FRAM, Montreal, Que 15 June 2005 Analysis of Hazardous Fog and Low Clouds Using Meteorological Satellite Data Gary P. Ellrod NOAA/NESDIS, Camp Springs,

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Presentation transcript:

FRAM, Montreal, Que 15 June 2005 Analysis of Hazardous Fog and Low Clouds Using Meteorological Satellite Data Gary P. Ellrod NOAA/NESDIS, Camp Springs, MD

FRAM, Montreal, Que 15 June 2005 Outline Benefits/limitations of remote sensing Detection of low clouds –Night: Longwave – Shortwave IR –Day: Visible and Shortwave IR Determination of low ceilings Fog depth estimates Technology upgrades needed Summary

FRAM, Montreal, Que 15 June 2005 Nighttime GOES Infrared Fog Detection Capabilities Advantages: –High frequency (15-30 min) –Good spatial coverage, resolution (4km) Limitations –Obscuration by higher clouds –Some fog too narrow, thin to detect –False signatures (sandy soils) –Is it fog or stratus?

FRAM, Montreal, Que 15 June 2005 Remote Sensing of Fog Radiative studies (Hunt 1973) Experience with AVHRR in U.K. (Eyre et al 1984) GOES investigations –Gurka 1978, 1980 –Ellrod 1991, 1994 –Lee (NRL) et al 1997 METEOSAT –Cermak, Bendix Nighttime fog product from GOES Sounder, June 1987

FRAM, Montreal, Que 15 June 2005 Radiative Properties of Clouds

FRAM, Montreal, Que 15 June 2005 Nighttime Fog Detection Using GOES Multi-spectral Image Data

FRAM, Montreal, Que 15 June 2005 Features Observed in Nighttime Fog Images Yellow = T4 – T2 > 2C

FRAM, Montreal, Que 15 June 2005 Fog-related Highway Accident Windsor, Ont., 3 Sep 1999 (Pagowski et al 2004)

FRAM, Montreal, Que 15 June 2005 Spread of Lake Fog – Time Lapse

FRAM, Montreal, Que 15 June 2005 Daytime Fog Detection Visible images –Smooth texture, sharply defined borders, moderate brightness 3.9 m IR (or 1.6m AVHRR) –Fog droplets are good reflectors at 3.9m Result is relatively warm T b –Snow is poor reflector at 3.9m –Result: Good contrast with snow or cold ground

FRAM, Montreal, Que 15 June 2005 Fog Clearing on 3 Sep 1999

FRAM, Montreal, Que 15 June 2005 Snow vs Fog Using Visible and Shortwave IR MODIS  m CH6 MODIS Visible CH1

FRAM, Montreal, Que 15 June 2005 Snow vs Fog Using Visible and Shortwave IR MODIS 3.9  m CH6 MODIS Visible CH1

FRAM, Montreal, Que 15 June 2005 RGB Depiction of Fog Over Snow-Covered Ground (MODIS) Red = Visible Green= 1.6  m Blue= 11  m IR Fog is yellow Snow is red Bare surface is green

FRAM, Montreal, Que 15 June 2005 Daytime Fog Discrimination Using Visible and IR Data

FRAM, Montreal, Que 15 June 2005 Estimation of Low Cloud Base Category from GOES When GOES IR cloud top is <4º K from surface temperature, low clouds (<1000 ft) likely Brown 1987 Ellrod 2003

FRAM, Montreal, Que 15 June 2005 Low Visibility Determination

FRAM, Montreal, Que 15 June 2005 GOES Low Cloud Base Product Available for all regions of the U. S. and parts of southern Canada at:

Verification of LCB Product * Overall verification for low clouds detected but not covered by cirrus clouds (N = 2381): POD = 72 % FAR = 11 % Regional Statistics * Completed in

FRAM, Montreal, Que 15 June 2005 San Francisco Fog Project (Terabeam Inc, 2001) GOES Ceiling Categories Categories created to compare satellite data with ceilometer data.

Brightness values plotted against ceilometer ceiling heights. Top-left and bottom- right quadrants (separated by dashed lines) show category 1 and 2 agreement, respectively. Top-right shows false alarms, bottom-left shows under-detection. San Francisco Fog Project (Terabeam)

FRAM, Montreal, Que 15 June 2005 Estimation of Fog Depth Based on BTD for 3.9m and 10.7m IR Developed using cloud top heights from aircraft pilot reports (PIREPs) Brightness count difference (GOES-7 Sounder) vs fog depth estimated from PIREPs

FRAM, Montreal, Que 15 June 2005 Fog Depth Verification

FRAM, Montreal, Que 15 June 2005 Fog Depth Product – 3 Sep 99

FRAM, Montreal, Que 15 June 2005 Fog Depth Estimation Application of fog depth to forecast burnoff time GOES Fog Depth, 1045 UTC

FRAM, Montreal, Que 15 June 2005 Results for 3 Sep 99 Case GOES Fog Depth, 1045 UTC GOES visible, 1415 UTC

FRAM, Montreal, Que 15 June 2005 Visible Brightness Differences Fog vs Cloud-Free to Estimate Clearing Time Requires visible (CH1) imagery >1.5 hours after sunrise (Gurka 1974) –Uses following data: Digital brightness count difference (fog vs clear region) Obtain incoming solar radiation –Larger brightness difference = longer clearing time after sunrise

FRAM, Montreal, Que 15 June 2005 Depth Threshold for GOES Detection 270 m ~160 m ~100 m ?

FRAM, Montreal, Que 15 June 2005 Technology Upgrades Needed for Better Fog Detection from GOES

FRAM, Montreal, Que 15 June Optimal SWIR wavelengths

FRAM, Montreal, Que 15 June Improved Resolution Based on AVHRR IR (3.7 m and 11.0 m)

FRAM, Montreal, Que 15 June Improved Signal to Noise MODIS Fog DepthGOES Fog Depth

FRAM, Montreal, Que 15 June 2005 Summary and Conclusions GOES can effectively detect fog/low clouds and show areal extent –Problems with small scale, shallow fog Able to estimate fog depth, ceilings –Good correlation with SFO visibility data GOES needs to be complemented by surface data to be most effective GOES-R will have major upgrades

FRAM, Montreal, Que 15 June 2005 References Hunt, G. E., 1973: Radiative properties of terrestrial clouds at visible and IR thermal window wavelengths. QJRMS, 99, Eyre, J. R., J. L. Brownscombe, and R. J. Allam, 1984: Detection of fog at night using AVHRR imagery. Meteor. Mag., 113, Ellrod, G. P., 1994: Advances in the detectio of fog at night using GOES multispectral IR imagery, Wea. Forecasting, 10, Pagowski, M., I. Gultepe, and P. King, 2004: Analysis and modeling of an extremely dense fog event in Southern Ontario. J. Appl. Meteor., 43, 3-16.

FRAM, Montreal, Que 15 June 2005 References Brown, R., 1987: Observations of the structure of a deep fog. Meteorological Magazine, 116, Ellrod, G. P., 2002: Estimation of low cloud base heights at night from satellite infrared and surface temperature data. Nat. Wea. Digest, 26, Fischer, K. et al, 2003: Validation of GOES Imager experimental low cloud data products for terrestrial free space optical telecommunications. 12 th AMS Conference on Satellite Meteor. and Oceanography, Long Beach, California, 9-13 Feb Gurka, J., 1974: Using satellite data for forecasting fog and stratus dissipation. Preprints, 5 th Conf. on Weather Forecasting and Analysis, March 4-7, 1974, St. Louis, MO, AMS, Boston,