hong Kong.

254. Mu Mu, Global classical solutions to initial-boundary value problems for the potential vorticity equation, Journal of computational and applied mathematics, Vol.28, 1989, 327-338.

255. Mu Mu, On the boundary value problem for a degenerate elliptic equation, Comm. Appl. Math. and Comput., Vol.3, 1989, 26-30 (in Chinese).

256. Mu Mu, A class of the boundary value problem for elliptic-parabolic composite type equations, Chin. Ann. of Math., Vol.10A, 1989, 351-358 (in Chinese)

257. Mu Mu, Classical solution to 3-dimensional balanced model in numerical weather prediction, Kexue Tongbao, Vol.33, 1988, 1628-1631.

258. Mu Mu, Necessary and sufficient conditions for existence of global classical solutions of two-dimensional Euler equations in time-dependent domain, Kexue Tongbao, Vol.33, 1988, 1295-1299.

259. Mu Mu, Results about propagations of singularities for certain composite type operators, Journal of Fudan Univ. (Natural Sciences), Vol.27, 1988, 127-130 (in Chinese).

260. Mu Mu and Zeng Qingcun, On wellposedness of an initial boundary value problem for a three-dimensional balanced model, Chinese Journal of Atmospheric Sciences, Vol.12, 1988, 189-199.

261. Mu Mu, Global classical solutions of initial boundary value problems for generalized vorticity equations, Scientia Sinica (Series A), Vol.30, 1987, 359-371.

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

263. Mu Mu, Existence and uniqueness of global strong solutions of two models in atmospheric dynamics, Applied Math. and Mech., Vol.7, 1986, 965-970.

264. Mu Mu, Existence and uniqueness of classical solution to an initial boundary value problem in baroclinic quasigeostrophic-quasinondivergent model, Scientia Atmospherica Sinica, Vol.10, 1986, 113-120 (in Chinese).

265. Mu Mu, Global classical solutions of initial-boundary value problems for nonlinear vorticity equation and its applications, Acta Mathematica Scientia, Vol.6, 1986, 201-218 (in Chinese).

266. Mu Mu, The identity of weak and strong solutions to first order linear partial differential equations with abstract homogeneous boundary conditions, J. of Fudan Univ. (Natural Sciences), Vol.25, 1986, 25-33 (in Chinese).

267. Mu Mu, The identity of weak and strong solutions of linear partial differential equation of higher order with abstract homogeneous boundary conditions. Acta Scientiarum Naturalium Universitatis Anhuiensis, 1984, 9-16 (in Chinese).

邀請報告

[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, 5^thChina-Thailand Joint Conference on Climate Change, November 27-29, 2017,Chiang Mai, Thailand.

[5]Mu Mu, Some Progresses in the studies of Target observations, 7^thInternational 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 prediction—ENSO, 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 ENSO↘️、blocking and kuroshio current, 7^thInternational 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 Xiaohao,A 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 University、University 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, 16^th 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, 1^stAlexander 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 ocean’s thermohaline circulation, 1^stEGU 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, 1^st  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 ocean’s 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, 1^stannual 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 27^thGeneral 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 27^thGeneral 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 26^thGeneral 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, Arnol’d’s 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 Arnold’s 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 Arnold’s 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, Arnold’s 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.

會議組織

[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, 2005，IAMAS，Aeronomy 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，更新時間：2024/07/23