Convective Initiation Studies at UW-CIMSS K. Bedka (SSAI/NASA LaRC), W. Feltz (UW-CIMSS), J. Sieglaff (UW-CIMSS), L. Cronce (UW-CIMSS) Objectives Develop day/night convective initiation nowcast methodology for use with GOES-12, MSG SEVIRI, and future GOES-R ABI imagery based on a box-average approach Explore cloud object tracking methods to facilitate product validation and improve convective initiation nowcasting especially for rapidly moving clouds Accomplishments UW-CIMSS CI nowcast product suite (UWCI) was evaluated within the NOAA Storm Prediction Center Spring Experiment. UWCI was one set of products supplied by the GOES-R Proving Ground to SPC Completed UWCI validation with MSG SEVIRI study using cloud-to-ground lightning data over South Africa GOES-12, MSG SEVIRI, and synthetic GOES-R imagery has been processed within the Warning Decision Support System-Integrated Information (WDSS-II) to investigate the applicability of this system for current and future CI nowcast activities. NOAA recently approved 2 years of funding for continuing work on this effort

UWCI Box-Average Nowcast Product Description Current and future imagers are operating in 5-min rapid scan, so cumulus do not move very far between images -For 50 CI cases over CONUS, average cloud movement=5 km/5 mins, 1 SD=2 km/5 mins One can disregard cloud motions by time-differencing “box-averaged” cloud top properties to determine CI Compute mean IRW BT for cloud categories identified by day/night cloud type product over 7x7 and 14x14 pixel SEVIRI IR pixel boxes Employ rules to eliminate situations where cirrus anvil moves into box with developing cumulus Compute cloud-top cooling rate, minimum threshold at -4 K/15 mins Use mesoscale NWP stability analysis to minimize CI nowcast false alarm from cooling of non-convective cloud. Most unstable LI used to capture surface-based and/or elevated storms Use cloud typing information with cooling rates to further minimize false alarms and develop confidence indicators for convective initiation -Filter out isolated noisy nowcast pixels -Cat 1: Cooling liquid water clouds -Cat 2: Cooling supercooled/mixed phase -Cat 3: Cooling with recent transition to thick ice cloud Though the method is optimized for 5-minute imagery, the examples and validation to the left show results when applied to 15-minute SEVIRI imagery M. Pavolonis (NOAA/NESDIS) Day/Night Cloud Microphysical Typing 15-Min Cloud Top Cooling CI Nowcast Using 15-min Data 45-min Accumulated Cooling 45-min Accumulated CI Nowcast Channel 9 BT At End Of 45-min Period Channel 9 BT 1 Hour Later SEVIRI Channel 9 IR Window BT Lightning Initiation POD (133 LI cases): 76% Lightning Nowcast FAR (10214 pixels): 29% Lead time decreases with cloud glaciation Product Validation

UW-CIMSS Participation in NOAA Storm Prediction Center Spring Experiment: UWCI Product Evaluation Time Accumulated Cloud Top Cooling Rate Animation A current CI nowcast method (Mecikalski and Bedka (MWR, 2006)) has focused on the use of visible imagery to objectively identify cumulus clouds and compute cloud motions, rendering this a daytime only product The UWCI nowcast product suite has been applied to GOES-12 imagery, as the Pavolonis cloud microphysical typing (submitted to JAS, 2009) can operate during day and night despite the more limited spectral information from current GOES The UWCI products were evaluated at SPC over a 1 month period as part of the GOES-R Proving Ground (see Chris Siewert), since the UWCI represents an algorithm that will have optimal performance in the GOES-R era - Products are also being evaluated at a local National Weather Service (NWS) office and NOAA/NESDIS Through these evaluations, the UWCI has been shown perform quite well, offering significant advantages in 1) day/night coverage, 2) processing speed, and 3) product spatial coherency/accuracy over current multiple interest field daytime-only methods Limitations and weaknesses of UWCI product suite: Thin cirrus moving over small cumulus and expanding anvil edge can induce false alarm Product limited to 15-min or better resolution imagery Little to no CI nowcast lead time in very moist, weakly capped environments. This is a likely issue with any IR-based CI nowcast product Contact Wayne Feltz for detailed information on UWCI algorithm

Exploring the Use of Object Tracking for CI Nowcasting UW-CIMSS and the University of Alabama in Huntsville (UAH) are working toward development of object- based methods for CI nowcasting in the GOES-R ABI era, using current GOES-12 and MSG SEVIRI as proxies for GOES-R UW-CIMSS is experimenting with the Warning Decision Support System-Integrated Information (WDSS-II, Lakshmanan et al. (J. Tech., 2009), (WAF, 2007)) to compute cloud-top cooling rates and cloud-top microphysical trends to produce object based CI nowcasts WDSS-II can handle non-overlapping clouds and can project object locations into the future Radar reflectivity can be remapped to the satellite resolution/projection and carried along with the satellite- derived objects for reliable product validation This capability is not available with current pixel-based CI nowcast methods which causes significant difficulty in evaluating current product accuracy over large scenes and numerous cases MSG SEVIRI Example GOES-12 Example