# Presentation: 923849

## Fog Monitor User Training

- http://www.nws.noaa.gov/mdl/fog_monitor/

- Mike Churma
- Jason Taylor
- May 2008

## Fog Monitor User TrainingTraining Objectives

- Introduction and Background
- Reviewing Station Observation Functionality
- Reviewing Fog Monitor’s presence in Guardian
- Explaining Satellite Algorithms
- Describing Satellite Algorithm Limitations

## The Fog Monitor is an AWIPS application that: 

Monitors and displays station observation data, to alert forecasters of low visibility conditions.

Uses GOES satellite imagery to identify and highlight potential areas of fog.

Allows users to configure alert thresholds, algorithm settings, and the application’s monitoring area.

- Monitors and displays station observation data, to alert forecasters of low visibility conditions.
- Uses GOES satellite imagery to identify and highlight potential areas of fog.
- Allows users to configure alert thresholds, algorithm settings, and the application’s monitoring area.

**Fog Monitor User Training**
***Background***

**Notes:**
The Fog monitor was developed to partially close the gap in fog monitoring by using GOES satellite imagery to monitor for fog areas not visible to in-situ observers and observing equipment.  But like most remote sensing tools and associated interpretation and monitoring algorithms, the Fog Monitor has some limitations, and can in certain situations produce incorrect results.

## Fog Monitor User Training Fog Monitor Display Features in D-2D

- D-2D fog threat level image

- Interactive Table

- Station Plot

- Guardian Icon

**Notes:**
The menu selection for Fog Monitor is located near the bottom of D-2D’s Obs menu.  When selected, three distinct display features will appear: a multi-loaded station plot , a satellite-derived fog threat level map, and an interactive display table.  By default, the monitoring area will consist of the local County Warning Area, each adjoining CWA, and the marine zones monitored by the local and adjoining CWA’s.  Red areas indicate the probable presence of fog, as determined by the algorithm settings.  Yellow areas indicate the possible presence of fog, and the green areas indicate no fog. Black areas are not monitored.  Gray areas denote regions of the monitoring area with an undetermined status.  Usually, gray areas will be caused by mid-level or high clouds, which will obstruct the Fog Monitor’s view of the surface. 
	In addition to the features listed above, the Fog Monitor also features an alert icon in Guardian, which reveals lowest visibility in the area, all reported obscurations, and the worst-case Fog Monitor algorithm results.  The icon updates automatically, with no intervention needed by the user.

## Fog Monitor User Training The Fog Monitor Zone/County Table

- Displays worst-case scenarios for counties and marine zones.
- Sorts data by column to reflect worst-case threat level.
- Displays colors (green-yellow-red) based on user-selectable thresholds
- Similar “buttonology” to SCAN and FFMP.
- Clicking on a zone/county name will reveal station information for that area

**Notes:**
The Fog Monitor table, upon loading, will show worst-case conditions for several attributes  on a county by county or marine zone by marine zone basis.  Red, yellow, and green thresholds are configurable; the R, Y, and G lettering in each box correspond to the threshold colors, for the benefit colorblind users.  Forecasters can to sort the columns, select attributes for display, align the table vertically, link the data to a D-2D frame, and configure the attribute thresholds.  Clicking on a zone/county ID will  These features are based on the SCAN & FFMP approach, so any users experience with those applications will find this table to be quite familiar.

## Fog Monitor User Training Fog Monitor Display Features in D-2D

- “Configure Thresholds” button activates an interface with which to modify color threshold s in the table.

**Notes:**
By selecting the “Configure Thresholds” button, users can display a window which will allow them to modify the red and yellow color thresholds.  Users can select threshols for their entire  monitoring area, or on a county, by county, zone by zone basis.  

## Fog Monitor User Training Fog Monitor Station Table

- Invoked by clicking on the county/zone ID in the zone table.  D-2D map will zoom to the corresponding area.
- Displays attributes for individual stations within the area.
- Sorts data by column
- Additional graphing and tabular features

**Notes:**
In the zone table, when a user left-clicks on the zone ID in the first (leftmost) column, the D-2D map will zoom and re-center to the selected area, and the Zone Table will be replaced by the Station Table.  Only those station platforms associated with the selected zone will be shown.  Values from each observation are displayed along the row.  At the station table level, users can invoke additional graphing and tabular features.

## Fog Monitor User Training Fog Monitor Display Features in D-2D

** ****Visibility**** **– in statute miles; rankable with an emphasis on lower values.
-  **Ceiling** – ***for METARS only*** – in hundreds of feet, ranked with emphasis on lower values;  “CLR” and “SKC” will be presented as necessary.
-  **Present Weather** – not rankable; “NM” (not monitored) at the zone level, text info available at the station level.
-  **Wind Direction** – rankable according to user-specified azimuths (“NM” if no angle is specified.)
-  **Wind Speed, Gust, Peak** -- in knots; rankable with an emphasis on higher values.
-  **Temperature, Dewpoint**, **Dewpoint Depression**– in degrees Fahrenheit; rankable with an emphasis on higher values.
-  **Relative Humidity** – In percent; rankable with an emphasis on higher values.
-  **Algorithm** – Green/Yellow/Red  worst-case thresholds in the zone; available at the zone level, but not at station level.

**Notes:**
This slide lists all the parameters shown by the Fog Monitor’s zone and station tables.  As mentioned before, the zone/county table shows “worst case” values for the area;  whether “worst” values  corresponds to highest or lowest values depends on each parameter.   The station table shows individual observation reports.  Note that Present Weather and Wind Direction values are not available in the Zone/County table This is due to the inherent difficulty in comparing present weather reports or directional values with the intent of determining the “worst” one (for Wind Direction, however a worst-case threat level is displayed in the zone/county table). Note also that the Algorithm parameter, which reflects the worst-case satellite-derived output for the area, is not yet available at the station level. 

## Fog Monitor User Training Fog Monitor Display Features in D-2D

**24-Hour trend graphs are available for most parameters.  Color levels correspond to those in the table.**

**Notes:**
Right-clicking on an individual data cell will invoke 24-hour trend graphs for most parameters.  The configurable color levels correspond to those seen in the station table.  In the current slide, trend graphs for visibility and wind speed are displayed.  Note that the visibility graph sets yellow and red thresholds for lower values, while wind speeds have yellow and red thresholds for higher values.

## Fog Monitor User Training Fog Monitor Display Features in D-2D

**Wind direction trend is represented by a hodograph**

**Notes:**
Third-button-clicking on a wind direction value will invoke a hodograph of directional values, with the latest values near the perimeter of the circle.  The color thresholds are represented as azimuthal arcs.

## Fog Monitor User Training Fog Monitor Display Features in D-2D

|  |
| --- |
| Observation History Table.  The parameters in the table will change depending on whether the site is land or sea-based, and also by how the user configures it. |

**Notes:**
The observation history table is invoked by third-button-clicking a station name within the Station Table.  This window displays a 24-hour history of the station’s data, in tabular form.  Users can click on the Configure button to choose various parameters to display – the list varies depending on whether the platform is land-based or maritime.

## Fog Monitor User Training Station Plots in Fog Monitor

- Fog Monitor provides a conventional observation display, differentiated in color by station type.

-  METARS
-  Fixed Buoys
-  Ships and Moving Buoys
-  Mesonets
-  MAROBS

**Notes:**
The Fog Monitor station plot consists of METARS, fixed buoys, moving buoys, ships, mesonets, and MAROBS.  The stations plotted in the map correspond to those viewable in the Fog Monitor station table.   The colors vary by station type, as selected by the D-2D.

## Fog Monitor User Training Fog Monitor Display Features in D-2D

_**Monitoring Area Configuration Tool (Zone Mode)**_
-  Found under the Fog Monitor selection in the Apps Launcher.
-  Add and remove counties/zones from the monitoring area.
-  Associate stations with zones/counties.
-  Set a time window to determine the duration of time to be monitored.
-  Set a distance from the nearest zone than a ship can be included.
-  Set the Fog Monitor algorithm status in Guardian.

**Notes:**
The Monitoring Area Configuration tool can be found under the Fog Monitor selection in the Apps Launcher.  By default, it launches in the “Zone” mode.  In this setup, users can select the counties and zones that the Fog Monitor will cover, by selecting the ID’s in the Monitoring Area Zones or Additional Zones windows, and clicking the Add and Remove buttons in between those two windows.  When a county or zone is highlighted in the “Monitor Area Zones” window, that area’s associated stations are listed in the “Associated Stations” window on the top right.  Users can then select the stations they wish to associate with, or disassociate from, the zones and counties, by highlighting their ID’s in the “Associated Stations” window or in the larger station list on the lower right.
     Users can also create their own zones (an offshore zone, for example), by selecting the “Add a New Zone to Monitor Area” button.  This new zone will be treated identically to the pre-existing zones, and can have stations associated with it.

## Fog Monitor User Training Fog Monitor Display Features in D-2D

_**Monitoring Area Configuration Tool (Station Mode)**_
-  Add and remove stations from the monitoring area.
-  Associate zones/counties to the stations.
-   Manually add a new station to the monitoring area

**Notes:**
Clicking on the “Station” button will switch the Monitoring Area configuration tool to the Station Mode.  In this setup, users can select the observing stations that the Fog Monitor will include, by selecting the ID’s in the “Monitoring Area Stns” or “Additional Stations” windows, and clicking the Add and Remove buttons in between those two windows.  When a station ID is highlighted in the “Monitoring Area Stns” window, the zones in which that station will appear are listed in the “Associated Zones” window on the top right.  Users can then select the zones and counties they wish to associate the station with, or disassociate the station from, by highlighting the ID’s in the “Associated Zones” window or in the larger station list on the lower right.  If a station is not represented in any of the Fog Monitor’s lists (e.g., a station that has just been commissioned), users can select the “Add a New Stn to Monitor Area” button to manually type in that station’s ID.

## Fog Monitor User Training Fog Monitor Display Features in D-2D

_**Monitoring Area Configuration tool -- Additional Features**_
-  Time Window
-  Ship Distance
-  Fog Monitor/Guardian toggle.

**Notes:**
There are a few additional features available in both the Zone and Station modes of the Monitoring Area Configuration tool.    
     The Time Window slider bar adjusts the time duration within which an observation will be included in the “worst-case” evaluations for Guardian.  It will also determine how far back the Fog Monitor algorithm results will be re-calculated if you change your algorithm thresholds on the fly.
     The Ship Distance slider bar determines how far a ship or moving buoy can be from a county or marine zone while still being included in that area’s station list.
     The “Fog Monitor algorithms....” button will allow the worst-case threat level from the satellite algorithm results to be included in the Guardian icon results.  By default, this button is set to “off”, to allow the Guardian icon to focus on station observations and measured visibility.

## Fog Monitor User Training Fog Monitor contribution to Guardian

- Fog Monitor’s fog icon in Guardian is colored according to worst-case threat level in the monitoring area.
- Scrolling the cursor over the icon reveals worst case visibility conditions, present weather obscurations, and satellite algorithm worst-case conditions.
- Users can control the visibility thresholds for this icon with a tool invoked from the Fog Monitor section of the Apps Launcher.

**Notes:**
The Fog Monitor’s background processor automatically evaluates observations and satellite data in the WFO-configured monitoring area for low visibility conditions.  It regularly updates a single, overall threat level for the monitoring area.  This threat level is displayed in the Guardian panel as a colored-coded icon containing a fog symbol.  The icon’s background color represents the overall threat level, determined by finding the worst-conditions for visibility, present weather obscurations, and, optionally satellite algorithm output. Scrolling the cursor over the icon reveals a popup with a summary of this worst-case information, including:
Fog/Vis Status: Latest update time for the Fog Monitor.
Lowest Vis:  Lowest reported visibility among the Fog Monitor’s collection of stations, and the time at which it was observed.
Monitored observations at GREEN/YELLOW/RED threshold level:  This line gives the worst case threshold level reached by the visibility values, as determined by user configuration.  Please note that the worst-case threshold may not always be generated from the lowest visibility, because users can set varying visibility thresholds on a county by county or zone by zone basis.  
Obscurations: Each unique present weather event that includes an obscuration will be listed in this row.  Obscurations include:
Fog (FG)
Mist (BR)
Smoke (FU)
Volcanic Ash (VA)
Widespread Dust (DU)
Sand (SA)
Haze (HZ)
Spray (PY)
Blowing Snow (BLSN)
 Monitored observations at GREEN/YELLOW/RED threshold level:  This line gives the worst case threshold level reached by the visibility values and present weather, as determined by users via the monitor thresholds interface.  Please note that the worst-case threshold may not always be generated from the lowest visibility, because users can set varying visibility thresholds on a county by county or zone by zone basis.  Also note that any reported obscuration will trigger a threat level of YELLOW (which can be superseded by RED threshold levels from visibility or the fog algorithms). 
Fog Monitor algorithms at GREEN/YELLOW/RED threshold level:  This is the worst-case threat level determined by the algorithms.  The results can be adjusted with the algorithm thresholds interface, and, optionally, this feature can be disabled using the Monitoring Area Configuration Interface, this allowing the overall threat level to be determined solely by the visibility and present weather.
Time Window (hours):  Also adjustable in the Monitoring Area Configuration Window, the time window reflects how long the Fog Monitor will store its worst-case evaluations before they expire.
In the App Launcher’s Fog Monitor sub-menus, the “Configure Visibility Thresholds for Guardian Monitoring” selection will activate the Station Monitoring Thresholds interface.  By selecting individual zones and threshold levels, then selecting the red or yellow values to the right of the arrows, users can move the values up or down by clicking on the arrows.  The “Select All” button will highlight all the zones.  Selecting Accept and then OK will modify the yellow and red threshold levels as seen in Guardian. 

## Fog Monitor User Training Fog Monitor Display Features in D-2D

- 	**black= this location is not within the Monitored Area.**
- 	gray= insufficient data available (usually due to clouds).
- 	green= there is *probably* no fog at this location.
- 	yellow= there *may* be fog at this location.
- 	red= there is *probably* fog at this location.

**Notes:**
The Fog Monitor ingests 3.9 micron and 10.7 micron infrared satellite products, as well as the visibile product during the day, and runs the data through several algorithms, to highlight areas of suspected fog.  This data is displayed in an image field  in the D-2D.  If the area is green, there is no likely no fog – the surface is visible to the satellite.  Yellows or reds indicate areas of potential and probable fog, respectively.  Gray portions of the image indicate areas in which the Fog Monitor could not make a determination, usually because of mid-level to high-level clouds that obscured the surface.  Black areas are not monitored.

## Fog Monitor User Training View Blocked by Opaque Higher Clouds

- Opaque high clouds can block the Fog Monitor’s view.

**Notes:**
When the area is overcast with mid-level or high clouds, the Fog Monitor will recognize the low brightness temperature of the clouds in the 10.7 micron image.  Overcast areas are shaded gray – the satellite algorithms cannot determine whether there is fog underneath the cloud cover.  The surface station observations, of course, are still available.

## Fog Monitor User Training Algorithm Scenarios

- _Nighttime_
- Use 3.9 and 10.7 m infra-red images to produce night time fog product.
- Fog areas based on night time fog product threshold

- Filter out high clouds using 10.7 m IR data.
- Apply a filter to eliminate small-sized areas as noise. (Optional)
- Apply a filter to eliminate rough-edged detected area (Optional)

- Daytime
- Use the visible image to identify areas of brightness consistent with fog.
- Apply smoothness filter to eliminate noise. (optional)
- Apply a filter to eliminate snow/ice (optional)

- Twilight
- No
- Detection

**Notes:**
The satellite products are filtered through a “pipeline” of several Fog Monitor  algorithms.  First, surface areas obscured by mid-level and high clouds are filtered out by identifying suitable low temperatures in the 10.7 micron data.  Then the algorithms search for contiguous areas in the data field that have characteristics – temperature, size, shape, consistency – that correspond to what we would expect to find in an area of fog.  Optional filters are available to filter out potential areas that may be to small for consideration, or may have a different shape that we’d reasonably expect (more on these algorithms later).
	These algorithms are -- or in the case of the optional ones, can be -- applied at any time of day.  The Fog Monitor, however, runs through different algorithms at different times of day.  At night, the process is simple  -- the 3.7 micron field is subtracted from the 10.7 micron field.  This is the established “Fog Product” that is already available independently on the D-2D.  In the daytime, 10.7 micron data is still used to identify midlevel and high clouds, but the visible product becomes the primary data source.  The visible product is analyzed to identify contiguous areas which have the range of brightness consistent with fog.  An optional filter may be then applied to evaluate the smoothness (i.e., uniform brightness) of the areas.  Where appropriate, a snow-ice filter can be applied to eliminate those bright areas from consideration.
	Twilight times near dawn and dusk represent temporary blind spots for the Fog Monitor’s algorithms.   The brightness is too low in the visible products for the daytime algorithms to reliably distinguish between fog and other features, while the 3.9 micron products are contaminated by scattered light, making it the fog product approach unreliable.  The Fog Monitor represents this blind spot with a gray “unknown” area.  It will also apply different algorithms – daytime or nighttime – to the areas on either side of the twilight area.

## Fog Monitor User Training Fog Monitor Image from Default Thresholds Settings

**Notes:**
Algorithms settings are controlled through the Fog Monitor’s Algorithm Thresholds tool, launched in the Fog Monitor’s App Launcher submenu (with the “Configure Algorithm Thresholds” selection).  Users are able to tailor the algorithms’ settings to reflect local conditions.

## Fog Monitor User Training Customizing Your Monitor Thresholds

-     The Fog Monitor GUI enables offices to customize the range of:
- IR brightness temperature differences - fog in fog product images.
- Normalized visible brightness values - fog in visible images.

**Notes:**

The algorithm tool allows uses to modify the temperature difference and brightness range within which potential areas of fog will be identified.

Fog Product [T (10.7) – T (3.9) 
This nighttime “Fog Product” threshold setting allows user to adjust the temperature difference range. Highlight the button by the text to select this threshold, and use the left and right arrows to modify the range in which yellow and red areas will appear. Increasing the area of yellow and red will increase the range which can be flagged as potential fog areas.

VIS (Normalized Count) 
This is a daytime range of normalized brightness values, perhaps less intuitive than the Fog Product, but the concept is similar. Increasing the range of red and yellow values will increase the likelihood that the application will highlight an area as fog. 

## Fog Monitor User Training Decreasing Maximum Cloud Temperature

- Decreasing the Maximum Cloud Temperature Threshold will increase the potential areas considers as fog.

**Notes:**
The Maximum Cloud Temperature setting is always applied, and it is the most influential threshold.  Temperatures lower than the setting will be discounted as mid-level or high clouds, and corresponding areas will be colored gray in the D-2D image.

## Fog Monitor ThresholdsIncreasing Maximum Cloud Temperature

- Increasing the Maximum Cloud Temperature Threshold will decrease the potential areas considered as fog.

**Notes:**
Increasing the temperature will increase the gray area in the D-2D map.  The Fog Monitor’s gray areas indicate an unknown condition , since the application does not know what is occurring on or near the surface.
	As with all algorithm thresholds within this GUI, the user should use meteorological knowledge to determine the settings. A temperature setting of -25 C, for example, is unnecessarily low for fog detection, while a setting of +15 C will be too warm for most mid-level or high clouds. 

## Fog Monitor User Training Daytime Ice/Snow vs. Fog Threshold

**Notes:**
Two other temperature thresholds are optional.  The first is the Daytime Ice/Snow versus Fog Threshold (C).  This algorithm evaluates bright areas in the visible satellite data, and tries to discern whether they are snow cover (or sea ice cover) or fog.  Snow cover and sea ice are weak scatters at a wavelength of 3.9 microns, while fog and status clouds are strong scatterers.  This algorithm takes advantage of the strong scattering properties of fog at 3.9 microns when compared to snow or ice., which leads to a higher brightness temperature for fog at 3.9 microns. If the Fog Monitor encounters a bright area that falls within the visible normalized count thresholds (set in this GUI, as described above), then this brightness temperature threshold will help the application distinguish fog from ice or snow cover. Raising the threshold will increase the brightness temperature range which the Fog Monitor will identify with snow or ice. Users can turn this algorithm off by toggling the small square button on the left.

## Fog Monitor ThresholdsCool Fog vs. Warm Surface Threshold

**Notes:**
The second optional temperature algorithm is the Cool Fog versus Warm Surface Threshold.  This scroll bar will set a 10.7 micron brightness temperature threshold between a cold fog area and a warmer surface. Because of the assumption of a warmer surface, this threshold will likely work best with radiation fog or evaporation fog, especially when the fog layer is thick (since the satellite data will reveal the brightness temperature of the cool top of the fog layer).  Used in combination with the maximum cloud temperature setting, this threshold can enforce a temperature range in which the application will look for fog.  This threshold will likely not work as well, however, during an advection fog scenario, when warm air travels over a cool surface. 

## Fog Monitor User Training Decreasing the Daytime Smoothness Threshold

- Decreasing the Daytime Smoothness threshold will increase the bright areas of depicted fog.

**Notes:**
One distinguishing feature between fog and mid-level clouds in visible satellite data is the relative brightness uniformity of fog – it will tend to have a more uniform, “smoother” brightness profile than will clouds. The Daytime Smoothness Threshold checks the variation of the brightness scale values in the visible data.  

## Fog Monitor User Training Increasing the Daytime Smoothness Threshold

- Increasing the **Daytime Smoothness Threshold **will help to filter out bright areas which may not be fog.

**Notes:**
Increasing this threshold will help to filter out bright areas which are not fog. This algorithm is not applicable to the nighttime regime, because both fog areas and mid-level clouds have relatively uniform IR signatures – it would be difficult to distinguish them using the smoothness algorithm. 

## Fog Monitor User Training Adjacency Threshold

- The **Adjacency Threshold** determines a minimum pixel size for the potential fog areas.

**Notes:**
The Adjacency Threshold determines a minimum pixel size of the potential fog areas.  This helps to eliminate spurious signals from individual bright pixels.

## Fog Monitor User Training Increasing Adjacency Threshold

- Increasing the Adjacency Threshold will increase the minimum size at which an area of fog will be flagged.

**Notes:**
Increasing the Adjacency Threshold will increase the minimum size at which an area of fog will be flagged.  This will filter out the noise from errant bright data pixels, though care must be taken to not set the thresholds so high as to eliminate legitimate small-scale, patchy fog.

## Fog Monitor User Training Increasing the Twilight Angle Threshold

- Increasing the Twilight Angle Threshold during twilight hours will allow Fog Monitor to apply an “unknown” determination to more areas illuminated by low angle sunlight.

**Notes:**
The higher the angle, the more area will be covered by the twilight default.

## Fog Monitor User Training Decreasing the Twilight Angle Threshold

- Decreasing the Twilight Angle Threshold during twilight hours will allow Fog Monitor to apply an “unknown” determination to less areas illuminated by low angle sunlight.

**Notes:**
Near dawn and dusk, a straight gray band can be seen cutting through the monitoring area. This indicates an area of twilight. The Fog Monitor is often ineffective near dawn and dusk, because those times provide “in-between” satellite data conditions: there is not enough reflected light for the visible-range algorithms to be effective, but there is too much scattering in the 3.9 micron channel to allow the use of the nighttime Fog Product channel differences (which assume black body emissions, not scattered returns).  The band identifies a blind spot for the Fog Monitor; it also marks the switchover between daytime and nighttime algorithm regimes.  The Twilight Angle Threshold determines the sun angle (from the horizon) that this band corresponds to.

## Fog Monitor User Training Default Twilight Angle Settings and Image

**Notes:**
Increasing the sun angle will increase the size of the twilight band.  

## Fog Monitor User Training Increasing Fractional Dimension Threshold

- Increasing the Fractional Dimension Threshold will allow for shapes with more jagged edges.

**Notes:**
The Fractal Dimension Threshold takes measure of the “jaggedness” of the edges of the detected area. Clouds are assumed to have rougher edges than fog banks, which often conform to the topography.  This algorithm will allow the user to filter out the rough edges of low-lying clouds, favoring the more linear edges of fog banks. 

## Fog Monitor User Training Decreasing Fractional Dimension Threshold

- Decreasing the Fractional Dimension Threshold will allow Fog Monitor to consider brightness areas with relatively straight edges.

**Notes:**
Lowering the threshold setting will filter out the rough edged areas that are more characteristic of clouds than foug.  Cases of valley fog can have jagged edges, though, so the user must be careful not to eliminate those features by setting this threshold too low. 

## Fog Monitor User Training Algorithm & Display Limitations

-  Low sun conditions/Twilight
-  Brightness Averaging at Feature Boundaries
-  Brightness averaging between clouds and surface
-  Brightness averaging of cloud shadows
-  Sun Glint

**Notes:**
The Fog Monitor’s satellite display helps to highlight potential areas of fog, but in doing so, can also sometimes highlight areas mistaken for fog.  These “false positive” results are often artifacts of how the satellite data is processed.  Users routinely recognize and discount these areas when looking at normal satellite imagery, and it is important that these areas will be recognized in the Fog Monitor’s green/yellow/red color scheme as well.

## Fog Monitor User Training Low Sun Conditions/Twilight

- Decreasing sunlight at lower angles affects Fog Monitor’s ability to properly normalize the visible satellite images.

**Notes:**
Brightness levels in a visible satellite image will be affected by the sun angle – areas under direct sunlight will appear brighter than areas in which the sun is low on the horizon.  To offset this affect, the Fog Monitor will attempt to normalize brightness levels over the entire visible image.  At low sun angles, though, the correspondingly low brightness values can be greatly altered by normalization.  The Fog Monitor’s data therefore becomes degraded, and inaccurate fog threat levels may result.
	This is why visible data will be unreliable for fog threat detection at sunrise and sunset.  This affect may be more persistent at high latitudes around the time of the winter solstice.
	As was mentioned previously, the nighttime fog product also has a blind spot at sunrise and sunset, because near-infrared scattering will intermingle with the 3.9 micron energy emitted from the clouds, contaminating the data received by the satellite.

## Fog Monitor User Training Brightness Averaging at Feature Boundaries

- Satellite’s View
- (with pixel boundaries superimposed)

- fog

- altostratus

- snow

- ground

- fog

- ground

- Actual Situation
- (with pixel boundaries superimposed)

- (A)

- (B)

- (C)

- Fog Threat Image
- (with pixel boundaries superimposed)

- Boundary between fog and dark ground.  Top row of green pixels is too dark to recognize as fog.  The fog area looks smaller.
- Boundary between dark ground and snow.  Column of red pixels is false fog.
- Boundary between fog and bright higher cloud.  Left column of green pixels is too bright to recognize as fog.  The fog area looks smaller.

**Notes:**
Pixel values are the average of the brightness values of everything within the ground area corresponding to the pixel.  When that average value is within the range of brightness values recognized as fog by the Fog Monitor, then the pixel is wrongly identified as fog.  When that average value is not within the range of brightness values recognized as fog by the Fog Monitor, then the Fog Monitor will identify the pixel as not-fog, even when fog is present.  These problems are most likely along feature boundaries.  This can make fog areas look a little smaller than they actually are.
The satellite’s sensor has limited resolution.  Each pixel’s brightness value is basically the average of the brightness values for everything within that pixel.  Suppose the ground area represented by a pixel consists of dark green evergreen trees scattered in an area that is snow-covered, or in an area where the soil is a bright, nearly white sand.  The sensor only sees some average brightness for the whole area.  It is possible for that average brightness value to be within the brightness range recognized as fog by the Fog Monitor.
The area represented by a pixel may contain the edge of a region of fog.  The satellite’s sensor sees the average of the brighter fog and the darker ground, possibly resulting in a brightness value too dark to be recognized as fog by the Fog Monitor.  Thus a region of fog may be larger than it appears in the fog threat image.
The area represented by a pixel may contain the edge of a deck of higher clouds, but no fog.  The satellite’s sensor sees the average of the brighter cloud deck and the darker ground, possibly resulting in a brightness value within the brightness range recognized as fog by the Fog Monitor.  The same thing can happen when the area represented by a pixel contains the edge of a snow-covered region.
The area represented by a pixel may contain both fog and the edge of a deck of higher clouds.  The satellite’s sensor sees the average of the brighter cloud deck and the darker fog, possibly resulting in a brightness value too bright to be recognized as fog by the Fog Monitor.  Thus a region of fog may be larger than it appears in the fog threat image.

## Fog Monitor User Training Brightness averaging between clouds and surface

**Small mid-level or translucent high-level clouds**

- ground

- fog

**Actual**
**Situation**

- Averaged brightness
- matches fog.

- Averaged brightness
- too high for fog.

**Satellite’s**
**View**

**(A)**

**(B)**

- Small bright clouds or high translucent clouds makes the ground below look brighter to the satellite, causing the Fog Monitor to:
- (A) incorrectly identify the ground below the cloud deck as fog.
**(B)** fail to recognize the fog below the cloud deck.

**Notes:**
The illustration above demonstrates how the satellite’s brightness averaging can lead erroneous Fog Monitor output.  
	Each pixel (represented by the small squares in the diagrams) is assigned an averaged brightness value by the satellite.  In scenario A, the pixel area contains dark ground and bright high clouds.  The pixels’ averaged value falls into a brightness range in between the ground and cloud values, which may correspond to brightness values associated with fog.  The Fog Monitor may therefore mistakenly evaluate the averaged pixel values as indicators of fog. 
	In scenario B, fog lies  beneath the bright clouds, but the averaged pixel values may be too bright to fall into the expected brightness ranges for fog.  The Fog Monitor algorithms may therefore miss detecting the fog.
	These types of scenarios may also occur with a layer of thin, translucent high clouds, because the satellite would be averaging scattered light from both the clouds and the surface.

## Fog Monitor User Training Brightness Averaging of Cloud Shadows

- Satellite’s View

- Fog Threat Image

- snow-covered ground

- fog

- ground

- (A)

- (B)

**The red area is the ground directly under the cloud.  The medium gray area is the ground obscured from the satellite’s view by the cloud.   The blue area is the cloud’s shadow.**

- The area outlined in red  is the ground directly under the cloud.  The medium gray area is the area that is obscured from the satellite’s view by cloud.  The area outlined in blue is the cloud’s shadow.

**lenticular**

**cumulus**

- Satellite’s View

- Fog Threat Image

**Notes:**
Cloud shadows can cause the Fog Monitor to misinterpret a situation.   In Case A, a cumulus cloud shadow darkens bright, snow-covered ground enough to cause the Fog Monitor to wrongly identify the shadowed area as fog.  In Case B, an lenticular cloud shadow covers a fog bank, and darkens the image enough that the Fog Monitor misses the shaded fog area.

## Fog Monitor User Training Limitations -- Sun Glint

**Fog Monitor User Training**** *****Limitations***** ****-- *****Sun Glint***

**Notes:**
Often in a visible satellite image,  sun glint – the sun’s reflection-- can be seen on the water,  range from a small bright spot to a large dull area with diffuse boundaries, depending on the roughness or smoothness of the water surface.  
Sun glint does not have a sharp boundary, rather it gradually fades out from the center of the reflection.  The ocean otherwise appears quite dark in visible images.  Somewhere within the area where the reflection is fading, the sea surface may appear to have brightness values within the range recognized as fog by the Fog Monitor.  

## Fog Monitor User Training Web Site

- http://www.nws.noaa.gov/mdl/fog_monitor/

- Users Guides
- Technical Briefs
- Troubleshooting Tips
- SAFESEAS/Fog Monitor listserve information

## Fog Monitor User Training Training Summary

- During this training the user has been:
- Introduced to the Fog Monitor.
- Informed about the Fog Monitor surface observation functionality.
- Informed about the Fog Monitor information available in Guardian.
- Informed about the Fog Monitor’s satellite algorithms.
- Informed about the limitations of the Fog Monitor’s satellite algorithms.

## Fog Monitor User Training

- http://www.nws.noaa.gov/mdl/fog_monitor/

- Michael Churma
- Jason Taylor