Joe Sienkiewicz 1, Michael Folmer 2 and Hugh Cobb 3 1 NOAA/NWS/NCEP/OPC 2 University of Maryland/ESSIC/CICS 3 NOAA/NWS/NCEP/NHC/ Tropical Analysis and.

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Presentation transcript:

Joe Sienkiewicz 1, Michael Folmer 2 and Hugh Cobb 3 1 NOAA/NWS/NCEP/OPC 2 University of Maryland/ESSIC/CICS 3 NOAA/NWS/NCEP/NHC/ Tropical Analysis and Forecast Branch 05/01/12 NOAA Satellite Sciences Week

2 High Seas Warning Categories GALE – knots Force 8/9 STORM – knots Force 10/11 HURRICANE FORCE - >64 knots Force e.php / National Hurricane Center

3 Wind Warning Categories GALE – knotsForce 8/9 STORM – knotsForce 10/11 HURRICANE FORCE - 64 knots and greater Force 12 Tropical Cyclone Warning Categories TROPICAL STORM – knots Force 8-11 HURRICANE - >64 knots Force National Hurricane Center

 Warning focus (wind)  Extratropical and tropical cyclones, orographic enhanced flows, wave generation areas  Cyclones  Structure, intensity, evolution  Performance of NWP analyses, forecasts  Thunderstorms  Wind producers  Larger scale flow  Environment  Assessment of NWP

 Tropical Weather Discussion  Atlantic – MIATWDAT  East Pacific – MIATWDEP  Primary use of AMV products in TWDs  Define and estimate movement/speed of mid/upper level synoptic scale features  Estimate strength of subtropical jet core  Estimate low-level winds ( mb) associated with tropical waves

Ocean Prediction Center Scatterometer winds (ASCAT,OSCAT) Imagery (GOES, MSG, MTSAT) National Hurricane Center Tropical Analysis and Forecast Branch Scatterometer winds GOES AMV Imagery (GOES, MSG, MTSAT)

Water Vapor Image Interpretation: Satellite-Derived Wind Vectors

8 Application of GOES-R Winds Algorithm to GOES-N/O/P Cloud-drift winds derived from 15-minute GOES-13 11um imagery 1000 UTC 22 April 2012 – 0800 UTC 23 April 2012  Since September 2011, we have been routinely generating experimental winds from GOES-13 using the GOES-R winds algorithm (ie., nested tracking)  Setting up processing of experimental winds for GOES-15 (Apr 2012)  Supporting GOES-R PG Activity at SAB/OPC/HPC  Funded PSDI projects in place to replace heritage AMV algorithm running in NESDIS operations with GOES-R Winds algorithm  GOES (funded effort) – March 2013  VIIRS (funded effort) – Dec 2012 High-Level mb Mid-Level mbLow-Level >700 mb

Cloud-drift Winds derived from a Full Disk Meteosat-8 SEVERI 0.60 um image triplet centered at 1200 UTC 01 February 2007 Low-Level >700 mb Using SEVIRI as a Proxy For the Future GOES-R ABI

Cloud-top Water Vapor Winds derived from Full Disk Meteosat-8 SEVERI 6.2um image triplet centered at 1200 UTC 01 February mb mb mb

Application to Simulated ABI Imagery High-Level mb Mid-Level mbLow-Level >700 mb  GOES-R AWG Data Proxy Team has generated a large number of simulated ABI datasets  All ABI bands  Various spatial and temporal resolutions  Simulated datasets have been used by some of the algorithm teams to generate Level-2 products  Simulated datasets will support a number of tests for elements of the GOES-R ground system segment Cloud-drift AMVs derived from a Simulated GOES-R ABI image (Band 14; 11um) triplet centered at 0000Z on 05 June 2005

 Geostationary products still under-utilized resource  OPC  Presently not available (NAWIPS / AWIPS II)  Improve usage  diagnostic for NWP (large scale and cyclone)  Low level winds - relate to near surface winds  TAFB  GOES AMV available in NAWIPS, used  Proxy products  SEVERI and Simulated ABI