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Satellite Convection Analysis for Convective Nowcasting

Learn about the SATCAST system for convective initiation nowcasting using satellite data, confidence analysis, and lightning forecasting with MODIS integration. Explore the impact of microwave data and GOES-R risk reduction initiatives in improving convective forecasts.

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Satellite Convection Analysis for Convective Nowcasting

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  1. Convective (and Lightning) Nowcast Products: SATellite Convection AnalySis and Tracking (SATCAST) System John R. Mecikalski1 (Assistant Professor) Kristopher M. Bedka2 Todd A. Berendes1 Simon J. Paech1 and Laci Gambill1 1Atmospheric Science Department University of Alabama in Huntsville 2Cooperative Institute for Meteorological Satellite Studies University of Wisconsin-Madison Supported by: NASA New Investigator Program (2002) NASA ASAP Initiative The NASA SPoRT Initiative

  2. Outline • Current capability: Overview Convective initiation (CI) • Background Error assessments in Daytime CI 0-1 h Nowcasting • Confidence analysis • Incorporation of MODIS information • Discriminant scoring for CI --> QPE • Current & new initiatives: 2006 • Impacts of microwave data toward 0-2 hour QPE forecasting • Nighttime CI forecasting • Lightning (event) & Lightning Initiation forecasting • CI/LI Climatology as f(location, time of year) • GOES-R Risk Reduction (using MSG & MODIS)

  3. How this began… • •

  4. Methods: Convective Nowcasts/Diagnoses How is this done? Determine the necessary data to evaluate convective and lightning initiation from satellite Is satellite data the best?? If so, how can it be used? Why might it be superior to radar? A: Satellites “see” cumulus before they become thunderstorms! A: There are many available methods for diagnosing/monitoring cumulus motion/development in real-time (every 15-min). See the published research on satellite data usage !!! So, once well-read, all the pieces are in place to move the (science) forward in the CI nowcasting arena, with satellite analysis as the centerpiece for 0-1 h CI nowcasting.

  5. Where are we now … • Applying CI algorithm over U.S., Central America & Caribbean • Validation & Confidence analysis • Satellite CI climatologies/CI Index: 1-6 h • Work with new instruments • Data assimilation possibilities

  6. Convective Cloud Mask • Foundation of the CI nowcast algorithm: Calculate IR fields only where cumulus are present (10-30% of a domain) • Utilizes a multispectral and textural region clustering technique for classifying all scene types (land, water, stratus/fog, cumulus, cirrus) in a GOES image • Identifies 5 types of convectively-induced clouds: low cumulus, mid-level cumulus,deep cumulus,thick cirrus ice cloud/cumulonimbus tops,thin cirrus anvil ice cloud

  7. 50% shown “Mesoscale” Atmospheric Motion Vector Algorithm “Operational Settings” New Mesoscale AMVs (only 20% shown) • We can combine mesoscale AMV’s with sequences of 10.7 m TB imagery to identify growing convective clouds, which represent a hazard to the aviation community

  8. CI Interest Fields for CI Nowcasting from Roberts and Rutledge (2003)

  9. 2030 UTC 2100 UTC CI Nowcast Algorithm: 4 May 2003 2000 UTC CI Nowcast Pixels These are 1 hour forecasted CI locations! • Satellite-based CI indicators provided 30-45 min advanced notice of CI in E. and N. Central Kansas. • PODs ~45% at 1 km (FARs ~40%) • NEW Linear Discriminant Analysis methods provide ~65% POD scores for 1-hour convective initiation.

  10. An Example over the Tropics: CI • An example of the CI nowcasting method over Central America: • Real-time • Every 30 min during the day (nighttime coming soon) • GOES (MODIS soon) • RED/GREEN pixels have highest CI probability

  11. “Interest Field” Importance: POD/FAR 8.5-10.7 m (MODIS) > 0° C 3.7-10.7 m (MODIS) > 0° C • Instantaneous 13.3–10.7 um:Highest POD (84%) • Time-trend 13.3–10.7 um:Lowest FAR (as low as 38%) • Important for CI & Lightning Initiation

  12. Use of MODIS in Convective Initiation Forecasts

  13. The lower right shows the supercooled water in green. • Proof of concept for determining the difference between supercooled water and glaciated towering cumulus clouds. • Super-cooled tops: • Lightning indicator as a function of convective environment

  14. New: CI/LI Linear Discriminant Analysis (LDA) Some correlation between a confidence in CI [f(LDA score)] and 30-min dBZ (increase): QPE nowcast • Improved POD of ~65 • and FAR of ~34% • A virtual-radar from satellite

  15. Low correlation High correlation New: CI/LI Linear Discriminant Analysis (LDA) LDA Score LDA Score Number of Interest Fields Radar dBZ t=t+30 min

  16. Outline • Current capability: Overview Convective initiation (CI) • Background Error assessments in Daytime CI 0-1 h Nowcasting • Confidence analysis • Incorporation of MODIS information • Discriminant scoring for CI --> QPE • Current & new initiatives: 2006 • Impacts of microwave data toward 0-2 hour QPE forecasting • Nighttime CI forecasting • Lightning (event) & Lightning Initiation forecasting • CI/LI Climatology as f(location, time of year) • GOES-R Risk Reduction (using MSG & MODIS)

  17. Detecting Convective Initiation at Night • Detection of convective initiation at night must address several • unique issues: • Restricted to 4 km data (unless MODIS is relied upon) • Visible data cannot be used to formulate cumulus mask • Highly-dense, GOES visible winds are unavailable for tracking • Forcing for convection often elevated and difficult to detect (e.g., low-level jets, bores, elevated boundaries) However, the advantages are: a) Ability to use ~3.9 m channel (near-infrared) data (!!!) b) More “interest fields” become available for assessing cumulus cloud development Therefore, new work is toward expanding CI detection for nocturnal conditions, and/or where lower resolution may be preferred (i.e. over large oceanic regions). Wayne Mackenzie, MS student

  18. Detecting Convective Initiation at Night Nighttime CI: Southeast Oklahoma SHV: 3:44 UTC Enhanced 10.7 m

  19. 6.5-3.9 m 13.3-3.9 m Detecting Convective Initiation at Night Use of 3.9 µm channel: 10.7-3.9 m channel difference (Ellrod “fog” product) Evaluation is being done in light of the forcing for the convection (e.g., low-level jets, QG).

  20. Satellite-Lightning Relationships • Current Work: Develop relationships between IR TB/TB trends and lightning source counts/flash densities toward nowcasting (0-2 hr) future lightning occurrence • Supported by the NASA New Investigator Program Award #:NAG5-12536 • Incorporate in NWS Lightning Hazard/Prediction Tool Northern Alabama LMA Lightning Source Counts 2040-2050 UTC 2047 UTC 2147 UTC 2140-2150 UTC kkoooooooookkkkkkkkkkk

  21. Northern Alabama LMA Lightning Source Counts Lightning Initiation Potential 2040-2050 UTC 2140-2150 UTC kkkkkkkkkkkkkkk

  22. CI Climatology Research GOES CI Interest Fields: 21 July 2005 (afternoon) Details: -topography -main updrafts 1 km Resolution …for LI

  23. Hyperspectral: GOES-R & GLM Small wavenumber change results in significant changes in view:  Low-level water vapor  Surface temperature  Subtle cloud growth & microphysical changes LEFT 8.508-10.98 m Band Difference: Red (’s >0) = Ice Comparison between the 10.98 m (right) and 11.00 m (far right) bands: 22 UTC 6.12.2002

  24. For the NWS … Real-time use & evaluation In addition A web-based evaluation is being performed in a post- shift format during July and August 2006. Smoothing...

  25. For the NWS … Real-time use & evaluation

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