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Preface to the Special Issue on the "Observation, Prediction and Analysis of severe Convection of China" (OPACC) National "973" Project


doi: 10.1007/s00376-016-0002-3

  • Cao, Z. and H. Cai, 2016: Identification of forcing mechanisms of convective initiation in the mountain areas through high-resolution numerical simulations. Adv. Atmos. Sci.,33(10), doi: 10.1007/s00376-016-6198-4.ea4e9813176f7fdbc5f25fff72cecb26http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs00376-016-6198-4http://xueshu.baidu.com/s?wd=paperuri%3A%280e4cc44d8ce1a2cfef4d38a035eaa237%29&filter=sc_long_sign&tn=SE_xueshusource_2kduw22v&sc_vurl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs00376-016-6198-4&ie=utf-8&sc_us=2016461348397450219
    Chen X., K. Zhao, J. Sun, B. Zhou, and W.-C. Lee, 2016a: Assimilating surface observations in a Four-Dimensional Variational Doppler Radar Data Assimilation System to improve the analysis and forecast of a squall line case in OPACC. Adv. Atmos. Sci.,33(10), doi:10.1007/s00376-016-5290-0.10.1007/s00376-016-5290-01fce16de8882bed0d338e98f2117c986http%3A%2F%2Fwww.researchgate.net%2Fpublication%2F304349214_Assimilating_Surface_Observations_in_a_Four-Dimensional_Variational_Doppler_Radar_Data_Assimilation_System_to_Improve_the_Analysis_and_Forecast_of_a_Squall_Line_Casehttp://www.researchgate.net/publication/304349214_Assimilating_Surface_Observations_in_a_Four-Dimensional_Variational_Doppler_Radar_Data_Assimilation_System_to_Improve_the_Analysis_and_Forecast_of_a_Squall_Line_Case
    Chen Y.-D., R.-Z. Zhang, D.-M. Meng, J.-Z. Min, and L.-N. Zhang, 2016b: Variational assimilation of satellite cloud water/ice path and microphysics scheme sensitivity to the assimilation of a rainfall case. Adv. Atmos. Sci. ,33(10), doi:10.1007/s00376-016-6004-3.c4fe0fe1ddd2ecafdff7929670ea57f6http%3A%2F%2F159.226.119.58%2Faas%2FCN%2F10.1007%2Fs00376-016-6004-3http://159.226.119.58/aas/CN/10.1007/s00376-016-6004-3
    Deng G., Y. Zhu, J. Gong, D. Chen, R. Wobus, and Z. Zhang, 2016: The effects of land surface process perturbations in global ensemble forecast system. Adv. Atmos. Sci.,33(10), doi: 10.1007/s00376-016-6036-8.00c358a4d3a8cc78ee4bd88d006daf71http%3A%2F%2F159.226.119.58%2Faas%2FEN%2Fabstract%2Fabstract2928.shtmlhttp://159.226.119.58/aas/EN/abstract/abstract2928.shtml
    Li, L.-C. and W. Li, 2008: The development of integrated meteorological observation system. Meteorology, 3, 3- 9. (in Chinese)10.3724/SP.J.1047.2008.000149175a5ffedf0fabd9c1f4bad99bc14aahttp%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTotal-QXXX200803003.htmhttp://en.cnki.com.cn/Article_en/CJFDTotal-QXXX200803003.htmTo review the history of meteorological observation development,close relationship be- tween meteorological observation and weather forecasting has been analyzed,and the result shows that meteorological observation development has promoted weather forecasting development.Fur- thermore current development of meteorological observation is described,the prospect of new me- teorological observation technology application and the future trend of meteorological instrumental development are analyzed and depicted.Finally some international integrated meteorological ob- servation plans such as GCOS,GEOSS and WlGOS are introduced.
    Li S., Y. Wang, H.-L. Yuan, J. Song, and X. Xu, 2016a: Ensemble mean forecast skill and applications with the T213 ensemble prediction system. Adv. Atmos. Sci.,33(11), doi: 10.1007/s00376-016-6155-2.3f7d3805b52bc86786f9a6cd3bd74e5dhttp%3A%2F%2F159.226.119.58%2Faas%2FEN%2Fabstract%2Fabstract2930.shtmlhttp://159.226.119.58/aas/EN/abstract/abstract2930.shtml
    Li X., M. Zeng, Y. Wang, W. Wang, H. Wu, and H. Mei, 2016b: Evaluations of two momentum control variable schemes in 3DVAR and their impact on radar wind data assimilation: A case study on a squall line. Adv. Atmos. Sci.,33(10), doi: 10.1007/s00376-016-5255-3.
    Liu P., J. Sun, and L. Shen, 2016a: Parameterization of sheared entrainment in a well-developed CBL. Part I: Evaluation of the scheme through large-eddy simulations. Adv. Atmos. Sci.,33(10), doi: 10.1007/s00376-016-5208-x.a4480e655d303e9ee34b28695cc3be93http%3A%2F%2F159.226.119.58%2Faas%2FEN%2F10.1007%2Fs00376-016-5208-xhttp://159.226.119.58/aas/EN/10.1007/s00376-016-5208-x
    Liu P., J. Sun, and L. Shen, 2016b: Parameterization of Sheared Entrainment in a Well-Developed CBL. Part II: A Simple Model for Predicting the Growth Rate of the CBL. Adv. Atmos. Sci.,33(10), doi: 10.1007/s00376-016-5209-9.855f8549c5e31dcac03e640d852acee1http%3A%2F%2F159.226.119.58%2Faas%2FEN%2F10.1007%2Fs00376-016-5209-9http://159.226.119.58/aas/EN/10.1007/s00376-016-5209-9
    Ran L. and C. Chen, 2016: Diagnosis of forcing of inertial-gravity waves in a severe convection. Adv. Atmos. Sci.,33(11), doi: 10.1007/s00376-016-5292-y.
    Shen X., W. Huang, C. Guo, and X. Jiang, 2016: Precipitation responses to radiative effects of ice clouds: A cloud-resolving modeling study of a pre-summer torrential precipitation event. Adv. Atmos. Sci.,33(10), doi: 10.1007/s00376-016-5218-8.8f46caac9890120482eb45ec045a6a02http%3A%2F%2F159.226.119.58%2Faas%2FCN%2F10.1007%2Fs00376-016-5218-8http://159.226.119.58/aas/CN/10.1007/s00376-016-5218-8
    Sun J. Z., H. L.Wang, W. X. Tong, Y. Zhang, C.-Y. Lin, and D. M. Xu, 2016: Comparison of the impacts of momentum control variables on high-resolution variational data assimilation and precipitation forecasting. Mon. Wea. Rev., 144, 149- 169.10.1175/MWR-D-14-00205.1d95f35b7ffda06becfffa318c1f65b06http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2016MWRv..144..149Shttp://adsabs.harvard.edu/abs/2016MWRv..144..149SNot Available Not Available
    Wang M., K. Zhao, M. Xue, G. Zhang, S. Liu, L. Wen, and G. Chen, 2016a: Precipitation microphysics characteristics of a Typhoon Matmo (2014) rainband after landfall over eastern China based on polarimetric radar observations. J. Geophy. Res. (in press)
    Wang Q., M. Xue, and Z.-M. Tan, 2016b: Convective initiation by topographically induced convergence forcing over the Dabie Mountains on 24 June 2010 . Adv. Atmos. Sci.,33(10), doi: 10.1007/s00376-016-6024-z.95c9c5d1158a37d1f515bcfe6d39cff0http%3A%2F%2F159.226.119.58%2Faas%2FEN%2F10.1007%2Fs00376-016-6024-zhttp://159.226.119.58/aas/EN/10.1007/s00376-016-6024-z
    Wen L., K. Zhao, G. Zhang, B. Zhou, S. Liu, X. Chen, and M. Xue, 2016: Statistical characteristics of raindrop size distributions observed in east China during the Asian summer monsoon season from the 2D-video disdrometer and micro-rain radar. J. Geophy. Res., 121, 2265- 2282.
    Yang L., J.-F. Fei, X.-G. Huang, X.-P. Cheng, X.-R. Yang, J.-L. Ding, and W. Shi, 2016: Asymmetric climatology distribution of convection in tropical cyclones over the Western North Pacific Ocean. Adv. Atmos. Sci.,33(11), doi: 10.1007/s00376-016-5277-x.e3c6d107cc2cd3cfcd726be0bceadab6http%3A%2F%2F159.226.119.58%2Faas%2FEN%2F10.1007%2Fs00376-016-5277-xhttp://159.226.119.58/aas/EN/10.1007/s00376-016-5277-x
    Zhang, H. and P. M. Zhai, 2011: Temporal and spatial characteristics of extreme hourly precipitation over eastern China in the warm season. Adv. Atmos. Sci.,28, 1177-1183, doi:10.1007/s00376-011-0020-0.10.1007/s00376-011-0020-0e8c4b593a69b036cacf1dbda66a132e5http%3A%2F%2Fwww.cqvip.com%2FQK%2F84334X%2F201105%2F39695146.htmlhttp://d.wanfangdata.com.cn/Periodical_dqkxjz-e201105017.aspxBased on hourly precipitation data in eastern China in the warm season during 1961 2000,spatial distributions of frequency for 20 mm h-1 and 50 mm h-1 precipitation were analyzed,and the criteria of short-duration rainfall events and severe rainfall events are discussed.Furthermore,the percentile method was used to define local hourly extreme precipitation; based on this,diurnal variations and trends in extreme precipitation were further studied.The results of this study show that,over Yunnan,South China,North China,and Northeast China,the most frequent extreme precipitation events occur most frequently in late afternoon and/or early evening.In the Guizhou Plateau and the Sichuan Basin,the maximum frequency of extreme precipitation events occursin the late night and/or early morning.And in the western Sichuan Plateau,the maximum frequency occursin the middle of the night.The frequency of extreme precipitation (based on hourly rainfall measurements) has increased in mostparts of eastern China,especially in Northeast China and the middle and lower reaches of the Yangtze River,but precipitation has decreased significantly in North China in the past 50 years.In addition,stations inthe Guizhou Plateau and the middle and lower reaches of the Yangtze River exhibit significant increasing trends in hourly precipitation extremes during the nighttime more than during the daytime.
    Zhang Y., Z. Meng, P. Zhu, T. Su, and G. Zhai, 2016: Mesoscale modeling study of severe convection over complex terrain. Adv. Atmos. Sci.,33(11), doi: 10.1007/s00376-016-5221-0.
    Zheng Y., M. Xue, B. Li, J. Chen, and Z. Tao, 2016: Spatial characteristics of extreme rainfall over China with hourly through 24-hour accumulation periods based on national-level hourly rain gauge data. Adv. Atmos. Sci.,33(11), doi: 10.1007/s00376-016-6128-5.4bec197a4008799fd57ded7f20fe2734http%3A%2F%2Ftwister.ou.edu%2Fpapers%2FZhengEtal_JAMC2016.pdfhttp://twister.ou.edu/papers/ZhengEtal_JAMC2016.pdf31 Hourly rainfall measurements of 1919 national-level meteorological stations from 1981 32 through 2012 are used to document, for the first time, the climatology of extreme rainfall at hourly 33 through daily accumulation periods in China. Rainfall at 3-, 6-, 12-, and 24-h periods are 34 constructed through running accumulation from hourly rainfall data at each station with proper 35 quality control. For each station and for each accumulation period, the historical maximum is 36 found, and the corresponding 50-year return values are estimated using the generalized extreme 37 value theory. Based on percentiles of extreme rainfall values among all the stations, standard 38 thresholds separating Grade I, Grade II and Grade III extreme rainfall are established, which 39 roughly correspond to the 70th and 90th percentiles for each of the accumulation periods. 40 The spatial distributions of the two types of extreme rainfall are then examined for different 41 accumulation periods. The spatial distributions of extreme rainfall at hourly through 6-h periods 42 are more similar than those of 12- and 24-h periods. Grade III rainfall is mostly found over South 43 China, the western Sichuan Basin, along the southern and eastern coast lines, in the large river 44 basins and plains. There are similar number of stations with Grade III extreme hourly rainfall 45 north and south of 30鎺砃, but the percentage increases to about 70% south of 30鎺砃 as the 46 accumulation period increases to 24 hours, reflecting richer moisture and more prolonged rain 47 events in southern China. Potential applications of the extreme rainfall climatology and 48 classification standards are suggested at the end.
    Zhu, K. and M. Xue, 2016: Evaluation of WRF-based convection-permitting multi-physics ensemble forecasts over China for the July 21, 2012 Beijing extreme rainfall event. Adv. Atmos. Sci.,33(11), doi: 10.1007/s00376-016-6202-z.
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Preface to the Special Issue on the "Observation, Prediction and Analysis of severe Convection of China" (OPACC) National "973" Project

  • 1. School of Atmospheric Sciences, Nanjing University, Nanjing, China and Center for Analysis and Prediction of Storms and School of Meteorology, University of Oklahoma, Norman OK 73072, USA

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