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CAMS复杂云微物理方案与GRAPES模式耦合的数值试验
Numerical Experiment of the Coupling of CAMS Complex Microphysical Scheme and GRAPES Model
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摘要: CAMS复杂云微物理方案是混合相双参数方案, 包括11个云物理变量和31个云物理过程, 能够同时预报水成物的比质量和数浓度。通过在GRAPES非静力中尺度模式中增加预报量并修改相关程序后, 实现了二者的耦合, 耦合后模式运行稳定。选取2005年8月15—17日我国华北地区一次暴雨过程, 利用耦合后的模式进行48 h模拟试验, 同时还选取了GRAPES模式中其他3个比较复杂的微物理方案进行模拟, 着重分析了降水和水成物分布的模拟结果。研究结果表明: CAMS方案能够模拟出与实测相接近的雨带分布特征, 并且对降水演变的模拟结果与其他方案比较一致, 对暴雨中心位置的模拟有待改进。CAMS方案模拟的水成物垂直分布与其他方案相比具有相似的总体特征, 各相态粒子的量级和分布合理, 不同方案的结果在量值上有所差别。个例分析结果显示出CAMS方案对降水和水成物的分布能够合理描述。今后应通过更多个例进行更为精细的模拟试验, 对新方案进行检验。Abstract: The schemes describing the moist physical process in the meso-scale model include the microphysical scheme and the cumulus parameterization scheme. The rainfall calculated in cumulus parameterization scheme is in subgrid scale and the rainfall calculated in the microphysical scheme calculates is in grid scale. With the improvement of the model resolution, the microphysical scheme has become more and more important in the meso-scale model. More detailed microphysical processes are described in the mixed-phase microphysical scheme, so that it can be used in many researches such as microphysical mechanism of precipitation, the interaction between cloud and radiation, lighting activity of cloud and so on. Therefore, it is very necessary and significant to study and improve the mixed-phase scheme of the meso-scale model. GRAPES (short form of Global/Regional Assimilation and PrEdiction System) is the new generation numerical model system in China. In order to improve the physical processes in GRAPES model, CAMS (Chinese Academy of Meteorological Sciences) complex microphysical scheme is coupled with the meso-scale regional GRAPES system.CAMS complex microphysical scheme is a double-moment mixed-phase scheme. There are 5 kinds of hydrometeors in this scheme which are cloud water, rain water, ice, snow and graupel. The scheme includes 11 prognostic cloud variables. They are the mass content (Qv, Qc, Qr, Qi, Qs, Qg) and number concentration (Nr, Ni, Ns, Ng) and the extent of cloud droplet spectrum. There are 31 microphysical processes in the scheme. Not only the mass content can be predicted but also number concentration of hydrometeors. In this study, new microphysical variables and a new microphysical option are added into GRAPES. A numerical experiment is conducted using the new model. The case simulated is a heavy rainfall happening in North China during August 15—17, 2005. The model is integrated for 48 h with 60 s time step. Three other microphysical schemes are selected to simulate the same case to make a comparison.They are Thompson scheme, WSM6 scheme and NCEPcloud5 scheme. The simulated results of distribution of rainfall and hydrometeors are analyzed. Results are shown as follows. The distribution of rain band simulated by CAMS is similar to the observation and the development of rain band simulated by CAMS is consistent with those of other three microphysical schemes.The center of heavy rainfall simulated needs to be improved.The comparison of the regional average hydrometeors made between CAMS scheme and other three microphysical schemes shows the similar general characteristics. CAMS scheme is able to simulate the hydrometeors in reasonable distribution and value. Due to the different microphysical process in different scheme, the values of hydrometeors of four microphysical schemes are different. Results reveal the good capacity of CAMS scheme in describing cloud and precipitation processes in GRAPES model. The new scheme should be tested through numerical experiments and fine model design in the future.
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Key words:
- microphysical scheme;
- GRAPES model;
- hydrometeor
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图 1 2005年8月16—17日降水实况 (单位: mm)
(a)16日02:00—08:00, (b)16日08:00—14:00, (c)16日14:00—20:00, (d)16日20:00—17日02:00, (e)17日02:00—08:00, (f)17日08:00—14:00, (g)17日14:00—20:00, (h)16日08:00—17日08:00
Fig. 1 Observed rainfall during August 16—17, 2005 (unit:mm)(a)02:00—08:00 on Aug 16, (b)08:00—14:00 on Aug 16, (c)14:00—20:00 on Aug 16, (d)20:00 on Aug 16—02:00 on Aug 17, (e)02:00—08:00 on Aug 17, (f)08:00—14:00 on Aug 17, (g)14:00—20:00 on Aug 17, (h)08:00 on Aug 16—08:00 on Aug 17
图 2 2005年8月16—17日模拟降水分布 (单位: mm)
(a)16日02:00—08:00, (b)16日08:00—14:00, (c)16日14:00—20:00, (d)16日20:00—17日02:00, (e)17日02:00—08:00, (f)17日08:00—14:00, (g)17日14:00—20:00, (h)16日08:00—17日08:00
Fig. 2 Simulated rainfall during August 16—17, 2005 (unit:mm)(a)02:00—08:00 on Aug 16, (b)08:00—14:00 on Aug 16, (c)14:00—20:00 on Aug 16, (d)20:00 on Aug 16—02:00 on Aug 17, (e)02:00—08:00 on Aug 17, (f)08:00—14:00 on Aug 17, (g)14:00—20:00 on Aug 17, (h)08:00 on Aug 16—08: 00 on Aug 17
图 3 2005年8月16日08:00-17日08:00模拟总降水量（单位:mm）
Fig. 3 Simulated rainfall from 08:00 on Aug 16 to 08:00 on Aug 17, 2005(unit:mm)
图 4 2005年8月16日08:00-17日08:00模拟的显示方案降水（a, c, e, g) 和对流参数化降水（b, d, f, h)（单位:mm）
Fig. 4 Simulated grid scale rainfall (a, c, e, g) and subgrid scale rainfall (b, d, f, h) from 08:00 on Aug 16 to 08:00 on Aug 17, 2005(unit:mm)
图 5 不同试验32°~35°N, 106°~115°E区域平均 (a~c) 和35°~42°N, 115°~123°E区域平均 (d~f) 降水率随时间演变
Fig. 5 The simulated precipitation rate of four tests averaged in (32°—35°N, 106°—115°E) (a—c) and (35°—42°N, 115°—123°E)(d—f)
图 6 不同试验32°~35°N, 106°~115°E区域平均 (a) 和35°~42°N, 115°~123°E区域平均 (b) 水成物程长随时间演变
Fig. 6 The simulated hourly hydrometeor water path of four tests averaged in 32°—35°N, 106°—115°E (a) and 35°—42°N, 115°—123°E (b)
图 7 不同试验48 h内32°~35°N, 106°~115°E区域平均的水成物比质量48 h平均垂直分布
Fig. 7 The vertical distribution of mass content of four tests averaged in 32°—35°N, 106°—115°E in 48 h
图 8 exp-C试验的水成物数浓度和云滴谱拓宽度48 h内32°~35°N, 106°~115°E区域平均的垂直分布
(a) 冰晶数浓度和雪数浓度, (b) 雨滴数浓度和霰数浓度, (c) 云滴谱拓宽度
Fig. 8 The vertical distribution of number concentration of exp-C averaged in 32°—35°N, 106°—115°E in 48 h
(a) number concentration of ice and snow, (b) number concentration of rain water and grapel, (c) the broadness of cloud droplet spectrum
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[1] 薛纪善, 陈德辉, 陈贤.新一代气象数值预报模式系统研究开发取得丰硕成果.中国气象科学研究院年报 (2003), 2004: 6-8. http://www.cnki.com.cn/Article/CJFDTOTAL-ZQKN200300002.htm [2] 伍湘君, 金之雁, 黄丽萍, 等. GRAPES模式软件框架与实现.应用气象学报, 2005, 16(4): 539-546. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20050468&flag=1 [3] 楼小凤, 胡志晋, 王鹏云, 等.中尺度模式云降水物理方案介绍.应用气象学报, 2003, 14(增刊): 49-59. http://kns.cnki.net/KCMS/detail/detail.aspx?dbcode=CJFQ&dbname=CJFD2003&filename=YYQX2003S1006&v=MjM1NjNVUkwyZlpPUnRGeXJuVmJ6T1BEVGFkckc0SHRLdnJvOUZZb1I4ZVgxTHV4WVM3RGgxVDNxVHJXTTFGckM= [4] Fu Danhong, Guo Xueliang. A cloud-resolving study on the role of cumulus merger in MCS with heavy precipitation. Adv Atmos Sci, 2006, 27(6) :857-868. http://adsabs.harvard.edu/abs/2006AdAtS..23..857F [5] Chen Shoujun, Kuo Yinghwa, Wang Wei, et al. A modeling case study of heavy rainstorms along the Mei-Yu front. Mon Wea Rev, 1998, 126(9): 2330-2351. doi: 10.1175/1520-0493(1998)126<2330:AMCSOH>2.0.CO;2 [6] Zhu Tong, Zhang Dalin. Numerical simulation of hurricane Bonnie (1998). Part Ⅰ: Eyewall evolution and intensity changes. Mon Wea Rev, 2004, 132(1): 225-241. doi: 10.1175/1520-0493(2004)132<0225:NSOHBP>2.0.CO;2 [7] Zhu Tong, Zhang Dalin. Numerical simulation of hurricane Bonnie (1998). Part Ⅱ: Sensitivity to varying cloud microphysical processes. J Atmos Sci, 2006, 63(1) : 109-126. doi: 10.1175/JAS3599.1 [8] 史月琴, 楼小凤.显式云物理方案的研究进展.气象科技, 2006, 34(5): 513-520. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200605000.htm [9] 楼小凤. MM5模式的新显式云物理方案的建立和耦合及原微物理方案的对比分析.北京:北京大学地球物理系, 2002. [10] 胡志晋, 何观芳.积雨云微物理过程的数值模拟 (一) 微物理模式.气象学报, 1987, 45(4): 467-484. http://www.cnki.com.cn/Article/CJFDTOTAL-QXXB198704011.htm [11] 胡志晋, 严采蘩.层状云微物理过程的数值模拟 (一) 微物理模式.气象科学研究院院刊, 1986, 1(1): 37-52. http://www.cnki.com.cn/Article/CJFDTOTAL-YYQX198601005.htm [12] 孙晶, 楼小凤, 胡志晋, 等.梅雨期暴雨个例模拟及其中小尺度结构特征分析研究.大气科学, 2007, 31(1): 1-18. http://www.cnki.com.cn/Article/CJFDTOTAL-DQXK200701000.htm [13] Reisner J, Rasmussen R M, Bruintjes R T. Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model. Q J R Meteorol Soc, 1998, 124: 1071-1107. doi: 10.1002/(ISSN)1477-870X [14] Hong S Y, Lim J O J. The WRF single-moment 6-Class Microphysics scheme (WSM6).J Meteor Soc Korea, 2006, 42(2): 129-151. http://www.dbpia.co.kr/Journal/ArticleDetail/NODE00937254?q=%5Bproduct%20sound§coldb§2§51§3%5D&Multimedia=0&isFullText=0&specificParam=0&SearchMethod=0 [15] Hong S Y, Dudhia J, Chen S H. A revised approach to ice-microphysical processes for the bulk parameterization of cloud and precipitation.Mon Wea Rev, 2004, 132(1): 103-120. doi: 10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2 -
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