# Presentation: 790957

## Satellite Remote Sensing of Atmospheric Conditions Hazardous to Aviation

- Gary P. Ellrod (NOAA/NESDIS)
- Office of Research and Applications Camp Spring, MD

**Notes:**
Satellite remote sensing is critical to aviation due to the vast data-void areas over which aircraft must fly. This talk is an overview of how we can use satellite data and products to detect significant aviation weather hazards or conditions.

## Outline

- Weather impacts on aviation
- Analysis of hazards with satellite data
- Winds (convective gusts, jet stream)
- Fog and low clouds
- Inflight icing
- Turbulence
- Volcanic ash
- Future technology improvements

**Notes:**
Basic outline of talk.  Will close with a summary of expected new spacecraft and their capabilities during the next ten years.

## Impacts of Weather on Aviation

- $6B annual socio-economic impacts due to weather, 40% due to ceiling/visibility
- Thunderstorm microbursts: >20 accidents since 1970 resulting in ~500 deaths
- Ceiling & Visibility: Account for > 50% of average annual accident cost of $689.8M
- Turbulence: Accounts for most injuries to flight crews and passengers
- Icing: Resulted in 583 accidents and >800 fatalities in 19 year period (1982-2000)
- Volcanic ash: Several near-crashes due to engine failures on large jets

**Notes:**
Summary of significant impacts to aviation.  Sources: (1) Air Transport Association, (2) National Transportation Safety Board (NTSB), (3) MCR Federal, (4-6) NTSB.

## U.S. Weather Satellites

- Polar (low orbit) (NOAA-16/17)
- 1 km resolution
- 4 looks per day
- 6 channels
- Geostationary (GOES-10/12)
- 4 km IR, 1 km vis
- 15-30 min frequency
- 5 channel Imager
- 19 channel Sounder (10 km), hourly over CONUS

**Notes:**
Summary of the two primary U. S. operational weather satellite systems and their observing capabilities. Polar satellites have global coverage at high resolution but infrequent revisits. Geostationary satellites have hemispheric coverage at frequent intervals with moderate resolution.

## Convective DownburstsEffects on Flight

- Microburst on the High Plains

- Loss of lift and climb due to downdraft

**Notes:**
Schematic showing hazards to aircraft associated with convective downdrafts (left - MIT Lincoln Laboratories) and photo showing example in Northeast Colorado (Credit: Gary Ellrod). Aircraft experience rapid loss of lift due to change in headwind component.

## Wet Microburst Severity Index

- Uses GOES Sounder retrieval data
- Based on instability and vertical distribution of moisture (CAPE, dθe/dz)
- Correlates well with observed peak surface wind gusts

*WMSI > 200 indicates wind gusts > 65*
*knots possible. 85 knot gusts were *
*reported at Patuxent River, Maryland*
*at 2100 UTC (*).*

**Notes:**
Potential for high wind gusts based on Wet Microburst Severity Index (WMSI) from GOES Sounder on 14 July 2004.  WMSI developed by Ken Pryor (NESDIS SMCD)

## Convective Initiation

- Critical for air traffic management
- GOES Visible Imagery Applications (boundary interactions, stability, etc)
- Stability and moisture Products from Sounder (Lifted Index, PW, Cinh)
- Automated Nowcast Products
- Convective Initiation (UW-CIMSS and U. of Alabama-Huntsvile)

**Notes:**
GOES products used to determine areas of potential convective initiation.

## Convective Initiation (CI) Product(U. of Ala-Huntsvile/ U. of Wisconsin CIMSS)

- Uses satellite parameters to identify convective clouds:
- IR temp. change
- WV - IR temp. difference
- Cloud motion vectors to advect developing clouds, produce nowcast

- CI valid 2000Z, 4 May 2003

- Radar, 2100Z, 4 May 2003

**Notes:**
GOES Convective Initiation (CI) product (Mecicalski et al 2004) based on multi-spectral cloud mask, time change of satellite IR temperatures, and mesoscale cloud motion vectors (top).  Verifying radar in bottom panel.

## Nighttime Fog Detection Using GOES Multi-spectral Image Data

**Notes:**
Temperature slice across line A-B in right hand images showing the 10.7 and 3.9 um IR channel data across a region of cirrus, clear skies, and low stratus clouds.  The stratus clouds are highlighted best by the difference in the two channels (bottom image in right panel).

## Features Observed in Nighttime Fog Images

**Notes:**
Examples of features observed in nighttime fog images using a brightness temperature difference of 2C (CH4 – CH2). False detects are caused by low emissivity desert soils. Differences between very low fog/stratus and high-based stratiform are subtle.

## Determination of Low Clouds from GOES

- When GOES IR cloud top is <4o K from surface
- temperature, low clouds (<1000 ft) likely

- Brown 1987

- Ellrod 2003

**Notes:**
Likelihood of low ceilings (<1000 ft) can be determined from the difference between GOES IR cloud top temperature and surface shelter temperature obtained from METAR reports.  Differences less than 4C are associated with probabilities >50%.

## GOES Low Cloud Base Product

- Based on difference of two IR channels  (11 m-3.9 m)  and surface minus cloud top temp.
- Unable to observe low clouds covered by cirrus or middle clouds

*Red areas show where cloud bases <1000*
*ft are likely, green areas > 1000 ft, blue *
*are cirrus clouds.*

**Notes:**
Example of cloud base product over Southern California with low ceilings highlighted in red.

## Fog Depth Estimates

- Estimates of fog depth also possible based on two channel BTD (to forecast burnoff time)

**Notes:**
Estimate of fog depth (left) is based on brightness temperature difference (CH4 –CH2).  Thicker patches of fog tend to persist longer, as shown in right hand GOES visible images.

## Snow vs Fog Using 3.9um and Visible

- Snow

- Snow vs Fog Using 3.9um and Visible

**Notes:**
It is often difficult to determine the borders of fog during daylight hours.  GOES/NOAA shortwave channels highlight low clouds due to stronger reflectance by water droplet clouds at that wavelength compared with snow-covered surfaces.

## Meteorological Factors Conducive to Aircraft Icing	

- Temperature (0 to -20C)
- Liquid Phase (supercooled droplets)
- Larger drop sizes (>30 m = Supercooled Large Drop (SLD))
- High Liquid Water Content (>0.25 gm-3)
- Weak vertical motion                (~1 bar s-1)
- Embedded convection

**Notes:**
Conditions associated with significant airframe icing.  Many are difficult to detect using satellite data since only the cloud tops are observed and there is only limited sensitivity to droplet size.

## GOES Channels Useful in Icing Detection

**Visible (0.6 ********m)**
- Thickness, coverage, phase, convection
**IR2 (3.9 ********m)**
- Cloud phase, drop size (up to ~30m diam.)
**IR4 (10.7 ********m)**
- Cloud top temperatures, thickness, coverage
**IR5 (12.0 ********m) (GOES-10 only)**
- Thin cirrus detection
**IR6 (13.3 ********m) (GOES-12 only)**
- Thin cirrus detection

**Notes:**
Use of GOES channels in aircraft icing algorithms.

## Discrimination of Supercooled Clouds

**Notes:**
Scatterplot showing how supercooled clouds (o’s) can be distinguished from thin cirrus over land, and snow cover.  Thin cirrus over warm clouds or snow (*’s) can produce false alarms unless removed using split window IR techniques.

## Eliminating Thin Cirrus from Product

**Notes:**
Empirical method to screen out thin cirrus false alarms from NESDIS icing product based on GOES-12 Channels 4 (10.7um) and 6 (13.3um).

## GOES Icing Risk Product	

- Multiple channel screening technique
- Product available hourly day and night
- Strengths
- Good spatial, temporal coverage
- Good POD (~50-75%), low FAR (~25%)
- Weaknesses
- Obscuration by high clouds
- Unable to distinguish SLD regions

**Notes:**
Capabilities of NESDIS GOES icing potential product.

## GOES Combined Icing + Cloud Tops (‘ICECAP’)

*Icing intensity (3=mod, 4=mod/sev), aircraft type, altitude (feet)*

**Notes:**
Example of GOES-12 ICECAP product showing color-coded cloud tops in regions of potential icing. Pilot reports show intensity, aircraft type, and altitude (ft).

## GOES Water Vapor + IR  Winds

**Notes:**
Strong winds detected by GOES cloud motion in the North Pacific between Hawaii and the U. S. mainland.  Turbulence was reported in the banded cloud regions due to the decelerating flow and deformation.

## Detection of Mountain Waves Using Water Vapor Imagery

- Low and mid-Tropospherice waves
- can be seen in GOES 6.7 m water
- Vapor imagery, but not in IR or
- visible

**Notes:**
Water vapor channel images (6.7 um) can detect mountain wave patterns not seen in visible or infrared.  These waves in western North Carolina were associated with severe low level turbulence below 10 thousand feet. GOES-12 water vapor channel has a resolution of about 5 km at this latitude.

## Total Column Ozone from GOES Sounder

**Stratospheric **
**Intrusion**

**Notes:**
Total ozone product generated by University of Wisconsin CIMSS from GOES Sounder using statistical regression based on 9.7um ozone channel, plus other bands.  Maximum ozone band (green) is associated with Tropopause folding and possible clear air turbulence.

## Volcanic Hazards

- Hazards to jet airliners: Ash can damage engines and leading edges, flame-out
- SO2 cloud may contain undetected ash, cause respiratory problems

**Notes:**
Schematic of volcano hazards (from USGS).  Of main concern to aviation is the ash cloud that drifts away from the volcano, and can drift thousands of kilometers from its source.  It is composed of tiny (<5 micron) silicate particles that melt and stick to jet turbine blades when ingested.

## Volcanic Ash Detection

- Develop improved ash detection methods using current satellites
- Prepare for future satellites using data from research instruments
- Support for Volcanic Ash                                    Advisory Centers
- Washington DC
- Anchorage, Alaska
- Darwin, Australia

**Notes:**
NESDIS activities in volcanic ash research and operational support.

## International Warning System (VAACs)

- Established by ***International Civil Aeronautical Organization (ICAO)*** in mid-1990’s
- Volcanically active regions source: Smithsonian Inst.

**Notes:**
VAAC network (from ICAO), areas of responsibility, and active volcanic regions (from USGS).  

## Ash Cloud Discrimination With Longwave IR(Band 4 = 11m, Band 5 = 12m)

- (From Rose et al 2004, AGU Monograph, Vol. 139)

**Notes:**
Absorption is higher in Band 5 than Band 4 for a volcanic cloud, the opposite for a meteorological cloud (ice or water).  The result is a negative Band 4-5 BTD for volcanic ash, a positive BTD for meteorological clouds assuming semi-transparent clouds. Ambient moisture can result in overlap in these BTD values.

## Composite “Split Window” ImageryMt. Spurr, Sept. 1992, NOAA-AVHRR

- (Schneider et al 1992)

**Notes:**
Notable example of the use of “Split Window” (AVHRR Band 4-5) product in tracking ash cloud from Mt. Spurr eruption across Canada and the U. S. in Sept. 1992.

## Deficiencies of Two-Band Method

- Obscuration by high clouds
- Hekla 2001
- Cloud opacity in first few hours of an event
- Spurr 1992
- Ambient moisture (Tropics)
- Soufriere Hills 1997

**Notes:**
Volcanic ash was not clearly discriminated using split window techniques soon after the eruption of Spurr in Aug 1992 due to its opacity.  Obscuration by high clouds can prevent the observation of 25-50% of eruptions.

## Evaluation of GOES-12 CapabilityUsing MODIS Data

**Notes:**
Evaluation of proposed GOES-12 ash product (based on arithmetic difference of 3.9, 10.7 and new 13.3um channel) using MODIS data for eruption of Popocatepetl near Mexico City.

## The GOES Sounder was not optimized for SO2 detection 

- Proposed ABI channels shifted to obtain maximum benefits

- SO2 calculations from F. Prata

**Notes:**
A 7.4 um (7.3 to 7.5 um) channel proposed for GOES-R ABI has been shifted to 7.34 um  (7.24 to 7.44 um) to capture maximum benefits of SO2 absorption band.  7.0 um (6.8 to 7.2 um) channel shifted to a 6.95 um  (6.75 to 7.15 um) to allow better retrievals.

## Sulfur Dioxide (SO2) Detection

- UV measurements from TOMS (top), and OMI (Aura)
- IR techniques (MODIS, GOES Sounder) for high level SO2 with 7.5m band (lower)

**Notes:**
SO2 clouds may contain undetected volcanic ash, and can result in respiratory problems to air crews and passengers when ingested into aircraft ventilation systems.  The SO2 cloud, detected using both UV and IR techniques, may become detached from the main volcanic ash cloud due to wind shears.  

## SO2 Retrieval from GOES Sounder Compared with AIRS, TOMS (Prata- CSIRO)

**Notes:**
SO2 retrieval from GOES-8 Sounder (left, from Prata, 2004) compared with AIRS SO2 retrieval and TOMS SO2 index for comparison (right – UW-CIMSS).

## Hekla Case – Possible SO2 Plume

- Hekla Case – Possible SO2 Plume

**Notes:**
Detection of SO2 cloud from Hekla, Iceland eruption in Feb 2000 using MODIS 7.3um and 9.7um (T28, T30) channels (Ellrod and Im, 2004).  Little or no volcanic ash (determined from T31 – T32) could be detected.

## Technology OutlookOperational Spacecraft

***Near-Term***
- GOES-N (May 2005) through P
- Improved navigation, power to operate through satellite eclipse (Spring, Fall)
- Resolution of 13.3m improves to 4km (GOES-O)
***Mid-Term***
- NPOESS VIIRS imager (prototype late 2007)
- MODIS-like spectral selection (including 8.5m band)

**Notes:**
Near-term and mid-term improvements expected for operational U.S. spacecraft.

## Technology OutlookOperational Spacecraft

***Long-Term***
- GOES-R Advanced Baseline Imager (2012?)
- Sixteen spectral bands at 2km resolution
- Five minute CONUS, 15 min Full Disk
- GOES-R Sounder (HES)
- Hyper-spectral capabilities
- Hourly global coverage
- Good resolution (4 km horizontal, ~1 km vertical)

**Notes:**
Long-term expected improvements to U. S. spacecraft.

## Simulated GOES-R Fog ImageBased on AVHRR IR (3.7 m and 11.0 m)

**Notes:**
Example of low cloud image possible from GOES-R imager (simulated using AVHRR).

## Simulated GOES-R Ash ImageBased on MODIS IR, Near-IR, Visible Channels

- Volcanic ash (red)
- Composite of 8.5, 11, 12m channels
- Land (green)
- Near-IR (1.6m)
- Ocean/ice clouds (blue)
- Visible (0.6m)

- Popocatepetl, 20 Dec 2000, 1715 UTC
- Based on data from Terra MODIS

**Notes:**
Example of possible GOES-R volcanic ash product simulated using MODIS data.

## Simulations of Low vs High Spectral Resolution Retrievals Geo-I gets <1 K rms for 1 km T(p) and <10% rms for 2 km RH(p) 

**Notes:**
Simulations of possible Hyperspectral Environmental Sounder (HES) retrieval accuracy, based on radiosondes. 
Preliminary HES simulations using the noise specified in the HES Technical Requirements Documents. These simulations were done by Jun Li (UW-CIMSS). It can be seen that, in general, the NWS retrieval accuracy is acquired.
There’s a poster on this topic by J. Li of CIMSS at the 11th Satellite Conference.

## Summary

- Satellite remote sensing is critical in providing needed observations to support aviation warnings and forecasts
- Future instruments will provide excellent opportunities for improved products
- Much work is needed to fully utilize future  deluge of high quality data!

**Notes:**
Summary

## Research on Improved Aviation Weather Satellite Products 

- NCAR Research Applications Lab (Boulder)
- NOAA-Forecast Systems Lab (Boulder)
- NASA Langley Research Center (Virginia)
- Naval Research Laboratory (Monterey, CA)
- NOAA/NESDIS (Madison, WI & Camp Springs, MD)
- Univ. of Wisconsin CIMSS (Madison)
- NASA Marshall and Univ. Alabama-Huntsville
- USGS and Michigan Tech. U. (Volcano studies)
- Funding sources:
- FAA Aviation Weather Research Program
- NASA Aviation Safety
- NWS Aviation Initiative

**Notes:**
Ongoing research in aviation weather applications using satellite remote sensing to develop new products.  Main funding sources at bottom.

## Internet Resources:

- GOES Aviation Products (Imager and Sounder)
- _[http://www.orbit.nesdis.noaa.gov/smcd/opdb/aviation/](http://www.orbit.nesdis.noaa.gov/smcd/opdb/aviation/)_*  **(NESDIS)*
- _[http://www.cira.colostate.edu/RAMM/rmsdsol/main.html](http://www.cira.colostate.edu/RAMM/rmsdsol/main.html)_*  **(CIRA)*
- _[http://cimss.ssec.wisc.edu/asap/products/](http://cimss.ssec.wisc.edu/asap/products/)_* (CIMSS ASAP)*
- _[http://www.orbit.nesdis.noaa.gov/smcd/opdb/goes/sdpi/html/sdpiimgnewt.html](http://www.orbit.nesdis.noaa.gov/smcd/opdb/goes/sdpi/html/sdpiimgnewt.html)_*  (NESDIS)*

**Notes:**
Links to realtime GOES aviaton products.

## Thank you

**Notes:**
Eruption cloud from Anatahan, Marianas Islands, 10 May 2003 (Allan Sauter).