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[1] 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, doi: 10.1360/N072016-00420.

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

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

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

[4] Mu, M., R. Feng, and W.-S. Duan (2017), Relationship between optimal precursors for Indian Ocean Dipole events and optimally growing initial errors in its prediction, Journal of Geophysical Research: Oceans, 122(2), 1141-1153, doi:10.1002/2016JC012527. 【SCI】

[5] 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.

a) Mu, 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. 【SCI】

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

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

[8] Sun, G.-D., and M. Mu (2017b), 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. 【Book】

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

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

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

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

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

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

[15] Dai, Guokun,Mu, Mu,Jiang, Zhina. Relationships between Optimal Precursors Triggering NAO Onset and Optimally Growing Initial Errors during NAO Prediction. Journal of the Atmospheric Sciences: 2016

[16] Yongjian Ding,Mu Mu,Jianyun Zhang,... Impacts of Climate Change on the Environment, Economy, and Society of China. Springer Berlin Heidelberg:2016


[17] Dai,Guokun,Mu,Mu,Jiang,Zhina. Relationships between Optimal Precursors Triggering the Onset of North Atlantic Oscillation Events and Optimally Growing Initial Errors during Onset Prediction. Egu General Assembly Conference: 2016 摘要

[18] Guang’An Zou,Qiang Wang,Mu Mu. Identifying sensitive areas of adaptive observations for prediction of the Kuroshio large meander using a shallow-water model. Chinese Journal of Oceanology & Limnology: 2016