Abstract
The environment for the development of mesoscale precipitating systems in East Asia during the summer monsoon season is characterized by warm and humid conditions. Moist conditions provide a unique feature for the development of mesoscale precipitating systems. In this chapter, the morphology and predictability of mesoscale precipitating systems in moist environments are described through a comparison with those that occur in drier environments in midlatitude, continental regions. The role of moisture fluctuations in the free troposphere in characterizing and controlling mesoscale precipitating systems is a topic of specific focus. The predictability of deep moist convection is examined through a case study for a thunderstorm development over a mountain topography. It is argued that the moisture variability is essentially important in understanding the predictability of deep convection affected by topography. In moist environments, the humidity fluctuation is a key to characterize and determine the feature of mesoscale precipitating systems and their predictability.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Bachmann K, Keil C, Weissmann M (2019) Impact of radar data assimilation and orography on predictability of deep convection. Quart J Roy Meteor Soc 145:117–130. https://doi.org/10.1002/qj.3412
Bachmann K, Keil C, Craig GC et al (2020) Predictability of deep convection in idealized and operational forecasts: effects of radar data assimilation, orography, and synoptic weather regime. Mon Wea Rev 148:63–81. https://doi.org/10.1175/MWR-D-19-0045.1
Barnes GM, Sieckman K (1984) The environment of fast- and slow-moving tropical mesoscale convective cloud lines. Mon Wea Rev 112:1782–1794
Bellenger H, Yoneyama K, Katsumata M et al (2015) Observation of moisture tendencies related to shallow convection. J Atmos Sci 72:641–659. https://doi.org/10.1175/JAS-D-14-0042.1
Bluestein HB, Jain MH (1985) Formation of mesoscale lines of precipitation: Severe squall lines in Oklahoma during the spring. J Atmos Sci 42:1711–1732
Brown RG, Zhang C (1997) Variability of midtropospheric moisture and its effect on cloud-top height distribution during TOGA COARE. J Atmos Sci 54:2760–2774
Bryan GH (2005) Spurious convective organization in simulated squall lines owing to moist absolutely unstable layers. Mon Wea Rev 133:1978–1997. https://doi.org/10.1175/MWR2952.1
Bryan GH, Fritsch JM (2000) Moist absolute instability: the sixth static stability state. Bull Amer Meteor Soc 81:1207–1230
Bryan GH, Wyngaard JC, Fritsch JM (2003) Resolution requirements for the simulation of deep moist convection. Mon Wea Rev 131:2394–2416. https://doi.org/10.1175/1520-0493(2003)131%3c2394:RRFTSO%3e2.0.CO;2
Bryan GH, Rotunno R, Fritsch JM (2007) Roll circulations in the convective region of a simulated squall line. J Atmos Sci 64:1249–1266. https://doi.org/10.1175/JAS3899.1
Byers HR, Braham RR (1949) The thunderstorm project, U.S. Weather Bureau, U.S. Department of Commerce, Washington, DC, 287 pp
Cotton WR, Bryan GH, van den Heever SC (2011) Storm and cloud dynamics, 2nd edn. Academic Press, Burlington, USA
Das P (1979) A non-Archimedean approach to the equations of convection dynamics. J Atmos Sci 36:2183–2190
Davies-Jones R (2002) Linear and nonlinear propagation of supercell storms. J Atmos Sci 59:3178–3205
Derbyshire SH, Beau I, Bechtold P et al (2004) Sensitivity of moist convection to environmental humidity. Quart J Roy Meteor Soc 130:3055–3079
Ding Y, Liu Y (2001) Onset and the evolution of the summer monsoon over the South China Sea during SCSMEX field experiment in 1998. J Meteor Soc Jpn 79:255–276. https://doi.org/10.2151/jmsj.79.255
Ding Y, Zhang Y, Ma Q et al (2001) Analysis of the large-scale circulation features and synoptic systems in East Asia during the intensive observation period of GAME/HUBEX. J Meteor Soc Jpn 79:277–300. https://doi.org/10.2151/jmsj.79.277
Doswell CA III, Markowski PM (2004) Is buoyancy a relative quantity? Mon Wea Rev 132:853–863. https://doi.org/10.1175/1520-0493(2004)132%3C0853:IBARQ%3E2.0.CO;2
Durran DR, Weyn JA (2016) Thunderstorms do not get butterflies. Bull Amer Meteor Soc 97:237–243. https://doi.org/10.1175/BAMS-D-15-00070.1
Ehrendorfer M, Errico RM, Raeder KD (1999) Singular vector perturbation growth in a primitive equation model with moist physics. J Atmos Sci 56:1627–1648. https://doi.org/10.1175/1520-0469(1999)056%3c1627:SVPGIA%3e2.0.CO;2
Fan D, Greybush SJ, Chen X et al (2022) Exploring the role of deep moist convection in the wavenumber spectra of atmospheric kinetic energy and brightness temperature. J Atmos Sci 79:2721–2737. https://doi.org/10.1175/JAS-D-21-0285.1
French AJ, Parker MD (2008) The initiation and evolution of multiple modes of convection within a meso-alpha-scale region. Wea Forecast 23:1221–1252. https://doi.org/10.1175/2008WAF2222136.1
Fovell RG, Dailey PS (1995) The temporal behavior of numerically simulated multicell-type storms. Part I: modes of behavior. J Atmos Sci 52:2073–2095
Fovell RG, Ogura Y (1989) Effect of vertical wind shear on numerically simulated multicell storm structure. J Atmos Sci 46:3144–3176
Fovell RG, Tan PH (1998) The temporal behavior of numerically simulated multicell-type storms. Part II: the convective cell life cycle and cell regeneration. Mon Wea Rev 126:551–577
Fuelberg HE, Biggar DG (1994) The preconvective environment of summer thunderstorms over the Florida Panhandle. Wea Forecast 9:316–326
Fujitani T (1981) Direct measurements of turbulent fluxes over the sea during AMTEX. Pap Meteor Geophys 32:119–134. https://doi.org/10.2467/mripapers.32.119
Gamo M (1996) Thickness of the dry convection and large-scale subsidence above deserts. Bound Layer Meteor 79:265–278
George JJ (1960) Weather forecasting for aeronautics. Academic Press, New York
Goto Y, Satoh M (2022) Statistical analysis of “Senjo-Kousuitai” in East Asia and characteristics of associated large-scale circulations in the Baiu season. SOLA 18A:15–20. https://doi.org/10.2151/sola.18A-003
Hagos S, Feng Z, Landu K et al (2014) Advection, moistening, and shallow-to-deep convection transitions during the initiation and propagation of Madden-Julian oscillation. J Adv Model Earth Syst 6:938–949. https://doi.org/10.1002/2014MS000335
Hamada A, Takayabu YN (2018) Large-scale environmental conditions related to midsummer extreme rainfall events around Japan in the TRMM region. J Clim 31:6933–6945. https://doi.org/10.1175/JCLI-D-17-0632.1
Hamada A, Takayabu YN, Liu C, Zipser EJ (2015) Weak linkage between the heaviest rainfall and tallest storms. Nat Commun 6:6213. https://doi.org/10.1038/ncomms7213
Hirockawa Y, Kato T (2021) A new application method of radar/raingauge analyzed precipitation amounts for long-term statistical analyses of localized heavy rainfall areas. SOLA 18:13–18. https://doi.org/10.2151/sola.2022-003
Hirockawa Y, Kato T, Tsuguti H et al (2020) Identification and classification of heavy rainfall areas and their characteristic features in Japan. J Meteor Soc Jpn 98:835–857
Hohenegger C, Schär C (2007) Predictability and error growth dynamics in cloud-resolving models. J Atmos Sci 64:4467–4478. https://doi.org/10.1175/2007JAS2143.1
Houston AL, Niyogi D (2007) The sensitivity of convective initiation to the lapse rate of the active cloud-bearing layer. Mon Wea Rev 135:3013–3032. https://doi.org/10.1175/MWR3449.1
Houze RA Jr (2014) Cloud dynamics, 2nd edn. Academic Press, Oxford, UK
Houze RA Jr, Smull BF, Dodge P (1990) Mesoscale organization of springtime rainstorms in Oklahoma. Mon Wea Rev 118:613–654
Igau RC, LeMone MA, Wei D (1999) Updraft and downdraft cores in TOGA COARE: why so many buoyant downdraft cores? J Atoms Sci 56:2232–2245
Imada Y, Watanabe M, Kawase H et al (2019) The July 2018 high temperature event in Japan could not have happened without human-induced global warming. SOLA 15A:8–12. https://doi.org/10.2151/sola.15A-002
James RP, Fritsch JM, Markowski PM (2005) Environmental distinctions between cellular and slabular convective lines. Mon Wea Rev 133:2669–2691
James RP, Markowski PM, Fritsch JM (2006) Bow echo sensitivity to ambient moisture and cold pool strength. Mon Wea Rev 134:950–964. https://doi.org/10.1175/MWR3109.1
Johnson RH, Rickenbach TM, Rutledge SA et al (1999) Trimodal characteristics of tropical convection. J Clim 12:2397–2418
Johnson RH, Aves SL, Ciesielski PE et al (2005) Organization of oceanic convection during the onset of the 1998 East Asian summer monsoon. Mon Wea Rev 133:131–148
Jorgensen DP, LeMone MA (1989) Vertical velocity characteristics of oceanic convection. J Atmos Sci 46:621–640
Kato T (2020) Quasi-stationary band-shaped precipitation systems, named “senjo-kousuitai”, causing localized heavy rainfall in Japan. J Meteor Soc Jpn 98:485–509. https://doi.org/10.2151/jmsj.2020-029
Kato T, Goda H (2001) Formation and maintenance processes of a stationary band-shaped heavy rainfall observed in Niigata on 4 August 1998. J Meteor Soc Jpn 79:899–924. https://doi.org/10.2151/jmsj.79.899
Kato R, Shimose K, Shimizu S (2018) Predictability of precipitation caused by linear precipitation systems during the July 2017 Northern Kyushu Heavy Rainfall Event using a cloud-resolving numerical weather prediction model. J Disas Res 13:846–859. https://doi.org/10.20965/jdr.2018.p0846
Kingsmill DE, Houze RA Jr (1999) Thermodynamic characteristics of air flowing into and out of precipitating convection over the west Pacific warm pool. Quart J Roy Meteor Soc 125:1209–1229
Lau KM, Ding Y, Wang JT et al (2000) A report of the field operations and early results of the South China Sea Monsoon Experiment (SCSMEX). Bull Amer Meteor Soc 81:1261–1270
Leith CE (1971) Atmospheric predictability and two-dimensional turbulence. J Atmos Sci 28:145–161. https://doi.org/10.1175/1520-0469(1971)028%3C0145:APATDT%3E2.0.CO;2
LeMone MA, Zipser EJ, Trier SB (1998) The role of environmental shear and thermodynamic conditions in determining the structure and evolution of mesoscale convective systems during TOGA COARE. J Atmos Sci 55:3493–3518
Lilly DK (1990) Numerical prediction of thunderstorms-has its time come? Quart J Roy Meteor Soc 116:779–798
Lin YL (2007) Mesoscale dynamics. Cambridge University Press, Cambridge
Lorenz EN (1969a) The predictability of a flow which possesses many scales of motion. Tellus 21:289–307. https://doi.org/10.3402/tellusa.v21i3.10086
Lorenz EN (1969b) Atmospheric predictability as revealed by naturally occurring analogues. J Atmos Sci 26:636–646
Lucas C, Zipser EJ, LeMone MA (1994a) Vertical velocity in oceanic convection off tropical Australia. J Atmos Sci 51:3183–3193
Lucas C, Zipser EJ, LeMone MA (1994b) Convective available potential energy in the environment of oceanic and continental clouds: correction and comments. J Atmos Sci 51:3829–3830
Lucas C, Zipser E, Ferrier BS (2000) Sensitivity of tropical west Pacific oceanic squall lines to tropospheric wind and moisture profiles. J Atmos Sci 57:2351–2373
Maddox RA (1980) Mesoscale convective complexes. Bull Amer Meteor Soc 61:1374–1387
Markowski PM (2020) What is the intrinsic predictability of tornadic supercell thunderstorms? Mon Wea Rev 148:3157–3180. https://doi.org/10.1175/MWR-D-20-0076.1
Markowski P, Richardson Y (2010) Mesoscale meteorology in midlatitudes. Wiley-Blackwell, Chichester
McCaul EW Jr, Cohen C, Kirkpatrick C (2005) The sensitivity of simulated storm structure, intensity, and precipitation efficiency to environmental temperature. Mon Wea Rev 133:3015–3037
Melhauser C, Zhang F (2012) Practical and intrinsic predictability of severe and convective weather at the mesoscales. J Atmos Sci 69:3350–3371. https://doi.org/10.1175/JAS-D-11-0315.1
Meng Z, Yan D, Zhang Y (2013) General features of squall lines in east China. Mon Wea Rev 141:1629–1647. https://doi.org/10.1175/MWR-D-12-00208.1
Mitsuta Y, Fujitani T (1974) Direct measurement of turbulent fluxes on a cruising ship. Bound Layer Meteor 6:203–217. https://doi.org/10.1007/BF00232485
Moteki Q, Ueda H, Maesaka T et al (2004a) Structure and development of two merged rainbands observed over the East China Sea during X-BAIU-99. Part I: meso-α-scale structure and build-up processes of convergence in the Baiu frontal region. J Meteor Soc Jpn 82:19–44. https://doi.org/10.2151/jmsj.82.19
Moteki Q, Ueda H, Maesaka T et al (2004b) Structure and development of two merged rainbands observed over the East China Sea during X-BAIU-99. Part II: meso-α-scale structure and build-up processes of convergence in the Baiu frontal region. J Meteor Soc Jpn 82:45–65. https://doi.org/10.2151/jmsj.82.45
Nakamae K, Takemi T (2022) Relationships between the development of convective mixed layer and the occurrence of dust weather in arid and semi-arid regions of East Asia. Int J Climatol 42:3076–3093. https://doi.org/10.1002/joc.7408
Nastrom GD, Gage KS (1985) A climatology of atmospheric wavenumber spectra of wind and temperature observed by commercial aircraft. J Atmos Sci 42:950–960
Nishi A, Kusaka H (2019) Effect of foehn wind on record-breaking high temperature event (41.1 °C) at Kumagaya on 23 July 2018. SOLA 15:17–21. https://doi.org/10.2151/sola.2019-004
Nomura S, Takemi T (2011) Environmental stability for afternoon rain events in the Kanto plain in summer. SOLA 7:9–12. https://doi.org/10.2151/sola.2011-003
Park SK (1999) Nonlinearity and predictability of convective rainfall associated with water vapor perturbations in a numerically simulated storm. J Geophys Res 104:31575–31587. https://doi.org/10.1029/1999JD900446
Parker MD (2008) Response of simulated squall lines to low-level cooling. J Atmos Sci 65:1323–1341. https://doi.org/10.1175/2007JAS2507.1
Parker MD (2010) Relationship between system slope and updraft intensity. Mon Wea Rev 138:3572–3578. https://doi.org/10.1175/2010MWR3441.1
Parker MD, Johnson RH (2000) Organizational modes of midlatitude mesoscale convective systems. Mon Wea Rev 128:3413–3436
Pettet CR, Johnson RH (2003) Airflow and precipitation structure of two leading stratiform mesoscale convective systems determined from operational datasets. Wea Forecast 18:685–699
Pope SB (2000) Turbulent flows. Cambridge University Press, Cambridge
Powell SW (2019) Observing possible thermodynamic controls on tropical marine rainfall in moist environments. J Atmos Sci 76:3737–3751. https://doi.org/10.1175/JAS-D-19-0144.1
Powell SW (2022) Criticality in the shallow-to-deep transition of simulated tropical marine convection. J Atmos Sci 79:1805–1819. https://doi.org/10.1175/JAS-D-21-0155.1
Powell SW, Houze RA Jr (2013) The cloud population and onset of the Madden-Julian Oscillation over the Indian Ocean during DYNAMO-AMIE. J Geophys Res Atmos 118:11979–11995. https://doi.org/10.1002/2013JD020421
Prein AF, Rasmussen R, Stephens G (2017) Challenges and advances in convection-permitting climate modelling. Bull Amer Meteor Soc 98:1027–1030. https://doi.org/10.1175/BAMS-D-16-0263.1
Redelsperger JL, Parsons DB, Guichard F (2002) Recovery processes and factors limiting cloud-top height following the arrival of a dry intrusion observed during TOGA COARE. J Atmos Sci 59:2438–2457
Ridout JA (2002) Sensitivity of tropical Pacific convection to dry layers at mid- to upper levels: Simulation and parameterization tests. J Atmos Sci 59:3362–3381
Robe FR, Emanuel KA (2001) The effects of vertical wind shear on radiative-convective equilibrium states. J Atmos Sci 58:1427–1445
Romine GS, Schwartz CS, Berner J et al (2014) Representing forecast error in a convection-permitting ensemble system. Mon Wea Rev 142:4519–4541. https://doi.org/10.1175/MWR-D-14-00100.1
Romps DM (2014) An analytical model for tropical relative humidity. J Clim 27:7432–7449. https://doi.org/10.1175/JCLI-D-14-00255.1
Romps DM, Kuang Z (2010) Do undiluted convective plumes exist in the upper tropical troposphere? J Atmos Sci 67:468–484. https://doi.org/10.1175/2009JAS3184.1
Rotunno R, Klemp JB (1982) The influence of the shear-induced pressure gradient on thunderstorm motion. Mon Wea Rev 110:136–151
Rotunno R, Snyder C (2008) A generalization of Lorenz’s model for the predictability of flows with many scales of motion. J Atmos Sci 65:1063–1076. https://doi.org/10.1175/2007JAS2449.1
Rotunno R, Klemp JB, Weisman ML (1988) A theory for strong, long-lived squall lines. J Atmos Sci 45:463–485
Ruppert JH Jr, Johnson RH (2015) Diurnally modulated cumulus moistening in the preonset stage of the Madden–Julian oscillation during DYNAMO. J Atmos Sci 72:1622–1647. https://doi.org/10.1175/JAS-D-14-0218.1
Sakaeda N, Powell SW, Dias J et al (2018) The diurnal variability of precipitating cloud populations during DYNAMO. J Atmos Sci 75:1307–1326. https://doi.org/10.1175/JAS-D-17-0312.1
Schumacher RS (2015) Sensitivity of precipitation accumulation in elevated convective systems to small changes in low-level moisture. J Atmos Sci 72:2507–2524. https://doi.org/10.1175/JAS-D-14-0389.1
Schumacher RS, Johnson RH (2005) Organization and environmental properties of extreme-rain-producing mesoscale convective systems. Mon Wea Rev 133:961–976. https://doi.org/10.1175/MWR2899.1
Schumacher RS, Johnson RH (2006) Characteristics of U.S. extreme rain events during 1999–2003. Wea Forecast 21:69–85. https://doi.org/10.1175/WAF900.1
Schumacher RS, Johnson RH (2008) Mesoscale processes contributing to extreme rainfall in a midlatitude warm-season flash flood. Mon Wea Rev 136:3964–3986. https://doi.org/10.1175/2008MWR2471.1
Schumacher RS, Johnson RH (2009) Quasi-stationary, extreme-rain-producing convective systems associated with midlevel cyclonic circulations. Wea Forecast 24:555–574. https://doi.org/10.1175/2008WAF2222173.1
Schumacher RS, Peters JM (2017) Near-surface thermodynamic sensitivities in simulated extreme-rain-producing mesoscale convective systems. Mon Wea Rev 145:2177–2200. https://doi.org/10.1175/MWR-D-16-0255.1
Sekizawa S, Miyasaka T, Nakamura H et al (2019) Anomalous moisture transport and oceanic evaporation during a torrential rainfall event over western Japan in early July 2018. SOLA 15A:25–30. https://doi.org/10.2151/sola.15A-005
Shimizu S, Uyeda H (2012) Algorithm for the identification and tracking of convective cells based on constant and adaptive threshold methods using a new cell-merging and -splitting scheme. J Meteor Soc Jpn 90:869–899. https://doi.org/10.2151/jmsj.2012-602
Shimpo A, Takemura K, Wakamatsu S et al (2019) Primary factors behind the heavy rain event of July 2018 and the subsequent heat wave in Japan. SOLA 15A:13–18. https://doi.org/10.2151/sola.15A-003
Shinoda T, Uyeda H, Yoshimura K (2005) Structure of moist layer and sources of water over the southern region far from the meiyu/baiu front. J Meteor Soc Jpn 83:137–152. https://doi.org/10.2151/jmsj.83.137
Skamarock WC (2004) Evaluating mesoscale NWP models using kinetic energy spectra. Mon Wea Rev 132:3019–3032. https://doi.org/10.1175/MWR2830.1
Skamarock WC, Park SH, Klemp JB et al (2014) Atmospheric kinetic energy spectra from global high-resolution nonhydrostatic simulations. J Atmos Sci 71:4369–4381. https://doi.org/10.1175/JAS-D-14-0114.1
Skamarock WC, Klemp JB, Dudhia J et al (2019) A description of the advanced research WRF model version 4. No. NCAR/TN-556+STR. https://doi.org/10.5065/1dfh-6p97
Smagorinsky J (1963) General circulation experiments with the primitive equations. Mon Wea Rev 91:99–164. https://doi.org/10.1175/1520-0493(1963)091%3c0099:GCEWTP%3e2.3.CO;2
Stevens B, Vali G, Comstock K et al (2005) Pockets of open cells and drizzle in marine stratocumulus. Bull Amer Meteor Soc 86:51–57
Takayabu YN, Shige S, Tao WK et al (2010) Shallow and deep latent heating modes over tropical oceans observed with TRMM PR spectral latent heating data. J Clim 23:2030–2046. https://doi.org/10.1175/2009JCLI3110.1
Takayabu I, Rasmussen R, Nakakita E et al (2022) Convection-permitting models for climate research. Bull Amer Meteor Soc 103:E77–E82. https://doi.org/10.1175/BAMS-D-21-0043.1
Takemi T (2006) Impacts of moisture profile on the evolution and organization of midlatitude squall lines under various shear conditions. Atmos Res 82:37–54. https://doi.org/10.1016/j.atmosres.2005.01.007
Takemi T (2007a) A sensitivity of squall line intensity to environmental static stability under various shear and moisture conditions. Atmos Res 84:374–389. https://doi.org/10.1016/j.atmosres.2006.10.001
Takemi T (2007b) Environmental stability control of the intensity of squall lines under low-level shear conditions. J Geophys Res 112:D24110. https://doi.org/10.1029/2007JD008793
Takemi T (2010) Dependence of the precipitation intensity in mesoscale convective systems to temperature lapse rate. Atmos Res 96:273–285. https://doi.org/10.1016/j.atmosres.2009.09.002
Takemi T (2014a) Convection and precipitation under various stability and shear conditions: squall lines in tropical versus midlatitude environment. Atmos Res 142:111–123. https://doi.org/10.1016/j.atmosres.2013.07.010
Takemi T (2014b) Characteristics of summertime afternoon rainfall and its environmental conditions in and around the Nobi Plain. SOLA 10:158–162. https://doi.org/10.2151/sola.2014-033
Takemi T (2015) Relationship between cumulus activity and environmental moisture during the CINDY2011/DYNAMO field experiment as revealed from convection-resolving simulations. J Meteor Soc Jpn 93A:41–58. https://doi.org/10.2151/jmsj.2015-035
Takemi T (2018) Importance of terrain representation in simulating a stationary convective system for the July 2017 Northern Kyushu Heavy Rainfall case. SOLA 14:153–158. https://doi.org/10.2151/sola.2018-027
Takemi T (2021) Editorial for the special edition on extreme rainfall events in 2017 and 2018. J Meteor Soc Jpn 99:1145–1147. https://doi.org/10.2151/jmsj.2021-c
Takemi T, Rotunno R (2003) The effects of subgrid model mixing and numerical filtering in simulations of mesoscale cloud systems. Mon Wea Rev 131:2085–2101. https://doi.org/10.1175/1520-0493(2003)131%3c2085:TEOSMM%3e2.0.CO;2
Takemi T, Satomura T (2000) Numerical experiments on the mechanisms for the development and maintenance of long-lived squall lines in dry environments. J Atmos Sci 57:1718–1740. https://doi.org/10.1175/1520-0469(2000)057%3C1718:NEOTMF%3E2.0.CO;2
Takemi T, Unuma T (2019) Diagnosing environmental properties of the July 2018 Heavy Rainfall event in Japan. SOLA 15A:60–65. https://doi.org/10.2151/sola.15A-011
Takemi T, Unuma T (2020) Environmental factors for the development of heavy rainfall in the eastern part of Japan during Typhoon Hagibis (2019). SOLA 16:30–36. https://doi.org/10.2151/sola.2020-006
Takemi T, Hirayama O, Liu C (2004) Factors responsible for the vertical development of tropical oceanic cumulus convection. Geophys Res Lett 31:L11109. https://doi.org/10.1029/2004GL020225
Takemi T, Yoshida T, Yamasaki S et al (2019) Quantitative estimation of strong winds in an urban district during Typhoon Jebi (2018) by merging mesoscale meteorological and large-eddy simulations. SOLA 15:22–27. https://doi.org/10.2151/sola.2019-005
Takemura K, Wakamatsu S, Togawa H et al (2019) Extreme moisture flux convergence over western Japan during the Heavy Rain Event of July 2018. SOLA 15A:49–54. https://doi.org/10.2151/sola.15A-009
Terasaki K, Tanaka HL, Satoh M (2009) Characteristics of the kinetic energy spectrum of NICAM model atmosphere. SOLA 5:180–183. https://doi.org/10.2151/sola.2009-046
Thorpe AJ, Miller MJ, Moncrieff MW (1982) Two-dimensional convection in non-constant shear: a model of mid-latitude squall lines. Quart J Royal Meteor Soc 108:739–762. https://doi.org/10.1002/qj.49710845802
Trier SB, Skamarock WC, LeMone MA et al (1996) Structure and evolution of the 22 February 1993 TOGA COARE squall line: numerical simulations. J Atmos Sci 53:2861–2886
Trapp RJ (2013) Mesoscale-convective processes in the atmosphere. Cambridge University Press, New York
Tsuji H, Yokoyama C, Takayabu YN (2020) Contrasting features of the July 2018 heavy rainfall event and the 2017 Northern Kyushu rainfall event in Japan. J Meteor Soc Jpn 98:859–876. https://doi.org/10.2151/jmsj.2020-045
Tsuji H, Takayabu YN, Shibuya R et al (2021) The role of free-tropospheric moisture convergence for summertime heavy rainfall in western Japan. Geophys Res Lett 48:e2021GL095030. https://doi.org/10.1029/2021GL095030
Tsukamoto O, Ohtaki E, Ishida H et al (1990) On-board direct measurements of turbulent fluxes over the open sea. J Meteor Soc Jpn 68:203–211
Unuma T, Takemi T (2016a) Characteristics and environmental conditions of quasi-stationary convective clusters during the warm season in Japan. Quart J Royal Meteor Soc 142:1232–1249. https://doi.org/10.1002/qj.2726
Unuma T, Takemi T (2016b) A role of environmental shear on the organization mode of quasi-stationary convective clusters during the warm season in Japan. SOLA 12:111–115. https://doi.org/10.2151/sola.2016-025
Unuma T, Takemi T (2021) Rainfall characteristics and their environmental conditions during the heavy rainfall events over Japan in July 2017 of 2018. J Meteor Soc Jpn 99:165–180. https://doi.org/10.2151/jmsj.2021-009
Uyeda H, Yamada H, Horikomi J et al (2001) Characteristics of convective clouds observed by a Doppler radar at Naqu on Tibetan Plateau during the GAME-Tibet IOP. J Meteor Soc Jpn 79:463–474
van Zanten MC, Stevens B (2005) Observations of the structure of heavily precipitating marine stratocumulus. J Atmos Sci 62:4327–4342
Waite ML, Khouider B (2010) The deepening of tropical convection by congestus preconditioning. J Atmos Sci 67:2601–2615
Wang TCC, Lin YJ, Pasken RW et al (1990) Characteristics of a subtropical squall line determined from TAMEX dual-Doppler data. Part I: Kinematic structure. J Atmos Sci 47:2357–2381
Weisman ML (1992) The role of convectively generated rear-inflow jets in the evolution of long-lived mesoconvective systems. J Atmos Sci 49:1826–1847
Weisman ML, Klemp JB (1982) The dependence of numerically simulated convective storms on vertical wind shear and buoyancy. Mon Wea Rev 110:504–520
Weisman ML, Rotunno R (2004) “A theory for strong, long-lived squall lines” revisited. J Atmos Sci 61:361–382. https://doi.org/10.1175/1520-0469(2004)061%3C0361:ATFSLS%3E2.0.CO;2
Weyn JA, Durran DR (2017) The dependence of the predictability of mesoscale convective systems on the horizontal scale and amplitude of initial errors in idealized simulations. J Atmos Sci 74:2191–2210. https://doi.org/10.1175/JAS-D-17-0006.1
Wood R (2012) Stratocumulus clouds. Mon Wea Rev 140:2373-2423. https://doi.org/10.1175/MWR-D-11-00121.1
Wu P, Takemi T (2021) The impact of topography on the initial error growth associated with moist convection. SOLA 17:134–139. https://doi.org/10.2151/sola.2021-024
Wu P, Takemi T (2023) Impacts of mountain topography and background flow conditions on the predictability of thermally induced thunderstorms and the associated error growth. J Atmos Sci 80. https://doi.org/10.1175/JAS-D-21-0331.1
Xu KM, Randall DA (2001) Updraft and downdraft statistics of simulated tropical and midlatitude cumulus convection. J Atmos Sci 58:1630–1649
Yamada H, Geng B, Uyeda H et al (2007) Thermodynamic impact of the heated landmass on the nocturnal evolution of a cloud cluster over a meiyu-baiu front. J Meteor Soc Jpn 85:663–685
Yang X, Fei J, Huang X et al (2015) Characteristics of mesoscale convective systems over China and its vicinity using geostationary satellite FY2. J Clim 28:4890–4907. https://doi.org/10.1175/JCLI-D-14-00491.1
Yeo K, Romps DM (2013) Measurement of convective entrainment using Lagrangian particles. J Atmos Sci 70:266–277. https://doi.org/10.1175/JAS-D-12-0144.1
Yoden S (2007) Atmospheric predictability. J Meteor Soc Jpn 85B:77–102
Yokoyama C, Tsuji H, Takayabu YN (2020) The effects of an upper-tropospheric trough on the heavy rainfall event in July 2018 over Japan. J Meteor Soc Jpn 98:235–255. https://doi.org/10.2151/jmsj.2020-013
Yoneyama K (2003) Moisture variability over the tropical western Pacific Ocean. J Meteor Soc Jpn 81:317–337
Yoshizaki M, Kato T, Tanaka Y et al (2000) Analytical and numerical study of the 26 June 1998 orographic rainband observed in western Kyushu, Japan. J Meteor Soc Jpn 78:835–856
Zermeno-Dias DM, Zhang C, Kollias P et al (2015) The role of shallow cloud moistening in MJO and non-MJO convective events over the ARM Manus site. J Atmos Sci 72:4797–4820. https://doi.org/10.1175/JAS-D-14-0322.1
Zhang F, Snyder C, Rotunno R (2003) Effects of moist convection on mesoscale predictability. J Atmos Sci 66:1944–1961. https://doi.org/10.1175/2009JAS2824.1
Zhang F, Odins A, Nielsen-Gammon JW (2006) Mesoscale predictability of an extreme warm-season rainfall event. Wea Forecast 21:149–166. https://doi.org/10.1175/WAF909.1
Zhang F, Bei N, Rotunno R et al (2007) Mesoscale predictability of moist baroclinic waves: convection-permitting experiments and multistage error growth dynamics. J Atmos Sci 64:3579–3594. https://doi.org/10.1175/JAS4028.1
Zhang Y, Zhang F, Stensrud DJ et al (2016) Intrinsic predictability of the 20 May 2013 tornadic thunderstorm event in Oklahoma at storm scales. Mon Wea Rev 144:1273–1298. https://doi.org/10.1175/MWR-D-15-0105.1
Zipser EJ, LeMone MA (1980) Cumulonimbus vertical velocity events in GATE. Part II: synthesis and model core structure. J Atmos Sci 37:2458–2469
Zuidema P (1998) The 600–800-mb minimum in tropical cloudiness observed during TOGA COARE. J Atmos Sci 55:2220–2228
Acknowledgements
The comments from a reviewer are greatly appreciated in improving the original manuscript. I would like to thank Prof. Seon Ki Park who is the editor of this book for encouraging me to contribute a chapter. I would like to acknowledge the funding support from JSPS Kakenhi 20H00289 and 21H01591 and also by the MEXT-Program for the advanced studies of climate change projection (SENTAN) Grant Number JPMXD0722678534.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Takemi, T. (2023). Analysis and Predictability of Mesoscale Precipitating Systems in Moist Environments. In: Park, S.K. (eds) Numerical Weather Prediction: East Asian Perspectives. Springer Atmospheric Sciences. Springer, Cham. https://doi.org/10.1007/978-3-031-40567-9_14
Download citation
DOI: https://doi.org/10.1007/978-3-031-40567-9_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-40566-2
Online ISBN: 978-3-031-40567-9
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)