# Presentation: 923792

## Fog Monitor Overview

- Theory and Method
- Localization
- Customizing Your Monitoring Area
- Customizing Your Monitor Thresholds
- The Fog Monitor
- Customizing Your Display Thresholds
- The Fog Monitor Display

## Fog Monitor OverviewTheory and Method

- separate presentation
*by*
- Qin Zeng

## Supporting theory

- Spectral feature of fog in multiple satellite channels
- 1. Scattering radiation feature (Daytime)
-     (a) VIS Channel
-     (b) 10.7 (3.9) μm Channel
- 2. Emitting radiation feature (Nighttime)
-      (a) 3.9 μm Channel
-      (b) 10.7 μm Channel
- Kinematic feature of fog

*Fog monitoring is a kind of *_***object-oriented processing***__* *_*  *
*All we have to know is how to describe a fog object: its ****properties**** and its ****behaviors****** ***

***properties***

***behaviors****** ***

## Scattering/Reflecting Radiation(1) [1] 

- According to Mie scattering theory:
- In the VIS channel, reflectivity mainly is related to the depth of the cloud/fog.
- In channel 3.9μm, fog/stratus has maximum scatter rate with its size equivalent to 3.9 μm.

**Comments:**
**Here two differences can be used to distinguish fog and cloud: 1) VIS difference; 2**) **3.9 μm IR difference.**
**The fog region in satellite image should be smooth, edge-clear&regular.**
**Snow cover and sea ice are bad reflectors in channel 3.9 μm, while fog and stratus are good.**

## Scattering/Reflecting Radiation(2)[12]

**Data Normalization of the VIS satellite data**

## Normalization with fine tuning

**Scattering/Reflecting Radiation(3)**

## Scattering/Reflecting Radiation(4) [2][13][14]

- Assumed that all objects are black bodies:
- so TBemit3.9 = TB11 = Treal , and according to the Planck radiation law,

- This is how reflective product of RAMSDIS ONLINE is generated .  Because of the assumption of black body and TBemit3.9 = TB11 , it is an approximated reflective product and it does not take the angular correction into consideration
- So in our algorithms, it is not adopted for fog detection but for sea ice/snow cover exclusion.
- http://www.cira.colostate.edu/RAMM/Rmsdsol/main.html
- http://www.nrlmry.navy.mil/~turk/intro.html
- Allen, R.C., P.A. Durkee, and C.H. Wash, 1994: Snow-cloud discrimination with multispectral satellite images. J. Appl. Meteor

## Emitting Radiation(1)[2]

- 0 means “can be ignored”      1 means “major”

**Without the presence of sun light, in fog region, a positive value with**
**[10.7 ****μ****m channel - 3.9 ****μ****m channel]. This difference is caused by the emissivity difference of fog between 10.7 um and 3.9 ****μ****m.**
**Above will be good only during the night time:**
**Other water/ice clouds like AC/AS also look similar to Fog in  fog product [7]. But in 10.7 ****μ****m channel , the brightness temperature of fog is higher than that of higher water/ice cloud (AC/AS).  This can  in a degree help distinguish them.**

## Emitting Radiation(2) [2][3]

- R(satellite)  = R(ground) - R(absorbed) + R(cloud)
- Different emissivities of different cloud types
- Absorptivity is related to emissivity and the depth of the cloud/fog
- Planck radiation law

- Thin cloud          (night)   : TB(10.7 μm ) - TB(3.9 μm )  < 0
- Thick cloud        (night)   : TB(10.7 μm ) - TB(3.9 μm )  ~ 0
- Fog                     (night)   : TB(10.7 μm ) - TB(3.9 μm )  > 0
- ice cloud             (night)  :  TB(10.7 μm ) - TB(3.9 μm )  < 0
- Water/ice cloud  (night)  :  TB(10.7 μm ) - TB(3.9 μm )  > 0

**Comment:** So fog product should be checked to eliminate other higher water/ice cloud (AC/AS) by using TB derived from 10.7 μm channel.

- Sea Fog Discrimination Chart from Gary Elrod

## SAFESEAS Fog Monitor 

- _Nighttime_
- use 3.9 and 10.7 um infra-red images to produce night time fog product.
- Apply feature extraction to identify fog area based on night time fog product threshold

- Filter out high cloud using channel 10.7 um
- Apply a filter to eliminate very tiny size area as noise. (optional)
**Apply a filter to eliminate edge-irregular detected area (Optional)**

- process only those parts of the images that cover the monitoring area.

- _Daytime_
**use the visible image **
**Based on thresholds, apply feature extraction  algorithm to identify fog areas.**
**apply smoothness filter to eliminate noise. (optional)**
**Apply a filter to eliminate snow/ice (optional)**

- Twilight
- No
- Detection

## SAFESEAS Fog Monitor 

**Smoothness Definition****:**

- Smoothness = (1- deviation/mean) * 100%

- X denotes the gray value at the VIS pixel
- and n is the number of pixels

## SAFESEAS Fog Monitor Fog Monitor D2D display

## SAFESEAS Fog Monitor Fog Monitor D2D Display (Twilight)

## Limitations (1)

- When the sky is overcast with high level (thick) cloud, fog can not be seen through by satellite.
- During the transition of daytime and nighttime, neither VIS product nor fog product is good. And twilight is exactly the time when fog mostly affects marine interests.
-   Lack of observations in marine zones causes problem for verification
-   No effective approach to distinguish fog from stratus just using satellite data

## Limitations  (2)Data normalization

- At very low solar elevation, in the clear air region , there will still be small brightness values.  After normalization, they will be enhanced to look like fog areas and will be detected by the Fog Monitoring Processor.

## Limitations (3)

- Radiation from the ground goes through thin cirrus/high cloud ,which makes cirrus look like fog in VIS

## Limitations (3) (continue)  [14]

- Use fractal dimension to try to reduce the detection of the irregular area
- This is still not a good solution but supplied as an optional filter for user

**FD = 2ln(P/4)/ln(A)**
**P= perimeter A= Area**

- Count the outside edges of the grid boxes as the perimeter
- Amount of the grid boxes as the area.

## Limitations (3) (continue)

- Before

- After

- Application of Fractal Dimension to filter out irregular area

## Limitations (4) 

## Limitations (4) (continue)

## References

- [1] Liu Jian, Xu Jianmin, Fang Zongyi  Analysis of the particle sizes at the top of cloud and fog with NOAA/AVHRR data   Quarterly Journal of Meteorology
- [2] http://www.cira.colostate.edu/ramm/visit/fog.html fog product tutorial
- [3] http://meted.ucar.edu/topics_fog.php  Fog/stratus tutorials
- [4] Chen Weimin, Satellite Meteorology (Chinese version) Beijing Meteorological publishing house
- [5] Ellrod G P. Advances in Detection and Analysis of Fog at  night Using Advanced Very High Resolution Radiometer(AVHRR) Imagery [J] Meteo. Magazine
- [6] http://meted.ucar.edu/topics_satellite.php satellite products on METED
- [7] http://meted.ucar.edu/satmet/goeschan/ GOES channel selection on METED
- [8] http://www.ssd.noaa.gov/ satellite service division homepage
- [9] http://aviationweather.gov/awc/aviation_weather_center.html  Aviation Weather Center
- [10] http://www.cira.colostate.edu/  Cooperative Institute for Research in the Atmosphere, Colorado State University
- [11] http://www.nrlmry.navy.mil/  Naval Research Laboratory Monterey
- [12] ALBERS S. 1992: Photometric correction of GOES visible satellite images. Preprints, Sixth conf. on Satellite Meteorology and Oceanography, Atlanta, GA, Amer. Meteor. Soc., 223-225.
- [13] Allen, R.C., P.A. Durkee, and C.H. Wash, 1994: Snow-cloud discrimination with multispectral satellite images. J. Appl. Meteor
- [14] Olsen, E.R., R.D. Ramsey and D.S.Winn. 1993. A modified fractal dimension as a measure of landscape diversity.Photogram. Eng. Remote Sens. 59: 1517-1520
- [15]  http://www.cira.colostate.edu/RAMM/Rmsdsol/main.html    RAMSDIS ONLINE

## Fog Monitor OverviewKey Terms

*Area of Responsibility*
- 	An office’s area of responsibility (AOR) will consist of all the zones and counties for which it normally has the responsibility of issuing forecasts, watches, and warnings.
*Monitoring Area*
- 	An office’s monitoring area (MA) will consist of its AOR plus the AOR of each adjacent office.
*Channel 2*
- 	Channel 2 refers to the 3.9 micrometer infra-red satellite image.
*Channel 4*
- 	Channel 4 refers to the 10.7 micrometer infra-red satellite image.
*Fog Product*
- 	The fog product is the image derived by subtracting 10.7 micrometer image brightness temperatures from 3.9 micrometer image brightness temperatures.

## Fog Monitor OverviewLocalization

- will determine the default MA.
- 	*	which zones and counties are included in the MA.
- 	*	(OB-6) which fixed stations are in the MA.
- 	*	(OB-6) in which zone/county is each fixed station located.
- 	For the alpha test, the default MA will be based on the same “shape” files used for OB-4 SAFESEAS.  It is the responsibility of each office to make sure its systems have the current versions of these files *before* localization is run.
- will generate the “dummy” fog threat image to display for incomplete image sets.
- will generate the default (factory setting) monitor thresholds.
- (OB-6) will generate the default (factory setting) display thresholds.

## Fog Monitor OverviewCustomizing your Monitoring Area

- The Fog Monitor will provide a GUI for customizing the MA.  Specifically, the office will be able to:

- add and delete zones and counties.
- (OB-6) add and delete fixed stations.
- (OB-6) customize the association of fixed stations with zones and counties, that is, which stations are monitored to determine each zone’s / county’s threat level.

## Fog Monitor OverviewCustomizing Your Monitor Thresholds

- The Fog Monitor will provide a GUI that will enable offices to
- customize the range of:
- normalized brightness values that should be considered fog in visible images.
- temperature differences that should be considered fog in fog product images.

## Fog Monitor OverviewCustomizing Your Monitor Thresholds (continued)

- The customization GUI will also allow offices to enable/disable filters in the
- fog recognition algorithm:
- in channel 2 images, each pixel colder than a customizable threshold temperature should be considered snow/ice.
- in channel 2 images, each pixel having a brightness temperature colder than a  customizable threshold temperature should be considered cloud.
- in channel 2 images, each pixel having a brightness temperature warmer than a customizable threshold temperature should be considered ground or water surface.
- in visible images, a group of contiguous pixels having a brightness variation greater than a customizable threshold cannot be considered fog.
- in visible images, a group of contiguous pixels having fewer than a customizable number of pixels cannot be considered fog.
- a pixel within a configurable number of degrees from the terminator should not be monitored.

## Fog Monitor OverviewCustomizing Your Monitor Thresholds (concluded)

- In OB-6, a GUI will also be provided that will enable offices to customize the thresholds used for monitoring point observations (METARs, C-MAN reports, ship reports, buoy reports, and mesonet reports) for fog.  We will “negotiate” details for this tomorrow!

## Fog Monitor OverviewThe Fog Monitor

- The fog monitor will be a persistent background process, much like the SAFESEAS, SCAN, and
- FFMP processors.  The alpha test version will monitor:
- visible imagery at those times and in those places that the sun is sufficiently above the horizon;
- the fog product at those times and in those places that the sun is sufficiently below the horizon.
- In all cases, channel 2 images are used for certain kinds of filtering (unless the office has disabled
- the filters).
- The OB-6 fog monitor will also monitor point observations.  The details of this will be “negotiated”
- tomorrow.
- The fog monitor will determine a fog threat level for each zone/county in the MA, and an overall
- fog threat level for the entire MA.  The threat level is the most severe of all the individual pixel
- (OB-6: and point observation fog) threat levels for the past two hours.
- The fog monitor generates a fog threat level image and a zone fog threat file for use by the Fog
- Monitor display.  Finally, the Fog Monitor threat level indicator and the Fog Monitor display are
- signaled to update themselves.

## Fog Monitor OverviewThe Fog Monitor Display

- the Fog Monitor fog threat level image:
- 	*	black	= this location is not within the MA.
- 	*	gray	= insufficient data is available for determining
- 				the fog threat level for this location.
- 	*	green	= there *probably* is not fog at this location.
- 	*	yellow	= there may be fog at this location.
- 	*	red	= there *probably* is fog at this location.
- (OB-6) the Fog Monitor station plot:
- 	*	only reports from within the MA are plotted.
- 	*	variables to be plotted will be “negotiated” tomorrow.

## Fog Monitor OverviewThe Fog Monitor Display (concluded)

- the alpha test Fog Monitor zone fog threat table:
- 	*	two columns: zone ID and fog threat level (color).
- 	*	click column header to sort by that column.
- the OB-6 Fog Monitor zone/station fog threat tables and trends:
- 	*	except for variables, same as SAFESEAS.
- 	*	variables to be included will be “negotiated” tomorrow.