severe convective storms, theory Pieter Groenemeijer FMI Helsinki, 2 May 2005

one-slide introduction of myself I am Pieter Groenemeijer M.Sc. in Physics and Astronomy at Utrecht University Oklahoma University (spring semester 2002) ESWD (European Severe Weather Database) Sounding-derived parameters associated with large hail and tornadoes in the Netherlands Co-initiator of ESTOFEX (with Johannes Dahl and Christoph Gatzen), Oct, 2002.

my contribution this morning 1.Ingredients-based forecasting -instability -lift 2.Storm structure -wind shear: multicells and supercells -other factors: linear convective systems _________________________________________ (short break) Convection parameters Severe weather hazards -a study in Holland 5.A case Questions, discussion

what will we discuss? severe convective storms: storms that produce hazardous weather like: lightning heavy rain (leading to flash floods) strong winds (straight-line winds) large hail tornadoes

ingredients-based forecasting (Doswell, 2004) What isingredients-based forecasting? an ingredient is something necessary for some event to occur I will cover the theory by exploring those ingredients

ingredients for convective storms 1.latent instability 2.lift (rising motion)

instability lapse rate definition: dT/dz > 1.0 C/km in dry air or:dT/dz > moist adiabatic lapse rate in saturated air these are the definitions of absolute and conditional instability

instability layer definition: when lifting a layer, saturation occurs and dT/dz becomes > moist adiabatic lapse rate Or equivalently: theta-e (and theta-w) decrease with height potential instability

instability a convective bubble is more like a parcel than a layer... parcel definition: parcel becomes warmer than environment after lift latent instability (Normand, 1937) several convective parameters are based on the concept of latent instability: CAPE (in all its forms) LI (Lifted Index) Showalter Index

instability

parcel theory

limitations of parcel theory Realize that parcel theory is a simplification of reality: what in reality is a parcel? is it undiluted? and its environment? is it not influenced by convection? objection: We neglect pressure perturbation forces! (come back to that later)

lift latent instability storms a cap, CIN may be present, or entrainment may inhibit the development of convective storms lift can weaken the cap, or is associated with convergence at the surface: - helps to sustain initiating convective bubbles

lift and convective inhibition

entrainment

we have identified... two ingredients for convective storms... latent instability (sufficient) lift okay... but when should we become worried about extreme events? are other ingredients required?

storm structures / convective modes some severe events are associated with particular storm structures (or convective modes) multicell line multicell clustersisolated supercell EXAMPLES from my home country

storm structures / convective modes some severe events are associated with particular storm structures (or convective modes), others are not, e.g.: - strong tornadoes are known to occur mostly with supercell storms - extreme rainfall and lightning can occur with any storm structure, but generally... anticipating storm structure is very important to predict the quantity and quality of the severe weather that may occur

factors influencing storm structures 1.vertical wind shear 2.other factors

vertical wind shear vertical wind shear has a strong influence on convective organisation it affects storm propagation vertical speeds in up- and downdrafts storm longevity

storm in weak vertical shear weak shear: single-cell storms 1.updraft grows 2.precipitation forms 3.cold pool forms and spreads out 4.updraft ceases 5.storm ceases

reality a gust front made visible by blowing dust and sand

new cells form at the edge of the cold pool.... storm in moderate vertical shear moderate shear: multicell storms 1.updraft grows 2.precipitation forms 3.cold pool forms and spreads out >>>>> 4.updraft ceases 5.storm ceases time 1.new updraft grows 2.precipitation forms 3.cold pool forms and spreads out >>>>> 4.updraft ceases 5.storm ceases 1.new updraft grows 2.precipitation forms 3.cold pool grows and spreads out 4.updraft ceases 5.storm ceases

new cells form at the edge of the cold pool.... RKW-theory from Rotunno, Klemp and Wilhelmson, 1988 when horizontal vorticity produced by the cold pool and that of the environments are roughly equal the strongest lift will occur

RKW-theory from Xue et al., 1997 no vertical wind shear

RKW-theory from Xue et al., 1997 low-level vertical wind shear

RKW-theory RKW-theory is not undisputed... it seems to work better in the laboratory than in reality

storm in moderate vertical shear multicell cluster the cells may not be distinguished by a radar scanning at a low elevation....

storm in moderate vertical shear multicell line: squall line watch the cells forming at the front of the system that move backward w.r.t. the system

storm in strong vertical shear strong shear: supercell storms

supercell definition: a supercell is a storm with a persistent, deep rotating updraft (that is, a mesocyclone) a few characteristics: very strong updrafts often: very strong downdrafts...resulting in a high potential for severe weather dont move with the mean wind

hodographs

storm-relative helicity vertical shear implies horizontal vorticity

storm-relative helicity (e.g. Davies, 1985; Droegemeier et al., 1993)

hodographs

right-moving supercell

left-moving supercell

hodographs

LP supercell near Waynoka, OK April 17th 2002 Tornado Team Utrecht

Mesocyclone near Selby SD June 8th 2002 Tornado Team Utrecht

supercells on (Doppler) radar

we have identified... three ingredients for the most severe convective storms... latent instability (sufficient) lift vertical wind shear

we have identified... three ingredients for the most severe convective storms... latent instability (sufficient) lift vertical wind shear note that I didnt say that CAPE should by higher than some threshold. Storms have caused F4 tornadoes with only a few 100s of J/kg available!

other factors than wind shear that influence storm structure... It is hard to predict if and how quickly storms will cluster into a linear MCS. -MCSs often form when cold pools formed by multiple storms merge Factors favoring clustering into an MCS: -strong lift (e.g. caused by an intense shortwave trough, frontal wave) -convective initiation along a boundary -weak cap (low CIN)

bow echoes Convective systems may develop into bow echoes.

Amsterdam Rotterdam The Hague Image made at KNMI bow echoes

Image made at KNMI Amsterdam Rotterdam The Hague 1639 UTC bow echoes

Image made at KNMI Amsterdam Rotterdam The Hague 1639 UTC bow echoes

Image made at KNMI

17 July Image by Patrick Weegink

ingredients-based forecasting (Doswell, 2004) an ingredient is something necessary for some event to occur helps with information overload helps prevent overlooking important factors prevents tunnel-vision

we have identified... three ingredients for the most severe convective storms... latent instability (sufficient) lift vertical wind shear certain parameters may help to quantify those

convective parameters but, beware....

convective parameters Total totals index (TOTL) = T Td * T 500 [°C] K index = T Td T (T-Td) 700 [°C] Sweat index = 12*Td *(TOTL-49)+2*U *U *(0.2+sin(f)) where f=(wind direction 500 -wind direction 850 ), U=wind speed[kts], TOTL=0 if TOTL<49 but, beware, some parameters....

convective parameters...combine different physical atmospheric properties (moisture, temperature, wind shear) into one parameter in some magical way Total totals index (TOTL) = T Td * T 500 [°C] K index = T Td T (T-Td) 700 [°C] Sweat index = 12*Td *(TOTL-49)+2*U *U *(0.2+sin(f)) where f=(wind direction 500 -wind direction 850 ), U=wind speed[kts], TOTL=0 if TOTL<49 but, beware, some parameters....

convective parameters...combine different physical atmospheric properties (moisture, temperature, wind shear) into one parameter in some magical way Total totals index (TOTL) = T Td * T 500 [°C] K index = T Td T (T-Td) 700 [°C] Sweat index = 12*Td *(TOTL-49)+2*U *U *(0.2+sin(f)) where f=(wind direction 500 -wind direction 850 ), U=wind speed[kts], TOTL=0 if TOTL<49 but, beware, some parameters come with a list of thresholds, that may not be valid in your forecast region (if at all...)

convective parameters...combine different physical atmospheric properties (moisture, temperature, wind shear) into one parameter in some magical way Total totals index (TOTL) = T Td * T 500 [°C] K index = T Td T (T-Td) 700 [°C] Sweat index = 12*Td *(TOTL-49)+2*U *U *(0.2+sin(f)) where f=(wind direction 500 -wind direction 850 ), U=wind speed[kts], TOTL=0 if TOTL<49 but, beware, some parameters come with a list of thresholds, that may not be valid in your forecast region (if at all...)...require no physical understanding of the weather situation

convective parameters...combine different physical atmospheric properties (moisture, temperature, wind shear) into one parameter in some magical way Total totals index (TOTL) = T Td * T 500 [°C] K index = T Td T (T-Td) 700 [°C] Sweat index = 12*Td *(TOTL-49)+2*U *U *(0.2+sin(f)) where f=(wind direction 500 -wind direction 850 ), U=wind speed[kts], TOTL=0 if TOTL<49 but, beware, some parameters come with a list of thresholds, that may not be valid in your forecast region (if at all...)...require no physical understanding of the weather situation...dont increase ones understanding either. you can not find out what went wrong and do better next time!

* = will discuss this later on my convective parameters parameterfor prediction ofremarks CAPE (if not available: LIFTED INDEX) instabilitybeware of different parcels that are lifted CAPE RELEASED BELOW 3 KM* low-level instabilitybuoyant parcels close to the surface can cause rapid vortex stretching tornadoes INSTABILITY parameters

my convective parameters parameterfor prediction ofremarks forcing term of differential vorticity advection upward motion, convective initiation upward motion in numerical models may be contaminated by the convection itself.... forcing term of temperature advection upward motion, convective initiation or, alternatively Q-vector divergence or PV-analysis LIFT parameters * = will discuss this later on

my convective parameters parameterfor prediction ofremarks 0-6 km BULK SHEAR convective organisationremark: convective organisation is strongly influenced by the amount of lift as well 0-1 km BULK SHEAR* tornadoes 0-3 KM STORM- RELATIVE HELICITY potential for supercell convection 0-1 KM STORM- RELATIVE HELICITY* potential for tornadoes WIND SHEAR parameters * = will discuss this later on

my convective parameters parameterfor prediction ofremarks MOISTURE AT MID- LEVELS* strong downdrafts if low MOISTURE AT LOW LEVELS* strong downdrafts if lowdeep, dry boundary layers cause evaporative cooling and a high potential for strong wind gusts LCL HEIGHT*tornadoestornadoes unlikely with LCL > around 1500 m WIND SPEED AT 850 hPa* wind gustsvertical transport of horizontal wind speeds (very) relevant for wind speed in downdrafts other parameters * = will discuss this later on

study done at Institute for Marine and Atmospheric Research Utrecht Sounding-derived parameters associated with large hail and tornadoes in the Netherlands My M.Sc thesis research...

Basic idea 1.Find soundings taken in the proximity of severe weather events (here: tornadoes) 2.Find if they have special characteristics (w.r.t. other soundings) method: look at parameters that represent something physical and that have been studied before

Proximity soundings What is a proximity sounding…? Used definition: within 4 hours of the sounding (before or after) within 100 km from a point that is advected by the 0-3 km mean wind from the sounding location at the sounding time

radiosonde observations Dec 1975 – Aug 2003 (thanks to KNMI, DWD, KMI) severe weather reports from Dutch voluntary observers (VWK) Data sets Sinds 1974 Vereniging voor Weerkunde en Klimatologie (VWK)

Data soundings associated with:number hail ( cm) hail (>= 3.0 cm) tornadoes F0 tornadoes F1 tornadoes F2 waterspouts thunder ( only) all soundings67816

Most-unstable CAPE (MUCAPE) Number of events maximum median 75th perc. 25th perc. MUCAPE high with hail; less with tornadoes… US studies: MUCAPE highly variable with tornadoes. Strong tornadoes may occur with low CAPE when shear is high

Most-unstable CAPE released below 3 km A.G.L. MUCAPE<3km high with F0, not with F1+ US studies: Davies (2004) has found a relation between tornado occurrence and high CAPE below 3km (in his study mixed-layer CAPE)...

(most-unstable) LFC height (m) LFC relatively low with tornadoes (esp. F0)… US studies: Davies (2004) has found a relation between low LFC and tornado occurrence

LCL height (50 hPa mixed layer parcel) US studies: Low LCL favors significant tornadoes, e.g. Craven et al. (2002) LCL not sign. diff. between tornadic and thunder

LARGE HAIL F0 F1+ Average soundings note the distribution of parcel buoyancy with height

0-6 km A.G.L. bulk shear (m/s) (1) US studies: strong tornadoes and (very) large hail often occur with supercells. These are associated with >20 m/s 0-6 km shear (e.g. Doswell&Evans, 2003)

0-6 km A.G.L. bulk shear (m/s) (2) likelihood of hail increases with 0-6 km shear, but the majority of hail events occur with moderate shear

0-1 km A.G.L. bulk shear (m/s) 0-1 km shear high with F1, esp. F2 tornadoes... and with wind gusts US studies: strong 0-1 km shear favours sign. tornadoes (e.g. Craven et al., 2002).

0-1 km A.G.L. storm-relative helicity (m 2 /s 2 ) 0-1 km shear high with F1, esp. F2 tornadoes.. US studies: high values favor supercell tornadoes (e.g. Rasmussen, 2003).

MUCAPE and 0-6 km bulk shear are useful predictors for large hail, especially when combined most large (> 2cm) hail in the Netherlands is associated with multicells rather than supercells Conclusions of the study

F1 and esp. F2 tornadoes occur with higher-than- average 0-1 km shear and SRH. F0 tornadoes (and waterspouts) occur with lower- than-average 0-1 km shear values.(MU)CAPE is not extreme with tornadoes and thereby has limited value for tornado forecasting. Conclusions of the study Submitted to Atmospheric Research

MUCAPE released below 3 km / low LFC heights seem to be important for the formation of weaker (and likely non-supercellular) tornadoes…. (but of course we rather want to forecast the stronger tornadoes) LCL heights are probably not as much a limiting factor for tornado development in the NL than in much of the U.S.A. i.e. LCL heights are practically always low enough here for tornadoes Some conclusions

using convective parameters 23th June, 2004 analysis prepared in cooperation with Christoph Gatzen (ESTOFEX) photo: Christian Schöps source: ESTOFEX

23 June, 2004: 500 hPa height, wind speed

23 June, 2004: 850 hPa height, theta-e

23 June, 2004: MUCAPE, deep layer wind shear

23 June, 2004: MUCAPE, low level wind shear

23 June, 2004: LCL height

23 June, 2004: LFC height

Sounding from the action area. It indicates... rather weak CAPE most of it below 3km winds veer strongly with height (indicating helicity) strong low level wind shear In this case, the forecast didnt work out. The favourable veering of wind wind height in the lowest km, was not at all predicted by most numerical models that forecasted SWly winds instead of SEly winds.

Conclusion and highlights the ingredients-based methodology can help to structurize the forecasting process for severe convection the essential ingredients are: latent instability (CAPE) lift vertical wind shear (20 m/s…40 kts is supercell threshold) Convective parameters with a single obvious physical meaning are probably the most useful. Most important for forecasting…. HAILCAPE and convective mode TORNADOES0-1 km shear, SREH and convective mode WIND GUSTS850 hPa wind, dry low or mid-levels and convective mode

References Craven, J. P., H. E. Brooks, and J. A. Hart, 2002: Baseline climatology of sounding derived parameters associated with deep, moist convection. Preprints, 21st Conference on Severe Local Storms, San Antonio, Texas, American Meteorological Society, 643– 646. Davies, J. M., 2002: On low-level thermodynamic parameters associated with tornadic and nontornadic supercells. Preprints, 21 st Conf. on severe local storms, Kananaskis Park, Alberta, Canada, Amer. Meteor. Soc., 558–592. Davies, J. M., 2004: Estimations of CIN and LFC Associated with Tornadic and Nontornadic Supercells. Wea. Forecasting, 19, 714– 726. Fujita, T. T., 1971: Proposed Characterization of Tornadoes and Hurricanes by Area and Intensity, SMRP Research Paper No. 91, University of Chicago. Doswell, C. A. III, and J. S. Evans, 2003: Proximity sounding analysis for derechos and supercells: An assessment of similarities and differences. Atmos. Res., 67-68, 117–133. Rasmussen, E. N., 2003: Refined supercell and tornado forecast parameters. Wea. Forecasting, 18, 530–535.