1 / 40

On the diagnosis of deep convection

On the diagnosis of deep convection. Richard (Rick) Jones SWFDP Training Workshop on Severe Weather Forecasting Bujumbura, Burundi, Nov 11-16 , 2013. Overview . Overview of the key ingredients of deep convection Key stability indices and precipitable water (PW) or total column water TCW

aquene
Download Presentation

On the diagnosis of deep convection

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. On the diagnosis of deep convection Richard (Rick) Jones SWFDP Training Workshop on Severe Weather Forecasting Bujumbura, Burundi, Nov 11-16 , 2013

  2. Overview • Overview of the key ingredients of deep convection • Key stability indices and precipitable water (PW) or total column water TCW • PW is the prime driver of convection • Forecast of deep convection and limits of predictability

  3. Basic Ingredients • Source of moisture best described by precipitable water (PW) • Sustained PW plumes are often associated with prolonged and record/near record events • related to convectively available potential energy • Method to lift the air • Topography – upslope • Density boundaries fronts; sea-breeze fronts • Instability -> maximize lift & sustain development

  4. Classic Stability forecast Indices & Methods • The K-index • The Totals Totals Index • The Lifted Index • Showalter Stability index (more mid-latitude) • CAPE & CIN

  5. The K-Index Based on 850 to 500 hPa lapse rate to identify convective and heavy-rain producing environments as it accounts for moisture. With contribution of 850 hPa dew point and 700 hPadewpoint depression KI = (T850-T500)+Td850-(T700-Td700) KI = (T850-T500)+Td850-(DD700)

  6. KI normally above ~28-38 • KI good for potential areas of convection • Related to heavier rainfall when have lift and moisture • Limitations when terrain above 850 hPa • Good in models and in soundings

  7. Climate Prediction Centre Africa • http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/africa/africa.shtml

  8. KI NCEP

  9. PW

  10. Using the K-index • Heavy rainfall  combination of instability and deep moisture • Favors values of K-index upper 20s to mid 30s. • Still need deep moisture and lift to get convective response • Sample values tropical (Laing 2004)

  11. Totals Totals Index (TTI) • Stability relative to 850 hPa and 500 hPa • 2 components: • Cross Totals: CT = Td850 – T500 • Vertical Totals: VT = T850 - T500 TTI = (Td850 + T850 ) – 2T500 • Focus on instability between 850 and 500 hPa with a component of moisture at 850 hPa

  12. TT

  13. Lifted Index (LI) • Lifted index is based on a parcel reaching the Lifting condensation level (LCL) then adiabatically lifting it to 500 hPa. • It is often surface or moist boundary layer based • Accounts instability based on difference LI = Tlift- T500

  14. LI • Areas Low LI often have convection • LI < 0 is a good starting point • LI often related to CAPE and as we will see and CAPE often relates to Precipitable water

  15. LI

  16. Showalter Stability Index (SSI) • SSI similar to Lifted index but based an 850 hPa parcel reaching the Lifting condensation level (LCL) then adiabatically lifting it to 500 hPa. • It is often surface or moist boundary layer based • Accounts for instability based on difference SSI = Tlift- T500

  17. The Power of Convective Available Potential Energy (CAPE) • On energy diagram • Tephi or Skew-T area proportional to energy • Integrated value and like LI a theoretical parcel is lifted adiabatically from the LCL until the equilibrium level is reached. • CAPE: convective available potential energy • Release of energy produces deep updrafts • Greater the area stronger the updraft • Can have fat or skinny CAPE

  18. CIN: convective inhibition • Another equal area value based on Tephi- or Skew-T diagram • CIN is negative and represents stability and the lift must be able to over to overcome it unless it is diminished

  19. CCl convective condensation level LCL lifting condensation level

  20. LFC and LCL • See LFC2

  21. CAPE

  22. CAPE and updrafts • CAPE may also be related to updraft velocity via the relation Wmax = sqrt(2*CAPE) • For example a CAPE of 2500 J/kg, the maximum updraft velocity would be about 71 m/s!! • In reality, water loading, entrainment, and other factors can reduce Wmax by as much as a factor of 2.

  23. CAPE

  24. Direct Link CAPE & LINE US based study CAPE ~1200JKg-1 with LI <0

  25. NOAA NWS forecast soundings

  26. MOGREPS soundings

  27. Hail • Subtract the freezing level from the CCL. This represents the depth of the cloud from its base up to the freezing level. Call this a (hPa) • Subtract the EL from the freezing level. This represents the depth of the cloud from the freezing level up to its top. Call this b (hPa) • Determine the cloud depth ratio a/b. • On the nomogram, find the cloud depth ratio on the vertical axis and the freezing level on the horizontal axis and plot the point. For points that plot above the diagonal line, hail is unlikely, and vice versa. • (CCL - T0) / (T0 - EL)

  28. Other Parameters Associated with heavy rainfall and convection • Precipitable water (PW) • Main driver of convection related to rainfall and convection • Equivalent potential temperature • Vertical Velocity • Estimated from CAPE for updraft speed • Areas of ascent in Numerical guidance which could favor releasing instability

  29. Precipitable water is the main driver • Need to know • when PW is abnormally high • High PW source regions • PW often a proxy for CAPE • High CAPE is often co-located with high PW values • Heavy rainfall almost always associated with PW plumes

  30. Equivalent Potential temperature • Also known as pseudo-equivalent potential temperature is attained by parcel is lifted to the LCL and taken up a pseudo-adiabat (moist) to the level where air dries out and then dry adiabatically to 1000 hPa (the reference pressure). • Normally qe increases with height. • Convection it decreases with height • Can use qe • In vertical for stability • Horizontal for boundaries which could trigger convection

  31. qe

  32. NCEP qe • Produced in Plan view • 925, 850, 700, 500, 300 and 200 hPa • Should show boundaries • Low over high values could favor convection • CAPE easier to find convective instability

  33. NCEP qe

  34. Skew-T NCEP GFS profiles at: http://www.cpc.ncep.noaa.gov/products/african_desk/cpc_intl/skewt/gfs_profiles.shtml

  35. Limitations • Indices are computed with fixed levels • 850 hPa surface may be under ground • This impacts KI,TTI and need to modify to a level above terrain • Indices • Will vary from grid point to point • Model resolution will impact • The details • And what we can predict  next slide

  36. Salient Points • EFS and global models • are too course for features which can really impact the local and regional weather • Smooth out terrain features • Smooth out finer scale features • Flooding and severe weather events are typically meso scale features • Finer resolution models and Local Area Models, short range EFS (see next slide) play a valuable role in filling the gaps • Diagnosis of stability can help in many cases

  37. UK LAM

  38. Review/summary • Overview of the key ingredients of deep convection • Key stability indices and precipitable water (PW) • PW main driver • Forecast deep convection and limits of predictability

  39. References Convective Indices • Laing, Arlene G. (2004) Cases of Heavy Precipitation and Flash Floods in the Caribbean during El Niño Winters. Journal of Hydrometeorology. Volume 5, Issue 4 (August 2004) pp. 577-594 • N Ravi, U C Mohanty, O P Madan, R K Paliwal. (1999) Forecasting of thunderstorms in the pre-monsoon season at Delhi. Meteorological Applications6:1, 29-38 • UCAR Comet: https://www.meted.ucar.edu/index.php

More Related