The near-Full Moon provided ample illumination of fog/low stratus near the Oregon Coast early in the morning of 30 September, as shown above. Note also the clear skies near North Bend along the southern Oregon coast. What did the GOES-R IFR Probability field show at these two times? IFR Probability fields also suggest clear skies around North Bend/Coos Bay (and offshore), as observed. The fine fingers of fog/low stratus that are moving up river valleys in the 1125 UTC image most notably are not resolved by GOES-15 (which has a 4-km pixel size at the sub-satellite point). Both fields do capture the slow increase in cloud cover over land. Available surface observations show near-IFR conditions at some stations in Oregon.
See the CIMSS Satellite Blog for an analysis of this event from 25 September 2015.
Ceilings and visibilities over South Carolina decreased during the day on 24 September 2015. The animation of hourly IFR Probability fields, above, shows an increase in Probability over South Carolina as the visibilities decreased. IFR Probability fields can alert a forecaster to the possibility of IFR conditions at any time of the day. Visible imagery for the same period, below, shows the multiple cloud layers streaming inland. The accuracy of the IFR Probability field in highlighting the region with near-IFR and IFR Probability is testimony to the accuracy of the Rapid Refresh model data that are used.
The toggle above compares GOES-R IFR Probability fields and GOES-13 Brightness Temperature Difference fields at 1000 UTC on 21 September 2015. A shortcoming of Brightness Temperature Difference fields, or indeed of any low cloud detection algorithm that relies solely on cloud-top measurements, is that low stratus that does not reduce visibility and fog that does reduce visibility can look very similar from the cloud top. By incorporating surface and near-surface moisture information from the Rapid Refresh Model, the GOES-R IFR Probability algorithm can correctly screen out regions of stratus and highlight only those regions where fog and low stratus might affect transporation. In the example above, Guymon OK and Lamar CO are at the outer edge of the highest IFR Probability, and both report IFR conditions. South and west of those stations, IFR Probabilities drop quickly, but brightness temperature difference signals remain strong.
The chart above shows the relationship between the last pre-sunrise GOES-R Cloud Thickness product and Fog Dissipation time. Observations of the last pre-sunrise GOES-R Cloud Thickness (developed from an empirical relationship between 3.9 µm emissivity and sodar-observed cloud thickness of the west coast of the USA) can be related to the dissipation time relative to the last observation of Cloud Thickness. The scatterplot was developed using data mostly over the southeastern part of the USA, but also over the Great Plains. However, it does have value in other geographic regions too, as shown below.
On 16 September, river fog developed over the Ohio River and its tributaries in Ohio, West Virginia and Pennsylvania. The toggle above shows GOES-R IFR Probability and GOES-R Cloud Thickness fields at 1100 UTC on 16 September. This was the last pre-sunrise GOES-R Cloud Thickness over West Virginia (Indeed, the leading edge of twilight — where GOES-R Cloud Thickness is not computed — is apparent at the extreme eastern edge of the image, from Virginia up into central Pennsylvania). The GOES-R Cloud Thickness fields show largest values — around 800 feet — in/around the Ohio River between West Virginia and Ohio. The chart above suggest rapid dissipation. The best fit line (blue) suggests dissipation in about an hour, although there is considerable spread to the values, from 30 minutes up to almost 2-1/2 hours.
Almost two hours later (1245 UTC), fog is still present in isolated patches near the river, and GOES-R IFR Probability fields are suggesting fog is still present as well. The horizontal extent of the GOES-R IFR Probability field is greatly reduced because visible imagery can be used after sunrise to screen out clear regions (Cloud-clearing in the algorithm is more effective). By 1415 UTC (bottom), three hours after the GOES-R Cloud Thickness imagery above, all fog has evaporated.
MODIS data (from Terra and Aqua) and GOES data can both be used to create GOES-R IFR Probability fields. The differences between the two data sources — especially spatial resolution — are obvious in the toggle above. MODIS data can capture the development of fingers of fog that develop in small river valleys, and GOES data cannot (although, of course, a forecaster with knowledge of the topography might appropriately tailor a forecast). In the toggle above, MODIS data capture the small tributaries of the Ohio River in Ohio and West Virginia that likely contain fog at 0300 UTC (11 PM local time). GOES data smear out that information. This is true later at night as well, below, at 0715 UTC. River valleys show higher IFR Probabilities than adjacent mountains. Valley fog is easier to delineate with MODIS data than with GOES data.
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.
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.