Mesoscale Meteorology METR 4433
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22 Development and Evolution of Drylines The dryline is a mesoscale phenomena whose development and evaluation is strongly linked to the PBL Text books containing sections on dryline The Dry Line Chapter 23 Ray P S Editor 1986 Mesoscale Meteorology and Forecasting American Meteorological Soc 793 pp Pages 292 290 Bluestein H B 1993 SynopticDynamic Meteorology in Midlatitudes Vol 2 Observations and Theory of Weather Systems Oxford University Press 594pp The dryline 1 De nition A narrow zone of strong horizontal moisture gradient at and near the surface 2 Most observed in the Western Great Plains of the US also in India China Australia Central Africa U Over the US the dry line is a boundary between warm moist air from the Gulf of Mexico and hot dry continental air from the southwestern states or the MeXican plateau 2 054 67lt a 075 a 250 044 am I 83 257 093 200 205 7 2 054 034 25 5 as 78 250053 5 4 0475 200 1 oea 33 Sm E W 7 ea 1 7 32 2 0 2200 UTC 22 MAY I98 09 sis in Oklahoma Texas and Kansas of 3 drle Fi ure 238 Surface anal ne scalloped line under quotquiescent Conditions al 2200 UTC May 22 1981 Allimeter setting solid lrnes in mb wllhom Ihe leading 10 temperature and dc point plolled In C altimeter selling plotted in lens of mb wrthuut the Ieadmg I0 whole barb n5 7 half barb 25 ms At 1 lime of this analysis tornadic storms 19 were occurring just east of the dryhnc in wesern okIahomat erldgt cast or Ihe dryline are generally from the south and southeast while wind wesl of the dryllne are rum the southwest and west Dew pmnls east ol the dryhnc are around 20 C dew poinls west of the dryline are near and below me In this example some 200C dewpoint temperature gradient is observed across the dryline in the above example 399 drv air cu a W L measure ofrelativedensity ofmoist air is z 70 061q 2000 HEIGHT m a o a 20 no as 2 93 s w 500 39 o 20 AD 60 an m 7 9 7 olancE km O l 00 The dryline is often located near a surface pressure trough often a lee trough or quotheat troughquot but does not have to be coincident with the trough see the first example Typical moisture in terms of dewpoint temperature gradient is 150C per 100 km but 90C in 1 km has been observed Vertical structure Is nearly vertical for lt 1 km and then quottiltsquot to the east over the moist air see Figures NEIGNT Km 1v q n knquot O K 2000 mf 2000 V 3 1500 VKjtm g 1500 gt Z L a 316 8 woo Pquot f quot 3 iooo L ATl l m an A 12 I 4 I n i i y I I I 20 40 80 80 I00 I20 40 20 0 50 BO 100 20 I 0 turn J39Wl DISH m iaszN assWI mN nrw NSTANCE m new serum a b WINDSq g kgquot J H vw I L Figure 241 Example of the vertical mo 1 Lquot 39 structure across a quiescent dryline as g ALIit determined from an aircraft 20192228 E 1an SQ UTC May 24 1989 a Vertical cross E 5 section of potential temperature K b w as in a but for watervapor mixing 000 ratio g kgquot c winds and watervapor 39 5 m 1 mixing ratio Flight track indicated in a if quotquot 5 and b by dashed line Courtesy C 00 20 Ziegler National Severe Storms D 20 iflT39tL warw o I o msuuce nun 33 139 9 5quot C Labo rato ry Wind qV 257 7 M 044 2m 200I20 034 5 7 a Y 57 250 we 2n 39 mu 4 2200 UTC 22 MAY I98 Amarillo TX and OKC soundings at 12 UTC 6am CST May 22 1981 and 00 UTC 6pm CST May 23 1981 corresponding to last example case Amarillo TX OKC 12 UTC 22 May 6am LST 00 UTC 23 May 6 pm LST b CW mm 1 Figure 242 Soundings characteristic of the air masses a west and b east of the dryline on May 22 1981 Soundings skew T logp diagrams for a Amarillo Texas Figure 242 Soundings characteristic of the air masses 3 west and b east of the dryline on May 22 1981 Soundings skew T logp diagrams for a Amarillo Texas at 1200 UTC top and at 0000 UTC May 23 bottom b Oklahoma City Oklahoma at 1200 UTC top and at 0000 UTC May 23 bottom Skewed abscissa is temperature C logarithmic ordinate is pressure mb Temperature and dew point plotted as solid line and dashed line respectively Winds plotted at the right at the plotted heights krn MSL pennant25 m 5 whole barb5 m 5quot half barb25 msquot The morning Amarillo sounding has a very shallow moist layer near the ground which mixes out completely with the dry air above when the surface temperature warms up to 24 C at early evening there is a deep dryadiabatic layer from the surface up to 560 mb a shallow stable layer is found at the top of the dryadiabatic layer a very shallow superadiabatic layer is found near the ground The morning Oklahoma City sounding has a 130mb deep moist layer near the ground which is nearly well mixed capped by a sharp inversion and surmounted by a deep nearly dryadiabatic layer extending up to 560mb by early evening the moist layer has thickened somewhat while the capping inversion remains The dryadiabatic layer above the capping inversion has approximately the same potential temperature 313 K as the deep dryadiabatic layer to the west at Amarillo The May 11 1970 Case Figure 237 Cross section from Tucson Ariz to Shreveport LL for 0600 CST 11 May 1970 Solid lines are isentropes dashed lines are isohumes mixing ratio in g kg HUD H II MR I970 Figure 231 Surface analysis 0300 CSTl H Why l970 03 CST 11 May 1970 06 CST 11 May 1970 Dryline was between Carlsbad New Mexico Td 25 F and Wink Texas Td 57 F Strong moisture gradient is found across the dryline Nocturnal inversion is found at the surface An inversion is found to the east of the dryline at 850mb level capping moist air below No clear horizontal 6 gradient separating the dry and moist air Figure 23 Sumquot nuxlysu 1500 CST 11 May 1970 In the afternoon a typical dryline structure is found 0 To the west of dryline NIL extended to 600mb Upward bulge of moisture at the dryline is an indicator of moist convection A lid still eXits to the east above the surface moist layer V i TUS ELP CNM INK MAF JCT ABl FTW W SHV lNW ABC Second crosssection is about 200 miles to the north Figure 2310 Cross section from Tucson Arm to Shreveport L3 for 1800 CST 11 May 1970 Figure 2311 Cross section from Winslow AM to Little Rock Ark for 1800 CST 1t agaln ShOWS a typlcal 11 May 1970 dryline structure TYPICAL BACKGROUND CONDITIONS FOR DRY LINES 1 Surface anticyclone to the east allowing moist Gulf air to flow into the Great Plains Westerly flow aloft causing a lee trough and providing a con uence zone for the concentration of the moisture J gradient The presence of a stable layer or quotcapping inversionquot or quotlidquot aloft The southerly ow under this lid is often called quotunderrunningquot U Because the terrain slopes upward to the west the moist layer is shallow at the west edge of the moist air and deeper to the east A This sets the stage for understanding the movement of the dry line MOVEMENT OF THE DRY LINE Under quotquiescen quot ie in the absence of strong synopticscale forcing conditions the dryline usually moves eastward during the day and westward at night as shown by the following example we have just looked at the vertical structure of this case KW as or q l quot T s4 02 A u 4 Wang 2205 um v l 86 05 2 79gt W Masai gram 1 quotgkq J w m 7 79W Lg I500 csr 55 ll MAY I970 MAY I970 Figure 231 Surface analysis 0300 CST Figure 232 Surface analysis 1500 CST 11 May 1970 11 May 1970 0300 CST 1500 CST 22 u o s u m 5 5 J 5 0 12 m 2y 1 y l x MB K06 L m ax m 55 0s l 280 ALSUY a gtli gt quot 5 N I m 9 madam r2 D L no l 7 01 39 n y L93 3n b 0300 CST M l2 MAY I970 Figure 233 Surface analysis 0300 CST 12 May 1970 0300 CST day 2 Top of Moist Layer HEIGHT km MSL LOG P Figure 243 Schematic vertical cross section of the dryline and its relationship to topographyt ldealized soundings temperature solid lines dew point dashed lines at points A B C bottom represent the conditions west just east and far east of the dryline 1 As the sun rises the heating of the surface near the dry line is greater than that of the surface to the east in the deeper moist air the difference in soil moisture content and lowlevel cloudiness often also contribute to such differential heating 2 Thus it takes less insolation to mix out the shallow mixed layer just to the east of the initial dry line position see Figure This mixing out brings dry air and westerly momentum downward and the position of the dry line moves eastward 3 As the heating continues deeper and deeper moist layers are mixed out causing the apparent eastward quotpropagationquot of the dry line This propagation is not necessarily continuous or at a rate equal to the wind component normal to the dry line 4 Eventually the heating is insufficient to mix out the moist layer and propagation stops 5 If a welldef1nedjet streak exists aloft we often see a quotdry line bulgequot underneath thejet as this air has the most westerly momentum to mix downward The strong westerly momentum mixed down from above provides extra push for the eastward propagation of dryline 95 9W 4 45 also 2 Figure 2313 Dryline bulge from 1500 26 MAY 973 955 26 May 1973 After Tegtmeier 6 After sunset the vertical mixing dies out the westerly momentum at the surface west of the dryline weakens the surface winds will back to a southeasterly direction in response to the lower pressure to the west The moist air east of the dry line will be advected back toward the west and surface stations will experience an east to west dry line passage The above case assuming synoptic scale forcing is weak 7 the situation is quiescent If synoptic forcing is strong the dryline may continue to be advected eastward in association with a surface low pressure system Irquot 4L r jg jmm V 39 l m x w m o 1 m K I W A gure ma txample 013 dryline scalloped line being advected far in he gas by 39 Marth Z1 19 1 2006quot dawpuinl in C Sealevel prmsure in lens of rnb Without the leading 9 m 10 2 MA Em Wholegtwind barb5 ms haquot wind barb25 m5quot Searlevel isobar In mb solid lines wilhoul Ihe loading 9 or 10 Blowing dust is often observed when suang surface winds are Found behlnd the dryline from Can and Millard I935 Courtesy of m A w M I I run l 16 Sometimes there exists a cold front behind the dryline that eventually catch up to the dry line 40 an m 26 APRIL I934 500 est la lb Figure 239 Analysis of a cold front catching up to a dryline scalloped line at a 1500 CST b 1800 and c 2100 April 26 1984 and transforming it into a cold front lsobars solid lines in inches of mercury X 100 without the leading 29 Temperature and dew point plotted in F pressure plotted is altimeter setting in inches of mercury x 100 without the leading 2 whole wind barb 5 m s half wind barb 25 m 5quot Severe thunderstorms formed along the dryline during the afternoon and a severe squall line formed along the cold front when it caught up to the dryline from Burgess and Curran 1985 Courtesy of the Cl l 7 American Meteorological Society l7 The dryline as a focus of convection Possible reasons Why convection initiates near dry lines A Surface convergence between winds with easterly component east of the dry line and westerly component west of the dry line J Dryline is the westernmost boundary of moist convectively unstable air The area along it and immediately east is the first region susceptible to convection encountered by the vertical motion associated with traveling disturbances from the west U Gravity waves may form on or near the dry line possibly triggering the first release of potential instability Koch abd McCarthy 1982 5 Dryline bulges provide an even greater focus for surface moisture convergence U quotUnderrunningquot air moves northward until cap is weaker andor large or mesoscale forcing is strong enough to release the instability Convective temperature may be reached just east of the dry line Some observations The reason for most tornado chase quotbustsquot is that the advection of warm dry air over the moist layer is building the cap or lid strength faster than the surface heating can overcome thus convection never occurs Draft Chapter from Mesoscale Dynamic Meteorology By Prof Yulang Lin North Carolina State University Chapter 1 Overview 11 Introduction The socalled mesometeorology or mesoscale meteorology is de ned in the Glossary of Meteorology Huschke 1959 as that portion of meteorology concerned with the study of atmospheric phenomena on a scale larger than that of micrometeorology but smaller than the cyclonic scale Traditionally cyclonic scale is also called synoptic scale macroscale or large scale Based on this de nition the Glossary of Meteorology further elucidates that the mesometeorology is concerned with the detection and analysis of the state of the atmosphere as it exists between meteorological stations or at least well beyond the range of normal observation from a single point The types of major weather phenomena that are small enough to remain undetected within a normal observation network are sometimes called mesometeorological which include tornadoes thunderstorms and immature tropical cyclones The study of atmospheric phenomena based on the use of meteorological data obtained simultaneously over the normal observation network is then called synoptic meteorology Synoptic scale phenomena include general circulation long waves and synoptic cyclones These scales have been loosely used For example tornado is classi ed as a mesometeorological phenomenon by the Glossary of Meteorology while it is classi ed as a microscale meteorological phenomenon Other examples are fronts and hurricanes which have been classi ed as macroscale phenomena by some scientists eg Stull 1988 but are classi ed as mesoscale phenomena by others eg Orlanski 1975 Thunis and Bornstein 1996 Therefore a more precise de nition of the atmospheric scales is needed This will be discussed in the next section Due to the lack of observational data at mesoscale mesoscale meteorology is advanced less rapidly compared to synoptic meteorology For example some isolated unusual values of pressure winds etc shown on synoptic charts are suspected to be observational errors Even though this may be true in some cases others may represent true signatures of subsynoptic disturbances having spatial and temporal scales too small to analyzed on synoptic charts However due to the advancement of observational techniques and buildup of mesoscale observational network in the past two decades more and more mesoscale phenomena as well as their interactions with synoptic scale and microscale ow and weather systems have been revealed and better understood In order to improve our weather forecasting at such a scale it is essential to improve our understanding of the mesoscale dynamics and modeling Since the mesoscale spans from 2 to 2000 km there is no single theory such as quasigeostrophic theory for large scale which provides a unique tool for studying the mesoscale dynamics Actually the dominant dynamical processes vary dramatically depending on the type of mesoscale circulation system involved 12 De nitions of Atmospheric Scales Due to different force balances atmospheric motions behave differently for uid systems with different time and spatial scales In order to understand the dynamical and physical processes different approximations have been taken to resolve the problems Therefore a proper scaling will facilitate the choice of appropriate approximations of the governing equations Scaling of atmospheric motions is normally based on observational and theoretical approaches From observational approach the atmospheric processes are categorized through empirical direct d b d b whreh are then classlfled rnto dserete seales For example sea breezes oeeur on the hrne seale ofl day and spatral seale of 10 to 100 hrn whlle the eurnulus eonyeetrons oeeur on the hrne seale of 30 rnrnutes and spahal seale of several km Flgure 1 1 shows a lunatic energy speetrurn for vanous lme seales 1 year and 1 day a few rnlnutes thougn the latter may be an amfact of the analysls Thls may suggest a dlvlslon e l 1 small seale and me versa Flg 1 1 Average lunatic energy ofwestreast wlnd eornponent m the free atmosphere Adapted after Vlnnlchenko 1970 Based on radar storrn obseryahons ngda 1951 eategonzed the atmosphenc rnohons rnto a mlcroscale L lt 20 hrn b rnesoseale 20 hrn lt L lt 1000 hrn and e synophe seale L gt 1000 where L represents the honzontal seale of the atrnosphene rnotrons orlansln 1975 classlfled the atrnosphene rnohons rnto 8 seales narnely macrora L gt 10000 hrn macror 0 gt L gt 2000 km mesorOL 2000 hrn gt L gt 200 hrn mesor 200 hrn gt L gt 20 km mesor39y 20 hrn gt L gt 2 km microrOL 200 rn mlcror 200 rn gt L gt 20 rn and mlcror39y L lt 20 rn seales see Table 1 1 In addluon Fupta 1981 has proposed 5 seales of atrnosphene phenomena narnely rnasoeale rnesose e rnrsoseale rnososeale and rnusoseale Other elassr eahons of atmosphenc seales have also been proposed Table 1 Atmosphm39c scale definitions wha39e Ly is horizontal scale length adapted from Thunis 39 1996 andBorsteln 1 Slull nnxc Orllmkl lu Llf llm mm 1985 tlvm l mcnl Aimnsphcnc nhcnwmena s y lunuut n Macmvu Manna acueutnnnluiontorswam 100mm 3 M t c ermr Mumi Synnmiccyclnnm R amuhu weak 5 i n Mama Mamv Fromnttumcmex l 2min may C Murr Maw mwrlcvallel lllmldn umlzmuw 2 a 39 20km M I h 2 Mainw Murry Tnmduironu numb lurhulcmc 2k m sari Micros Mum cunulimarmdncs kaulmu lumps M 100m 30mm i c M g wimp Mans unmade unwind r dchL 20m 1mm 7 7 Mww39Y an I i M Mlcnr39r Tuxbllknw wnd wag r Michb t Atmosphaic motions may also be categorized by taking theoretical approaches F example air ow ovaquot a mountain or a lake the scales ofmechanically or thamally induced waves correspond to the scales offorcing Using the Eulzmzn time rcdze xed in space is reasonable For two steady cumulus clouds being blown by a basic wind the time scale to a pason staying at a emain location on the ground is approximately zU1000 r Howevaquot the above time scale has little to do with the physics of clouds It is more meaningful physically to use the Lagrangum tzme rcaze which gives the scale following the uid motion In the above example the Lagrangian time scale is the time for an air parcel to rise to its maximum va39tical extmL Anothaquot example is the Lagragian time scale of a cyclone is the circumference of an air parcel travels 272R divided by the tangential wind speed The Lagrangian time scales and Rossby numbers of the following systems may be summarized as T Lagrangian R0 Naf27VfT Tropical cyclone 27rRVT VTfR Inertia gravity waves 2717 to 2727f Nf to 1 Sealand breezes 2727f 1 Thunderstorms and cumulus 2721Nw Nwf KelvinHelmholtz waves 271N Nf PBL turbulence 277ihUgtxlt U gtxltfh Tornadoes 27rRVT VTfR where R radius of maximum wind wind scale VT maximum tangential wind scale f Coriolis parameter N buoynacy BruntVaisala frequency NW moist buoyancy frequency U scale for friction velocity h scale for the depth of planetary boundary layer Based on the above theoretical consideration Emanuel and Raymond 1984 define the following different scales a synoptic scale for motions which are quasigeostrophic and hydrostatic b mesoscale 7 for motions which are nonquasigeostrophic and hydrostatic and c microscale 7 for motions which are nongeostrophic nonhydrostatic and turbulent Therefore mesoscale may be defined as including those circulations which are large enough in scale to be considered hydrostatic but too small to be described quasigeostrophically This type of theoretical approach has been taken into scale definitions in textbooks Arya 1988 defines micrometeorological phenomena as limited to those that originate in and are dominated by the planetary boundary layer excluding phenomena whose dynamics are largely governed by mesoscale and macroscale weather systems Taking a similar approach Pielke 1984 de ne mesoscale phenomena as having a horizontal length scale large enough to be hydrostatic but small enough so that the Coriolis force is small relative to the advective and pressure gradient forces In fact Pielke s definition of mesoscale confines itself to the meso scale defined by Orlanski Orlanski s mesooc and macro scales are split into regional and synoptic scales in Pielki s classification Stull s textbook 1988 defines mesoscale the same way as Orlanski s but with microscale de ned as 2 m lt L lt 3 km and an additional micro5 scale for L lt 2 m Recently Thunis and Bomstein 1996 take a more rigorous approach based on some assumptions such as hydrostatic convection advection compressible and Boussinesq approximations of governing equations both time horizontal and vertical scales to standardize nomenclature for mesoscale concepts and to integrate existing concepts of atmospheric space scales ow assumptions governing equations and resulting motions into a hierachy useful in categorization of mesoscale models Horizontal and vertical scales of ow subclasses under unstable and stable stability conditions for deep and shallow convections are sketched in Figures 12 and 13respective1y 39 39 39 39 39 Orlanski s except that Orlanski s microy scale is divided into microy 2 m lt L lt 20 m and mi 6 lt 2 m scales phenomena for scale classi caqu of Thunis and B Table 11 shows the hon39zontal scales time seal es and associated omstein Orlansld Pielki 39 and stull In this book we will adopt Orlanski s scaling except otherwise speci ed L Nanhydrostntir k A Hydrostatic 10 km T Deep D Thermo Dynnm E Convzction Adveccian c r gt 1 P 2 km Thermal h h n I Convection mm NU Advention s h a m m shallow I Convention 1 o r I7 w Micru I l l Lquot mm m m 2 km 20 in m km micron moses t mewr t mama t Fig 12 Schematic of ow subclasses under unstable stability conditions where hatched zones indicate that nonphysic phenomena dotted line indicates merging o thermo mic advection with macroscale r represents scaled ratio of bouyancy and vertical pressure gradient forced ofthennal 39 39 39 A r 4Lquot pertur a ons regimes Adapted a er Thunis and Bornstein 1995 Nonhyi lmsutic v v Hydrostatic aim 1 7 hen vltl Thermo 11 Deep 2km Dynamic 6 P Convectia Adventiun Thermal Shallaw Athenian 200 in Convention h n S h a l l o w i 1 in m 3910 7 Ian 70 In 200 km ti m miuo i mean mean 1 musu i is i Fig 13 As in Fig 12 except for stable stability conditions Adapted a er Thunis and Bornstein 1996 13 Energy Generations and Scale Interaction l ough many mesoscale circulations and weather systems are forced by large scale or microscale ow er 39 l 39 l 39 4 weather systems may be classi ed into the following types Anthes 1986 Holton 1992 a forced by surface inhomogeneities thermal or orographic b internal adjustment oflargerscale ow systems c instabilities occurred on the mesoscale d energy tiansfer from either Exampre iur r an mnrmtain valley winds mountain waves heat island circulations coastal fronts dry lines and moist convection These mesosccale weather systems are more predictable Examples for the second e of weather systems are fronts cyclones and jet streaks These weather systems a predictable since they are generated by transient forcing associated with largerscale ows 39 39 39 39 39 39 39 irrerrrrar L J a rich energy source of atmospheric disturbances most atmospheric instabilities have their maximum growth ra es either on the large scale eg baroclinic baro opic an inertial instabilities or on the microscale eg KelvlnsHelmhalE and convective ms tabllltlzs symmetiic instability appears to be an intnnsically mesoscale instability Energy tiansfer from small scales to E a a o e E a is a M 3 e E a a 3 lt a 8 E 11 S esoscale convective complexes and humcanes On e o er hand energy ans er macroscale to mesoscale also serves as an energy source to induce mesoscale circulations weather systems For example temperature and vorticity advection associated with largescale ow systems may help develop frontal systems at mesoscale Another possible energy source for producing mesoscale circulations or weather systems is the interaction of cloud physical and dynamical processes For example mesoscale convective systems may be generated by this interaction process through scale expansion Scale interaction generally refers to the interactions between the time and zonal average zonal ow and a fairly limited set of waves that are quantized by the circumference of the earth while it means the multiple interactions among a continuous spectrum of eddies of all sizes in turbulent theory Emanuel 1986 However scale interaction should not be viewed as a limited set of interactions among discrete scales because on average the mesoscale is much more like a continuous spectrum of scales Scale interaction depends on the degree of relative strength of ow motions involved For example if a very weak disturbance embedded in a slowly varying mean ow the interaction is mainly from the mean ow on the weak disturbance If this disturbance becomes stronger then it may exert an increasing in uence on the mean ow and other scales of motion may develop The scale interactions become more and more numerous and the general degree of disorder becomes greater To the extreme when the disturbance becomes highly nonlinear such as a fully developed turbulent ow then the interaction becomes mutual and chaotic and an explicit description of their interaction becomes problematic Examples of scaleinterative processes may occur at mesoscale are Koch 1997 i synoptic forcing of mesoscale weather phenomena ii generation of internal mesoscale instabilities iii interations of cloud and precipitation processes with mesoscale dynamics iv in uence of orography boundary layer and surface properties on mesoscale weather system development and evolution v feedback contributions of mesoscale systems to largerscale processes vi energy budgets associated with mesoscale systems and vii mechanisms and processes associated with stratospheretroposphere exchange Figure 14 shows the mutual interactions between the jet streak inertiagravity waves and strong convection at the mesoscale Koch 1997 trmn I 7 t mH r u m Frg 4 Sketeh ofmutual rnteraehons between the jet streak rnertra1gravrty waves an eonveetron Adapted atterKoeh 1997 Frgure 1 5 sketehes the energy transfer proeess of the response of the free atmosphere to a T of deforrnataon rs e a1 twhreh the rotataon effect beeornes as rrnportant as buoyaney effects 611s t a a t a an mmal condmon as 77 a San 131 where sgn rs de ned as sgnx1 for x 20 and 71 for xlt0 The proeess from state a to b of Frg 1 proe equrhhnurn wrth a honzonta1 sea1e of NH The above example of cumulus adveetaon rrnphes as 1east2 distinct sea1es rnvolved r cumulus sea1e e H and n large sea1e rNHRassbymdms afdefarmanan Fig 15 a deformation Adapted atter Emanuel and Raymond 1984 14 Predictability I enea1 weather prediction or atmosphene modehng in genera1 the quesuon of predictabili b d to ht h diverging soiuuons when integrated in time using slightly different rmuai conditions eg Ehrendorfer and Emeo 1995 The weather phenomenon is eonsrdered to have hmrted predictability if the so1utrons diverge since there is an uneerntatnty assoerated with inrtrai conditions determined from rea1 observations The qu atmos hm hen mena was rst rnyesugated by Lorentz 1969 by using a simple mode1 ofthe interaetron of barotropre yoruerty perturb u n among dwerse honzonta1 sea1es Hts resu1ts faster than the synoptre and p1anetary sea1es essenua11y beeause the eddy umeseaie deereases with honzonta1 sea1e The predictability for synoptre sea1es is mamly hmrted by nonhnear interaetron between different eomponents of the wave speetrum These interaeuons depend on t e in the different w um s and on the number of wave inrtrai dsmbuuon of energy ayen ber s e o 1 1 in the resolvablersc e ntxoduced by the neg1eet of unreso1yab1e sea1es grow with me an pread throughout the spe txum even 1 g an 1 th and destroying the fore t A th s predictability for mesosea1e is 1 by the rapid transfer of en se uon dimensional turbu1enee Tneyrtabie errors or inrtrai condition uneertatnues in e sm sea1e of than the synopue sea1e rendering the mesosea1e1ess predetab1e eategorres Emanuei and Raymond 1984 1 steady for a stab1e system 7 perfeetiy predictable 2 penodie for a weakl unstab1e system 7 perfectly predic ab1e 3 apenode with a 1umpy mo spee eategory 3 Monotonrerty of e energy speetru the larger seales presumably beeause mesoseale phenomena are strongly eonstrarned by topography and other surface features Sueh eonstrarnts may only work when other dynamlcal roeesses are weak Beslde the natural eonstrarnts by forcmg and physlcal proeesses predetablllty of mesoseale phenomena ls also affected by the lnlual eonduons set up ln a mesoseale numeneal predeuon model e ose e es m s phenomenon do ot emst at the begmmng of the numeneal predeuon then the predetablllty ls less lnaueneed by the aeeuraey of the lmual condltlons used ln a mesoseale eneal weather predeuon model Under thls sltuatlon the Mes seale elreulauons are normally forced by surface lnhomogeneltles thermal or orographle lntemal a Justment of l g s ystems lnstablhu on seale e ergy m el er m r eale or mlcroscal lnteraetlon ofcloud physlcal and dy lcal proeesses as dseussed earller slne the m s seal lau lsl by thel r sealem on seale of predet blllty of pe of mesoseale syst s eould ed aetual tl seale of e m soseale systems themselves on the er hand ll mesoseale nomenon emsts at the a p beglnnlng ofthe numeneal predeuon then lt ls neeessary to lnclude the obserye and analyzed motlon and thermodynamle varlables ln the lmtlal condluon ln order to make an aeeurate 1n tlus be depleted by Kg 1 o The theoreueal hmlt of predetlon deereases Wth me from 100 at the b d The aeeurae b b beglnnlng and less on the model beeause lt takes me for the model to spln up Thus obseryauons are more lmportant than the numeneal model ln the begnmng of numeneal predeuon b b d l Hg 1 o A sketeh for demonstratlng the relauonshlp between obseryatlons numeneal models andtheoreueal hmlt ofpreddcnon Adapted afterUCAR 1983 References Anthes R A 1986 The general question of predictability In Mesoscale Meteorology and Forecasting Ed P S Ray Amer Meteor Soc 636656 Arya P 1988 Introduction to Micrometeorology Academic Press 307 pp Ehrendorfer M and R M Errico 1995 mesoscale predictability and the spectrum of optimal perturbations J Atmos Sci 52 34753500 Emanuel K 1986 Overview and de nition of 39 39 In 7 I Meteorology and Forecasting P S Ray Ed 116 Emanuel K and D J Raymond 1984 Dynamics of Mesoscale Weather Systems Ed J B Klemp NCAR 1984 Fujita T T 1981 Tornadoes and downbursts in the context of generalized planetary scales J Atmos Sci 38 15121534 Fujita T T 1986 Mesoscale classi cations Their history and their application to forecasting In Mesoscale Meteorology and Forecasting P S Ray Ed 1835 Gill A E 1982 Atmosphere ocean dynamics Academic Press 662 pp Holton J R Introduction to Dynamic Meteorology Academic Press Inc 511pp Huschke R E 1959 Ed Glossary ofMeteorology 3ml Edition Amer Meteor Soc 638pp Koch S E 1997 Atmospheric Convection Lecture notes North Carolina State University Ligda MGH 1951 Radar storm observations Compendium of Meteorology AMS Boston Mass 12651282 Lorentz E N 1969 The predictability of a ow which possesses many scales of motion Tellus 21 289307 Orlanski I 1975 A rational subdivision of scales for atmospheric processes Bull Amer Meteor Soc 56 527530 Ray P S 1984 Mesoscale Meteorology and Forecasting Amer Metoer Soc 793pp Stull R 1988 An Introduction to Boundary Layer Meteorology Kluwer Academic 666pp Thunis P and R Bomstein 1996 Hierachy of mesoscale ow assumptions abd equations J Atmos Sci 53 380397 UCAR 1983 The National STORM Program Scienti c and Technical Bases and Major Objectives University Corporation for Atmospheric Research 830pp Vinnichenko N K 1970 The kinetic energy spectrum in the free atmosphere one second to ve years Tellus 22 158166