Analysis and Prediction Thrust - IP1 Report 2007 Site Visit Presented by Ming Xue and Jerry Brotzge

Outline Detection algorithms in MC&C Nowcasting and integration into MC&C Near-realtime NWP DA and forecasts IP1 cases and morphology studies

MC&C Feature Repository Detection Algorithms KSAO KCYR KRSP KLWE KTLX KFDR ldm2netcdf Reflectivity Velocity KVNX w2merger_refl w2circ w2mdalite w2merger_vel NEXRAD Feature Table casaIngestor Currently running Velocity-data Reflectivity-data Dual Pol-data DebrisSig Debris Sig Table AzShear MDALite Table WindField Shear feature VortDiv LLSD Table Multi-Doppler Table NetRad Circulation Table MR_feature Merged Reflectivity SCIT-CASA Reflectivity Threshold Algorithms (not including velocity-based detection) in the shaped area are running in MC&C currently. Cell Features Storm Cell Table MC&C Feature Repository

SCIT (Storm Cell ID and Tracking)-CASA Running in MC&C - Identifies local maxima in reflectivity data Identifies local maxima in reflectivity data Feature must match size criteria (~2.5km2) If not large enough, will include next lower reflectivity threshold and re-analyze Limit to the number of threshold lowerings allowed Uses thresholds of 5 dBZ increments between 20 and 60 dBZ Reports all features Only features whose min dBZ values are >40 dBZ are passed to the MC&C Colored areas are identified as local reflectivity maxima (or storm centroids) 0043 UTC, 5/9/2007

Local Max Feature (SCIT-CASA) Pros Works well with strong isolated echoes Not fooled by ground clutter or 2nd trip echoes Variable threshold limits and MC&C reporting limits Cons Won’t detect initial echoes if they are too small/weak Allows large regions where reflectivity varies by small values Might not identify storms if only 2 deg elevation surveillance scan data is available

Reflectivity Threshold (RT) and SCIT-CASA RT: Operates on single radar data. Relativistic 2d model, no hard dBZ thresholding. Detects reflectivity echoes as they first appear Complement SCIT Designed to steer radars to important reflectivity areas, not to classify storms. Operates on single radar data, in polar coordinate system. Relativistic 2d model, identifies areas of significance in relation to others contained in the scan. dBZ thresholds are met in areas of a minimum 1 Km radius that are greater than 2 standard deviations above the mean of the data file. No hard dBZ thresholding Crafted specifically to work within MC&C architecture. Detects reflectivity echoes as they first appear unless areas of substantially higher reflectivity already exist in the domain. During widespread, strong, but non-stratiform storms (e.g., squall lines), RT focuses in only on strongest areas, which is not ideal to forecasters. A fix is being tested. 5/27/2007 Click for movie

Linear Least Squares Derivative (LLSD) Azimuthal Shear 1 deg elev LLSD Shear Velocity Reflectivity 2 deg elev Improved shear estimates (compared to MDA) Less subject to noise Calculates both rotational shear and divergence Filter kernel must be matched to size of feature being detected Requires feature detector for automated use in the MC&C

Detection Plan for Spring 2008 Data Quality Control Remove residual clutter/noise Use dual-pol data for identification of non-met targets – RhoHV is being used. Testing and adjustments with/for IP1 data Thresholding and identification of bad detections with MDAlite Modify LLSD to run at multiple scales to identify both mesocyclones and tornados May also need testing with larger samples of simulated data, produced by CASA radar emulator Activate velocity algorithms (MDAlite and LLSD) and WSR-88D detection in MC&C and evaluate their impact Run velocity algorithms in realtime in spring 2008 Future Work Will be running in realtime in spring 2008.

Nowcasting Systems Growth-Decay Storm Tracker (GDST) (Wolfson et al 1999, MIT Lincoln Laboratory) Multiscale Storm Identification and Forecast (MSIF) in NSSL WDSS-II system (Lakshmanan et al. 2003 JAR) Thunderstorm Identification, Tracking, Analysis and Nowcasting (TITAN) (Dixon & Wiener 1993, NCAR) Dynamic and Adaptive Radar Tracking of Storms (DARTS): a spectral based real time nowcasting system achieves robust global estimation of the spatially non-uniform motion fields Designed to take advantage of CASA high spatial and temporal resolution data runs very fast   author =       {Lakshmanan et al. 2003 JAR), V. and Rabin, R. and DeBrunner, V.},   title =        {Multiscale Storm Identification and Forecast},   journal =      {J. Atm. Res.},   year =         2003,   volume =       67,   pages =        {367-380},   publisher =    {Elsevier},   address =      {Shannon, Ireland},   month =        {July}

Example: DART v.s. GDST with IP1 Data Aug 15 – Aug 16, 2006 5 min forecast DARTS 5 min forecast GDST Observed GDST DARTS DARTS GDST GDST DARTS Critical Success Index Probability of Detection False Alarm Rate

Nowcasting Goal, Status and Plan Goal: To produce realtime reflectivity-based forecasts up to 60 min, and use 1-5 min forecast in MC&C Status: Real time experiments had been done by streaming archived CASA data. DARTS nowcasting performance is similar to GDST but uses significantly less computation time. Preliminary results show improvement in performance in DARTS with better spatial / temporal resolution. Hour-long nowcasting will be implemented in real time for Spring 2008 season, for use/evaluation by forecasters. Possible use of nowcasting product in MC&C in spring 2008. will evaluate impact carefully.

2007 Spring NWP Experiments Goals: Examine, in near realtime, the impact of IP1 data on convective storm forecast; collect data and provide a baseline benchmark for post-real time case studies. Four 6-hour 1-km resolution forecasts daily, assimilating 1. Both 4 CASA IP1 and 6 WSR-88D radars 2. WSR-88D radars only 3. CASA IP1 radars only 4. No radar data Using 280 processors on OU OSCER supercompuer (~4 hours for each forecast) Forecast products posted at http://www.caps.ou.edu/wx/casa

Forecast Configurations 22UTC 00 UTC 04 UTC Example 40-min Assimilation & 5.5-hour forecast Dx = 1 km 600x540x20 km Start time determined daily by the time when convection initially develops within or when an existing system enters the IP1 network. Run only on days with echoes in IP1 network. Actual runs are done in quasi-real time. Takes up to 18 h to complete all four forecasts.

Assimilation Strategy 2210 2220 2230 04 2200 00 IAU 01 02 03 5.5-hour Forecast 40-min Assimilation 2150 Using ADAS and its cloud analysis package Reflectivity data were used, but not radial velocity (parallelization of software not ready) 10-min assimilation cycles over 40 min window, with Incremental Analysis Update (IAU) Prediction using ARPS Special handling and QC of IP1 sector data (data, form, and scanning new) ETA 12-km analysis and forecasts used as analysis background and BC

2007 Spring Cases Date Time Weather Summary 1 10 April 23 Z Cluster of cells, one rotating with funnel 2 13 April 21 N-S Oriented Squall Line Moving W-E 3 17 April 19 Synoptic Low, TRW in Okla, Severe TRW in N-Tx 4 24 April 16 Squall Line developing & moving ESE 5 27 April 18 Weak Convection in IP1 ahead of cold front 6 1 May Broken line cells developing in IP1 & moving SE 7 3 May Cells develop in IP1, move E, form line in E Okla 8 7 May 05 Squall line forms in IP1, additional cells in IP1 later 9 8 May 07 E-W line convection in IP1 10a 23 Cells form ahead of squall line in IP1, rotation after 00z 10b 9 May 01 Additional start time during the 1st rotating cells within IP1 11 11 May 22 E-W line of TRW moving S, skirts E side of IP1 12 15 May 14 Weak rain showers on E-W cold front 13 24 May Nocturnal Squall line moving from NW to SE 26 May 20 Clusters of moderate-to-heavy cells moving from SSW to NNW 15 30 May 10 Strong nocturnal squall line with high winds moving from NW to SE 1 June 09 Decaying nocturnal squall line moving from W to E across network 17 Cells develop within IP1, severe warnings within network 3 June Squall line with severe reports in IP1, declines after about 13 UTC

Verification. 11:00pm (0400 Z) May 8-9, 2007 A series of low-level © Patrick Marsh 11:00pm (0400 Z) May 8-9, 2007 A series of low-level circulations. NWS Tornado Warnings: 7:16pm, 7:39pm, 8:29pm 9:54pm 8:30pm (0130Z) © KSWO TV 7:21pm (0021Z)

Impact of IP1 Data on Low-level Analysis 0050 UTC 9 May 2007 Analyzed Hydrometeors Converted to Reflectivity Hgt = ~250 m AGL WSR-88D Only NetRad & WSR-88D

N-S Vertical Cross-Section 5km 5km WSR-88D Only WSR-88D & NetRad 0050 UTC 9 May 2007

24-min Prediction ~ 600 m AGL KCYR Indicated Circulation Vorticity centers WSR-88D Only WSR-88D & IP1 Positive impact on low-level vorticity prediction with ADAS and even without Vr data

04 UTC May 09 Forecast Animation Used both IP1 and 88D data Link to movie – put a picture here 3 h 10 min forecast Click on figure for movie

Near-realtime NWP Accomplishments Completed MPI of ADAS with cloud analysis Pre-processing of CASA radar data Data selection scripts Data I/O and Quality Control (ref & vel) Remapping and qr assignment Reflectivities are well-handled in model Automated assimilation system operational Showed preliminary positive impact of including IP1 data Provide a set of baseline forecasts for post-realtime case studies, using better DA methods

Near Future Plan for NWP Quantify the impact of IP1 data on spring 2007 forecasts Test additional benefit of Vr data from 2007 cases Parallelize ARPS 3DVAR and optimize other programs and prepare for spring 2008 realtime experiments Perform detailed case studies and refine assimilation capabilities Secure computational resources to run 88D+IP1 case in real time for use by forecasters in spring of 2008 Plan on comparing realtime NWP and nowcasting in spring 2008

Evaluate higher temporal/spatial resolution. KFDR 02:16:10 UTC KCYR 02:16:39 UTC © Val Castor, News9 Higher Resolution Data Nov 30, 2006

Evaluate higher temporal/spatial resolution. 12:36:42 UTC 12:37:30 UTC © Val Castor, News9 Higher Resolution Data April 24, 2007

KLWE at 1.0 deg elevation, 21km range (~200m AGL) Evaluate ability to scan adaptively. May 8-9, 2007 KLWE at 1.0 deg elevation, 21km range (~200m AGL) 7:26pm 7:28pm 7:32pm 7:34pm 7:36pm 7:38pm 7:39pm © KSWO TV 7:23pm 7:28pm 7:34pm 7:39pm 7:40pm

Evaluate collaborative scanning. May 9, 2007 KCYR © Val Castor, News9 KLWE Higher Resolution Data 01:16:28UTC

Verification. 2324 UTC 14.0° 11.0° 9.0° April 10, 2007 7.0° 3.0° 5.0° 7.0° 9.0° 2.0° 11.0° 14.0° © Val Castor, News9 April 10, 2007 Cluster of isolated severe storms. Photo taken near Elgin, OK.

Verification. 11:00pm May 8, 2007 Series of low-level circulations. © Patrick Marsh 11:00pm May 8, 2007 Series of low-level circulations. NWS Tornado Warnings: 7:16pm, 7:39pm, 8:29pm 9:54pm 8:30pm © KSWO TV 7:21pm