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Mesoscale Modeling Study of Severe Convection over Complex Terrain


doi: 10.1007/s00376-016-5221-0

  • Short squall lines that occurred over Lishui, southwestern Zhejiang Province, China, on 5 July 2012, were investigated using the WRF model based on 1°× 1° gridded NCEP Final Operational Global Analysis data. The results from the numerical simulations were particularly satisfactory in the simulated radar echo, which realistically reproduced the generation and development of the convective cells during the period of severe convection. The initiation of this severe convective case was mainly associated with the uplift effect of mesoscale mountains, topographic convergence, sufficient water vapor, and enhanced low-level southeasterly wind from the East China Sea. An obvious wind velocity gradient occurred between the Donggong Mountains and the southeast coastline, which easily enabled wind convergence on the windward slope of the Donggong Mountains; both strong mid-low-level southwesterly wind and low-level southeasterly wind enhanced vertical shear over the mountains to form instability; and a vertical coupling relation between the divergence on the upper-left side of the Donggong Mountains and the convergence on the lower-left side caused the convection to develop rapidly. The convergence centers of surface streams occurred over the mountain terrain and updrafts easily broke through the lifting condensation level (LCL) because of the strong wind convergence and topographic lift, which led to water vapor condensation above the LCL and the generation of the initial convective cloud. The centers of surface convergence continually created new convective cells that moved with the southwest wind and combined along the Donggong Mountains, eventually forming a short squall line that caused severe convective weather.
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  • Anderson H. A., 2010: Characteristics of decaying storms during lightning cessation at Kennedy Space Center and Cape Canaveral Air Force Station. M.S. thesis, Department of Meteorology, Florida State University, 75 pp.10.1002/qua.10339b9b5ff4b371cdcca75ddc42d2855430ehttp%3A%2F%2Fwww.researchgate.net%2Fpublication%2F254670921_Characteristics_of_Decaying_Storms_During_Lightning_Cessation_at_Kennedy_Space_Center_and_Cape_Canaveral_Air_Force_Stationhttp://www.researchgate.net/publication/254670921_Characteristics_of_Decaying_Storms_During_Lightning_Cessation_at_Kennedy_Space_Center_and_Cape_Canaveral_Air_Force_StationABSTRACT Improved knowledge of thunderstorm behavior near the end of its lifecycle is essential to improving the prediction of lightning cessation. This study documents the characteristics of decaying storms near the end of their lightning activity at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). Total lightning data were obtained by combining information from the Lightning Detection and Ranging (LDAR) network with the Cloud-to-Ground-Surveillance System (CGLSS) and the National Lightning Detection Network (NLDN). The lightning data were used in conjunction with WSR-88D radar data and Rapid Update Cycle (RUC) model analyses. The study focuses on a dataset of 116 isolated unicellular and multicellular storms during the warm-seasons (May-September) of 2000-2005. Twenty of the 116 storms were tracked through lightning cessation using the K-Means storm clustering and tracking algorithm within the Warning Decision Support System – Integrated Information (WDSS-II). This tracking yielded time-series of radar-derived, RUC-derived, and lightning parameters. Flash characteristics of the 116 storms showed trends during storm growth and dissipation; however, none exhibited clear relationships with the final flash. Although most storms experienced gradually decaying flash rates until cessation, two other cessation behaviors also were observed, making flash activity an unreliable indicator of cessation. Trends in composite reflectivity, reflectivity at three temperatures crucial to storm electrification (i.e., 0C, -10C, -20C), storm thickness of 30 dBZ above -10C, and vertical gradients of reflectivity were analyzed for 20 storms during the 8 min period prior to cessation to determine if any indicated imminent cessation. Results showed substantial variability in the decaying storms. Although these parameters decreased in most storms during the 8 min period, some increased. Distributions of the parameters at the last flash also were considered, but no clearly preferred value was evident at the last flash. Neither the inversion of lightning initiation criteria (e.g., 40 dBZ at -10C) nor the descent of 45 dBZ below -10C were found to be a useful indicator of cessation. Previously-documented lightning “bubbles” of LDAR sources were observed and were consistent with pulses in the intensifying updrafts. The last lightning “bubble” signatures were found to precede lightning cessation by ~35 min.
    Barthlott C., D. J. Kirshbaum, 2013: Sensitivity of deep convection to terrain forcing over Mediterranean islands. Quart. J. Roy. Meteor. Soc., 139( 676), 1762- 1779.10.1002/qj.2089c31707762bd234998b3205a107cab921http%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1002%2Fqj.2089%2Fabstracthttp://onlinelibrary.wiley.com/doi/10.1002/qj.2089/abstractThe influence of mountainous islands on the initiation of deep convection is investigated using the Consortium for Small-scale Modeling (COSMO) model. A case study and sensitivity analysis is performed for 26 August 2009, when moist convection occurred over both Corsica and Sardinia islands in the western Mediterranean Sea. Sensitivity runs with systematically modified topography are explored to evaluate the relative importance of the landea contrast and the terrain height for convection initiation. Whereas no island precipitation is simulated when the islands are completely removed, all simulations that represent these land surfaces develop convective precipitation. Although convection initiates progressively earlier in the day over taller islands, the precipitation rates and accumulations do not show a fixed relationship with terrain height. This is due to the competing effects of different physical processes. Firstly, whereas the forcing for low-level ascent increases over taller islands the boundary-layer moisture supply decreases, which diminishes the conditional instability and precipitable water. Secondly, whereas taller islands enhance the inland propagation speeds of sea-breeze fronts they also block these fronts mechanically and prevent them from reaching the island interior. As a result, the island precipitation is rather insensitive to island terrain height except for one particular case in which the island precipitation increases considerably due to an optimal superposition of the sea breeze and upslope flow. Comparing the two islands, convective precipitation develops earlier over Corsica due to its increased terrain height and reduced convective inhibition. However, precipitation amounts are substantially larger over Sardinia, where a stronger landea contrast gives rise to a more intense and organized line of sea-breeze convergence. These results demonstrate the complexity of interactions between sea breezes and orography and reinforce that an adequate representation of detailed topographic features is necessary to account for thermally induced wind systems that initiate deep convection.
    Barthlott C., J. W. Schipper, N. Kalthoff, B. Adler, C. Kottmeier, A. Blyth, and S. Mobbs, 2010: Model representation of boundary-layer convergence triggering deep convection over complex terrain: A case study from COPS. Atmos. Res., 95( 2-3), 172- 185.10.1016/j.atmosres.2009.09.010b2e0b6c4a3722dd377517505125329f2http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0169809509002671http://www.sciencedirect.com/science/article/pii/S0169809509002671An isolated thunderstorm from the Convective and Orographically-induced Precipitation Study in southwest Germany and east France in 2007 is analyzed. On July 15, deep convection developed east of the Black Forest crest, although convective available potential energy (CAPE) was only moderate and convective inhibition (CIN) was high. Data analysis revealed that convection was triggered by updrafts penetrating the capping inversion of the planetary boundary layer as a result of low-level convergence. Although the numerical weather prediction model COSMO-DE of the German Weather Service (2.8km grid resolution) simulated a convergence line and the evolution of a line of low clouds in good agreement with radar and satellite observations, no precipitating deep convection developed from this line of clouds. For an improved representation of orographic effects, simulations with a finer grid resolution of 1km were performed. Despite almost optimal conditions, i.e. moderate amount of CAPE and almost vanishing CIN, the updrafts required to overcome CIN were not reached in both model configurations. Although both simulations did not initiate deep convection, the results suggest that in an air mass convection situation without mid-tropospheric forcing, the simulated location and timing of convergence lines with coexistent large values of CAPE and low values of CIN can be used as diagnostic parameters for deep convection nowcasting.
    Byers H. R., R. R. Braham, 1949: The Thunderstorm: Report of the Thunderstorm Project. U. S. Government Printing Office,287 pp.500a956b31e57acdd43161b6b3065e25http%3A%2F%2Fci.nii.ac.jp%2Fncid%2FBA75220625http://ci.nii.ac.jp/ncid/BA75220625
    Chen F., J. Dudhia, 2001: Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part II: Preliminary model validation. Mon. Wea. Rev., 129, 587- 604.10.1175/1520-0493(2001)1292.0.CO;25315527203b9a4a6186814b1238287d5http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2001MWRv..129..587Chttp://adsabs.harvard.edu/abs/2001MWRv..129..587CNot Available
    Chen M., B. P. Fu, and Q. Yu, 1995: Influence of topography on storm rainfall. Acta Geographica Sinica, 50( 3), 256- 263. (in Chinese)0694218c8d99c27ade1354816abbcd46http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTotal-DLXB503.007.htmhttp://en.cnki.com.cn/Article_en/CJFDTotal-DLXB503.007.htmIn this article. we analyse the influence of complex mountain surface layer on the formation and distribution of storm rainfall. The results show that topographically induced convergence and upward motion is one of the most important mechanism that may cause and strengthen storm rainfall. In moist regions, precipitation of storm rainfall caused by topography is much more than in less moist regions.In the humid region. leeward slope is usually dry with little or no rainfall, that is the so called rain shadow. In the semi-humid region with strong stable air passing over niountain. there is a high frenquency of leeward wave storm rainfall. In this srtuation. leeward wave storm rainfall is about eight times of that of windword slope. In the arid region. local gale may occur on leeward slope with little or no rainfall.Local thermal circulation and land-water circulation may cause cyclonic convergence with violent convective motion which can motivate nocturnal storm rainfall in the semi-humid region. In humid region, however. it may cause storm rainfall which is very strong but only lasts a short time.This kind of storm rainfall is dangerous but difficult to predict.In the mountain valleys. the moist warm air flows more paralell to the valley. storm rainfall is more easy to form or become strong. On the contrary. with air flow direction perpendicular to valley direction, the valley will be filled by dry and relatively hot air with no rainfall.
    Hong S. Y., J. O. J. Lim, 2006: The WRF single-moment 6-class microphysics scheme (WSM6). Journal of the Korean Meteorological Society, 42( 2), 129- 151.7308c59e0fe08d8147ff5b2869261e63http%3A%2F%2Fwww.dbpia.co.kr%2FJournal%2FArticleDetail%2F773025http://www.dbpia.co.kr/Journal/ArticleDetail/773025This study examines the performance of the Weather Research and Forecasting (WRF)-Single-Moment- Microphysics scheme (WSMMPs) with a revised ice-microphysics of the Hong et al. In addition to the simple (WRF Single-Moment 3-class Microphysics scheme; WSM3) and mixed-phase (WRF Single-Moment 5-class Microphysics scheme; WSM5) schemes of the Hong et al., a more complex scheme with the inclusion of graupel as another predictive variable (WRF Single-Moment 6-class Microphysics scheme; WSM6) was developed. The characteristics of the three categories of WSMMPs were examined for an idealized storm case and a heavy rainfall event over Korea. In an idealized thunderstorm simulation, the overall evolutionary features of the storm are not sensitive to the number of hydrometeors in the WSMMPs; however, the evolution of surface precipitation is significantly influenced by the complexity in microphysics. A simulation experiment for a heavy rainfall event indicated that the evolution of the simulated precipitation with the inclusion of graupel (WSM6) is similar to that from the simple (WSM3) and mixed-phase (WSM5) microphysics in a low-resolution grid; however, in a high-resolution grid, the amount of rainfall increases and the peak intensity becomes stronger as the number of hydrometeors increases.
    Janjić, Z. I., 1994: The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122( 5), 927- 945.10.1175/1520-0493(1994)1222.0.CO;221adf0bb81ffbc01b483730fef95b787http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1994MWRv..122..927Jhttp://adsabs.harvard.edu/abs/1994MWRv..122..927JAbstract The step-mountain eta model has shown a surprising skill in forecasting severe storms. Much of the credit for this should be given to the Betts and Miller (hereafter referred to as BM) convection scheme and the Mellor-Yamada (hereafter referred to as MY) planetary boundary layer (PBL) formulation. However, the eta model was occasionally producing heavy spurious precipitation over warm water, as well as widely spread light precipitation over oceans. In addition, the convective forcing, particularly the shallow one, could lead to negative entropy changes. As the possible causes of the problems, the convection scheme, the processes at the air-water interface, and the MY level 2 and level 2.5 PBL schemes were reexamined. A major revision of the BM scheme was made, a new marine viscous sublayer scheme was designed, and the MY schemes were retuned. The deep convective regimes are postulated to be characterized by a parameter called “cloud efficiency.” The relaxation time is extended for low cloud effic...
    Kain J. S., J. M. Fritsch, 1993: Convective parameterization for mesoscale models: the Kain-Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, K. A. Emanuel and D. J. Raymond, Eds., Amer. Meteor. Soc., 165- 170.10.1080/02571862.2012.6883739e3e4062-0132-4ba7-bd9c-11f872ba8e8ba32d742d9455dfe97c522bdb7157e896http%3A%2F%2Flink.springer.com%2F978-1-935704-13-3refpaperuri:(da7138f9cbe1db3d8157501c2e48f99d)http://link.springer.com/978-1-935704-13-3stress was aggravated by simultaneous drought stress.
    Lascaux F., E. Richard, C. Keil, and O. Bock, 2004: Impact of the MAP reanalysis on the numerical simulation of the MAP-IOP2a convective system. Meteor. Z., 13( 1), 49- 54.10.1127/0941-2948/2004/0013-0049c1afb3813fe0edc9f1602eab9679a992http%3A%2F%2Fwww.ingentaconnect.com%2Fcontent%2Fschweiz%2Fmz%2F2004%2F00000013%2F00000001%2Fart00008http://www.ingentaconnect.com/content/schweiz/mz/2004/00000013/00000001/art00008Numerical simulations of the convective system observed during the MAP IOP2a have been performed with the Meso-NH mesoscale model, using a threefold nesting technique with horizontal mesh-sizes of 32, 8 and 2 km. The reference experiment initialized from the operational ECMWF analysis of 17 September 1999 12 UTC succeeds reasonably well in initiating the convective line over the Alpine foothills and reproducing its propagation towards the East. The sensitivity of these results to the reanalysis products is investigated. In the ECMWF MAP reanalysis, the lower atmosphere above Northern Italy is found considerably drier than in the operational analysis. As a consequence, convection is almost entirely inhibited in the mesoscale simulations based upon the reanalysis. Different sensitivity experiments further highlight the strong dependence of the mesoscale results upon the initial moisture fields. Für das konvektive System, das w01hrend MAP IOP2a auftrat, wurden numerische Simulationen durchgeführt mit Hilfe des Mesoskalen-Models Meso-NH in Dreifachnestung mit horizontalen Gitterweiten von 32, 8 und 2 km. Ein Kontrollexperiment, das mit der operationellen ECMWF Analyse am 17. September 1999, 12 UTC, initialisiert wurde, reproduziert die linienartige Konvektion am Alpenrand samt ihrer ostw01rts Verlagerung zufriedenstellend. Die Abh01ngigkeit dieser Befunde von den Ergebnissen der MAP Re-Analyse am ECMWF wird untersucht. Es zeigt sich, dass die untere Atmosph01re über Norditalien deutlich trockener ist als in der operationellen Anaylse. Folglich wird in Simulationen, die auf der Re-Analyse fu08en, Konvektion fast v02llig unterdrückt. Weitere Sensitivit01tsexperimente unterstreichen die starke Abh01ngigkeit der mesoskaligen Ergebnisse von den Feuchtefeldern zum Anfangszeitpunkt.
    Li Y. Y., W. Huang, and Zhao, J. Z., 2007: Roles of mesoscale terrain and latent heat release in typhoon precipitation: A numerical case study. Adv. Atmos. Sci.,24(1), 35-43, doi: 10.1007/s00376-007-0035-8.10.1007/s00376-007-0035-8c74eebbd8716a2adbdfb41973c500c6bhttp%3A%2F%2Fwww.cqvip.com%2FMain%2FDetail.aspx%3Fid%3D23633563http://d.wanfangdata.com.cn/Periodical_dqkxjz-e200701004.aspx
    May P. T., A. Ballinger, 2007: The statistical characteristics of convective cells in a mnsoon regime (Darwin, Northern Australia). Mon. Wea. Rev., 135( 1), 82- 92.10.1175/MWR3273.1bf2cb64d80b8e5116f355bcc258d8409http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D1299020http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1299020A season of operational cell and track data from Darwin, Australia, has been analyzed to explore the statistical characteristics of the convective cell heights. The statistics for the monsoon and break regimes are significantly different with the break season cells being higher for a given reflectivity threshold. The monsoon cells produce more rain, but there are fewer intense cells and there is a much larger contribution from stratiform rain. The monsoon cells are also slightly larger, but shorter lived than the breaks. The shorter lifetime may reflect a more rapid transition to a longer-lived stratiform character. The monsoon regime is shown to be associated with large-scale ascent and higher humidity that may lead to more frequent, but weaker cells. Within regimes, the subset of intense cells generally reach near the tropopause or overshoot. However, there is little evidence in the data for a multimodal distribution of cell heights, except perhaps for the intense monsoon cases. Instead, the picture is a continuous distribution of cell heights with the peak of the distribution shifting to higher values as the distributions are conditioned on higher reflectivity.
    Mecikalski J. R., K. M. Bedka, S. J. Paech, and L. A. Litten, 2008: A statistical evaluation of GOES cloud-top properties for nowcasting convective initiation. Mon. Wea. Rev., 136( 12), 4899- 4914.10.1175/2008MWR2352.1a4065047d913ab65c41d3f759d4fa693http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2008MWRv..136.4899Mhttp://adsabs.harvard.edu/abs/2008MWRv..136.4899MThe goal of this project is to validate and extend a study by Mecikalski and Bedka that capitalized on information the Geostationary Operational Environmental Satellite (GOES) instruments provide for nowcasting (i.e., 0–1-h forecasting) convective initiation through the real-time monitoring of cloud-top properties for moving cumuli. Convective initiation (CI) is defined as the first occurrence of a ≥35-dBradar echo from a cumuliform cloud. Mecikalski and Bedka’s study concluded that eight infrared GOES-based “interest fields” of growing cumulus clouds should be monitored over 15–30-min intervals toward predicting CI: the transition of cloud-top brightness temperature to below 0°C, cloud-top cooling rates, and instantaneous and time trends of channel differences 6.5–10.7 and 13.3–10.7 m. The study results are as follows: 1) measures of accuracy and uncertainty of Mecikalski and Bedka’s algorithm via commonly used skill scoring procedures, and 2) a report on the relative importance of each interest field to nowcasting CI using GOES. It is found that for nonpropagating convective events, the skill scores are dependent on which CI interest fields are considered per pixel and are optimized when three–four fields are met for a given 1-km GOES pixel in terms of probability of detection, and threat and Heidke skill scores. The lowest false-alarm rates are found when one field is used: that associated with cloud-top glaciation 30 min prior to CI. Subsequent recommendations for future research toward improving Mecikalski and Bedka’s study are suggested especially with regard to constraining CI nowcasts when inhibiting factors are present (e.g., capping inversions).
    Mei\ssner, C., N. Kalthoff, M. Kunz, G. Adrian, 2007: Initiation of shallow convection in the Black Forest mountains. Atmos. Res., 86( 1), 42- 60.10.1016/j.atmosres.2007.03.003c38947ea789d272225e07aff1921acf8http%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS016980950700049Xhttp://www.sciencedirect.com/science/article/pii/S016980950700049XThe temporal evolution and spatial distribution of shallow convection over complex terrain are examined by observational data and compared with model calculations using the Local Model of the Deutscher Wetterdienst with 2.8 km (LM2.8) and 7 km horizontal resolution (LM7). For this, the 01 June 2002 was chosen from the VERTIKATOR (Vertical Exchange and Orography) measurement campaign performed in the northern Black Forest mountains. On this day shallow convection was restricted to the mountainous regions. This can be explained by the fact that the conditions of initiation of convection, i.e. that the near-surface temperature reaches the convective temperature, are only met at upper sites of the mountains. Additionally, the initiation of convection over the mountain ridges is enhanced by up-slope and up-valley winds, generating convergence zones over the ridges. The resulting vertical lifting supports convective processes. The areas of convergence primarily comply with the areas of convection, as confirmed by satellite images from NOAA. The LM2.8 and LM7 simulations do not show significant differences concerning the large-scale meteorological conditions. However, LM2.8 better reproduces the near-surface temperature and humidity at most sites leading to a more realistic representation of convective clouds. Another important difference concerns the near-surface winds, that is only LM2.8 reproduces the main characteristics of the thermally induced wind systems which prove to support convection. Convergence zones and upward lifting is simulated by LM2.8 above the mountain crests resulting in the accompanied formation of clouds. The onset and position of simulated convective clouds generally fit with the observations. In contrast to LM2.8, LM7 simulates clouds above the transition zone between the northern Black Forest and the Rhine valley, where the large-scale easterly flow converges with the channelled northerly wind over the Rhine valley, that is, the position does not agree with the observations.
    Purdom J. F. W., K. Marcus, 1982: Thunderstorm trigger mechanisms over the southeast U. S. Preprints, 12th Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., 487- 488.
    Raymond D., M. Wilkening, 1980: Mountain-induced convection under fair weather conditions. J. Atmos. Sci., 37( 12), 2693- 2706.10.1175/1520-0469(1980)0372.0.CO;2e90c17ac3056f7d4419ea79bcef51bd7http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1980JAtS...37.2693Rhttp://adsabs.harvard.edu/abs/1980JAtS...37.2693RMeasurements of the structure of dry convection over an isolated mountain range heated by the sun are presented. Filter techniques are used to deduce those scales of motion of significance to the circulation. A two-scale process is observed in which a toroidal, heat island circulation 6520 km in diameter is driven by 3–4 km convective eddies. Large negative heat fluxes are found in the upper part of the convective core over the mountains.
    Roe G. H., 2005: Orographic precipitation. Annual Review of Earth and Planetary Sciences, 33, 645- 671.
    Rudari R., D. Enteldaabi, and G. Roth, 2004: Terrain and multiple-scale interactions as factors in generating extreme precipitation events. J. Hydrometeor., 5( 3), 390- 404.10.1175/1525-7541(2004)0052.0.CO;2584da044fff7ec5c6e7dd6e49585553ahttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2004jhyme...5..390rhttp://adsabs.harvard.edu/abs/2004jhyme...5..390rAbstract The Mediterranean region is often affected by flooding and landslides due to heavy precipitation events. These events have been the subject of specific interest because they represent complex interaction of synoptic-scale upper-level steering flows and local topographic barriers. In the present work, data from a dense network of surface precipitation gauges over northern Italy and a global atmospheric analysis at a coarser scale are combined to develop a multiscale diagnostic model of the phenomenon. Composite maps are formed based on departures from climatology and standard deviation of sea level pressure, 500-hPa geopotential, wind, and water vapor flux. A diagnostic model is built based on the evidence that shows the spawning of secondary mesoscale features in the steering synoptic flow. The mesoscale features draw moisture and energy from local sources and cause extreme precipitation events over adjoining areas. The primary trough system steering the flow often originates in the North Sea and...
    Smith R. B., 1979: The influence of mountains on the atmosphere. Advances in Geophysics, 21, 87- 230.698ce93fbbecc0a30c85fd103b73130chttp%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fpii%2FS0065268708602629http://www.sciencedirect.com/science/article/pii/S0065268708602629The chapter reviews the meteorological phenomena that are associated with topography. The study of airflow past mountains is complicated by the wide range of scales that must be considered. The ratios of the mountain width to each of the natural length scales are important in determining the physical regime of the flow. This idea is emphasized in the chapter by treating the effects of boundary layers and buoyancy. The theory of two-dimensional mountain waves with the help of its governing equations is presented and the observations of mountain waves are presented. The chapter also examines the influence of the boundary layer on mountain flows and slope winds and mountain and valley winds. It considers the perturbation to the wind flow caused by a mountain of intermediate scale where the rotation of the Earth cannot be neglected. For this the flow near mesoscale and synoptic-scale mountains, quasi-geostrophic flow over a mountain, the effect of inertia on the flow over mesoscale mountains, and theories of lee cyclogenesis are discussed. Finally the chapter describes planetary-scale mountain waves; a vertically integrated model of topographically forced planetary waves; the vertical structure of planetary waves; models of stationary planetary waves allowing meridional propagation and lateral; and variation in the background wind.
    Tao S. Y., 1980: Heavy Rainfalls in China. Science Press, 225pp. (in Chinese)
    Toth J. J., R. H. Johnson, 1985: Summer surface flow characteristics over Northeast Colorado. Mon. Wea. Rev., 113( 9), 1458- 1469.10.1175/1520-0493(1985)1132.0.CO;28377a8d5ff89ae272c6091593e6d4c93http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1985MWRv..113.1458Thttp://adsabs.harvard.edu/abs/1985MWRv..113.1458TAbstract Surface wind data from the program for Regional Observing and Forecasting Services (PROFS) have been analyzed to investigate the diurnal wind flow pattern over the broad drainage are of the South Platte River in northeast Colorado. A consistent diurnal pattern appears in monthly averages as well as on most undisturbed individual days, and is similar to the classic descriptions of mountain-valley wind flows. It is observed that rather than occurring simultaneously at all elevations, downslope-to-upslope and upslope-to-downslope surface flow transitions along the Front Range of northeast Colorado begin near the foothills of the Rocky Mountains and propagate eastward across the plains. During the summer months, local confluence is found at midday along major east-west ridges in the region (e.g., Cheyenne Ridge and Palmer Lake Divide). Consequently, in addition to the north–south Continental Divide, these east–west ridges are preferred regions for initial afternoon thunderstorm development The late a...
    Weckwerth T. M., 2000: The effect of small-scale moisture variability on thunderstorm initiation. Mon. Wea. Rev., 128( 12), 4017- 4030.10.1175/1520-0493(2000)1292.0.CO;2ecae4ececa2347a1ffd4b7ff2cb6ec70http%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F2000mwrv..128.4017whttp://adsabs.harvard.edu/abs/2000mwrv..128.4017wObservations during the Convection and Precipitation/Electrification (CaPE) project illustrate that horizontal convective rolls are capable of providing sufficient forcing to initiate free moist convection. Rolls occurred on the majority of days during CaPE but on only some of those days were they able to trigger thunderstorms. This study was undertaken to ascertain the difference between the two types of roll days: the storm days and the no-storm days. All obvious sounding parameters were examined: stability parameters, midlevel moisture, and vertical wind shear. None of them showed a difference between the storm and no-storm days. This is not surprising in light of recent work showing that soundings within rolls are not representative of the environmental stability unless they happen to be launched into roll updraft branches. This is due to the upward transport of warm, moist air in the roll updraft regions atop which cloud streets and sometimes thunderstorms form. Numerous other parameters examined were also fruitless in identifying any difference between the days. These included surface station measurements, cell motion relative to roll updraft locations, surface topography, and roll circulation strength and depth. The only useful predictor was obtained by modifying the soundings using aircraft data as they were flying across the rolls and sampling moisture contained within the roll updraft branches. Using these roll updraft moisture measurements to recalculate sounding stability parameters provided an effective means of predicting thunderstorm formation.
    Weckwerth T. M., L. J. Bennett, L. J. Miller, J. Van Baelen, P. Di Girolamo, A. M. Blyth, and T. J. Hertneky, 2014: An observational and modeling study of the processes leading to deep, moist convection in complex terrain. Mon. Wea. Rev., 142( 8), 2687- 2708.10.1175/MWR-D-13-00216.18e91d84dd633e7a4a28e4d9bee4c77cchttp%3A%2F%2Fconnection.ebscohost.com%2Fc%2Farticles%2F97319535%2Fobservational-modeling-study-processes-leading-deep-moist-convection-complex-terrainhttp://connection.ebscohost.com/c/articles/97319535/observational-modeling-study-processes-leading-deep-moist-convection-complex-terrainAbstractA case study of orographic convection initiation (CI) that occurred along the eastern slopes of the Vosges Mountains in France on 6 August 2007 during the Convective and Orographically-Induced Precipitation Study (COPS) is presented. Global positioning system (GPS) receivers and two Doppler on Wheels (DOW) mobile radars sampled the preconvective and storm environments and were respectively used to retrieve three-dimensional tomographic water vapor and wind fields. These retrieved data were supplemented with temperature, moisture, and winds from radiosondes from a site in the eastern Rhine Valley. High-resolution numerical simulations with the Weather Research and Forecasting (WRF) Model were used to further investigate the physical processes leading to convective precipitation.This unique, time-varying combination of derived water vapor and winds from observations illustrated an increase in low-level moisture and convergence between upslope easterlies and downslope westerlies along the eastern slo...
    Wilson J. W., W. E. Schreiber, 1986: Initiation of convective storms at radar-observed boundary-layer convergence lines. Mon. Wea. Rev., 114( 12), 2516- 1536.10.1175/1520-0493(1986)1142.0.CO;27bbb5251b6fddec45bac08b7c7d2e2fahttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1986MWRv..114.2516Whttp://adsabs.harvard.edu/abs/1986MWRv..114.2516WAbstract The origin of 653 convective storms occurring over a 5000 km2 area immediately east of the Colorado Rocky Mountains from 18 May to 15 August 1984 was examined. Seventy-nine percent of the 418 storms that initiated within the study area occurred in close proximity to radar-observed boundary-layer convergence lines. This percentage increased to 95% when only the more intense storms (BZe) were considered. Colliding convergence lines initiated new storms or intensified existing storms in 71% of the cases. A new storm took a median time of 24 min to grow to 30 dBZ following line collision. The convergence lines ranged in length between ten and several hundred kilometers. Both radar and mesonet stations indicated that the primary convergence was concentrated in a zone 0.5 to 5 km in width. These lines were characterized on Doppler radar as thin lines of enhanced reflectivity between 0 and 20 dBZe and as a line of strong radial or azimuthal gradient in Doppler velocity. These lines were observed ev...
    Xu X., Q. W. Wang, and Y. Wang, 2010: On the contribution of upslope precipitation to the observational precipitation over southeastern China. Journal of Nanjing University (Natural Sciences), 46( 6), 625- 630. (in Chinese)10.3788/gzxb20103906.0998d8e5f0220291b4f6815875519a7939f4http%3A%2F%2Fen.cnki.com.cn%2FArticle_en%2FCJFDTOTAL-njdz201006004.htmhttp://en.cnki.com.cn/Article_en/CJFDTOTAL-njdz201006004.htmPossible contribution of upslope precipitation to the observational precipitation over southeastern China is studied using the daily precipitation data of 84 stations and 0.5°×0.5° topography data.The reanalysis datasets of wind,temperature and humidity with a resolution of 20 km×20 km from Japan Meteorological Agency are used to calculate the upslope precipitation.The results show that upslope precipitation has the largest contribution to the observational precipitation in the northern part of southeastern China,while it is much smaller in the central region.The meridional distribution of upslope precipitation in the observational precipitation is in good agreement with that of topography gradient,indicating the notable influence of topography on the precipitation over southeastern China.
    Yue C. J., S. T. Gao, L. Liu, and X. F. Li, 2005: A diagnostic study of the asymmetric distribution of rainfall during the landfall of typhoon Haitang (2005). Adv. Atmos. Sci.,32(10), 1419-1430, doi: 10.1007/s00376-015-4246-0.10.1007/s00376-015-4246-0118d8fdbf47c845ab4aa5bbfa4c6f4c5http%3A%2F%2Fwww.cqvip.com%2FQK%2F84334X%2F201510%2F665874442.htmlhttp://d.wanfangdata.com.cn/Periodical/dqkxjz-e201510009The precipitation during landfall of typhoon Haitang(2005) showed asymmetric structures(left side/right side of the track). Analysis of Weather Research and Forecasting model simulation data showed that rainfall on the right side was more than 15 times stronger than on the left side. The causes were analyzed by focusing on comparing the water vapor flux,stability and upward motion between the two sides. The major results were as follows:(1) Relative humidity on both sides was over80%,whereas the convergence of water vapor flux in the lower troposphere was about 10 times larger on the right side than on the left side.(2) Both sides featured conditional symmetric instability [MPV(moist potential vorticity) 0],but the right side was more unstable than the left side.(3) Strong(weak) upward motion occurred throughout the troposphere on the right(left) side. The Q vector diagnosis suggested that large-scale and mesoscale forcing accounted for the difference in vertical velocity. Orographic lift and surface friction forced the development of the asymmetric precipitation pattern. On the right side,strong upward motion from the forcing of different scale weather systems and topography caused a substantial release of unstable energy and the transportation of water vapor from the lower to the upper troposphere,which produced torrential rainfall. However,the above conditions on the left side were all much weaker,which led to weaker rainfall. This may have been the cause of the asymmetric distribution of rainfall during the landfall of typhoon Haitang.
    Zhang G. J., 2003: Roles of tropospheric and boundary layer forcing in the diurnal cycle of convection in the U. S. southern great plains. Geophys. Res. Lett., 30( 24), 2281.10.1029/2003GL018554fb9f519d002557e4317934ef56f9c08ahttp%3A%2F%2Fonlinelibrary.wiley.com%2Fdoi%2F10.1029%2F2003GL018554%2Fabstracthttp://onlinelibrary.wiley.com/doi/10.1029/2003GL018554/abstract[1] This study examines the roles of the tropospheric large-scale forcing, surface sensible and latent heat fluxes and convective inhibition in the diurnal variation of convection in the U.S. Southern Great Plains using data from the Atmospheric Radiation Measurement program. It is shown that the diurnal variation of the tropospheric large-scale forcing has a strong in-phase relationship with convection, whereas the diurnal variations of surface sensible and latent heat fluxes as well as the thermodynamic properties of the near-surface air are nearly out of phase with that of convection. Both the single column version and the full global model of the NCAR CCM3 are used to test the roles of the tropospheric and boundary layer forcing in the observed diurnal variation of convection. When convection is parameterized based on the tropospheric large-scale forcing, the diurnal variation of convection is in good agreement with the observations.
    Ziegler C. L., T. J. Lee, and R. A. Pielke, 1997: Convective initiation at the dryline: A modeling study. Mon. Wea. Rev., 125( 6), 1001- 1026.10.1175/1520-0493(1997)1252.0.CO;22d2d7c48669e34103f397cb7f43591aehttp%3A%2F%2Fadsabs.harvard.edu%2Fabs%2F1997MWRv..125.1001Zhttp://adsabs.harvard.edu/abs/1997MWRv..125.1001ZAbstract A nonhydrostatic, three-dimensional version of the Colorado State University Regional Atmospheric Modeling System (CSU-RAMS) is used to deduce the processes responsible for the formation of drylines and the subsequent initiation of deep, moist dryline convection. A range of cumuliform cloud types are explicitly simulated along drylines on 15, 16, and 26 May 1991 in accordance with observations. In the simulations, narrow convergence bands along the dryline provide the lift to initiate deep moist convection. The thermally direct secondary convective boundary layer (CBL) circulations along the dryline are frontogenetic and solenoidally forced. Maximum updrafts reach 5 m s611 and the bands are 3–9 km wide and 10–100 km or more in length. The updrafts penetrate and are decelerated by the overlying stable air above the CBL, reaching depths of about 2000 m in the cases studied. Moisture convergence along the mesoscale updraft bands destabilizes the local sounding to deep convection, while simultaneously...
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Manuscript received: 12 October 2015
Manuscript revised: 17 July 2016
Manuscript accepted: 08 August 2016
通讯作者: 陈斌, bchen63@163.com
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Mesoscale Modeling Study of Severe Convection over Complex Terrain

  • 1. Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou 310007, China
  • 2. Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100080, China

Abstract: Short squall lines that occurred over Lishui, southwestern Zhejiang Province, China, on 5 July 2012, were investigated using the WRF model based on 1°× 1° gridded NCEP Final Operational Global Analysis data. The results from the numerical simulations were particularly satisfactory in the simulated radar echo, which realistically reproduced the generation and development of the convective cells during the period of severe convection. The initiation of this severe convective case was mainly associated with the uplift effect of mesoscale mountains, topographic convergence, sufficient water vapor, and enhanced low-level southeasterly wind from the East China Sea. An obvious wind velocity gradient occurred between the Donggong Mountains and the southeast coastline, which easily enabled wind convergence on the windward slope of the Donggong Mountains; both strong mid-low-level southwesterly wind and low-level southeasterly wind enhanced vertical shear over the mountains to form instability; and a vertical coupling relation between the divergence on the upper-left side of the Donggong Mountains and the convergence on the lower-left side caused the convection to develop rapidly. The convergence centers of surface streams occurred over the mountain terrain and updrafts easily broke through the lifting condensation level (LCL) because of the strong wind convergence and topographic lift, which led to water vapor condensation above the LCL and the generation of the initial convective cloud. The centers of surface convergence continually created new convective cells that moved with the southwest wind and combined along the Donggong Mountains, eventually forming a short squall line that caused severe convective weather.

1. Introduction
  • The conditions that trigger severe convection over mountainous terrain are highly complex, particularly over mesoscale terrain. In recent decades, the trigger and enhancement mechanisms of orographic precipitation have been identified as thermodynamic factors as well as dynamical and orographic factors such as shape and size (Smith, 1979; Roe, 2005). The effect of mountainous topography plays a very important role for weather in China. (Tao, 1980) reported topography to have a considerable influence on the triggering and growth of heavy rain in China. (Chen et al., 1995) analyzed the impact of mountainous terrain on heavy rain under various natural conditions and reported that the influence of heavy rain to vary widely among different terrain types with the same geographical background. Topography-forced lifting and topographic convergence are important mechanisms for the triggering and growth of heavy rain in mountainous regions, whereas topographic divergence and downdraft areas correspond to low-frequency regions. Many researchers have used numerical models to study the impact of topography on rainfall in China, in which the effect of the terrain on precipitation under particular weather conditions has been considered (Yue et al., 2005; Li et al., 2007).

    The thermally driven local wind system in mountainous areas also plays a very important role in the triggering of convection (Raymond and Wilkening, 1980; Toth and Johnson, 1985). Large amounts of solar radiation contribute to the development of slope and valley winds, and high evapotranspiration leads to an increase of moisture in the PBL. Thermally driven circulation systems form a convergence zone along mountain crests, which often results in severe convection. In dynamic terms, (Tao, 1980) considered the windward slope of the terrain to have a blocking effect that forces the flow to climb or split around the terrain, reporting that mountain terrain can also trigger a severe convection system to cause the release of instability energy.

    Figure 1.  (a) The three WRF domains used in this study. The map size is the outer domain; the d02 and d03 boxes indicate the second and third domains, respectively. The inset shows a map of Zhejiang Province. (b) Terrain-contoured base map of Zhejiang Province and its surrounding areas. The Donggong Mountains are located at the junction of Zhejiang and Fujian provinces. The black dots show the locations of Lishui and Jingning weather stations; the open circle represents the Wenzhou Doppler Radar (WDR); and the cross marks Quxian radiosonde station.

    The cyclonic convergence caused by the effect of the terrain is often the basic environment of heavy rain events (Rudari et al., 2004). Therefore, cumulus clouds accompanied by sufficient dynamic lifting and moisture convergence are prone to generating local rainstorms. Early studies determined that in areas with no large-scale weather, low-level convergence zones are the initial locations of convection (Byers and Braham, 1949; Purdom and Marcus, 1982; Wilson and Schreiber, 1986). However, these low-level convergence zones are generally ignored because of the complexity of the topography and low density of automatic weather stations. A possible explanation for the location and timing of convection initiation (CI) is that boundary layer convergence zones often form and force new deep and moist convection (Weckwerth et al., 2014).

    Mesoscale mountains, such as the small hills of South China and other regions, have an important impact on the arriving airflow, as well as on severe convection at the local level. Although the interaction between the terrain and atmosphere is highly complex, researchers consider the effect of terrain in precipitation studies because it is highly important in the generation and development of local heavy rain. Therefore, many scholars have conducted numerical simulation work in studies of topography-related precipitation (Mei\ssner et al., 2007; Barthlott and Kirshbaum, 2013).

    Local severe convection in complex terrain regions often indicates that the terrain plays a role in the triggering of severe convection. However, rainfall is a highly complicated physical process. Orographic precipitation is not only limited to the local vertical motion caused by orographic lift, but also to the rainfall caused by changes in the weather system owing to the orographic dynamical effect. However, if the atmospheric environment approaches instability, other disturbances or trigger mechanisms are likely, which makes it difficult to separate the topographic effects. Therefore, verification of topographic lift as the only trigger of orographic precipitation is difficult.

    Researchers worldwide have considered terrain effects to often be the main triggers of topographic precipitation. Zhejiang Province, a coastal area in Southeast China, has unique geographic and geomorphic characteristics, including the Donggong Mountains (Fig. 1b). The role of coastal mesoscale terrain in severe convection is unknown, particularly for the initiation of a short mountain squall lines, and the mesoscale features of the convection mechanism. Therefore, in this study, we conducted a WRF model simulation to examine these factors. Specifically, we selected a typical short squall line case that occurred over Zhejiang's southeastern mountains, which we introduce briefly in section 2 along with the large-scale synoptic conditions. A description of the experimental design and large-scale data is provided in section 3. Comparisons between the model-produced and observed thermal conditions, surface wind field and radar reflectivity, rainfall rates, and synoptic conditions, are presented in section 4. Section 5 analyzes the simulated surface stream and divergence, CI, and instability mechanism results. A discussion on the effect of the sea breeze is presented in section 6, followed by conclusions in section 7.

2. Case description
  • The low mountainous terrain of the southeastern Zhejiang Province and Fujian Province border region (Fig. 1b) often produces mesoscale convective cells that can cause local severe weather. To examine the occurrence and development of severe convective weather over coastal mesoscale terrain, we selected a short squall line that occurred on 5 July 2012 over the southern mountains in Zhejiang as a case study. This short squall line mainly moved along the southwest-northeast direction of the Donggong Mountains, and ultimately produced severe weather on the eastern side of the mountains (see Fig. 2c).

    Figure 2a shows that at 0000 UTC 5 July 2012 a shallow trough slowly traveled eastward in East China at 500 hPa. Zhejiang Province was under the northwest shoulder of the western Pacific subtropical high; the 588 dagpm isoline passed through the north of Zhejiang. A southwesterly airstream had been maintained in the Lishui area at 850 hPa, which transported a steady stream of water vapor. Southern Zhejiang was mainly in the warm sector, which caused instability in the atmospheric stratification to provide favorable large-scale background conditions for strong convective weather. According to the blackbody temperature (TBB) image (Fig. 2b), there was a mass of convective clouds in southern Zhejiang Province, and it is clear that the convective clouds of this process were isolated and localized (see the red box in Fig. 2b). Figure 2c demonstrates that the disastrous weather in the area indicated by the red box in Fig. 2b was short in duration (1000-1200 UTC) and low in range. The accumulated rainfall during the two hours from 1000 to 1200 UTC, as recorded by multiple observation stations in the Lishui area, was more than 25 mm, indicating a short-term rainstorm; the maximum accumulated precipitation was 74 mm. The distribution of this 2-h accumulated precipitation was mainly in the region of the radar echo at 1100 UTC and to its east (Fig. 2c). Moreover, a hailstorm occurred for several minutes at approximately 1040 UTC, and multiple locations in Lishui experienced thunderstorms and gales during the period of severe convection, with a maximum surface wind speed of 24.5 m s-1. Disastrous weather occurred mainly near Jingning County, in the northeastern Donggong Mountains, which caused considerable economic losses in the region.

    To reveal the occurrence mechanism of this severe convection process over complex terrain, dense surface observation data, Wenzhou Doppler radar (WDR) data and numerical simulation data were used to explore the severe convection triggers in Lishui.

    Figure 2.  (a) 500 hPa geopotential height field (blue lines, units: gpm), the bold blue line is 5880 geopotential meters, the thick red lines are trough lines, and 850 hPa wind field at 0000 UTC 5 July 2012. (b) TBB at 1200 UTC 5 July 2012. (c) Two-hour accumulated precipitation (solid black contours for observed and dotted black contours for simulated results; units: mm), in the red box in (b). Wind barbs represent observed surface station wind speed $\ge$17.2 m s$^-1$, and the black triangle represents the location of the automatic station that reported hail. The color legend on the right indicates the composite reflectivity (units: dB$Z$) from the WDR (marked by the open circle in Fig. 1b) at 1100 UTC. The color legend at the bottom indicates the terrain height (units: m).

3. WRF simulations
  • Version 3.5.1 of the WRF mesoscale numerical model was used in this study. The three nested domains (D1, D2, D3; Fig. 1a) were centered on (28°N, 118°E), with two-way nesting schemes adopted. The horizontal grid resolutions were 36, 12 and 4 km, with 236× 195, 292× 313 and 316× 316 grid points for D1, D2 and D3, respectively. In order to obtain a finer simulated result in the vertical direction, we increased the density of vertical layers to 57 levels, ranging from the ground to 50 hPa. The model physical parameterizations included WSM6 (Hong and Lim, 2006), the Mellor-Yamada-Janjic turbulent kinetic energy PBL scheme (Janjić, 1994), the Kain-Fritsch (new Eta) cumulus scheme (for D1 and D2 only; Kain and Fritsch, 1993), and the Noah land surface scheme (Chen and Dudhia, 2001). NCEP Final Operational Global Analysis data, on 1°× 1° grids, prepared operationally every six hours, were used as the initial fields and lateral boundary conditions. The integration time period was 24 hours, from 0600 UTC 5 July to 0600 UTC 6 July 2012.

4. WRF-observation comparisons
  • To evaluate the performance of the WRF simulation, we compared the simulation results with observations. Specifically, we chose the sounding data from the nearest rawinsonde station (at Quxian), which is located approximately 150 km west of the convection occurrence at 1200 UTC 5 July 2012 (Fig. 1b), in order to compare with the large-scale WRF simulations. In Fig. 3, the observed sounding is shown in red and the simulation is shown in black. Except for the small difference in surface temperature and surface dew-point temperature between the simulation and observation (possibly associated with the complex underlying surface), the trends of the WRF temperature profile and dew-point temperature profile with height are almost consistent with the observation (see Fig. 3).

    The analysis and comparison of observed and simulated ground wind field (Fig. 4) in the early stage clearly shows the ground wind field (data from automatic stations) convergence existed in the Donggong Mountain areas. This ground convergence airflow was composed of two flows. The first was from the northwest edge of the subtropical high known as southwest air flow, and the second was variable wind from the East China Sea affected by the friction of the coast that turned to the southeast wind near the coastline. The simulated radar echoes were compared with those observed by the Wenzhou Doppler Radar (WDR) (Fig. 5) to examine the occurrence of the convective weather under such background conditions.

    Figure 5 compares the simulated and observed (WDR data) radar echoes during the period of severe convection. As can be seen, the WRF simulation largely reproduced the radar echoes. The simulated results in Figs. 5b, d and f agree with the results shown in Figs. 5a, c and e, during the occurrence and development of the severe convection. That is, the convective cells continually ascended over the mountains (Figs. 5a and c; Figs. 5b and d) and gradually formed a zonal echo along the mountains (Figs. 5e and f).

    Figure 3.  Comparison of the Quxian rawinsonde station profile (red) and the WRF simulated profile (black) at 1200 UTC 5 July 2012. The dashed and solid lines indicate dew-point temperature and temperature, respectively.

    Figure 4.  Comparison between the (a, b) WRF and (c, d) observed surface winds, under conditions at 0700 UTC and 0900 UTC. The thick dashed lines represent surface convergence lines. The grayscale legend at the bottom indicates the terrain height (units: m).

    Figure 5.  Comparison of (a, c, e, g) observed and (b, d, f, h) WRF-simulated composite reflectivity. The legends of terrain height (units: m) and radar reflectivity (units: dB$Z$) are respectively displayed on the upper- and lower-right sides of the images. The line M-N in (d) indicates the location of the cross section shown in Fig. 7. A, B, C and D in are four echo cells listed from northeast to southwest.

    In analyzing the occurrence and development convection, we sorted the multiple cell echoes in the order of A, B, C and D from northeast to southwest (Fig. 5e). A small convective cell (A), which is shown in the radar reflectivity (dBZ) image in Fig. 5a, was also evident at a similar location in the simulation (Fig. 5b); however, the radar reflectivity in the simulations did not reach the trigger conditions. In this study, CI was defined as radar echoes exceeding 35 dBZ (May and Ballinger, 2007; Mecikalski et al., 2008; Anderson, 2010). At 0710 UTC, the radar reflectivity of the simulations of cells A and B (Fig. 5d) both exceeded 35 dBZ, which agreed with the echo intensity in the corresponding observation (Fig. 5c). Cells A, B, C and D showed development (Fig. 5e) and occurred in a linear arrangement that laid the foundation for the generation of the short squall line over the mountains. In contrast, after one hour's integration in the simulations, the corresponding cells appeared at similar locations. Cells B and C merged, and two echo centers were obvious. In addition, the strongest echo developed from cell C (Figs. 5g and h); therefore, we focused mainly on cell C in the present study. In summary, the experiment successfully simulated the radar echoes.

    Figure 6.  (a-e) Simulated surface stream line fields, divergence fields (black dotted lines; units: 10$^-4$ s$^-1$) and radar echoes; cells A, B and C are the same as the echo cells in Fig. 5e. The gray shading is the same terrain height as shown in Fig. 1b. (f) WRF-simulated cross section along line E-F of cell C shown in (b) at 0710 UTC (red line). In (f), the colored shading is the divergence (units: 10$^-4$ s$^-1$). The black contours indicate the wind zonal component; the interval is \hbox1 m s$^-1$. Yellow contours denote vertical velocity greater than 0.3 m s$^-1$.

    The precipitation during the convection process was concentrated mainly between 1000 and 1200 UTC (the solid black contours in Fig. 2c represent the two-hour observed accumulative precipitation, while the dotted black contours are for the same period but for the simulated precipitation). Comparison shows that the main precipitation area and precipitation intensity agreed with the observation in the northern mountains, while the simulated precipitation was larger in the Zhejiang Province and Fujian Province border region. In addition, compared with the synoptic conditions and other physical quantities (not shown), we detected agreement between the simulated results and observations, which contributed further to the verification of the WRF simulation of this case. Therefore, the results of the simulation were found to be appropriate for subsequent spatiotemporal analysis.

5. Results and discussion
  • To study the mesoscale features of the convective weather that occurred in the Donggong Mountains, we obtained the WRF output data of 4 km horizontal grid resolutions to analyze the evolutions of the surface stream and radar echo. Figure 6a shows an obvious 10 m surface stream at 0630 UTC; surface convergence beyond -2× 10-4 s-1 appeared over the mountains. A roughly long and narrow convergence zone appeared 30 minutes later along the Donggong Mountains, accompanied by surface wind. At that time (0700 UTC), abundant low cloud was generated near the main convective cell over the mountains in the boundary cloudiness image (not shown). The strong updrafts caused by surface mesoscale convergence played a highly important role in the formation of convection clouds (Barthlott et al., 2010). The above analysis shows that convergence centers appeared over this mountainous terrain, and the corresponding convective cells originated at the convergence centers. Figure 6b shows that radar echoes A and C occurred in the convergence zone over the mountainous terrain. From a different perspective, the cross-section of cell C (Fig. 6f) indicates that from the mountaintop upward to approximately 2 km, strong convergence was present. Above this level (2-3 km), strong divergence forced the low-level flow to lift strongly. Thus, the dynamic conditions were important in rapidly triggering the convection. The contour lines of the westerly wind component (solid black line) in Fig. 6f show that the westerly wind component mainly appeared on the west side and east side of cell C above 2 km; however, the low-level flow on the east side of cell C was a marine current from the East China Sea. These two flows met in the mountains and constituted vertical characteristics of low-level convergence and mid-level divergence. New small cells generated in the convergence zone over the peripheral mountain at 0730 UTC (Fig. 6c). At this time, cells A and C underwent further development and had smaller displacement and extension toward the northeast. However, the locations of the convergence centers that generated the convective cells over the mountains showed no change (Figs. 6c and d). At 0820 UTC, at the location of the generation of cell A, a new convective cell (B) was created by the convergence center and developed into a strong convective cell in a short time. At this time, all three convective cells (A, B and C) had matured and organically combined to form a short squall line along the southwest-northeast direction of the mountains.

  • The above analysis indicates that cell C played a major role in the generation of the short mountain squall line. To realize the occurrence of orographic convection, further analysis of convective cell C was required.

    Figure 7.  WRF-simulated cross sections along line M-N of cell C shown in Fig. 5d. The background field of the water vapor mixing ratio (colored shading; units: g kg$^-1$) is shown along with horizontal wind vectors in the overlying cross section. The dark gray shading indicates four peaks in the terrain, marked P$_1$, P$_2$, P$_3$ and P$_4$. The thin black contours are the cloud water mixing ratio values (units: kg kg$^-1$; the interval is 0.3 kg kg$^-1$ from 0.1 kg kg$^-1$). The thick black line denotes the PBL; the thick white dotted line is the LFC; the thick blue line is the LCL; and the brown lines in (b-d) are convergence lines at the CI location. The white shading in (h) is radar reflectivity exceeding 35 dB$Z$.

    Using fine mesh data, the M-N cross-section line shows meteorological factors that changed over time (Fig. 7). Figure 7 shows that the water vapor mixing ratio extended from the sea to the inland mountain area in the lower atmosphere, and the water vapor vertical gradient in the mountains was clearly low in the high-humidity area. Initially, the easterly wind from the sea surface within the boundary layer passed P1 and P2 and moved deep into P3 until it met the westerly wind (Fig. 7a). With time, the east and west winds produced vertical disturbances within the boundary layer (brown line at P2 in Fig. 7b). Consequently, water vapor mixing took place along these updrafts (Figs. 7c and d). At 0650 UTC (Fig. 7e), the disturbance flow together with the water vapor mixing ratio broke through the LCL (white thick line at P3), forming clouds above the height of approximately 2 km. Subsequently, the cloud water mixing ratio (thin black solid line in Fig. 7e) rapidly increased, moved upward vertically, and the updrafts broke through the LCL and the level of free convection (LFC) above the mountaintop completely (Figs. 7f and g). The radar echo exceeded 35 dBZ, at 0720 UTC (gray area in Fig. 7f).

    The convective cells were generated at the convergence center of the surface stream over the mountains (Fig. 6b). Vertical cross sections at the same time (Fig. 6f) suggest that the convergence extended upward to 2 km , within the boundary layer, whereas the divergence existed above 2 km. The maximum speed of the zonal wind on the eastern side of cell C at 2.5 km was the main cause for the divergence above 2 km. This suggests a relatively strong southwest low-level jet above 2 km in the Donggong Mountains. The vertical coupling relation between the divergence on the upper-right side of P3 and the convergence on the lower-right side caused the convection to develop rapidly. The low-level easterly flow was dominant over the east of mountains; however, this turned to southwesterly flow at the edge of the subtropical high in the mid-low levels, such that a low-level warm advection structure formed. The wind veer with increased height in the low level formed unstable stratification, and the warm moist flow from the southeast of the mountains was lifted upward with a vertical speed of 0.9 m s-1 when it met the mountains. This was shown in the slope of P3 near the peak. Clearly, the dynamic lifting effect owing to the high mountains, together with the low-level convergence, made the updrafts reach the LCL quickly, and the condensation of water vapor formed the orographic clouds. Radar reflectivity that greater than 35dBZ was then observed because of the effect of the mountains (Fig. 7h).

    The LCL and LFC, as critical indicators of atmospheric instability, were at constant altitude before the convective cells appeared (0710 UTC). Subsequently, both decreased gradually; however, at the start of convection, both decreased rapidly (0720 UTC). The decrease in the LCL was higher, and the low LCL was conducive to moisture condensation. The location of cell C was characterized by high CAPE (>2000 J kg-1) and extremely low convective inhibition (CIN) (0.1 J kg-1). The joint occurrence of low CIN and high CAPE, combined with the low LCL and LFC, increased the probability of severe convection, which is of significance to the forecasting of convection (Ziegler et al., 1997; Zhang, 2003).

  • To observe the temporal and spatial variations of the convective cell C, time-height plots of the simulated cell C (the location of cell C in Fig. 5e) are shown in Fig. 8. It can be seen that the low-level southeasterly (dashed line in Fig. 8a) from the sea gradually strengthened and moved upward with time (note: in order to make the spatiotemporal diagram and cross-section diagram look similar, we set the time coordinate from right to left to indicate that the right of the figure is the ocean and the left is the mountainous area). Before the convection triggered (0710 UTC), there was a 2 m s-1 zonal component near the surface. Meanwhile, the westerly wind strengthened above the boundary layer in the lower troposphere over the terrain and the meridional component exceeded 5 m s-1. That is, the southeasterly airflow strengthened in the low level, the southwesterly airflow strengthened in the upper layer, and the location of CI appeared at the overlap between the two enhanced airflows. Thus, it can be seen that enhanced vertical shear over the mountains was conducive to a decrease in Richardson number to form instability, and the water vapor and temperature conditions made it easy for convection to develop. Also, the equivalent potential temperature strengthened and moved upward with time (Fig. 8a). When the low-level easterly and mid-level westerly wind reached their highest values, the equivalent potential temperature gradient also reached a maximum, as did the vertical gradient of wind speed, and clouds started to form at about 2 km at the location of the easterly turning to westerly wind (Fig. 8a). This apparent wind conversion, increased wind speed and strong equivalent potential temperature gradient favored the accumulation of convective instability energy and the formation of convective instability stratification. As shown in Fig. 6, the surface convergence provided the disturbance conditions for the convection. In contrast, as can be seen from the time-height plots of the cloud water mixing ratio and humidity (Fig. 8b), the high-humidity area almost exactly matched the large area of the equivalent potential temperature gradient; therefore, the significant humidification at approximately 2 km helped to trigger this severe convection. Interestingly, Fig. 8 shows that the humidifying layer mainly appeared at the top of the boundary layer above 1 km, as well as above the zero line of the zonal component and near the equivalent potential temperature of about 350 K, where the level of wind direction shifted and a rapid vertical decrease in equivalent potential temperature occurred. The relative humidity and cloud water mixing ratio showed no obviously upward development until the convection initiated. This illustrates that before the severe convection occurred over the mountainous terrain, relative humidity first accumulated in the overlapping area of the southeasterly and southwesterly airflow, almost near the top of the boundary layer. When the vertical gradient of equivalent potential temperature increased gradually, the wind speed reached a certain condition, and dynamic conditions such as convergence were satisfied, the convection initiated.

    Figure 8.  (a) Time-height plot of the equivalent potential temperature (units: K), radar reflectivity (above 35 dB$Z$; gray shading) and zonal wind (black contours; interval: 1 m s$^-1$) in cell C (Fig. 5e). (b) Time-height plot of relative humidity (units: %) and cloud water mixing ratio (purple contours; units: g kg$^-1)$ in cell C (Fig. 5e). The layer number of sigma is the left $y$-axis and the height (units: km) is the right $y$-axis. Note that the $x$-axis should be read from right to left.

    Figure 9.  (a) Average daily wind contours at 0600 UTC in July 2012 for the height of sigma = 0.995. (b) Wind contours (units: m s$^-1$) at 0600 UTC 5 July 2012. The wind contours fit into the new $X'$ and $Y'$ axes coordinate system [shown in the top-right corner of (a)]; $X'$ is perpendicular to the shoreline, pointing inland, and $Y'$ is parallel to the shoreline, pointing northeast.

    According to Fig. 8b, a new horizontal water vapor flux (not shown) was calculated along the boundary layer to check the source of moisture. In this layer, the water vapor flux, together with the wind, showed that moisture was continually transported into the convection region along with the southwesterly. Therefore, large amounts of water vapor were carried by the low-level southwesterly airflow, which also facilitated convection. (Weckwerth, 2000) and (Lascaux et al., 2004) proved that, in addition to low-level convergence, water vapor at the boundary layer is critical to a convective system. Moreover, the southwesterly flow pushed the clouds and convective cells to move northeastward.

6. Effect of southeasterly airflow
  • From Figs. 6 and 7, the convergence caused by the southeasterly wind from eastern sea and the prevailing southwesterly airflow in the Donggong Mountains was critical to the strong convection on 5 July 2012. (Xu et al., 2010) studied the observed relation between the windward slope and orographic precipitation in the eastern coastal areas of China, and reported the terrain to be the most important factor affecting the proportion of windward slope rainfall in the total precipitation, and the windward slope rainfall increases during the summer monsoon because of the difference in the water vapor source and average wind speed. A Global Forecast System (0.5°× 0.5°) dataset was used and a new coordinate system was created with X' and Y' axes. To study the strength of the wind from the ocean toward the land, the surface zonal and meridional wind vectors were decomposed to the X'-Y" coordinates. Figure 9a shows the daily average wind contour at 0600 UTC in July 2012 for sigma (WRF Eta) level = 0.995. Figure 9b shows the wind contour map at 0600 UTC 5 July 2012. The positive values represent wind from the ocean toward the land, and vice-versa for the negative values. Figure 9a shows that the surface monthly average wind field comprised airflow from the sea to the land, with the average speed of wind that perpendicular to the shoreline reaching 7 m s-1 at 0600 UTC, and the wind speed gradually diminishing at 100 km inland. The Donggong Mountains represented the low wind speed zone, and there was a clear speed gradient between the mountains and the coastline. The lower atmosphere was affected by enhanced southeasterly airflow and the coastal mountains, which easily caused convergence on the windward slope of the mountains.

    Figure 9b shows that the center of the maximum value of the southeasterly wind from the sea on 5 July was stronger than the average values in Fig. 9a. The seasonal low-level southeasterly wind increased to 10 m s-1 on 5 July and moved further inland. Furthermore, the wind speed on the side of the mountains far from the coastline was negative, suggesting that the wind component from the mountains to the sea increased the wind speed gradient on the windward slope of the mountains and enhanced convergence. Therefore, it is necessary for convective storms on coastal mountains to have increased winds from the ocean toward the land and decreased mountain winds from the mountains to the sea. On 5 July 2012, the two south-deflected airflows produced stronger than usual convergence and convective cells over the Donggong Mountains. The combination of water vapor conditions and topography ultimately produced the short squall line.

7. Summary and conclusions
  • A short squall line occurred on 5 July 2012 in the southern mountainous area of Zhejiang Province. The weather conditions produced heavy rain, gales and hail, causing significant damage to local communities. To explore the triggering conditions of the severe convection at Lishui, a numerical simulation experiment of the severe convection over the mountains was conducted using the mesoscale WRF numerical model with three nested domains. Results showed that the physical assumptions in the experiment were realistic and, thus, the simulation results satisfactory. Based on the simulation, the main conclusions of this study can be summarized as follows:

    The simulation results matched the observations well. In particular, the radar echoes in the model realistically reproduced the convective cells that originally generated and then developed along the mountains, forming the squall line that moved to the northeast coast before ultimately disappearing.

    There was always a convergence line over the Donggong Mountains during the severe convection. The convergence centers of the surface streamline all appeared over the mountainous terrain and triggered new convective cells. Then, the short squall line was generated along the mountains because of the movement and combination of these convective cells. Consequently, ground-level convergence was critical to the generation and development of the convective cells (mainly the CI location).

    The vertical coupling relation between the convergence within the boundary layer and the divergence caused by the strong southwest low-level jet above the boundary layer was critical to the rapid development of the convection under dynamic conditions. There was always a high-humidity area from the coastline of southern Zhejiang to the Donggong Mountains, while the sea wind was affected by the orographic uplift on the windward slope. The uplifted airflow that carried the high moisture broke through the LCL and formed convective clouds above the LCL. The CI location appeared at the overlap between the enhanced zonal and meridional components, as well as in the area of high wind shear and equivalent potential temperature gradient. Furthermore, this type of configuration helped to generate convectively unstable stratification. In contrast, if the LCL at the CI location was low, the moist air was easily uplifted to the LCL, causing water vapor condensation.

    The low-level southeasterly airflow from the eastern sea was critical to the severe convection in this study. The surface monthly average wind field showed obvious airflow from the sea to the land, and the average speed of wind perpendicular to the shoreline reached a maximum in the coastal sea and gradually decreased inland from the coast. The Donggong Mountains represented a zone of low wind speed; therefore, there was an obvious wind speed gradient between the mountains and the coastline, and the lower atmosphere was where convergence formed on the windward slope of the mountains when affected by marine currents and the coastal mountains. Therefore, convective storms over coastal mountains require both high winds from the ocean toward the land and high mountain winds from the mountains toward the sea. When southeast and southwest winds in southern Zhejiang Province are strong during summer, the two airflows described in this study can easily produce stronger than usual convergence over the Donggong Mountains, thus creating convective cells owing to the effect of topography that, in this case, produced the short-lived squall line.

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