Neil Taylor1 and Bill Burrows2 Using GEM REG Output for Forecasts of Convective Initiation on the Canadian Prairies Experimental Techniques Under Development in the Hydrometeorology and Arctic Lab (HAL) Neil Taylor1 and Bill Burrows2 1Hydrometeorology and Arctic Lab 2Cloud Physics and Severe Weather Research Section / Hydrometeorology and Arctic Lab PASPC Spring Workshop 5/7 May 2009

Outline Introduction and review from 2008 Some parameter relationships to observed lightning from 2007 and 2008 convective seasons Working towards objective forecasts of convective initiation – combined fields Preliminary objective verification of combined fields Summary / Future work

Introduction Timing and location of convective initiation (CI) is of primary importance to forecasters during the summer months On short timescales, and once convection is underway, observational data are the key to success On longer timescales, and to fill in data voids, an (intelligent) integration of observational and NWP data can be used GEM REG will not explicitly resolve storm-scale processes but may help identify CI and storm-supporting environments Can we apply scientific understanding of CI to available model data to generate (better) objective first-guess convective initiation forecasts? That will be consistent with forecaster conceptual models and observed data and will not replace a rigorous convective analysis / diagnosis / prognosis In the future, can these forecasts then be integrated into the next generation of forecast production tool / nowcasting system?

Review Climatological studies suggest the troposphere is conditionally unstable on most days during the summer months ABL processes are important for CI Observational and modeling studies on CI suggest that thermodynamic and kinematic processes related to CI are linked CI has long been associated with convergence boundaries (70% or more of storms associated with detectable boundaries, e.g., Wilson and Schreiber 1986) can influence local climatology, tornadogenesis & other severe weather We have targeted the following with respect to CI: ABL water vapour (including moisture depth) ABL convergence (including convergence depth) Low-level wind shear and buoyancy (affecting parcel trajectories in / near the ABL) Convective inhibition

ABL Moisture Higher Td (mixing ratio) can promote CI and lead to stronger updrafts Lifted parcels entrain dry air below cloud base ML lifting attempts to account for this deeper mixed moist layers should contribute to less entrainment and stronger ABL updrafts Depth of moisture is an important factor for CI Consider a Surface-Based Parcel LCL LFC Shallow ABL Moisture Deep ABL Moisture Lifting parcels using a mean layer mixing ratio is an attempt to account for dry-air entrainment below cloud base. Unsaturated lifted parcels will entrain dry air A deep, well-mixed ABL will reduce sub-cloud entrainment => stronger updrafts

ABL Convergence Convergence boundaries can act to provide lift and deepen moisture Strength of convergence => strength of ABL updraft Boundaries associated with secondary circulations Divergence below LFC can offset low-level convergence Parcels have a better chance of reaching their LFC if they remain under the influence of low-level convergence (e.g., Ziegler and Rasmussen 1998) Both magnitude and depth of convergence are important factors for CI

ABL Convergence Divergence occurring below the LFC can weaken ABL updrafts and inhibit or delay CI LFC Convergence Divergence Convergence boundaries are often associated with secondary circulation Convergence locally deepens moisture

ABL Convergence Deep Convergence Divergence LFC Deep layer convergence acts to reduce divergence below the LFC and acts to maintain the influence of low-level convergence (i.e., deeper lift) on ascending parcels thus promoting CI

Low-Level Vertical Shear Vertical shear below the LFC can act to tilt parcel trajectories downshear and increase entrainment (e.g., Markowski et al. 2006) Updrafts should remain vertical and deeper if associated with convergence and if shear on either side of the boundary is equal in magnitude (Rotunno et al. 1988) Applies for both stationary and moving boundaries Shear near and just above the LFC can act to tilt updrafts downshear to delay CI and storm organization Strong shear below the LFC and near and just above the LFC may act to delay or inhibit CI If updrafts persist this shear may act to enhance storm organization over time

Low-Level Vertical Shear Weak shear near the LFC promotes deeper penetration of ABL updraft and organized convection Strong shear near the LFC (within 2 km ?) may delay or inhibit CI and organized convection LFC Vertically oriented updraft minimizes dry air entrainment below cloud base As trajectories are tilted parcels may entrain more dry air to reduce buoyancy and weaken updrafts Weak Shear Below LFC Strong Shear Below LFC A role of convergence boundaries may be to promote vertical updrafts (Markowski et al. 2006) to support CI

Progress To Date… In 2007 a suite of NWP fields were introduced for preliminary consideration and evaluation in operations Consisted of new fields targeting the concepts previously mentioned and a number of severe weather forecast fields that were previously unavailable (at least hourly) Preliminary and informal evaluation conducted on RSD in 2007 Fields available in 2008 and used in support of UNSTABLE operations (15 km, 2.5 km and 1.0 km GEM) – but not yet formally evaluated Parameter values interpolated to CG lightning flashes in space and time using data from May-Sep 2007 Results and subjective estimates used to define combined fields associated with observed lightning Previous and new combined fields interpolated to observed CG flashes using 2007 and 2008 data (1,865,694 CG flashes) Preliminary objective verification underway Real-time subjective evaluation on RSD in 2009

New Combined Fields Moisture Supply and Depth Depends on 50 mb mean Td Mixed Moist Layer Depth BLUE 50 mb Td ≥ 4 °C Moist. Depth ≥ 200 m GREEN 50 mb Td ≥ 8 °C Moist. Depth ≥ 500 m YELLOW 50 mb Td ≥ 10 °C Moist. Depth ≥ 750 m RED 50 mb Td ≥ 12 °C Moist. Depth ≥ 1000 m

New Combined Fields Convergence and Depth Depends on surface divergence (SDIV) convergence depth (COND) ratio of convergence depth to MLLFC height (RCLF) BLUE SDIV ≤ -3x10-5 s-1 GREEN SDIV ≤ -5x10-5 s-1 COND ≥ 500 m YELLOW SDIV ≤ -10x10-5 s-1 COND ≥ 1000 m RCLF ≥ 0.5 RED SDIV ≤ -15x10-5 s-1 COND ≥ 1500 m RCLF ≥ 0.75

New Combined Fields Low-Level Shear and 0-3 km SBCAPE Depends on 0-MLLFC Bulk Shear (0-MLLFC Shr) LFC + 2 km Bulk Shear (LFC+2 Shr) 0-3km surface-based CAPE (SBCAPE) Most unstable CAPE (MUCAPE) ≥ 100 J kg-1 BLUE 0-MLLFC Shr ≤ 40 kt LFC+2 Shr ≤ 25 kt GREEN 0-MLLFC Shr ≤ 30 kt LFC+2 Shr ≤ 15 kt 0-3 SBCAPE ≥ 75 J kg-1 YELLOW 0-MLLFC Shr ≤ 20 kt LFC+2 Shr ≤ 10 kt 0-3 SBCAPE ≥ 125 J kg-1 RED 0-MLLFC Shr ≤ 10 kt LFC+2 Shr ≤ 5 kt 0-3 SBCAPE ≥ 200 J kg-1

New Combined Fields Convective Inhibition Depends on Most unstable CIN (MUCIN) Difference in MULFC and MULCL height (MULFC-MULCL) Most unstable CAPE (MUCAPE) BLUE MUCIN ≤ 100 J kg-1 MULFC-MULCL ≤ 1000 m GREEN MUCIN ≤ 50 J kg-1 MULFC-MULCL ≤ 500 m MUCAPE ≥ 0 J kg-1 YELLOW MUCIN ≤ 25 J kg-1 MULFC-MULCL ≤ 250 m MUCAPE ≥ 100 J kg-1 RED MUCIN ≤ -1 J kg-1 MULFC-MULCL ≤ 100 m MUCAPE ≥ 250 J kg-1

New Combined Fields Objective CI Forecast Uses selected components of previous fields Moist. Depth SDIV COND RCLF MUCIN MULFC-MULCL MUCAPE 0-3 km SBCAPE 0-MLLFC Shear MLLFC+2 km Shear

Some Preliminary Verification Combined fields were also interpolated to observed CG lightning flashes (nearest grid point value) using 2007 and 2008 data from 1 May to 30 Sep Contingency tables were constructed to evaluate POD, FAR, CSI and other parameters for comparison with existing objective forecasts of thunderstorms Kain-Fritsch deep convection parameterization scheme A pseudo-SCRIBE method (total 1 hr precipitation ≥ 0.2 mm and Showalter Index ≤ 0 – does not include use of 30% PoP as in SCRIBE) Cloud Physics Thunder Parameter (Bright et al. 2005) to determine if the “environment” will support lightning Parameters designed to target CI Working on verification of CI-only flashes Are certain time periods more useful than others (e.g., for SFC-based storms)? Model inability to specify “right place, right time” influences objective verification scores (e.g., position / timing of convergence features, thermal or other features aloft, etc.) => subjective verification req’d

Probability of Detection 12 UTC Run: T+3 (T+1) to T+18 for 2007 (2008) Good POD Bad POD

False Alarm Ratio

Critical Success Index

POD By Hour: Low-Level Shear and 0-3 km SBCAPE Marked Improvement in Typical CI Period

FAR By Hour: Low-Level Shear and 0-3 km SBCAPE Some Improvement in Typical CI Period

CSI By Hour: Low-Level Shear and 0-3 km SBCAPE Marked Improvement in Typical CI Period

Future Work Real-time subjective verification of parameters will be main focus of RSD work in 2009 Verify parameters against CI-only flashes (CI flash identification under development) Design fields targeting elevated convection specifically Generate hourly fields incorporating surface observations (a poor man’s RUC system) to move towards a more useful nowcasting tool Incorporate selected predictors into a new statistical lightning forecast Formulate statistical forecasts of CI (similar approach to existing statistical lightning forecasts) Application to ensemble forecast data (?) Exploit this dataset of lightning-correlated NWP parameter values to characterize GEM REG behaviour (e.g., regional, SFC-based vs. elevated storm environments, etc.)

Summary GEM REG (or other models) won’t consistently pinpoint CI (model-generated cold pools, boundaries in wrong place / wrong time) but may provide useful information about the mesoscale environment Parameters have been developed to characterize processes in the ABL that have been shown (in reality) to be important for CI New combined fields will be available to operations in 2009 Keep in mind these are still be verified / adjusted – experimental only If you do use them please let me know what you think Interpolation results suggest some preferred parameter values that may be useful for forecasting lightning / CI Preliminary objective verification of combined fields indicates reasonable POD but poor FAR CSI poor for all parameters KF and pseudo SCRIBE methods => low POD but slightly better FAR Some improved stats during typical CI period for daytime convection