EOS Direct Broadcast Real-Time Products for the US National Weather Service
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1 EOS Direct Broadcast Real-Time Products for the US National Weather Service Liam E. Gumley,, K. Strabala, J. Gerth,, S. Bachmeier, R. Dengel,, S. Dutcher, and J. Robaidek University of Wisconsin-Madison, USA 16th International TOVS Study Conference Angra dos Reis, May 2008 University of Wisconsin-Madison 1
2 EOS Direct Broadcast Activities at SSEC, UW-Madison Objectives: Acquisition and processing of EOS Terra and Aqua direct broadcast (DB) data. Distribution of data to customers in real-time. Development of software for data processing. Accomplishments: Have acquired more than 20,000 Terra and Aqua passes. MODIS, AIRS, and AMSR-E Level 1B data, browse images, and Level 2 products are produced automatically and made available via anonymous FTP and the Web. IMAPP MODIS/AIRS/AMSR-E software now in use in on every continent. Funding: NASA, NOAA IPO University of Wisconsin-Madison 2
3 Major Customers for EOS Direct Broadcast Data from SSEC National Weather Service Imagery for Forecasters Naval Research Lab Monterey NexSat Website Product Development Canadian Ice Service Ice Analyses NOAA Great Lakes Environmental Research Lab JPEG and GeoTIFF images for Great Lakes NASA/Environmental Protection Agency IDEA Project L1B data and images for air quality forecasts University of Wisconsin-Madison 3
4 University of Wisconsin-Madison 4
5 NASA/EPA Air Quality Monitoring and Forecasting MODIS Aerosol Optical Depth and Surface PM2.5 integrated with Trajectory Model University of Wisconsin-Madison
6 MODIS Today: Google Earth Integration University of Wisconsin-Madison 6
7 MODIS Today: Google Earth Integration Images available within 60 min. University of Wisconsin-Madison 7
8 SSEC Direct Broadcast Processing System: Schematic University of Wisconsin-Madison 8
9 SSEC Direct Broadcast Processing System: Data Flow University of Wisconsin-Madison 9
10 MODIS Products for the US National Weather Service SSEC began routine insertion into NWS Central Region data feed on 30 June Current feed consists of: MODIS L1B Bands 1 (.86 micron), 7 (2.1 micron), 26 (1.38 micron), 20 (4.0 micron), 27 (6.7 micron) and 31 (11 micron) Cloud Phase, TPW, Cloud Top Temperatures, Fog, SST, NDVI, LST Keys to success: Provide something better or new to forecasters (e.g., higher resolution) Must be delivered in a format that can be accepted by AWIPS Must have a person at the forecast offices to champion the data Steve Hentz, Lead Forecaster, NWSFO MKE University of Wisconsin-Madison 10
11 AWIPS: The NWS Display System AWIPS Advanced Weather Interactive Processing System Main AWIPS display tool is known as D2D Display 2 (Two) Dimensions University of Wisconsin-Madison 11
12 SSEC Real-time Products: Value to NWS Forecasters Near-term (less than 12 hours) forecasts Diagnosing heavy precipitation potential Total Precipitable Water (TPW) Determining precipitation type Snow or freezing drizzle? Short-term (12 to 36 hours) forecasts Areas of fog formation Temperatures in lakeshore areas Post-event analysis Temperature of significant convective cells Aviation Small-scale orographic turbulence Climatology Diagnosing areas of accumulated snow Formation of ice on sizeable lakes and other waterways Marine Wind shift on Great Lakes University of Wisconsin-Madison 12
13 CIMSS/SSEC AWIPS Imagery Distribution Network Davenport, Iowa La Crosse, Wisconsin Milwaukee, Wisconsin Riverton, Wyoming Reno, Nevado Indianapolis, Indiana Billings, Montana Springfield, Missouri Aberdeen, South Dakota Wichita, Kansas Green Bay, Wisconsin Duluth, Minnesota Minneapolis, Minnesota Spokane, Washington Des Moines, Iowa Kennedy Space Center University of Wisconsin-Madison 13
14 National Weather Service: Kennedy Space Center NWS at KSC began using MODIS real-time products from SSEC in Nov to support NASA Space Shuttle launch and landing forecasts. MODIS Sea Surface Temperature (SST) near to shore helps to forecast duration of rain showers at the Cape. MODIS SST in AWIPS NWS Radar University of Wisconsin-Madison 14
15 Milwaukee Area Forecast Discussion MAIN SHORT TERM FORECAST PROBLEM IS EAST FLO W AND MARINE LAYER INFLUENCE OVER EASTERN WISCONSIN...AND DENSE FOG POTENTIAL IN THE WEST. THINK MOST OF THE DENSE FOG WOULD BE IN THE RIVER VALLEYS...WITH A TENDENCY FOR PATCHY FOG AND SO ME STRATUS AGAIN IN THE EAST WITH MORE OF A GRADIENT. M O DIS 1 KM IMAGERY LAST NIG HT S H O W E D THE DE N S E FO G IN LO N E R O C K AN D B O S C O B EL W A S C O NFIN E D T O T HE IM M E DIATE WIS C O N SIN RIVER VALLEY...IMPORTANT INFORMATION. THE LOCAL RIVER VALLEY DENSE FOG IS NOT SEEN IN THE NORMAL 2 KM GOES.(HENTZ/MKX) University of Wisconsin-Madison 15
16 MODIS Imagery in AWIPS Band 1: Visible channel (0.6µm) MODIS visible channel GOES visible channel
17 MODIS Imagery in AWIPS Band 7: Snow/Ice channel (2.1µm) 0.66 µm channel 2.1 µm channel Snow/ice vs. supercooled water cloud discrimination
18 MODIS Imagery in AWIPS Band 20: Shortwave Infrared (3.7µm) 1-km MODIS 4-km GOES Improved fire detection capability
19 MODIS Imagery in AWIPS Vegetation Index and Land Surface Temperature Vegetation Index (NDVI) Land Surface Temperature Helps with Fire Weather Forecasting
20 MODIS Imagery in AWIPS Band 31: Infrared window (11.0µm) 1-km MODIS 4-km GOES Improved feature identification (overshooting tops, enhanced-v)
21 MODIS Imagery in AWIPS Fog/stratus product (11.0µm - 3.7µm) 1-km MODIS 4-km GOES Improved fog/stratus detection capability
22 MODIS Imagery in AWIPS Sea surface temperature Milwaukee Chicago Identify areas of upwelling Maximum temperature forecast
23 MODIS Imagery in AWIPS Cloud phase product Can aid in the precipitation type forecast problem
24 MODIS True Color Imagery Viewer
25 MODIS True Color Imagery Viewer
26 MODIS True Color Imagery Viewer
27 MODIS Images in Google Earth Dust vs. Smoke can be Discriminated in True Color Imagery Texas Smoke Dust Image courtesy of J. Zeitler, NWS Austin TX Mexico 18 March 2008
28 For more information, see the online lesson University of Wisconsin-Madison 28
29 International TOVS Study Conference, 16 th, ITSC-16, Angra dos Reis, Brazil, 7-13 May Madison, WI, University of Wisconsin-Madison,, Cooperative Institute for Meteorological Satellite Studies, 2008.
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