Category Archives: California

Marine Stratus over southern California

GOES-R IFR Probability, hourly from 0300 to 1300 UTC, 13 March 2017 (Click to enlarge)

Note:  GOES-R FLS products are currently derived from GOES-13 and GOES-15 data.  A GOES-16 version of the GOES-R FLS products will not be available until later in 2017.

IFR Conditions developed early on March 13th 2017 as Marine Stratus moved over the southern California. This is a typical occurrence that nevertheless requires timely monitoring because of the impact of fog on transportation. The Brightness Temperature Difference fields, below, show the tops of the clouds. Water clouds do not emit 3.9 µm radiation as a blackbody, but they do emit 10.7 µm radiation nearly as a blackbody. Result: Inferred brightness temperatures (a computation that assumes blackbody emission from the source) are cooler and 3.9 µm than at 10.7 µm, and a difference field will highlight clouds made up of water droplets, i.e., stratus. If the stratus is at the surface, fog is a result. Low IFR Probability fields, above, include surface information in the form of low-level relative humidity fields from the Rapid Refresh model. Only where saturation near the surface is indicated by the model will Low IFR Probabilities be large.

In the animation above, IFR conditions develop along the coast and penetrate inland as Low IFR Probabilities increase.  Probabilities are decreasing by 1300 UTC.

IFR and Low IFR Conditions are shown in this plot from the Aviation Weather CenterThis toggle, from 0300 UTC, shows both Low IFR Probability and IFR Probability.  As might be expected, IFR Probabilities exceed Low IFR Probabilities

GOES-15 Brightness Temperature Difference (3.9 µm – 10.7 µm) Fields, hourly from 0300 to 1300 UTC on 13 March 2017 (Click to enlarge)

IFR Probability vs. Brightness Temperature Differences over California


GOES-15 Brightness Temperature Difference Fields (3.9 µm – 10.7 µm), 0600-1200 UTC on 21 November 2016 (Click to enlarge)

GOES-15 Brightness Temperature Difference fields (3.9 µm – 10.7 µm, above, from 0600-1200 UTC on 21 November) can detect low clouds because water-based clouds do not emit 3.9 µm radiation as a blackbody, but they do emit 10.7 µm radiation as a blackbody. Consequently, the brightness temperature computed from 3.9 µm radiation is cooler than that computed by 10.7 µm radiation. The animation above depicts two challenges that arise from using brightness temperature difference fields. If mid-level clouds or cirrus are present, the satellite cannot view the low-level clouds that might be associated with fog. That is the case above over the San Joaquin Valley at the start of the animation. Later on, as the higher clouds move out, a strong signal develops everywhere. Brightness Temperature Difference fields are not giving useful information because alone they cannot distinguish between mid-level stratus and low stratus/fog.

In contrast, the GOES-R IFR Probability fields suggest the likelihood of IFR conditions in three distinct regions: Along the Sierra Nevada, where terrain is likely to rise up into the Cloud Base, in the San Joaquin Valley, and along the coastal range. Largest values of IFR Probability do occur where (or near where) ceilings and visibilities are reduced and can help a forecaster restrict interest to where it is actually warranted. IFR Probability fields combine satellite observations of stratus with Rapid Refresh model predictions of low-level saturation, so IFR Probability fields are better able to highlight regions of low stratus and fog.


GOES-R IFR Probability Fields, 0600-1200 UTC on 21 November 2016 (Click to enlarge)

Multiple Cloud Layers and Topography


GOES-R IFR Probability Fields, 1315 UTC on 22 April 2016, along with surface observations of ceilings and visibilities (Click to enlarge)

The 1315 UTC image of GOES-R IFR Probabilities, above, shows an axis of higher probabilities aligned with the topography of the Sierra Nevada. Note that Blue Canyon (KBLU) is the sole station reporting IFR Conditions. Did conventional satellite data capture this event? The Water Vapor (6.5µm) and Brightness Temperature Difference fields (10.7µm – 3.9µm), below, do not show evidence of low clouds;  indeed, the cirrus signature in the water vapor must mask any satellite observation of low clouds banked along the Sierra Nevada. Thus a fused product that combines model data and satellite data (such as IFR Probability fields) must be used, and the relatively flat nature of the IFR Probability field above confirms that Rapid Refresh information on low-level saturation is the reason why IFR Probability values are elevated along the mountains.


GOES-15 Water Vapor (6.5 µm), left, and GOES-15 Brightness Temperature Difference Field (10.7 µm – 3.9 µm), right, at 1315 UTC 22 April 2016 (Click to enlarge)

IFR Probability Fields earlier in the night did have a satellite component to them. The values at 0300 and 0600, below, show the gradual encroachment of cirrus from the south and west over the low clouds along the Sierra Nevada. After 0600 UTC, only model data were used over the Sierra as high-level cirrus blocked the satellite view.


Brightness Temperature Difference (10.7µm – 3.9µm) Fields (Left) and GOES-R IFR Probaility Fields (Right) from 0300 (Top) and 0600 (Bottom) on 22 April 2016 (Click to enlarge)

IFR Probability and Topography


It is not unusual for land to ascend into the clouds in regions where Moutains abut large valleys or gently sloping plains.  This is especially apparent in California on either side of the Central Valley.  The toggle above shows IFR Probability fields at 1645 UTC on 9 March, and a high-resolution topographic image.  High IFR Probabilities are well correlated with high terrain. This is something a user must consider when using the product.

Fog in California’s Central Valley


GOES-R IFR Probability Fields and GOES Brightness Temperature Difference (10.7 µm – 3.9 µm) at 0500 UTC, 25 January 2016 (Click to enlarge)

Fog developed over California’s central Valley during the early morning of 25 January 2016.  The toggle above shows the GOES-R IFR Probability field and the GOES Brightness Temperature Difference field at 0500 UTC, before any IFR conditions were reported. Note that the brightness temperature difference field reports large regions of water-based clouds over Nevada — IFR Probability fields screen out this region because low-level saturation is not occurring in the Rapid Refresh Model.  The inference should be that any cloud present there is mid-level stratus rather than fog. That screening of water-based clouds continues at 0700 UTC, below.  Around Hanford, IFR Probability values have increased as ceilings and visibilities have lowered.


As above, but at 0700 UTC (Click to enlarge)


As above, but at 0900 UTC (Click to enlarge)

By 0900 UTC, above, high clouds have moved over Hanford (shown as dark streaks in the brightness temperature difference field enhancement) where IFR conditions are occurring. IFR Probability fields correctly continue to maintain a strong signal around Hanford even though brightness temperature difference fields cannot detect low clouds because of the presence of high clouds. Thus, GOES-R IFR Probability in that region is controlled by Rapid Refresh Model output that successfully predicted the presence of low-level saturation. By 1100 UTC, below, the high clouds have moved south, and GOES-R IFR Probability values rebound. When both Satellite data and Model data can be used as predictors, IFR Probability field values are larger than when only satellite data or only model data are used as predictors.


As above, but at 1100 UTC (Click to enlarge)


As above, but at 1300 UTC (Click to enlarge)

By 1300 UTC, the region of IFR Conditions near Hanford has expanded — and a second region has developed closer to Sacramento.  IFR Probability fields continue to screen out regions that the brightness temperature difference field alone suggests are regions of low stratus.  Surface-based observations do show regions of mid-level stratus over Nevada, around San Francisco, and over northern California, three regions where the brightness temperature difference signal is strong.  The higher terrain of the Sierra Nevada to the east of the Central Valley also shows higher IFR Probability as might be expected where terrain rises up into mid-level stratus.

The 1500 UTC images, below, continue these trends.  By 1700 UTC, at bottom, there is enough solar radiation reflecting off the clouds that the brightness temperature difference has flipped sign.  The IFR Probability field, however, has a consistent signal over the persistent region of low clouds/fog around Hanford and around Sacramento.


As above, but at 1500 UTC (Click to enlarge)


As above, but at 1700 UTC (Click to enlarge)

Central Valley Fog under High Clouds

A potent storm in the Gulf of Alaska (Link to surface map) is allowing high clouds to spread inland over much of the west coast of the United States. Dense fog has formed underneath that cloud deck in the California’s Central Valley, and advisories have been issued (Scroll down to see the screen-grab of the NWS Sacramento Office Website). How can satellite products be used to detect such a fog that is hidden by high clouds?

The toggle below shows the GOES-15 Brightness Temperature Difference fields (with a pattern characteristic of mostly high (ice) clouds with a few breaks in the high cloud allowing the satellite to view lower water-based clouds) and the GOES-R IFR Probability field.  IFR Probability is correctly alerting any forecaster to the probability that IFR conditions are occurring in the Central Valley.  IFR Probability fuses information from the Satellite (not particularly helpful in this case) and information from the Rapid Refresh Model predictions of low-level saturation.  The Rapid Refresh is correctly diagnosing the presence of saturation, and IFR Probabilities are enhanced over the Central Valley.


GOES-15 Brightness Temperature Difference and GOES-R IFR Probability fields, 1115 UTC on 8 December 2015 (Click to enlarge)


Coastal California Fog


Toggle between Suomi NPP Day Night Band Visible (0.70 µm) Image and Brightness Temperature Difference (11.45 µm – 3.74 µm) , 1003 UTC 12 August 2015 (Click to enlarge)

Suomi NPP data from 1003 UTC on 12 August, above, shows evidence of a cloud bank hugging the northern California coast from Cape Mendocino to San Francisco Bay. It also penetrates inland to Santa Rosa in Sonoma County. (Note also how the fires burning in interior show up well in the Day Night Band — they are emitting visible light — and in the Brightness Temperature Difference band — because they are much warmer in the 3.74 µm image than in the 11.45 µm image).

Terra overflew the California coast at ~0600 UTC and Aqua overflew the coast at ~1000 UTC; MODIS-based IFR Probabilities could be constructed from these overpasses, and they are shown below.  At 0609 UTC, High IFR Probabilities (>90%) are confined to coastal Sonoma County and along the coast from Humboldt county north.  By 1023 UTC, high IFR Probabilities stretch along the entire coast from Cape Mendocino to the mouth of San Francisco Bay, with evidence of inland penetration along river valleys.  (The Russian River, for example, and perhaps the Noyo River in Mendocino County)


Terra MODIS-based GOES-R IFR Probability fields, 0609 UTC, 12 August 2015 (Click to enlarge)


Aqua MODIS-based GOES-R IFR Probability fields, 1023 UTC, 12 August 2015 (Click to enlarge)

MODIS can give high-resolution imagery, but the infrequency of the scenes tempers its usefulness. In contrast, GOES-15 (as GOES-West) views the California coast every 15 minutes, and this excellent temporal resolution (that will improve in the GOES-R era) allows a better monitoring of the evolution of coastal fog. Hourly plots of GOES-R IFR Probability, below, computed from GOES-15 and Rapid Refresh Data show the slow increase in GOES-R IFR Probabilities along the coast as ceilings and visibilities drop.


GOES-R IFR Probability fields, 0400-1200 UTC 12 August 2015 (Click to enlarge)

In the animation above, note the general increase in GOES-R IFR probabilities at 0900 UTC relative to 0800 and 1000 UTC. We are close enough to the Solstice that Stray Light Issues are starting. The 0800, 0900 and 1000 UTC brightness temperature difference imagery, below, shows the large signal increase at 0900 UTC that can be attributed to stray light. GOES-R IFR Probabilities can tone down that increase somewhat — because the model data will now show low-level saturation in regions where stray light erroneously suggests low clouds/fog might exist. GOES-R IFR Probabilities also screen out the constant fog signal over the Central Valley of California (and over Nevada) that is driven not by the presence of low clouds but by soil emissivity differences.


GOES-15 Brightness Temperature Difference (10.7 µm – 3.9 µm), 0800, 0900 and 1000 UTC 12 August 2015 (Click to enlarge)

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GOES-14 in SRSO-R mode (see also this link) viewed the west coast starting at 1115 UTC today. The Brightness Temperature Difference field, below, (click here for mp4) shows the slow expansion/evaporation of the low stratus/fog. (GOES-R IFR Probabilities were not computed with the GOES-14 1-minute imagery). The rapid change in the field at sunrise occurs because solar radiation at 3.9 µm quickly changes the brightness temperature difference from negative to positive.

Visible Imagery is below (Click here for mp4).


GOES-14 Visible Imagery (1330-1700 UTC) (Click to animate)

Resolution Matters


GOES-R IFR Probabilities computed from MODIS data and from GOES-15 data, ~1000 UTC on 22 June 2015 (Click to enlarge)

GOES-R IFR Probability was created with an eye towards using data from GOES-R (currently scheduled for launch at the end of March 2016). GOES-R will have better spatial, temporal and spectral resolution than the present GOES. A benefit of better spatial resolution is shown in the toggle above between present GOES (nominal 4-km resolution — vs. the nominal 2-km resolution that will be on GOES-R) and MODIS (1-km resolution). The small valleys along the northern California coastline are far better resolved. The fog/low clouds over San Francisco bay is also better resolved (and the same could be said for the Salinas Valley, south of Monterey Bay if this scene were shifted slightly south). (You might notice a slight 1-pixel shift between MODIS and GOES-15 IFR Probabilities. GOES-15 navigation is compromised by the lack of star-tracking data, so MODIS data are probably better navigated.)


GOES-15 Brightness Temperature Difference (10.7 µm – 3.9 µm) and GOES-R IFR Probabilities, 1000 UTC on 22 June 2015 (Click to enlarge)

IFR Probabilities are derived from GOES-15 brightness temperature difference fields, and a benefit of the IFR Probabilities is obvious above. Brightness Temperature Differences can be driven by emissivity differences in soil. These false positives over Nevada (from the point of view of fog detection) are easily removed if the Model Data does not show low-level saturation.


Suomi NPP Day/Night band imagery, Brightness Temperature Difference Fields (11.45 µm – 3.74 µm), and 3.74 µm Image, 0921 UTC on 22 June 2015 (Click to enlarge)

Suomi/NPP’s early morning overpass also detected the presence of fog/low stratus over the valleys along the northern California coast. The Brightness Temperature Difference field shows things distinctly. The Day-Night Visible imagery shows little in the way of fog on this day, as the waxing crescent moon had already set so no lunar illumination was present. The Day Night band is included here because it shows a very bright wildfire south of Lake Tahoe. That feature is also present in the 3.74 µm imagery. Fog and stratus is also evident in the 3.74 µm imagery, detectable based on its very smooth appearance.

Fog over Coastal California


GOES-R IFR Probabilities computed from GOES-West and Rapid Refresh Data, 0300-1200 UTC on 29 May 2015 (Click to enlarge)

GOES-R IFR Probability fields are challenged most days by the diurnal penetration of coastal fog and stratus that occurs overnight along the California Coast. In the animation above, IFR Probabilities increase in regions along the coast, and also in valleys (such as the Salinas Valley) where fog moves inland. Note above how Monterey, Watsonville and Paso Robles all show IFR (or near-IFR) conditions as the IFR Probabilities increase. The same is true farther north at Santa Rosa and at Marin County Airport, and farther south at Avalon, Ontario, Point Mugu and LA International. IFR Probability fields routinely do capture these common fog events.

The Brightness Temperature Difference Field (10.7 µm – 3.9 µm), below, captures the motion of these low clouds as well. However, numerous ‘false positive’ signals occur over the central Valley of California (likely due to differences in soil emmissivities). The GOES-R IFR Probability field can screen these regions out because the Rapid Refresh data in the region does not show saturation in the lowest kilometer. Note also how the Brightness Temperature Difference field gives little information about low clouds where high clouds are present (over the Pacific Ocean in the images below). IFR Probability fields, however, do maintain a strong signal there because data from the Rapid Refresh strongly suggests the presence of low clouds/fog.


GOES Brightness Temperature Difference Fields, 0400-1200 UTC on 29 May 2015 (Click to enlarge)

Suomi NPP makes an overflight over the West Coast each day around 1000 UTC, and the toggle of the Day Night Band and the Brightness Temperature Difference field (11.45 µm – 3.74 µm) is shown below. The moon at this time was below the horizon, so illumination of any fog is scant; the brightness temperature difference field does highlight regions of water-based clouds (that is, stratus); however, it does not contain information about the cloud base. In other words, it’s difficult to use the brightness temperature difference product alone to predict surface conditions.


1010 UTC Imagery from Suomi NPP VIIRS Instrument: Day Night Visible Band (0.70µm) and Brightness Temperature Difference Field (11.45µm  – 3.74µm) (Click to enlarge)

GOES-14 is in SRSO-R mode, and its view today includes the west coast. The animation below shows the erosion of the fog after sunrise at 1-minute intervals. (Click here for mp4, or view it on YouTube). (Click here for an animation centered on San Francisco).

GOES-14 Visible (0.6263 µm) animation, 29 May 2015 [click to play very very large animation]

GOES-14 Visible (0.6263 µm) animation, 29 May 2015 [click to play very very large animation]

When Cirrus overlies Fog


GOES-15 Visible Imagery at 1800 UTC on 12-15 January 2015 (Click to enlarge)

Fog and low stratus has persisted in California’s central valley during the week of 12-16 January 2015. The visible imagery above shows the extent of the fog/low stratus at 1800 UTC on 12-15 January.

During the early morning hours of 16 January, high cirrus started to overspread the central Valley (That cirrus is apparent in the visible iamgery from 15 January above). The presence of cirrus makes use of the traditional method of fog detection — brightness temperature difference — problematic because the satellite no longer senses radiation from the low clouds; rather, cirrus radiation is being detected.

The four toggles below show Brightness temperature Difference and GOES-R IFR Probabilities at 0300 (top), 0700 (second from top), 1100 (second from bottom) and 1400 UTC (bottom) on 16 January 2015. At 0300 UTC, cirrus has overspread the northern part of the central Valley. At this time Merced, CA, shows IFR conditions. IFR Probabilities under the cirrus there show a flat field characteristic of conditions when IFR Probabilities are governed by Rapid Refresh data only. Probabilities are higher where satellite data are also included as predictors.

At 0700 UTC and 1100 UTC, cirrus has overspread the entire valley (with occasional breaks). Values of GOES-R IFR Probability are therefore suppressed, so interpretation of the IFR Probability value should be tempered by knowledge of the cloud field. A low value under clear skies means something different than a low value under a cirrus canopy. Under a cirrus canopy, the accuracy of the GOES-R IFR Probability Field depends on the accuracy of the Rapid Refresh model.

AT 1400 UTC, as the cirrus shield retreats, IFR Probabilities increase again over the central Valley.


Toggle between GOES-R IFR Probabilities from GOES-15 and Brightness Temperature Difference Fields, 0300 UTC 16 January 2015 (Click to enlarge)


Toggle between GOES-R IFR Probabilities from GOES-15 and Brightness Temperature Difference Fields, 0700 UTC 16 January 2015 (Click to enlarge)


Toggle between GOES-R IFR Probabilities from GOES-15 and Brightness Temperature Difference Fields, 1100 UTC 16 January 2015 (Click to enlarge)


Toggle between GOES-R IFR Probabilities from GOES-15 and Brightness Temperature Difference Fields, 1400 UTC 16 January 2015 (Click to enlarge)