Category Archives: Alaska

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

GOESWIFR_AK_19JUL2016

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_1413_19July2016

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

Barrow_1414_19July2016

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

Deadhorse_1415_19July2016

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


==============================================================================

GOES_IFR_1645_19July2016

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.

FalsePass_1653_19July2016

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

ColdBay_1654_19July2016

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

KingCove_1655_19July2016

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

NelsonLagoon_1656_19July2016

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

Perryville_1659_19July2016

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

PortHeiden_1657_19July2016

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

PilotPoint_1658_19July2016

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

Fog Detection at Very High Latitudes

Barrow_0930_1230_14July2016

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.

Barrow_1100_1400_14July2016

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.

OregonIFR_1300_1400_14July2016anim

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_GOES_IFR_2100_08July2016toggle

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

MODIS_GOES_IFR_2245_08July2016toggle

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

MODIS_GOES_IFR_2300_08July2016toggle

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

MODIS_GOES_IFR_0645_09July2016toggle

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

MODIS_GOES_IFR_0815_09July2016toggle

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

MODIS_GOES_IFR_1230_09July2016toggle

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

MODIS_GOES_IFR_1400_09July2016toggle

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.

METARS_1700_11July2016

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_IFR_1700_11July2016

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

AK_DenseFog_8Sep2015

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 and MODIS IFR Probabilities over Alaska

MODIS_GOES_IFRPROB_0700_14Apr15

GOES-R IFR Probabilities computed from MODIS and from GOES-15, both at ~0700 UTC on 14 April 2015 (Click to enlarge)

At very high latitudes, limb effects can alter the brightness temperature difference between 10.7 µm and 3.9 µm. GOES also has very large pixel sizes at high latitudes. The image above toggles between the GOES-R IFR Probability computed using MODIS and GOES-15. Observations — scant over Alaska — of ceilings and observations are superimposed on the imagery. GOES-based GOES-R IFR Probabilities are elevated over much of Alaska; in contrast, MODIS-based IFR Probabilities show larger values in only a few regions.

MODIS-based values at high latitudes are available frequently compared to lower latitudes. At 0830/0845 UTC, below, MODIS data show a slow expansion in values (note that eastern Alaska was not viewed by MODIS at this time). At about 1100 UTC, the slow areal increase in IFR Probabilities continues.

MODIS_GOES_IFRPROB_0830_14Apr15

GOES-R IFR Probabilities computed from MODIS and from GOES-15, both at ~0830 UTC on 14 April 2015 (Click to enlarge)

MODIS_GOES_IFRPROB_1100_14Apr15

GOES-R IFR Probabilities computed from MODIS and from GOES-15, both at ~1100 UTC on 14 April 2015 (Click to enlarge)

The 1100 UTC MODIS pass was over only eastern Alaska, and it shows relatively large values in some spots of northeastern Alaska. The high values from the GOES-based GOES-R IFR Probabilities over central Alaska can probably be discounted. Note, however, that the highest GOES-based GOES-R IFR Probabilities do have a counterpart in the MODIS-based field.

At 1400 UTC, no MODIS pass was available. The GOES-based image, below, again has large values over northern Alaska (with corroborating surface observations at Point Lay (where snow is falling) and at Atqasuk (where freezing fog is reported).  MODIS-based data from earlier in the day adds confidence to the discounting of widespread modest (40-50%) IFR Probability values over central Alaska.

GOESIFRPROB_1400_14Apr15

GOES-R IFR Probabilities computed from GOES-15 at 1400 UTC on 14 April 2015 (Click to enlarge)

 

GOES-R IFR Probabilities at High Latitudes

MODIS_GOES_IFR_1300_27Oct2014

GOES-R IFR Probabilities computed using GOES-15 and Aqua Data, both near 1300 UTC on 27 October 2014 (Click to enlarge)

GOES-R IFR Probabilities are created using both GOES-15 Imager and Terra/Aqua MODIS. The toggle above shows MODIS-based IFR Probabilities (computed using data from Aqua and the Rapid Refresh) and GOES-based IFR Probabilities (computed using data from GOES-15 and the Rapid Refresh). There are three regions in the fields that warrant comment.

(1) Over East-central Alaska and the Yukon, large values of MODIS-based IFR Probabilities are limited in area (and near stations — such as Northway Airport — that are reporting IFR or near-IFR conditions). GOES-based IFR Probabilities in that same region include a large area with modest values — around 50%. Limb brightening may have an effect at high latitudes on the brightness temperature difference fields that are used in the computation of IFR probabilities because limb brightening is a function of wavelength. MODIS data (which will have far less limb brightening) can be used as a good check on the IFR Probabilty fields computed from GOES.

(2) Over Southwestern Alaska, and into the eastern Aleutians, GOES-based and MODIS-based IFR Probabilities are very similar. In this region, multiple cloud layers prevent satellite data from being used as a predictor in the computation of GOES-R IFR Probabilities. Rapid Refresh data is the main predictor for low clouds/fog, so MODIS-based and GOES-based fields will look similar.

(3) In the northeastern part of the domain, over the Northwest Territories of Canada, MODIS-based and GOES-based IFR Probabilities are very high. Satellite data are being used as a predictor here, and the satellite-based signal is strong enough to overwhelm any limb-brightening. (Note that southern Northwest Territories and northern British Columbia are south of the MODIS scan).

Terra- and Aqua-based MODIS observations yield frequent observations that result in good spatial and temporal coverage for IFR Probability fields over Alaska. GOES-15 temporal coverage is better, but the frequent MODIS passes can be used to benchmark GOES-based IFR Probability fields that may be misrepresentative because of limb-brightening effects at high latitudes.

Use MODIS data at High Latitudes

Alaska_NorthSlope_201410114

GOES-West IFR Probabilities, MODIS IFR Probabilities and surface topography over northern Alaska, ~2000 UTC on 14 January 2014 (click image to enlarge)

GOES pixels grow to large sizes at high latitudes, such as those found over northern Alaska. Consequently, the IFR Probabilities can give information that is difficult to interpret. Data from the polar-orbiting MODIS instrument (on board Aqua and Terra satellites), in contrast, have nominal 1-km resolutions even at high latitudes. In the toggle of imagery above, the MODIS IFR Probabilities suggests low clouds just north of the Brooks Range in northern Alaska. In contrast, the IFR Probabilities based on GOES-15 are difficult to interpret.

Consider using the MODIS-based IFR Probabilities. At very high latitudes, data from polar orbiters is more frequent than at mid-latitudes. Thus, there is a benefit from higher spatial resolution without an onerous loss of temporal resolution as happens in mid-latitudes.

IFR Probability fields in extreme cold

GOES_IFR_11-3_20131226_1800toggle

GOES-R IFR Probabilities from GOES-15 with surface ceilings/visibilities and GOES-15 Brightness Temperature Difference (10.7 µm – 3.9 µm) Fields with surface plots at 1800 UTC 26 December 2013 (click image to enlarge)

The image toggle above shows IFR Probability and the Brightness Temperature Difference Field over northern Alaska. Plotted METAR observations show very cold surface temperatures in the -30 to -50 F range. At such cold temperatures, the pseudo-emissivity computation can become noisy because a very small change in 10.7 µm radiance (used to compute the 3.9 µm radiance) can cause a large change in 3.9 µm brightness temperature. (The effect is shown graphically below — a small change in radiance at 3.9 µm leads to a very large temperature change). This noise can lead to a speckled appearance to the IFR probability fields. This effect can also occur in the northern Plains of the United States when surface temperatures dip below zero.

Noise_in_3.9um_ch

Radiance (y-axis) vs. Brightness Temperature (x-axis) for 3.8 µm (left) and 10.7 µm (right)

(update) Below is the IFR Probability in the heart of a Polar Airmass over northwestern Ontario.

GOES_IFR_11-3.9_20131230_1215

GOES-R IFR Probabilities from GOES-13 with surface ceilings/visibilities and GOES-13 Brightness Temperature Difference (10.7 µm – 3.9 µm) Fields with METAR plots at 1215 UTC 29 December 2013 (click image to enlarge)

Fog/Low Stratus over southwest Alaska on November 8

GOES_IFR_PROB_20131108loop

GOES-15-based GOES-R IFR Probabilities every half hour from 0300 UTC through 1530 UTC (click image to animate)

Fog and low stratus were present over southwestern Alaska early on November 8. How did the GOES-R IFR Probability fields perform compared to the heritage brightness temperature difference (in this case, 10.7 µm – 3.9 µm from GOES-15). Consider the airport PARS (southwest of Anvik — PANV and northwest of Aniak — PANI). IFR conditions are present there until 0900 UTC, when ceilings rise and IFR probabilities drop. Subsequently, IFR Probabilities increase again as a north-south oriented region of higher IFR probabilities moves over, and IFR conditions are again present by 1600 UTC. Further south, PAJZ and PAIG report IFR conditions when IFR Probabilities are high, and conditions improve as IFR Probabilities decrease. IFR Probabilities initially around PAIG have the characteristic flat field (and somewhat lower probability) associated with a region where high-level clouds are present. In these regions, only Rapid Refresh data can be used to compute the probability; because satellite predictors are not used, the computed IFR probabilities are lower.

Compare the IFR Probability field, above, to the Brightness Temperature Difference field, below, that has been color-enhanced to highlight regions where water-based clouds may be present. The IFR Probability field correctly reduces the regions where IFR conditions might be occurring. That is, the traditional brightness temperature difference field is plagued by many false positives. This is because mid-level stratus that is unimportant for transportation looks to a satellite to be very similar to low-level stratus that is important for transportation.

alaska_11-3.9_Sat_20131108_0300

GOES-15 Brightness Temperature Difference (10.7 µm – 3.9 µm) every hour from 0300 UTC through 1500 UTC (click image to animate)

MODIS data from the polar-orbiting satellites Terra and Aqua can also be used to compute IFR Probabilities, and MODIS data — although less frequent than the data from the geostationary GOES-15 — has far superior horizontal resolution (nominal MODIS resolution is 1 km at nadir) to GOES data (nominally 4 km at the sub-satellite point over the Equator) over Alaska. Small-scale features are much more likely to be detected in MODIS data, as shown below.

GOES_IFR_PROB_20131108_0815_4panel

GOES-15-based GOES-R IFR Probabilities (Upper Left), GOES-15 Brightness Temperature Difference Product (10.7 µm – 3.9 µm) (Upper Right), Suomi-NPP Brightness Temperature Difference (11.45 µm – 3.74 µm) and Day/Night band (Lower Left), MODIS-based GOES-R IFR Probabilities (Lower Right), all times as indicated (click image to enlarge)

VIIRS_DNBFOG_20131108_1358

GOES-15-based GOES-R IFR Probabilities (Upper Left), GOES-15 Brightness Temperature Difference Product (10.7 µm – 3.9 µm) (Upper Right), Suomi-NPP Brightness Temperature Difference (11.45 µm – 3.74 µm) and Day/Night band (Lower Left), MODIS-based GOES-R IFR Probabilities (Lower Right), all times as indicated (click image to enlarge)

The Day/Night band from Suomi/NPP can sometimes be used to detect cloud features. However, when the Moon is not present to provide illumination, cloud detection is a challenge. In the toggle above between the Day/Night band and the brightness temperature difference from VIIRS (11.45 – 3.74), for example, there is little evidence of the apparent cloud edge that is visible both in VIIRS data, in GOES-15 data (Upper right) and in the IFR Probability fields from GOES (Upper Left) and MODIS (Lower Right).

IFR Conditions over southwest Alaska

Strong extratropical storms that move northward into the Gulf of Alaska, or into the Bering Sea, can bring IFR conditions to many parts of Alaska. However, they typically also bring multiple cloud layers that make traditional satellite-only methods of detecting fog and low stratus problematic. In cases like these, a fused product that incorporates model predictions of low-level saturation is helpful in defining just where IFR conditions are most likely.

alaska_11-3.9_Sat_20131015loop

GOES-15 Brightness Temperature Difference Product (10.7 µm – 3.9 µm), times as indicated (click image to enlarge)

For example, the brightness temperature difference field, above, does not show a strong signal in regions where near-IFR conditions are present. In contrast, the IFR Probability field, below, that incorporates model fields that are influenced by surface features, better highlights the region of IFR conditions. It captures the edge of the fog/low stratus field over SW Alaska, and probabilities are highest in regions where IFR and near-IFR conditions exist. The relatively flat field over land is a typical feature of the IFR Probability when it is determined chiefly by model data. Because satellite data are not included in the predictors, the total probability is somewhat smaller. Where the satellite brightness temperature difference field does have a strong signal is where the IFR Probabilities are highest (over the Bering Sea).

GOES_IFR_PROB_20131015loop

GOES-R IFR Probabilities derived from GOES-15 and Rapid Refresh data Brightness Temperature Difference Product (10.7 µm – 3.9 µm), times as indicated (click image to enlarge)

One shortcoming with IFR Probability is the pixel resolution at high latitudes. MODIS data can also be used to compute IFR Probabilities, and three comparisons between MODIS and GOES values are shown below. Alaska’s high latitudes means not only large GOES pixels, but also fairly frequent coverage from the polar-orbiting Terra and Aqua satellites that hold the MODIS instrument.

MODISGOES_IFRPROB_20131015_0900

Toggle between GOES-R IFR Probabilities derived from GOES-15 and from MODIS satellite data at ~0900 UTC 15 October (click image to enlarge)

MODISGOES_IFRPROB_20131015_1300

As above, but at ~1300 UTC (click image to enlarge)

MODISGOES_IFRPROB_20131015_1430

As above, but at ~1430 UTC (click image to enlarge)