Category Archives: Alaska

Alaskan IFR Probability with GOES-17

GOES-17 Night Time Brightness Temperature (10.3 µm – 3.9 µm), Night TIme Microphysics RGB and GOES-17 IFR Probability, 1100 UTC on 24 September 2021 (Click to enlarge)

The animation above steps through the Night Fog brightness temperature difference (10.3 µm – 3.9 µm), the Nighttime Microphysics RGB (which RGB has as its green component the Night Fog brightness temperature difference) and the GOES-17 IFR Probability fields at 1100 UTC on 24 September 2021. (Note that the Night Fog Brightness Temperature difference and Night Microphysics RGB are at reduced resolution)

A low pressure system is moving onshore through southeastern Alaska. The animation includes two regions that demonstrate particular strengths of the IFR Probability field: over inland and coastal southeastern Alaska, east of Anchorage and west of Yakutat, where low clouds are diagnosed under the multiple cloud layers; over western Alaska where low clouds are diagnosed by the brightness temperature difference field — and color-enhanced as cyan/blue — but where fog observations are not occurring. Over western Alaska, model data allows the IFR Probability to screen out the region of elevated stratus.

Animations of the brightness temperature difference field, the night time microphysics RGB and the IFR Probability are shown below.

GOES-17 Night Time Brightness Temperature (10.3 µm – 3.9 µm), 0820-1310 UTC on 24 September 2021 (Click to enlarge)

GOES-17 Night Microphysics RGB, 0820-1310 UTC on 24 September 2021 (Click to enlarge)

GOES-17 IFR Probability Fields, 0820-1310 UTC on 24 September 2021 (Click to enlarge)

On this day, GOES_17 IFR Probability fields were better able to highlight regions of low ceilings and visibilities over Alaska by combining the strength of satellite detection of clouds and the ability of Rapid Refresh model simulations to predict where low-level saturation is most likely. Note that in the animation of the IFR Probability fields there are slight changes on the hour that are related to incorporation of new model output into the computation of the fields.

GOES-17 IFR Probability fields are slated to be operational as of 13 October 2021.

IFR Probability fields over the Bering Sea

GOES-17 IFR Probability from 1220 – 1710 UTC on 6 April 2021 (Click to enlarge)

GOES-17 IFR Probability fields, above, show a large region of high probabilities to the south and west of Alaska over the Bering Sea. This region of low clouds is encroaching onto shore and demonstrates how the field could be used to predict the onset of lower ceilings. The Night Fog brightness temperature difference animation, below, spanning the same times, documents how high clouds can make mask the satellite detection of low clouds. The animation also shows how the signal changes when the Sun rises (mot noticeable after about 1600 UTC). The Night Fog Brightness Temperature difference field is a component of the Nighttime Microphysics RGB; if the Night Fog Brightness Temperature difference cannot detect low fog because of high clouds, then the Nighttime Microphysics RGB similarly will not detect low clouds.

GOES-17 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) fields, 1220 UTC – 1710 UTC on 6 April 2021 (click to enlarge).

The toggles below of Night Fog Brightness Temperature difference and GOES-17 IFR Probability at 1400 UTC (below) and 1620 UTC (bottom) underscore how the IFR Probability field can give useful information in regions underneath high clouds. If you were scheduled to be on a boat in the Bering Sea on this day, for example, would you expect any visibility?

Toggle between GOES-17 IFR Probability and GOES-17 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) fields, 1400 UTC on 6 April 2021 (click to enlarge). Surface observations of ceilings and visibilities at 1600 UTC are also plotted.

Toggle between GOES-17 IFR Probability and GOES-17 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) fields, 1620 UTC on 6 April 2021 (click to enlarge). Surface observations of ceilings and visibilities at 1600 UTC are also plotted.

The imagery below, from webcams at Togiak (at 1700 UTC) (source), show the low clouds along the coast.

Webcam image from Togiak AK, 1715 UTC 6 April 2021, looking north

Webcam image from Togiak AK, 1715 UTC 6 April 2021, looking west

IFR Conditions over southwest Alaska

GOES-17 IFR Probability fields, 1120 – 2110 UTC on 7 March 2020 (Click to enlarge)

GOES-17 IFR Probability fields over southwestern Alaska and the Aleutians, shown above, characterize several areas of likely IFR conditions on 7 March. One region is over the Bering Sea, north of the Aleutians. This is a region where multiple cloud layers prevent the satellite from viewing low clouds. However, the Rapid Refresh model simulation there does show saturation at low levels; large values of IFR Probability are the result. When model fields control the IFR Probability values, there is little pixel-to-pixel variability and field has a uniform look. This example also shows values from two different models — the Alaska version of the Rapid Refresh (over most of the domain) and the GFS model over parts of Asia.

A second region of high IFR Probabilities is over land in southwest Alaska. There, an absence of high clouds means that satellite detection of low clouds occurs. There is good agreement between IFR Probability fields and observations of ceilings and visibility. For example, note how IFR Probability decreases around PAUN (Unalakeet) as the visibility improves and ceilings lift.

The toggle between the Night Fog Brightness temperature difference and IFR Probability field at 1210 UTC, below, reveals differences as well. The Brightness Temperature Difference field shows uniformity (except for a path of high clouds centered on Dillingham). IFR Probability fields show that the low clouds and reduced visibilities are not so widespread: note the conditions near McGrath and Sleetmute — IFR Probabilities are low, and IFR conditions are not present.

GOES-17 IFR Probability fields and Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 1220 UTC on 7 March 2021 (Click to enlarge)

The animation of Night Fog Brightness temperature below demonstrates challenges in using the field. When high clouds overspread a region, the low cloud signal is lost; perhaps because the fog lifts, and perhaps not. The signal is also lost as the sun rises: the emissivity differences that drive the difference field at night are overwhelmed by solar reflectance as the sun rises.

GOES-17 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm) field, 1220 – 1830 UTC on 7 March 2021 (Click to enlarge)

IFR Probability over southeast Alaska

GOES-17 Clean Window (10.3 µm) infrared imagery, 1000 – 1510 UTC on 19 February 2021 (Click to enlarge)

Clean Window infrared imagery from GOES-17, above, shows a cyclonic storm making landfall over the southeast Alaska peninsula. Multiple cloud levels can be inferred from this animation, and satellite detection of low clouds (and stratus), as reported in sparse METAR observations, is a challenge. Note also the occasional striping that suggests the Loop Heat Pipe on GOES-17 is not cooling the satellite (The Cooling Timeline — every 15 minutes for a Full Disk, is being used at the start of the animation).

In particular, the GOES-based ‘Night Fog ‘ Brightness Temperature Difference field, below, commonly used alone, and as part of the night time microphysics RGB, does not show a consistent signal (cyan in the enhancement) associated with low clouds/stratus/fog — because higher clouds (grey in the applied enhancement) are interfering with the view.

Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 1000 UTC – 1510 UTC on 19 February 2021 (click to enlarge)

GOES-17 IFR Probability combines satellite information with Rapid Refresh model (resolution: 11 km) predictions of low-level saturation. More recent model data are incorporated every hour; you might notice that fields adjust slightly at the top of the hour as that happens.

IFR Probability fields show that the likelihood of IFR conditions are extending southward along the coastal range with time, and increasing in the Inside Passage as well. Note also how IFR Probability is generally larger near mountain tops: it is created with knowledge of topography

GOES-17 IFR Probability fields, 1000 – 1510 UTC on 19 February 2021 (Click to enlarge)

GOES-17 IFR Probability around Bristol and Kvichak Bays

GOES-17 IFR Probability, 0820 – 1800 UTC on 17 November 2020 (Click to enlarge)

GOES-17 IFR Probability fields, above, show a thin region along the northern shore of Bristol and Kvichak Bays in southwestern Alaska, north of the Aleutian Peninsula, where IFR conditions are likely . Probabilities are highest around King Salmon (PAKN) and Igiugig (PAIG) northeast of King Salmon. Several nearby airports are not reporting observations (PAII — Egegik — just south of King Salmon; PATG –Togiak — along the northern shore of the Bay, east of PAEH (Cape Newenham). IFR probability uses satellite and model information to create an estimate of whether or not IFR conditions will be met in regions where observations are missing. Sometimes, as over Cape Newenham at the end of the animation, high clouds are present and only model data can be used to create the estimate.

The Night Fog Brightness Temperature Difference field, below, shows that low clouds (made up of water droplets) exist over the same region — but this one product cannot indicate whether the stratus deck observed is reducing visibility near the surface (where aviation interests require that information). The model data that are incorporated into IFR Probability in concert with satellite data allow for a better estimate of where visibility is reduced than do satellite data alone. This is especially important when the presence of high clouds, as at the end of the animation in the western part of this domain, makes it difficult for the satellite to view low clouds.

GOES-17 ‘Night Fog’ Brightness Temperature Difference field (10.3 µm – 3.9 µm), 0820-1800 UTC on 17 November 2020 (Click to enlarge)

IFR Probability, Low IFR Probability, and Night Fog Brightness Temperature difference at 1000 UTC on 17 November 2020 (Click to enlarge)

Toggles at 1000 UTC (above) and 1600 UTC (below) of IFR Probability, Low IFR Probability and Night Fog Brightness Temperature Difference, suggest that the greatest likehihood of reduced visibilities are not along the bay shore, but rather inland along the Kvichak River.

IFR Probability, Low IFR Probability, and Night Fog Brightness Temperature difference at 1600 UTC on 17 November 2020 (Click to enlarge)

GOES-17 IFR Probability over western Alaska

GOES-17 IFR Probability fields and GOES-17 Night Fog Brightness Temperature Difference (10.3 µm – 3.9 µm), 1310 UTC on 19 October 2020 (Click to enlarge)

CIMSS is now creating GOES_17 IFR Probability fields for Alaska and will presently be distributing them to the Alaska Region. An example of the utility of the products occurred on 19 October over western Alaska. The toggle above between the Night Fog brightness temperature difference field and the IFR Probability field at 1310 UTC 19 October shows several regions where IFR Probability refines where ceilings and visibilities might restrict aviation — an important piece of information in Alaska.

The default Night Fog Brightness Temperature enhancement is constructed so that stratiform clouds containing water droplets are colored different shades of blue. Higher clouds are various shades of grey.

Consider station PANV — Anvik, AK, near 62.7 N, 160 W. This is a station reporting IFR conditions, and IFR probabilities are near 80%. However, it is also under high clouds; GOES-17 is prevented from viewing low clouds, but the Rapid Refresh model data used in IFR Probability is showing saturation. Model data fills in regions of IFR conditions where high (of mid-level) clouds prevent the satellite from viewing near-surface clouds. Note how IFR Probability is also able to distinguish — correctly — between the IFR conditions at Anvik with the more benign sky conditions to the north at St. Michaels (PAMK), Unalakleet (PAUN) and Shaktoolik (PFSH) along Norton Sound.

In contrast, station PASM — St. Mary’s AK, near 62 N, 163 W — is beneath a strong signal in the Night Fog brightness temperature difference field. However, IFR conditions are not reported, and IFR probabilities are near 40% (and decreasing abruptly to the south). In this region, IFR Probability fields are screening out a region of mid-level stratus.

Station PAMC — McGrath, AK, near 63 N, 155 W — shows near-IFR conditions with a local minimum IFR Probability near 40% and a strong signal of stratus clouds in the Night Fog Brightness Temperature difference. For this station it would be prudent to see how IFR Probabilities were changing with time.

IFR Probability combines the strengths of satellite detection of low clouds with the strength of Rapid Refresh model predictions of low-level saturation to create a product useful in regimes with single or multiple cloud layers.

Comparing GOES-R IFR Probability Fields and Webcam Observations over Alaska

GOES-R IFR Probability, 1345 UTC on 19 July 2016, and 1400 UTC Observations of surface Visibility. Blue arrows point to, from left to right, Wainwright, Barrow, and Deadhorse Alaska (Click to enlarge)

The FAA website that includes webcams over much of Alaska provides a great opportunity to match IFR Probability fields with surface observations. In the image above, Wainwright AK shows a 3-mile visibility, but Barrow and Deadhorse farther east report 10-mile visibilities. All three stations are very near high IFR Probabilities — the red/orange region has IFR Probabilities exceeding 90%. What to the webcams at the three stations show? Screen captures from the three webcams are below. Webcams from both Barrow and Deadhorse show non-IFR conditions. Wainwright shows a dense fog through which the sun is dimly visible. These webcam observations are in general agreement with the GOES-based IFR Probability fields: only Wainwright is in a region where IFR Probabilities are consistently high.

Wainwright AK webcams at 1413 UTC on 19 July 2016 (Click to enlarge)

Barrow AK webcams at 1413 UTC on 19 July 2016 (Click to enlarge)

Deadhorse AK webcams at 1413 UTC on 19 July 2016 (Click to enlarge)

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GOES-R IFR Probabilities, 1645 UTC on 19 July 2016, and 1700 UTC Observations of Ceilings/Visibilities (Click to enlarge)

The image above is of GOES-R IFR Probabilities over the Aleutians, along with surface observations of ceilings and visibilities. In general, IFR Probabilities are a bit higher on the northern side of the Aleutians (False Pass, Cold Bay, Nelson Lagoon, Port Heiden, Pilot Point) than the southern side (Perryville, King Cove). That is confirmed with the screen captures of webcam imagery, seen below. The webcam scenes are aligned from west to east, starting at False Pass AK and ending at Pilot Point.

Webcam imagery from False Pass AK (PAKF) at 1653 UTC, 19 July 2016 (Click to enlarge)

Webcam imagery from Cold Bay, AK (PACD) at 1654 UTC on 19 July 2016 (Click to enlarge)

Webcam imagery from King Cove, AK, (PAVC) at 1655 UTC on 19 July 2016 (Click to enlarge)

Webcam imagery from Nelson Lagoon, (PAOU) 1656 UTC on 19 July 2016 (Click to enlarge)

Webcam Imagery from Perryville, AK, 1659 UTC on 19 July 2016 (Click to enlarge)

Webcam imagery from Port Heiden, AK, (PAPH) 1657 UTC on 19 July 2016 (Click to enlarge)

Webcam Imagery from Pilot Point, AK, (PAPN) at 1658 UTC on 19 July 2016 (Click to enlarge)

Fog Detection at Very High Latitudes

GOES-R IFR Probability Fields, 0930-1230 UTC on 14 July 2016 (Click to enlarge)

The low Sun Angle at very high latitudes during Summer presents a challenge to the GOES-R IFR Probability algorithm. Solar backscatter from clouds in the visible and near-infrared (3.9 µm) channels make traditional fog detection methods (Brightness Temperature Difference between 10.7 µm and 3.9 µm) problematic, but they also are a challenge for GOES-R IFR Probability. At mid-latitudes, when 3.9 µm radiation is changing quickly because of rapid changes associated with a rising (or setting) sun, the ‘satellite’ portion of GOES-R IFR Probability will be frozen for a time step or two. In the GOES-R Algorithm, temporal data (in other words, data from previous times) are used starting at the beginning of the terminator transition periods (that is, when the sun is rising or setting) and it’s used until valid data, either day or night predictors, depending on whether it’s sunrise or sunset, is again available. At mid-latitudes (as seen in the example at the bottom of this post), the transition period is typically less than thirty minutes in length. At high latitudes, however, when the sun lingers near the horizon for hours, the use of temporal data can stretch out for several hours and products will not be updated during that time. This effect happens only in the months surrounding the Summer solstice.

Consider the animation above, of GOES-R IFR Probability north of Alaska, over the Arctic Ocean. IFR Probabilty varies with each time step over much of the image, especially, for example, near the lower left corner (a region that includes the Brooks Range). There is a significant region, though, where values do not change over the three hours of the animation — this is because of the low sun angle and the difficulty in relating the 3.9 µm emissivity to a fog property. (You can detect at the end of the animation changes starting to impinge on the region of a static signal from the west) The three hour animation from 1100-1400 UTC, below, shows changes in the field over much of the domain over the Arctic Ocean.

Barrow Alaska (PABR) develops IFR conditions during this animation as low clouds move south from the ocean. GOES-R IFR Probability fields suggest that the fog does not penetrate far inland. Much of northern Alaska had record high temperatures on 13 July (It was 85 in Deadhorse, for example) with light south/southwest winds that would keep the ocean stratus offshore. Webcam views at Barrow (from this link) confirm the presence of IFR conditions.

GOES-R IFR Probability fields, 1100-1400 UTC on 14 July 2016 (Click to enlarge)

When GOES-R is flying, data the 8.4 µm channel will be incorporated into the GOES-R IFR Probability algorithm. This channel (Band 11 on the GOES-R ABI) is not so adversely affected by reflected solar radiation as the 3.9 µm channel so the unchanging nature of GOES-R IFR probability fields will be mitigated.

This stationarity in the GOES-R IFR Probability is apparent at mid-latitudes as well. Careful inspection of the animation below, from 1300-1400 UTC on 14 July 2016, shows a region of static IFR Probability fields off the coast of northern Oregon between 1315 and 1345 UTC.

GOES-R IFR Probability, 1300-1400 UTC on 14 July 2016 (Click to enlarge)

MODIS and GOES IFR Probabilities over Alaska

GOES-R IFR Probabilities computed using GOES-15 pixels over Alaska suffer from problems inherent in any Geostationary Data Product at high latitudes: Pixel sizes are large. In addition, ‘limb brightening’ — that is, the shift in a brightness temperature towards cooler values because the path length of photon towards the satellite travels through more of the upper (colder) troposphere (a cooling that is also dependent on wavelength being sensed) — affects the brightness temperature difference product that is used to detect water-based clouds. MODIS data from Terra and Aqua has a much higher spatial resolution and a superior view angle. It’s fairly simple to use both MODIS data to get an idea of conditions in and around Alaska, and then use GOES data to approximate the temporal change. Terra and Aqua view Alaska frequently (link) — it’s uncommon to go more than 6 hours without a view.

The toggles below show a series of MODIS IFR Probabilities and corresponding GOES-15 IFR Probabilities from late on 8 July 2016 through mid-day on 9 July 2016. From 2100 UTC to 1400 UTC — 17 hours — there are 7 separate MODIS views of Alaska, and they show similar features. For example, the high terrain of the Brooks Range is apparent: larger values of IFR Probabilities are noted there. The same is true over south central Alaska, over the Alaska Range in between Anchorage and Fairbanks. Interpretation of IFR Probability fields over the State require this background knowledge of Topography.

MODIS-based and GOES-15-based GOES-R IFR Probability fields, 2100 UTC on 8 July 2016 (Click to enlarge)

MODIS-based and GOES-15-based GOES-R IFR Probability fields, 2245 UTC on 8 July 2016 (Click to enlarge)

MODIS-based and GOES-15-based GOES-R IFR Probability fields, 2300 UTC on 8 July 2016 (Click to enlarge)

MODIS-based and GOES-15-based GOES-R IFR Probability fields, 0645 UTC on 9 July 2016 (Click to enlarge)

MODIS-based and GOES-15-based GOES-R IFR Probability fields, 0815 UTC on 9 July 2016 (Click to enlarge)

MODIS-based and GOES-15-based GOES-R IFR Probability fields, 1230 UTC on 9 July 2016 (Click to enlarge)

MODIS-based and GOES-15-based GOES-R IFR Probability fields, 1400 UTC on 9 July 2016 (Click to enlarge)

The scenes above suggest that most IFR Conditions near Alaska are offshore during the early morning of 9 July. On 11 July 2016, some of those regions of reduced visibility crept onshore, as shown in the plot below from this site, where surface stations are color-coded by Flight Rules: Red and Magenta denote IFR and Low IFR conditions.

Surface METARS, 1700 UTC on 11 July 2016 (Click to enlarge)

GOES-15-based IFR Probability fields from near that time show high probabilities along the coastline of Alaska. Note that the presence of IFR Conditions can also be deduced from this set of webcams! Consider, for example, this webcam site just west of Prudhoe Bay, in a region where GOES-based IFR Probabilities are high.

GOES-15-based GOES-R IFR probability fields, 1700 UTC on 11 July 2016, along with surface observations of ceilings and visibilities (Click to enlarge)

GOES-R IFR Probabilities at High Latitudes

Screenshot from the Juneau, AK WFO on 8 September 2015. The yellow region has a Dense Fog Advisory (Click to enlarge)

A challenge in using GOES-R IFR Probabilities at high latitudes is that GOES pixels are larger, typically twice or three times the size of pixels over the lower 48. If Fog is starting out as a small-scale phenomenon, the early development of the feature can be missed. Dense fog developed over southeast Alaska on the morning of 8 September. The animation of GOES-15-based IFR Probabilities, below, shows the slow increase in areal extent to the IFR Probabilities in the six hours between 0445 and 1045 UTC; values also increased. This slow increase in concert with observations can increase confidence that wide-spread dense fog is possible.

AK_GOES_IFRPROB_0445_1045UTC_08Sept2015stepanim

GOES-15 based GOES-R IFR Probabilities, 0445, 0715 and 1045 UTC on 8 September 2015 (Click to enlarge)

MODIS data from Terra and Aqua can also be used to compute IFR Probabilities, and the high resolution information from these two polar orbiting satellites can clarify where fog might be occurring. Additionally, MODIS fields are a bit more frequent over Alaska than they are over the lower 48. The 0600 and 0737 UTC passes, shown below, show how MODIS data can be used to refine the GOES-based information at times during the night. The temporal change between MODIS information at 0600 and 0737 UTC also confirms the trend observed in GOES data alone.

AK_GOES_MODIS_IFRPROB_0600UTC_08Sept2015toggle

GOES-15 and MODIS-based GOES-R IFR Probabilities, 0600 UTC 8 September 2015 (Click to enlarge)

AK_GOES_MODIS_IFRPROB_0730UTC_08Sept2015toggle

GOES-15 and MODIS-based GOES-R IFR Probabilities, ~0730 UTC 8 September 2015 (Click to enlarge)

GOES-R Fog Product Examples

Fog detection fusing GOES, Terra/Aqua or Suomi/NPP Satellite data with Model output