Hurricane Ophelia and Wildfires in Spain and Portugal

Ever since last week, Hurricane Ophelia was meandering in the eastern Atlantic Ocean, not knowing where to go. Ophelia gradually became a tropical storm, then hurricane, as it moved northeastward and past through the Azores. As of this past weekend (14-15 October 2017), Ophelia inched closer and closer to the country of Ireland. Before Ophelia made landfall, the strength of Ophelia decreased slightly and had maximum sustained winds of 85 mph. Hurricane Ophelia made landfall along Ireland’s coast in the early morning hours on 16 October 2017. Ophelia brought heavy rain, flooding and storm surge to Ireland, and with how large the areal extent of Ophelia, it advected smoke from the wildfires that were blazing in Spain and Portugal. Even local European airlines, re-routing around Ophelia, noticed the odor of the fires in their airplanes that day.

Static polar-orbiting satellite images taken of the event are seen below via the Day/Night Band (DNB), and the Imagery Band (I-4) (3.74um) at 0248Z, 16 October 2017. More detailed information about each satellite image is described below.

DNB 

The DNB utilizes a sun/moon reflectance model that illuminates atmospheric features, senses emitted and reflected light sources, and assists with cloud monitoring during the nighttime. The DNB image below shows Hurricane Ophelia before it made landfall along the coast of Ireland and its approximate location to a few European countries such as the United Kingdom, France, Spain, and Portugal. The emitted city lights from these countries can be seen as well. Additionally, this image was taken during the ‘new moon’ phase of the lunar cycle, and where the moon is physically below the horizon, not providing adequate moonlight to see atmospheric features via satellite. Due to the lack of moonlight, the satellite imagery can still see the atmospheric features primarily by a phenomena called ‘airglow’. ‘Airglow’ are produced via photochemical reactions during the daytime, that produce a faint ‘glow’ during the nighttime, wherein the satellite can sense the ‘airglow’ and the ambient atmospheric features. Lastly, notice the orange ellipse in Spain and Portugal, this is the general location of where the wildfires were occurring. We’ll refer to this area in the next image.

Imagery Band (I-4), (3.74um), Inverse Gray Scale

The I-4 band is at a spatial resolution of 375-meters, and is used in complement of the DNB to identify wildfire ‘hotspots’, areas that are significantly hotter than their surroundings. If you look within the orange ellipse, you will see ‘hotspots’, one hotspot in Western Spain, and a few in Northern Portugal, highlighted by the darker, black colors. Within the ellipse, the brighter white colors are combination of clouds and smoke, although one cannot clearly differentiate between the two. It is inferred that the smoke and clouds are advecting to the north/northeast as Hurricane Ophelia approaches Ireland.

Imagery Band (I-4), (3.74um), New Color Scale

Utilizing the same I-4 band image from above, and implementing a new color scale to it, to identify the locations of the wildfire ‘hotpsots’ (hotter brightness temperatures sensed by satellite) in Spain and Portugal, are shown in red.

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California Wildfires

It is finally October, where the fall season has hit its stride, but unfortunately wildfires are still a-brewing in the Golden State. California, in recent days, has been subjected to more wildfires along the Northern side of the state. The majority of the fires are north of San Francisco and San Pablo Bays. The cause of these fires are unknown and under investigation as of 10 October 2017.

Supplemental satellite images are provided highlighting the relative location of the fires via the Near-Constant Contrast (NCC) that illuminates atmospheric features, senses emitted and reflected lights and assists with cloud monitoring during the nighttime and the GOES-16 infrared band (Band 7, 3.9um) that observes ‘hotspots’ over Earth’s surface.

If you look at both static images (below) at 0947Z, 10 October 2017, there are collocated ellipses (orange and white) that encircle the general areas of the fires. The confusion becomes, how can one differentiate between the emitted city lights and the emitted light from the wildfires that are shown in the NCC? That is where geostationary data comes into play, specifically the infrared band 7 (a.k.a. 3.9um channel).

The 3.9um channel is notorious for identifying ‘hotspots’ or surface areas that are significantly warmer than their surroundings and are represented by the black pixels. The differentiation between the emitted city lights and emitted lights from the wildfires becomes easier when the NCC and GOES-16 infrared image are used in complement with one another to identify and infer the areal extent of wildfires. In addition, if you look closely on the southernmost ellipse in the infrared image, you can see that one black pixel senses over 60+ degrees Celsius at the surface, indicating hot fires sensed within that pixel!

NCC @ 0947Z, 10 October 2017

GOES-16, IR, Band 7 – 3.9um @ 0947Z, 10 October 2017

Here’s the latest article covering the fires in Northern California via CNBC.

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Advected Layer Precipitable Water product for Hurricane Harvey

The CIRA advected layer precipitable water (ALPW) product for Hurricane Harvey is quite interesting:

http://rammb.cira.colostate.edu/templates/loop_directory.asp?data_folder=training/visit/loops/28aug17&loop_speed_ms=600

The loop spans from 12Z 23 August to 12Z 29 August.  During that time period, we see the development of Hurricane Harvey in the western Gulf of Mexico.  There are clear indications of moisture convergence in the vertical during the early stages which would add confidence to a forecast of a strengthening tropical cyclone.  In the later periods of the loop, the system slows down along the coast of Texas.  It is clear that abundant moisture exists over a deep layer in the vertical in the vicinity of the slow-moving circulation.  High precipitation efficiency can be inferred from this imagery.  Abundant moisture over a deep layer in the vertical, very slow movement and high precipitation efficiency came together and contributed to the significant flooding in the vicinity of the circulation over coastal Texas.

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Hurricane Harvey

Just a few days after Hurricane Harvey made landfall in southeast Texas, Harvey has downgraded to a Tropical Storm, however it is still bringing torrential rainfall and massive flooding to southeast Texas and Louisiana. To recap, Hurricane Harvey made late-night landfall on 25 August 2017 as a Category 4 Hurricane.

Some of the latest precipitation totals are as high as 40+ inches as of late Monday evening, 28 August 2017. Flooding is widespread and power outages have affected many cities along the Gulf Coast, especially in Houston, Texas.  Below is an example of the number of river gauges observing major flooding along the Gulf Coast via the National Weather Service – Advanced Hydrologic Prediction Service website. The red and purple dots represent river gauges that are experiencing moderate to major flooding in and around the Houston, TX area.

If we look a little bit closer, at one of the purple gauges that represent major flooding, below is an image of the West Fork San Jacinto River Gauge near Conroe, TX, where the gauge is experiencing record flooding so far, peaking at a flood stage of 127.3 feet!

More precipitation and flooding are expected throughout the week, where recovery efforts will last for the next few months. Below is an image of the Imagery Band 5 (11.45um), an infrared band on the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on-board the Suomi-National Polar Orbiting Partnership satellite, showing the relative location of the storm along the Gulf Coast at 0816Z, 28 August 2017. The brightness temperature values are expressed from a range of colors; 180K (brighter colors representing temperatures of cold clouds/convective cloud tops) to 320K (darker colors, land and ocean temperatures). The spatial resolution of the imaging band is at 375 meters.

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