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Ingredients for deep, moist convection Bogdan Antonescu University of Manchester (some slides courtesy of C. Doswell)

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Presentation on theme: "Ingredients for deep, moist convection Bogdan Antonescu University of Manchester (some slides courtesy of C. Doswell)"— Presentation transcript:

1 Ingredients for deep, moist convection Bogdan Antonescu University of Manchester (some slides courtesy of C. Doswell)

2 Mesoscale

3 Ingredients for deep, moist convection Instability – conditional instability: (lapse rate) needed to develop CAPE CAPE Lift – to bring parcels to their level of free convection (LFC) Moisture – source of latent heat to drive the convection (C. Doswell)

4 The Three Ingredients for Deep, Moist Convection Instability Lift Moisture

5 Instability

6 Dry convection Rayleigh–Benard convection: heated bottom plate and chilled top plate, producing vertical gradient of temperature

7 Dry convection

8 Conditions for Deep Moist Convection CIN Instability Moisture Upmotion Moisture

9 Conditions for Deep Moist Convection CIN Instability Moisture Upmotion Click on a topic for more detail Moisture Animate

10 Conditions for Deep Moist Convection CIN Instability Moisture Upmotion Moisture

11 Unstable vertical distribution of mass can be measured by the vertical distribution of potential temperature (θ) The instability condition for dry convection gas constant of air the specific heat capacity at constant pressure standard reference pressure (1000 mb)

12 Unstable vertical distribution of mass can be measured by the vertical distribution of potential temperature (θ) dθ/dz > 0 absolutely stable (to dry displacements) dθ/dz = 0 neutral dθ/dz < 0 absolutely unstable The instability condition for dry convection

13 if dθ/dz = 0, then the lapse rate of temperature (change of temperature with height) is d = g/c p = 9.8 o C/km. d is called the dry adiabatic lapse rate. a layer of air possessing the dry adiabatic lapse rate is called well-mixed or isentropic (meaning “of the same isentrope”). vertical temperature gradients in the free atmosphere rarely exceed d. Lapse rates for dry convection (C. Doswell)

14 When moisture is present and the air is saturated, further cooling will result in condensation of water vapor to the liquid phase. This process releases latent heat to the environment, slowing down the cooling due to dry adiabatic expansion. Thus, moist ascending air parcels cool at a slower rate than dry ascending air parcels. (4–7 o C/km, instead of 9.8 o C/km) Moist convection (C. Doswell)

15 Unstable vertical distribution of mass can be measured by the vertical distribution of saturated equivalent potential temperature (θ es ). dθ es / dz > 0 absolutely stable (to moist displacements) dθ es / dz = 0 neutral d θ es / dz 0 conditionally unstable Moist convection (C. Doswell)

16 if dθ es /dz =0, then the lapse rate of temperature (change of temperature with height) is d, which varies with pressure and temperature. d is called the moist adiabatic lapse rate (4–7 o C/km, described earlier). An alternate statement of conditional instability is d > > m. Lapse rates for moist convection (C. Doswell)

17 Stability is a measure of the atmosphere’s resistance to vertical motions Parcel theory: moving air parcels around to test their buoyancy relative to their environment (air outside the air parcel) parcels warmer than their environment will rise parcels colder than their environment will sink for an excellent, detailed discussion of buoyancy and parcel theory, read Doswell and Markowski (2004, Monthly Weather Review). (C. Doswell)

18 How to read a skew T–logp graph (C. Doswell)

19 pressure (hPa or mb) How to read a skew T–logp graph (C. Doswell)

20 temperature ( o C) How to read a skew T–logp graph pressure (hPa or mb) (C. Doswell)

21 equal area=equal energy How to read a skew T–logp graph (C. Doswell)

22 dewpoint temperature profile temperature profile How to read a skew T–logp graph

23 dry adiabatic lapse rate moist adiabatic lapse rate How to read a skew T–logp graph (C. Doswell)

24 constant mixing ratio How to read a skew T–logp graph (C. Doswell)

25 LCL Lifting Condensation Level (LCL) Level at which a lifted parcel becomes saturated (an estimate of the cloud base height) To find the LCL, take the temperature of a parcel and go up a dry adiabat Also, take the dew point of a parcel and go up a constant mixing ratio line Where these two intersect is the LCL (C. Doswell)

26 LCL Lifting Condensation Level (LCL) (C. Doswell)

27 LCL Level of Free Convection (LFC) Level at which a lifted parcel begins a free acceleration upward to the equilibrium level. The LFC is found where the parcel temperature becomes warmer than the environmental temperature LFC (C. Doswell)

28 LCL LFC Lifting Condensation Level (LCL) (C. Doswell)

29 LCL Equilibrium Level (EL) Level at which a lifted parcel becomes cooler than the environmental temperature and is no longer buoyant. The EL is the point above the LFC where the parcel path crosses the temperature trace May also hear it referred to as “level of neutral buoyancy LFC EL (C. Doswell)

30 CAPE - Convective Available Potential Energy - The “positive area” of the skew-T diagram represents the CAPE - CAPE is a measure of instability through the depth of the atmosphere and is related to updraft strength in thunderstorms. - CAPE is usually an overestimate of updraft strength due to water loading and entrainment of unsaturated environmental air. CIN – Convective Inhibition - The “negative area” on the skew-T represents CIN, which must be overcome for the initiation of convection - Some CIN can be good for severe storm development because it suppresses growth of a lot of small cells permitting the explosive growth of an energetic few. CAPE CIN (C. Doswell)

31 Maximum vertical motion is related to the CAPE, according to parcel theory w max = (2 x CAPE) 0.5 Maximum vertical motion is a measure of the strength of the convection. It is related to the potential for precipitation production. (C. Doswell)

32 Lift

33 Air must rise to its LFC in order for convection to occur. This implies some kind of lifting mechanism. ascent over orography surface or low-level convergence : cold, warm or stationary fronts; surface wind-shift lines; drylines; sea- breeze fronts; boundary layer convection (e.g., horizontal convective rolls); outflow boundaries from previous convection, etc. elevated lifting : above a warm front or surface-based inversion (C. Doswell)

34 Orographic Ascent the faster the horizontal wind speed or the steeper the gradient in elevation, the greater the ascent. Even small hills can produce orographic precipitation enhancement (e.g., Bergeron 1960, 1961; Browning et al. 1974; Colle et al. 2003). (C. Doswell) w = –V h ∇ z

35 Moisture

36 Latent heat release is what gives the updraft buoyancy. No absolute measure of what is adequate amount of moisture for deep, moist convection. Low-level moisture may not be deep enough to provide sustained moist updrafts. Too little moisture aloft will result in evaporation of towering cumulus, which inhibits deep, moist convection. Moisture (C. Doswell)

37 Vertical wind shear is important for organized deep, moist convection Vertical wind shear – changing speed and orientation of the horizontal wind with height Too little vertical wind shear: short-lived storms. Too much vertical wind shear: sloped updrafts or updrafts cannot be sustained. (C. Doswell)

38 How to produce heavy rain from an individual convective cell? The lifetime of an individual convective cell is only about 20–40 minutes. Producing heavy rain from such a short-lived cell is unlikely. Need to have a mesoscale organization to promote a sustained and long-lived convective system. (C. Doswell)

39 Ingredients for Heavy Precipitation Deep, moist convection Lots of condensation (moist air going up quickly) Long duration High precipitation efficiency (minimal evaporation)

40 Proper amount of vertical wind shear separates the updrafts and downdrafts in a mesoscale organization, allowing sustained convection. (Houze 1993) vertical wind shear

41

42 Deep, moist convection Strong updrafts in the lower part of the mixed-phase region of the cloud Ingredients for Electrification

43 LCL (~cloud base) warmer than –10°C (ensures supercooled liquid water) Equilibrium level (~cloud top) colder than –20°C (ensures ice nucleation over adequate depth) CAPE > 100–200 J/kg in –10° to –20°C layer (ensures ascent > 6–7 m/s in lower mixed-phase region) Diagnostic Quantities for Electrification van den Broeke et al. (2005, WAF)

44 Ingredients are physical processes or conditions Ingredients are not the diagnostic quantities used for measurements! (C. Doswell)

45 Now you know the ingredients… How do you measure them?

46 Appropriate parameters/variables “Ingredients” - general terms Parameters to be considered in operations can take many forms: – –Moisture Surface dewpoint temperature, surface relative humidity, surface mixing ratio, surface q e or q w or q v, mean values through some shallow surface-based layer, mean values through a deep layer, remotely-sensed moisture, etc.

47 Are all such variables equally useful? Consider measures like θ e, that combine several variables: Associated with a particular moist adiabat on a thermodynamic diagram

48 Parameters that combine variables the variables can evolve more or less independently (not totally so, of course) therefore, such a variable is much more useful as a diagnostic parameter than a prognostic one – –It indicates where multiple variables “overlap” now, not where they will overlap – –Some variables are more difficult to forecast than others (e.g., mixing ratio vs. static stability)

49 Diagnostic vs. Prognostic Parameters diagnostic - tells you something about the existing structure of the atmosphere prognostic - tells you something about the likely evolution of atmospheric processes any variable or parameter can be forecast — not always useful for anticipating future events all “indices” are inherently diagnostic

50 Commonly-used diagnostic parameters moisture flux divergence potential vorticity differential vorticity advection thermal advection Q-vectors surface  e or  w CAPE, CIN, etc. frontogenesis etc.

51 Important limitations Diagnosis is inevitably data (or model) resolution dependent – –Values of kinematic quantities (e.g., vorticity and divergence) are tied to the resolution – –Gradient magnitudes and higher order derivatives for any variable Any diagnosis is conditional - changes with time as new data arrive

52 Variables for “ingredients” somewhat arbitrary – –Base variables are best (T, p [or  ], r, V) – –Forecasts most accurate and robust – –Should be independent (more or less) – –At least necessary for the event being forecast therefore, should not be diagnostic parameters should be robust and reliable

53 A possibly poor choice upper-level divergence as a proxy for the “lift” ingredient in anticipating DMC – –unrobust - sensitive to small changes in V h – –can be contaminated by ongoing DMC – –synoptic-scale w is not generally useful – –the wrong level, in many cases – –common misconception: ascent is caused by n n upper divergence or n n lower convergence

54 Moisture flux convergence (MFC) is not an appropriate diagnostic for forecasting convective initiation. surface MFC has been used for over 30 years as a diagnostic parameter. combination of moisture (q) and lift (divergence) ingredients: difficulty in diagnosing each independently often poorly related to convective initiation Banacos and Schultz (2005) argue against its use.

55 Indices as a forecasting tool generally, diagnostic rather than useful for forecasting sensitive to data issues (not robust) – –errors in the data – –arbitrary choices (e.g., at standard levels) – –limitations on data accuracy and resolution A place to begin? No!! - Anticipation

56 Six Questions to Ask (from Bosart 2003, “Whither the Weather Analysis and Forecasting Process?”, Weather and Forecasting) 1. What happened? 2. Why did it happen? 3. What is happening? 4. Why is it happening? 5. What is going to happen? 6. Why is it going to happen? (Don’t be tempted to “cheat” and only consider #5!) (Courtesy of Russ Schumacher)

57 A Philosophy of Diagnosis how do we assess weather features in the atmosphere? suppose you see something on the radar and you don’t know what is causing it. first attempt should be QG thinking: advection of vorticity by thermal wind (e.g., vorticity advection, warm advection) if not QG, then try frontogenesis at different levels. if not frontogenesis, then something else: topography, PBL circulations, diabatic effects, etc. note that assessing instability is also important, but secondary to this philosophy. Gravitational stability or moist symmetric instability only modulates the response to the given forcing.

58 Petterssen (1936) Frontogenesis F = d/ dt |  | F = 1/ 2 |  | ( E cos2  - D) q = potential temperature E = resultant deformation b = angle between the isentrope and the axis of dilatation D = divergence

59 Frontogenesis Facts frontogenesis is “following the flow” (Lagrangian). fronts that are weakening can still possess frontogenesis. note that tilting effects are not included in Petterssen’s (1936) form of frontogenesis. diagnosis of frontogenesis results in a diagnosis of the forcing for vertical motion on the frontal scale. ascent occurs on the warm side of a maximum of frontogenesis and on the cold side of a region of frontolysis.

60 Frontogenesis: Example 1 frontogenesis can occur even in the presence of strong topographic contrasts In this case, from the Intermountain precipitation Experiment, we’ll see that synoptic-scale influences can dominate over topographic influences. Schultz et al. (February 2002 BAMS)

61 IPEX IOP 5: 17 February 2000 Surface cyclone south of SLC Weak flow field at all levels Snowband northwest of cyclone 4–12 in. snow in Tooele Valley 500 hPa SURFACE

62

63 6-h median reflectivity from KMTX yellow maxima are 20-25 dBZ

64 700-hPa FRONTOGENESIS 500-hPa omega 700-hPa theta shading 700-hPa frontogenesis 700-hPa winds RUC-2: 1500 UTC L

65 Frontogenesis: Example 2 Snowstorm in Oklahoma not well forecast Most snowfall fell well to the north of the surface frontal boundary Trapp et al. (2001) in March 2001 MWR

66

67

68 OUNSEP

69 Elevated Convection and Frontogenesis Frontogenesis: solid lines CAPE: shading Theta-e: thin solid lines 80% RH: dotted line Heavy snow location: * Frontogenesis at 1000 mb (dotted) and 600 mb (dashed) CAPE at 1000 mb (shading) and 600 mb (overprinted shading)

70 Elevated Convection and Frontogenesis Vertical motion: shaded Theta-es: solid lines circulation within plane of cross section (i.e., frontal circulation) Vertical motion: shaded Theta: solid lines circulation normal to plane of cross section (i.e., synoptic-scale circulation)

71 Frontogenesis: Example 3 Frontogenesis in northwesterly flow, apparently unrelated to surface frontogenesis. Often misinterpreted as associated with upper-level jet circulations.

72 1300 UTC 13 Sept. 2001 surface observations, CAPE, and radar LBF

73 1300 UTC 13 Sept. 2001 surface observations, CAPE, and radar LBF

74 753 J/kg CAPE 482 J/kg CIN

75 700-hPa Frontogenesis and Theta

76 Summary Ingredients-based methodology Deep moist convection: lift, instability, moisture Frontogenesis Elevated convection

77


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