James Purdom & Kenneth Eis CIRA Colorado State University, Fort Collins, CO 80523

1. Geostationary Hyperspectral Imaging from 0.4 to 1 microns:A Potent Tool for Convective Analysis and Nowcasting James Purdom & Kenneth Eis CIRA Colorado State University, Fort Collins, CO 80523

2. Nowcasting convection requires frequent imaging and sounding that can only be provided by geostationary satellites. GOES-R: NOAA’s next generation geostationary satellite – “unique” in spectra, space and time (2012 timeframe) The spatial and temporal variability of the phenomena being nowcast drive the observational needs as a function of its spectral, spatial and temporal domains, as well as signal to noise.

3. Advanced Baseline Imager Hyperspectral Environmental Suite Hyperspectral IR Sounder Global mode Mesoscale mode Hyperspectral visible to near IR imager Lightning detection sensor The spatial and temporal variability of the phenomena being nowcast drive the observational needs as a function of its spectral, spatial and temporal domains, as well as signal to noise. GOES-R’s Primary Earth Viewing Sensors: All play a role in nowcasting

4. Advanced Baseline Imager Hyperspectral Environmental Suite Hyperspectral IR Sounder Global mode Mesoscale mode Hyperspectral visible to near IR imager Lightning detection sensor 16 or more channels 5 minute full disk capability with rapid scan capability ½, 1 and 2 km resolution depending on channel Anticipated Highlights

5. Advanced Baseline Imager Hyperspectral Environmental Suite Hyperspectral IR Sounder Global mode Mesoscale mode Hyperspectral visible to near IR imager Lightning detection sensor Hyperspectral regions from about 3.9 to 15 microns Hourly global at 10 km spatial resolution with capability of adaptive observing with more frequent limited areas (mesoscale) at 4 km resolution Anticipated Highlights

6. Advanced Baseline Imager Hyperspectral Environmental Suite Hyperspectral IR Sounder Global mode Mesoscale mode Hyperspectral visible to near IR imager (HES-VNIR) Lightning detection sensor Possible attributes Hyperspectral from about 0.4 to 1.0 microns with 10 or 20 nanometer spectral resolution 150 to 300 meters spatial resolution 6 second views of around 4000 to 5000 sq km Anticipated Highlights

7. Advanced Baseline Imager Hyperspectral Environmental Suite Hyperspectral IR Sounder Global mode Mesoscale mode Hyperspectral visible to near IR imager Lightning detection sensor 10 km resolution over most of earth disk (basically within 62 degree zenith angle) Near instantaneous refresh Anticipated Highlights

8. In satellite remote sensing, four basic parameters need to be addressed: all deal with resolution • temporal (how often) • spatial (what size) • spectral (what wavelengths and their width) • radiometric (signal-to-noise) Compare cloud field evolution at different time intervals –GOES-R’s ABI with 5 minute full disk imagery (along with rapid scan capability and HES-VNIR) will provide unparalleled monitoring capability for nowcasting convection.

9. In satellite remote sensing, four basic parameters need to be addressed: all deal with resolution • temporal (how often) • spatial (what size) • spectral (what wavelengths and their width) • radiometric (signal-to-noise) The cold thunderstorm overshooting top region more accurately depicted using higher resolution data: this is important because the overshooting and coldness reflects storm updraft intensity - GOES-R’s ABI will provide unparalleled capability for assessing thunderstorm development, evolution and intensity. * GOES-R’s hyperspectral sounder, in the mesoscale mode, will have a spatial resolution similar to the 4 km GOES-8 image (bottom left)

10. 1 Km (today’s GOES) to 250 m (GOES-R HES-VNIR) GOES-8: ~1 km MODIS: ~250 m Hurricane Erin 09/09/01 ~1530 Z Note the detail in the eye wall (you can see up its side), improving the resolution of visible imagery (ABI and HES-VNIR) provides enhanced ability to analyze its cloud field

11. In satellite remote sensing, four basic parameters need to be addressed: all deal with resolution • temporal (how often) • spatial (what size) • spectral (what wavelengths and their width) • radiometric (signal-to-noise) Each spatial element has a continuous spectrum that may be used to analyze the surface and atmosphere

12. In satellite remote sensing, four basic parameters need to be addressed: all deal with resolution • temporal (how often) • spatial (what size) • spectral (what wavelengths and their width) • radiometric (signal-to-noise) Next slide will show - Spectral animation from AIRS covering much of the mid-wavelength infrared portion of the spectrum With the hyperspectral sounder operating in the mesoscale mode this type data will be available at 4 km resolution (AIRS is 10x20 km res.)

13. High Spectral Resolution (AIRS) resolves H2O spectral Features (right) GOES-I/M era sounder H20 Channels (above)

14. Texas Spikes down - cooling with height (No inversion) Brightness Temperature (K) Spikes up - warming with height Ontario (low-level inversion) Hyperspectral IR sounders: the potential for very accurate surface temperatures and detection of temperature inversions Wavenumber (cm-1) Detection of inversions is critical for severe weather forecasting. Combined with improved low-level moisture depiction, key ingredients for night-time severe storm development can be monitored.

15. In satellite remote sensing, four basic parameters need to be addressed: all deal with resolution • They all deal with resolution: • temporal (how often) • spatial (what size) • spectral (what wavelengths and their width) • radiometric (signal-to-noise) AVIRIS Loop - Linden CA 20-Aug-1992 224 Spectral Bands: 0.4 - 2.5 mm Pixel: 20mx 20mScene: 10km x 10km

16. Example of AVIRIS Spectral Information from a Scene Depicting Cloud, Smoke and Active Burn Areas AVIRIS Image - Linden CA 20-Aug-1992 Spectral Signatures of Selected Pixels Smoke - large part. Shadow Grass Lake Fire Hot Area Cloud Soil Smoke - small part. The unique characteristics of the spectral signatures provide a way to identify and characterize each feature and to derive other useful information about the scene. HES-VNIR has the potential for numerous atmospheric, ocean, land applications – for some we need to filter atmospheric effects and use that information

17. Water Vapor: a filtered atmospheric effectnote water vapor change every 15 minutes HES VNIR at high resolutions will be able to monitor pre-cumulus cloud moisture and moisture convergence – this will be enhanced by HES-IR

18. Water vapor exhibits remarkable variability in space and time (as above!); it serves as the key energy source for deep convective development. For example, releasing latent heat: a gram of water vapor condensed into a kilogram of air (about 1 cu meter) will raise that air’s temperature about 2.5 ºK. Water vapor is important on scales ranging from climate to convection.

19. EO-1’s hyperion: a glimpse to the future

20. Hyperion (IHOP Day 173, 1650 UTC) Hyperion is hyperspectral sensor on NASA’s EO-1 Derived Water Vapor Image Mean CWV: 35.1 mm 37.4 mm (no clds) Raob @ 18 UTC: 34.5 mm WV Image Histogram CWV (cm) This case is being investigated with Mike Griffin of MIT/LL

21. Spatial Simulations (7.5 km x 30 km) HSI 30m HES-VNIR 150m ABI IR 2km ABI VIS 480m ABS 7.5km 256 x 1000 16 x 65 51 x 210 4 x 16 1 x 4 Notice how readily cloud free fields of view can be detected at higher resolutions, allowing for detailed column water vapor retrievals – in synergy with HES-IR, this will provide powerful information for nowcasting convection

22. Great Plains severe thunderstorm viewed by GOES-West and GOES-East From geostationary altitude we see the side of the base, side and top of clouds. Different viewing perspectives allow for stereo height determination of various features.

23. The development and evolution of deep convection Unique in space and time • To the right is the first ever one minute interval imagery taken by a geostationary satellite. It covers 6 minutes, and illustrates the dynamic nature of a strong (large hail) thunderstorm. The area covered is approximately 160 x 160 km. • Notice the cloud field variability, differences in cloud motion, cloud top and anvil growth, cloud growth along a front at the top of the image

24. Viewing Perspective, dt and l, determine what we see with HES-VNIR • Differences in scattering as a function of sun-scatterer-detector geometry allow for a variety of atmospheric, land, costal zone and ocean applications (think of MISR) • Stereo cloud height determinations: accuracy is in large part a function of spatial resolution (shadows can also provide exceptionally accurate cloud height depending on time of day and viewing geometries) • Exceptional CMV’s (u, u', v, v', w') in complex situations: potential for nearly 50 times higher resolution than today (150m vs 1000m) and over 10 times higher than GOES-R’s ABI (150m vs 500m) • Pre-cumulus moisture field and its changes in time

25. Over land atmospheric instability can change dramatically due to surface heating, an increase in low level moisture due to advection and evaporation as well as precipitation effects • For nowcasting, one question is how representative is a sounding the further one is displaced from it as a function of space and time

26. Thermodynamic soundings at different locations in these images will provide different information. This is especially true in the boundary layer where the fuel for deep convection is found. GOES-R will provide greatly enhanced capabilities to monitor moisture with HES-IR and HES-VNIR, and surface temperature with HES-IR and ABI. Photo of thunderstorm from manned s/c Photo of convection from airplane

27. GOES-8 loop from 1033 to 1615: this loop illustrates the changes that have occurred in the cloud field (and boundary layer) since the launch of a “representative” rawinsonde.

28. MODIS at 1 km resolution compared to same data at 250 meters (similar to HES-VNIR)

29. Notice how well the cloud field can be analyzed at 250 meters. Everywhere there isn’t a cloud you can compute moisture from HES-VIS/NIR, and where there are the bigger holes you can do the total job with HES-IR (some are representative of a modified boundary layer due to storm outflow air)

30. Severe Weather

31. GOES Visible Loop at 1 to 30 minute Intervals • July 24, 2000 severe weather outbreak across South Dakota and Nebraska produces hail, tornadoes, flash flooding and damaging winds • One minute interval visible imagery shows storm evolution over 2 hr period • Important for severe weather: Vertical wind shear, evolving instability field, updraft strength, anvil development and blocking, rotating cloud top

32. Vertical shear • ABI (cloud motion) • HES-IR (moisture motion) • HES-VNIR (cloud and moisture motion) • Evolving instability field • ABI (surface heating) • HES-IR (instability and surface heating) • HES-VNIR (detailed moisture field) • Updraft strength • ABI (IR top temperature) • ABI and HES-VNIR (overshooting top height) • Above with HES-IR (updraft efficiency)

33. Updraft strength • ABI (IR top temperature) • ABI and HES-VNIR (overshooting top height) • Above with HES-IR (updraft efficiency) • Anvil development and blocking • ABI (growth and detailed upper level atmospheric motion and water vapor behavior) • HES-IR and VNIR (as ABI but with better spectral definition) • Rotating overshooting top • ABI and HES-VNIR

34. Oklahoma City tornado of May 3, 1999 left damage easily detected by Landsat 5 several days later (30 meter resolution), with residual damage even evident almost one year later. There are other instances where Landsat imagery has been used to locate areas of storm damage from hail, wind and tornadoes. Frequent hyper-spectral views possible from HES-VNIR point to a new and exciting potential

35. Very accurate cloud motion vectors with accurate cloud bases and cloud tops High resolution water vapor measurements in the presence of cumulus cloudiness A few implications (with ABI and HES-IR & VNIR) Monitor the growth and destabilization of the boundary layer over land Cloud growth rate and cloud top behavior Smoke, haze, dust, aerosols, visibility in cloud free areas Damage paths for large storms Areas of flooding (wet ground) Shear, cold air production, evolving instability field, updraft strength, anvil development, blocking, cloud motion, rotating cloud top, rain area, hail swath and tornado damage path – High resolution Hyperspectral: We infer today, we will see and measure with GOES-R

36. High resolution Hyperspectral: And we haven’t even talked about hurricanes and other phenomena – like moisture, aerosols and plume tracking for “local disasters”