1. The Advanced Baseline Imager (ABI) Timothy J. Schmit NOAA/NESDIS/ORA Advanced Satellite Products Team (ASPT) in Madison, Wisconsin in collaboration with the Cooperative Institute for Meteorological Satellite Studies (CIMSS) UW-Madison GOES-R Users Conference 22 May 2001

2. 30 years of 1 km IR data from AVHRR 10 years of high-resolution MODIS (AM and PM platforms) data - 36 channels with 1 km or finer spatial resolutions 10 years of China’s 10-channel polar-orbiting imager 7 years of MSG (METEOSAT Second Generation) data - 12 channels 7 years since the first GMS (-1R) with 2 km spatial resolutions Imagers, circa 2010

3. Limitations of Current GOES Imagers –Regional/Hemispheric scan conflicts –Low spatial resolution –Missing spectral bands –Eclipse and related outages

4. The need is documented. The technology is proven. The time is right to update the GOES imager! ABI - A Continuing Evolution To keep pace with the growing needs for GOES data and products, the Advanced Baseline Imager (ABI) follows an evolutionary path and addresses unmet NWS requirements.

5. Geostationary Imager Specifics ABICurrent GOES Spatial resolution Visible (0.64  m)0.5 km Approx. 1 km All other bands2 kmApprox. 4 km Spatial coverage Full diskEvery 15 minsEvery 180 mins CONUS Every 5 minsEvery 15/30 mins Operation during eclipse YesNo Spectral Coverage 8-12 bands5 bands

6. 19 January 2001, 1720 UTC MODIS 0.5 km GOES-8 1 km MODIS 0.25 km MODIS 1 km Lake Effect Snow Bands: Visible

7. Severe convection: IR windows 25 February 2001 The simulated ABI clearly captures the over-shooting (cold) cloud tops, while the current GOES Imager does not. Images shown in GOES projection. MODIS (1 km) ABI (2 km) GOES-8 (4 km)

8. ABI spatial coverage rate versus the current GOES Imager ABI coverage in 5 minutesGOES coverage in 5 minutes The anticipated schedule for ABI will be full disk images every 15 minutes plus CONUS images every 5 minutes.

9. Outages due to Eclipse and the Keep-Out-Zone GOES-8 (~3 hours of data outage) No data ! ABI (~0 hours of data outage)

10. 0.59 – 0.690.64VisibleDaytime cloud, smoke, fog 0.81 ­ 0.91 0.86 * Solar windowDaytime cloud, NDVI, fog, aerosol, ocean studies 1.36 - 1.391.375 * Near IRDaytime thin cirrus detection 1.58 – 1.641.61Near IRDaytime clouds/snow, water/ice clouds 3.8 – 4.0 3.9Shortwave IRNighttime low clouds, fog, fire detection 5.7 – 6.66.15Water Vapor 1Upper tropospheric flow, winds 6.8 – 7.27.0Water Vapor 2Mid tropospheric flow, winds 8.3 – 8.78.5 * IR Window 1Sulfuric acid aerosols, cloud phase 10.1 – 10.610.35 * IR Window 2Cloud particle size, sfc properties 10.8 – 11.611.2IR Window 3Clouds, low-level water vapor, fog, winds, SST 11.8 – 12.8 12.3IR Window 4Low-level water vapor, volcanic ash, SST 13.0 – 13.613.3Carbon DioxideCloud-top parameters, heights for winds Proposed ABI (8 or 12) channels WavelengthsDescription Primary Use Range (  m) Center * proposed additional channel to baseline of eight channels.

11. IR channels on current GOES and proposed 12-band ABI UW-Madison/CIMSS

12. (For the standard atmosphere at a 40 degree Local Zenith Angle) Pressure Units:  m and K Weighting Functions for the IR Channels

13. Simulated GOES (from MODIS) Visible (at 1 km), WV (at 8 km), and three IR windows (at 4 km)

14. Two visible bands, two near IR and eight IR bands (10.3 not shown) Simulated ABI (from MODIS) All images are displayed at 2 km resolution

15. ABI High Spatial Resolution Visible (0.64  m) Based on GOES Imager Ch 1 Daytime clouds, smoke, fog

16. Utility of the 0.86  m band Provides synergy with the AVHRR/3. Helps in determining vegetation amount, aerosols and for ocean/land studies. Enables localized vegetation stress monitoring, fire danger monitoring, and albedo retrieval.

17. 01 September 2000-- Pre-burning MODIS Detects Burn Scars in Louisiana CIMSS, UW Burn Scars Scars (dark regions) caused by biomass burning in early September are evident in MODIS 250 m NIR channel 2 (0.85 μm) imagery on the 17 th. MODIS Data from GSFC DAAC 17 September 2000-- Post-burning

18. Smoke plumes from fires in Louisiana and Texas as seen by the GOES Imager visible channel Experimental Wildfire Automated Biomass Burning Algorithm GOES Imager Observed the Fires UW/CIMSS (September 5, 2000)

19. 01 September 2000-- Pre-burning GOES Visible Cannot Detect Burn Scars 17 September 2000-- Post-burning The GOES visible channel (0.52 - 0.72 μm) does not delineate the burn scars. However, the 0.85 μm channel on MODIS was able to detect the burn scars. This is another reason to include a second visible channel (0.81 - 0.91 μm) on the Advanced Baseline Imager (ABI).

20. 1.88  m (or 1.38  m) is helpful for contrail detection Examples from MAS (Chs 2, 10, 16). Contrail detection is important when estimating many surface parameters. There is also interest in the climate change community.

21. Utility of the 1.6  m band Daytime cloud detection. This band does not sense into the lower troposphere due to water vapor absorption and thus it provides excellent daytime sensitivity to very thin cirrus. Daytime water/ice cloud delineation. ( used for aircraft routing) Daytime cloud/snow discrimination. Based on AVHRR/3 and MODIS experience.

22. ABI (1.61  m) Example of MAS 0.66, and 1.61 Visible 1.61 um During the day, the 1.61  m detects clouds that the 0.66  m doesn’t.

23. Goals of ABI Simulations Use MODIS data to simulate images from both Advanced Baseline Imager (ABI) and current GOES Imager for a range of phenomena. Use simulated images to demonstrate improved capabilities of ABI over simulated or actual GOES images. Use simulated ABI data sets to help with preparations for real ABI data (risk reduction)

24. 1 km MODIS Image (near center of pass) ImagerABI Average to 2 km Average to 4 km Display MODIS # μm 22(21) 3.9 27 6.7 31 11 32 12 MODIS # μm 2 0.85 6 1.6 26 1.3 22(21) 3.9 27 6.7 31 11 32 12 28 7.3 29 8.5 33 13.3 ABI blurImager blur ABI Simulations

25. Average 1-km MODIS data to 2-km spacing, apply blurring function (Point Spread Function) Point Spread Function (affects sharpness) GOES Imager (left) and ABI (right) for IR Window PSF data provided by MIT/LL

26. Caveats to these Simulations Quantization: 12-bit MODIS not reduced to 10-bit GOES Noise: MODIS noise used for ABI and Imager (latter is noisier) Spectral response: no corrections were made Striping: not included Channels: ABI 10.3 μm channel not simulated (there is no MODIS equivalent channel) View angles: non-isotropic atmosphere not accounted for. Orbital geometry: pixel size increase is approximately 1:10 for MODIS and 1:2 for GOES (going from 0 to 55 degrees zenith angle). 12-bands: ABI is assumed to have 12 bands for these simulations. Advantages of ABI are additional bands, faster coverage rate, and increased spatial resolution.

27. GOES and ABI and MODIS Spectral Widths

28. ABI (3.9  m) Based on GOES Imager Ch 2 useful for fog, snow, cloud, and fire detection Smoke From Fires in ID and MT The experimental Wildfire Automated Biomass Burning Algorithm (ABBA) identified numerous fire pixels in ID and MT from GOES-8 imagery using the 3.9 and 11  m data.

29. 5 March 2001 - Nocturnal Fog/Stratus Over the Northern Plains ABI image (from MODIS) shows greater detail in structure of fog. GOES-10 4 minus 11 μm Difference ABI 4 minus 11 μm Difference Fog UW/CIMSS Both images are shown in the GOES projection. ABI (3.9  m) Based on GOES Imager Ch 2 useful for fog, snow, cloud, and fire detection

30. GOES-10 and ABI Simulations of Viejas Fire Smoke Plume (Using MODIS Data) MODIS (0.5 km) - GOES-ABI: visible 3 January 2001, 1900 UTC GOES-10 (1.0 km): visible 3 January 2001, 1900 UTC

31. GOES ABI and GOES-8/M Simulations of Viejas Fire Using MODIS Data: 3 January 2001 at 1900 UTC Simulated GOES ABI: 3.9 micronSimulated GOES 8/M: 3.9 micron Temperature (K)

32. Simulated ABI Mountain Waves in WV channel (6.7 um) 7 April 2000, 1815 UTC Actual GOES-8 Mountain waves over Colorado and New Mexico were induced by strong northwesterly flow associated with a pair of upper-tropospheric jet streaks moving across the elevated terrain of the southern and central Rocky Mountains. The mountain waves appear more well-defined over Colorado; in fact, several aircraft reported moderate to severe turbulence over that region. UW/CIMSS Both images are shown in GOES projection.

33. Units:  m and K Pressure Applications: upper level moisture, jetstreaks, and satellite-derived winds. ABI (6.15 and 7.0  m) Based on MSG/ SEVIRI and GOES Sounder Ch 11

34. Utility of the 8.5  m band - volcanic cloud detection can be improved by detecting sulfuric acid aerosols (Realmuto et al.). Baran et al. have shown the utility of a channel near 8.2  m to detect sulfuric acid aerosols. - microphysical properties of clouds can be determined. This includes a more accurate and consistent delineation of ice clouds from water clouds during the day or night. - thin cirrus can be detected in conjunction with the 11  m. This will improve other products by reducing cloud contamination. - SST estimates can be improved by a better atmospheric correction in relatively dry atmospheres. - international commonality is furthered as MSG carries a similar channel (8.5 to 8.9  m) as well as MODIS and GLI. - surface properties can be observed in conjunction with the 10.35  m channel.

35. ABI Simulations: Water/Ice Clouds and Snow/Lake Ice 3-color composites12 February 2001; 1627 UTC Vis/4um/11um Vis/1.6um/11um Vis/4um/8.5-11um Vis/1.6um/8.5-11um UW/CIMSS Water cloud Ice cloud Lake Ice Snow Lake Ice Ice cloud Super-Cooled cloud Current Imager

36. Water/Ice Clouds and Snow/Lake Ice ABI Simulations (from MODIS data) 3-color composite (Visible/1.6 μm/8.5-11 μm) 12 February 2001; 1627 UTC UW/CIMSS Vis/1.6um/8.5-11um Water cloud Ice cloud Lake Ice Snow Super-Cooled cloud UW/CIMSS

37. Utility of the 10.35  m band - microphysical properties of clouds can be determined. This includes a more accurate determination of cloud particle size during the day or night. - cloud particle size is related to cloud liquid water content. - particle size may be related to the “enhanced V” severe weather signature. - surface properties can be observed in conjunction with the 8.5, 11.2, and 12.3  m bands. - low level moisture determinations are enhanced with more split windows.

38. Cloud particle size emerges in high resolution IR window spectra Based on HIS data, with ABI IR windows useful for effective radius

39. ABI (11.2  m) Based on GOES Sounder Ch 8 The many uses of the longwave infrared window: cloud images and properties, estimates of wind fields, surface properties, rainfall amounts, and hurricane and other storm location.

40. Hurricane Alberto IR -Window 19 August 2000, 1415 UTC ABIGOES-8

41. Satellite-derived winds will be improved with the ABI due to: - higher spatial resolution (better edge detection) - more frequent images (offers different time intervals) - better cloud height detection (with multiple bands) - new bands may allow new wind products (1.38  m?) - better NEdT’s - better navigation/registration Satellite-derived winds

42. Current GOES daily composite provides good spatial coverage ABI (12.3  m) Based on GOES Imager Ch 5 useful for low atmospheric moisture, volcanic ash, and SST

43. David Foley, Joint Institute for Marine and Atmospheric Science, Univ of Hawaii SST will be improved with the ABI due to: - higher spatial resolution- more frequent images - better cloud and aerosol detection- better NEdT’s ABI (12.3  m) Based on GOES Imager Ch 5 useful for low atmospheric moisture, volcanic ash, and SST

44. UW/CIMSS Simulated Imager (11-12 μm) Simulated ABI (11-12 μm) Simulated ABI (8.5-11 μm) One day after the eruption 20 February 2001, 0845 UTC Volcanic Ash Plume: 11-12 and 8.5-11 μm images

45. ABI (13.3  m) Based on GOES Sounder Ch 5 useful for cloud heights and heights for winds ClearLow CloudHigh Cloud

46. ABI addresses NWS Imager concerns by: increasing spatial resolution - closer to NWS goal of 0.5 km IR scanning faster - temporal sampling improved - more regions scanned adding bands - new and/or improved products enabled Simulations of the ABI show that the 12 channel version addresses NWS requirements for improved cloud, moisture, and surface products. Summary -- ABI

47. What if we could have more bands? 9.6  m -- total ozone 14.2  m -- better cloud heights 4.57  m -- better TPW 0.47  m -- aerosol particle size ( over land ) plus true color images (with other visible bands)

48. ABI-12 (top bars) and MSG/SEVIRI (bottom bars) Channels

49. More information can be found at http://cimss.ssec.wisc.edu/goes/abi/ http://cimss.ssec.wisc.edu/modis1/modis1.html –MODIS –MAS http://cimss.ssec.wisc.edu/nast/index.html http://cimss.ssec.wisc.edu/goes/goes.html –Real-time Sounder page –GOES Gallery –Biomass Burning http://www2.ncdc.noaa.gov/docs/klm/html/c3/sec3-0.htm –NOAA KLM User's Guide http://www.eumetsat.de/en/ –MSG..System..MSG..Payload..Spectral bands..Spectral bands

50. Phase Discrimination with Current Channels Daytime phase discrimination is most effective for fairly thick clouds. The split- window shows similar differences between water and ice clouds

51. Phase Discrimination with Future Channels With the addition of the 8.5  m, phase discrimination is improved for both day/night time clouds for non-opaque clouds. The 8.5-11 difference shows differences of different signs between water and ice clouds