ATL: ERNESTO - Post-Tropical - Discussion

[Sciencerocks]

[toad strangler]

Cat 3 into the North Pole?

[AnnularCane]

Cat 3 into the North Pole?

Not sure Santa's workshop is designed for Cat 3 hurricanes.

[Category5Kaiju]

Cat 3 landfall in Greenland incoming

[USTropics]

This might be a dumb question but I'll ask it anyway: why isn't it possible to determine wind speeds of a tropical cyclone just by analyzing satellite footage alone? We know the time interval between satellite frames and we know the amount of distance covered by any individual part of the storm, so I would think that there would be an accurate method of measuring the wind speed at the higher levels of the atmosphere and then extrapolating that to surface winds without needing the Dvorak and other satellite estimates. Is it that the satellite resolution isn't high enough to accurately measure wind speeds in the lower levels of the atmosphere? But even then would the initializations of hurricane-specific models like HAFS, HWRF, etc. not be better estimates of wind speed than the other methods? Like here, the 00z HAFS-A initialization of Ernesto seems to be reasonably accurate to me:

https://i.ibb.co/dr89pC6/hafsa-sat-IR-05-L-5.png

https://i.ibb.co/QptXk1v/1a16b16e-8dd7-4ffb-969b-82ead5aad5fb.jpg

https://i.ibb.co/PcJtK4b/hafsa-mslp-wind-05-L-5.png

So I guess my real question is, and I'm not sure if anyone will even be able to answer, why does the NHC favor certain methods of approximating wind speeds (Dvorak, etc.) over others like HAFS-A/B, HWRF, or even just directly measuring wind speeds by measuring each frame of satellite imagery?

This might be a dumb question but I'll ask it anyway: why isn't it possible to determine wind speeds of a tropical cyclone just by analyzing satellite footage alone? We know the time interval between satellite frames and we know the amount of distance covered by any individual part of the storm, so I would think that there would be an accurate method of measuring the wind speed at the higher levels of the atmosphere and then extrapolating that to surface winds without needing the Dvorak and other satellite estimates. Is it that the satellite resolution isn't high enough to accurately measure wind speeds in the lower levels of the atmosphere? But even then would the initializations of hurricane-specific models like HAFS, HWRF, etc. not be better estimates of wind speed than the other methods? Like here, the 00z HAFS-A initialization of Ernesto seems to be reasonably accurate to me:

https://i.ibb.co/dr89pC6/hafsa-sat-IR-05-L-5.png

https://i.ibb.co/QptXk1v/1a16b16e-8dd7-4ffb-969b-82ead5aad5fb.jpg

https://i.ibb.co/PcJtK4b/hafsa-mslp-wind-05-L-5.png

So I guess my real question is, and I'm not sure if anyone will even be able to answer, why does the NHC favor certain methods of approximating wind speeds (Dvorak, etc.) over others like HAFS-A/B, HWRF, or even just directly measuring wind speeds by measuring each frame of satellite imagery?

Because there is an established process for the Dvorak technique, and research supporting its efficacy. I agree there is probably value in model sat analysis too and research should be done. For what it’s worth, ADT currently pegs this at 95kt.

First, we need to differentiate different satellite orbits (i.e., geostationary vs. polar) and their instruments capabilities (i.e
., passive vs remote radiation measurements).

GOES (geostationary)
Distance and field of view (FOV) are the main issues here, since geostationary satellites typically carry sensors that observe the Earth's atmosphere and surface from a considerable distance (approximately 22,336 miles above the equator to stay in poplar orbit with the Earth's rotation). The instruments onboard, such as infrared and visible light imagers, are optimized for wide-area coverage rather than high spatial resolution. They measure passive radiation, meaning they can only measure the infrared radiation that is produced by cloud tops and convectively free surface temperatures. As a result, they cannot resolve small-scale features like surface winds accurately.

ASCAT (polar orbiting)
Polar orbiting satellites like ASCAT (Advanced Scatterometer) are typically placed in low Earth orbit (LEO) at altitudes ranging from about 700 kilometers (435 miles) to 800 kilometers (497 miles) above the Earth's surface. These satellites orbit the Earth from pole to pole, passing over different parts of the Earth's surface on each orbit. This low altitude allows the instruments on the satellite to use active sensing, which essentially means the instruments use their own source of light or emission to scan objects and areas. A sensor then detects and measures the radiation that is reflected or backscattered from the target.

TL;DR Surface winds vary on a scale much smaller than what geostationary satellites can discern. Polar orbiting satellite instruments have a much higher resolution to gather detailed data on various parameters such as weather patterns, atmospheric composition, and environmental changes with high spatial resolution.

With that said, their are algorithmic techniques that can infer surface wind values, but they are relatively new or subject to large errors. Here is one such example from a recent article published in 2023:

Low orbit satellites such as Jason 3 and Sentinel 1 infer surface winds using geophysical inversion algorithms, based on peak backscattered power and the shape of radio signal waveforms (ESA, 2016). However, the satellites cannot monitor winds continuously in space and time, as they are in low earth orbit. Ground monitors can measure surface winds continuously in time but are sparse in space. Winds in the upper level of the atmosphere can be observed using weather balloons or aircraft measurements, but these observations are also very sparse in space and time.

On the other hand, geostationary weather satellites provide data from the surface and the atmosphere with a very high temporal resolution. The data comprise a series of images which essentially make them a “movie”. While the satellites do not directly measure wind, they measure infrared channel radiations in terms of brightness temperature. These brightness temperature image sequences are used to infer wind estimates by tracking movements of atmospheric tracers such as clouds or moisture features over time. Figure 1 shows a sequence of brightness temperature images captured by the Geostationary Operational Environmental Satellite (GOES)–15, operated by the National Oceanic and Atmospheric Administration (NOAA). Wind data obtained from satellite images play a major role in data assimilation (Lahoz & Schneider, 2014). Numerical climate models perform better with accurate wind data, especially over the oceans, resulting in improved weather forecasts and warnings (Tomassini et al., 1999). For example, the European Centre for Medium-Range Weather Forecasts (ECMWF) has been incorporating atmospheric motion winds into their forecast models operationally since the 1980s. This has dramatically improved the model's ability to forecast the track of tropical cyclones and has also increased the model's ability to predict wave heights and storm surges (Tomassini et al., 1999).

https://onlinelibrary.wiley.com/doi/full/10.1002/env.2818

[Ubuntwo]

First, we need to differentiate different satellite orbits (i.e., geostationary vs. polar) and their instruments capabilities (i.e
., passive vs remote radiation measurements).

GOES (geostationary)
Distance and field of view (FOV) are the main issues here, since geostationary satellites typically carry sensors that observe the Earth's atmosphere and surface from a considerable distance (approximately 22,336 miles above the equator to stay in poplar orbit with the Earth's rotation). The instruments onboard, such as infrared and visible light imagers, are optimized for wide-area coverage rather than high spatial resolution. They measure passive radiation, meaning they can only measure the infrared radiation that is produced by cloud tops and convectively free surface temperatures. As a result, they cannot resolve small-scale features like surface winds accurately.

ASCAT (polar orbiting)
Polar orbiting satellites like ASCAT (Advanced Scatterometer) are typically placed in low Earth orbit (LEO) at altitudes ranging from about 700 kilometers (435 miles) to 800 kilometers (497 miles) above the Earth's surface. These satellites orbit the Earth from pole to pole, passing over different parts of the Earth's surface on each orbit. This low altitude allows the instruments on the satellite to use active sensing, which essentially means the instruments use their own source of light or emission to scan objects and areas. A sensor then detects and measures the radiation that is reflected or backscattered from the target.

TL;DR Surface winds vary on a scale much smaller than what geostationary satellites can discern. Polar orbiting satellite instruments have a much higher resolution to gather detailed data on various parameters such as weather patterns, atmospheric composition, and environmental changes with high spatial resolution.

With that said, their are algorithmic techniques that can infer surface wind values, but they are relatively new or subject to large errors. Here is one such example from a recent article published in 2023:

Low orbit satellites such as Jason 3 and Sentinel 1 infer surface winds using geophysical inversion algorithms, based on peak backscattered power and the shape of radio signal waveforms (ESA, 2016). However, the satellites cannot monitor winds continuously in space and time, as they are in low earth orbit. Ground monitors can measure surface winds continuously in time but are sparse in space. Winds in the upper level of the atmosphere can be observed using weather balloons or aircraft measurements, but these observations are also very sparse in space and time.

On the other hand, geostationary weather satellites provide data from the surface and the atmosphere with a very high temporal resolution. The data comprise a series of images which essentially make them a “movie”. While the satellites do not directly measure wind, they measure infrared channel radiations in terms of brightness temperature. These brightness temperature image sequences are used to infer wind estimates by tracking movements of atmospheric tracers such as clouds or moisture features over time. Figure 1 shows a sequence of brightness temperature images captured by the Geostationary Operational Environmental Satellite (GOES)–15, operated by the National Oceanic and Atmospheric Administration (NOAA). Wind data obtained from satellite images play a major role in data assimilation (Lahoz & Schneider, 2014). Numerical climate models perform better with accurate wind data, especially over the oceans, resulting in improved weather forecasts and warnings (Tomassini et al., 1999). For example, the European Centre for Medium-Range Weather Forecasts (ECMWF) has been incorporating atmospheric motion winds into their forecast models operationally since the 1980s. This has dramatically improved the model's ability to forecast the track of tropical cyclones and has also increased the model's ability to predict wave heights and storm surges (Tomassini et al., 1999).

https://onlinelibrary.wiley.com/doi/full/10.1002/env.2818

Unfortunately, atmospheric motion is a very limited method for TCs given structure is generally obscured by high cloud cover. SAR derived wind speed estimates (falling into the LEO category with satellites like the Sentinel series) are a huge advancement in remote TC intensity estimates, although we haven’t really seen them used operationally yet. Part of RED’s suggestion was comparing high-resolution hurricane model satellite output to observed cloud top temps to infer intensity, which I find intriguing.

[Sciencerocks]

[Xpost] https://x.com/CIRA_CSU/status/1825567400315732428


[/Xpost]

[Travorum]

Speaking of SAR, here's a comparison between the SAR measured wind speeds from this morning (left) and the first peak (right). The right picture was captured right after when recon was measuring 107kts FL but only 75 kts SFMR.

The recorded Vmax in each is 84kts (left picture, NE quadrant) and 102kts (right picture, NW quadrant).

[MEANINGLESS_NUMBERS]

What's that? Oh, just a strengthening hurricane at 43N.

[PDKlikatino]

Given that the pressure's tied with Ernesto's previous low (968 mbar) and the structure seems to be in much better shape, I wonder what's the reasoning behind not upgrading to 85kt or higher?

[ElectricStorm]

05L ERNESTO 240819 1800 42.9N 57.6W ATL 80 968

[Sciencerocks]

[Teban54]

Inspired by this tweet... Could the Canadian wildfires have to do with Ernesto ingesting a lot of dry air leading up to its first peak? I know people suspected this happened to Paulette, another storm that peaked below the NHC forecasts.

 https://x.com/severeweatherEU/status/1825578736973922528

[Kazmit]

Why are there no warnings up for Newfoundland?

[TallyTracker]

Why are there no warnings up for Newfoundland?

I believe the NHC thought Ernesto would be fully non-tropical by now when it was impacting Newfoundland. The CHC had already issued standard warnings and decided not to switch them. I’ve noticed that they do one or the other and stick with it.

[abajan]

Why are there no warnings up for Newfoundland?

I believe the NHC thought Ernesto would be fully non-tropical by now when it was impacting Newfoundland. The CHC had already issued standard warnings and decided not to switch them. I’ve noticed that they do one or the other and stick with it.

For the last several advisories I'd been wondering about the absence of even a tropical-storm-watch for the Avalon peninsula of Newfoundland.

[Hammy]

Given that the pressure's tied with Ernesto's previous low (968 mbar) and the structure seems to be in much better shape, I wonder what's the reasoning behind not upgrading to 85kt or higher?

NHC tends to be conservative in the absence of data, as they usually use satellite estimates at that point (which themselves can sometimes be inaccurate)

Speaking of SAR, here's a comparison between the SAR measured wind speeds from this morning (left) and the first peak (right). The right picture was captured right after when recon was measuring 107kts FL but only 75 kts SFMR.

The recorded Vmax in each is 84kts (left picture, NE quadrant) and 102kts (right picture, NW quadrant).

https://i.imgur.com/0eAPaW3.png

What is this, microwave? Cloud motion? I haven't seen it before so I'm quite curious, especially given the very high resolution.

[Travorum]

Speaking of SAR, here's a comparison between the SAR measured wind speeds from this morning (left) and the first peak (right). The right picture was captured right after when recon was measuring 107kts FL but only 75 kts SFMR.

The recorded Vmax in each is 84kts (left picture, NE quadrant) and 102kts (right picture, NW quadrant).

https://i.imgur.com/0eAPaW3.png

What is this, microwave? Cloud motion? I haven't seen it before so I'm quite curious, especially given the very high resolution.

This is only tangential to my area of expertise so I might not be getting this exactly right. SAR (Synthetic Aperture Radar) is a remote sensing method used by LEO satellites similar to ASCAT, using the same C-band (4-8 GHz) backscattered microwave returns to estimate wind speed based on the roughness of the water surface. The intricacies of the algorithm that relates microwave reflection of various water roughness to wind speed escapes my knowledge, but afaik SAR, ASCAT, and SFMR all use a similar process. The difference between the two is that while ASCAT measures wind speed directly below the satellite and produces results along its entire orbit, SAR focuses the microwave beam on where the storm should be, and captures more data over a large swath of the orbit on just one point. This allows the effective virtual aperture of the imaging device to be much larger than the actual physical antenna is. SAR allows for a resolution of 500m while ASCAT only allows 25km resolution, so the finer resolution of SAR is much more likely to measure the actual peak winds present in a TC. To the best of my knowledge the NHC doesn't look at SAR data as it is still experimental and not operational, but it may be utilized in the future.

TLDR: SAR is basically a fancy version of ASCAT that focuses on a specific feature to measure it in higher resolution in exchange for not capturing data anywhere else along its orbit in that area.

SAR data for tropical cyclones can be found here:
https://www.star.nesdis.noaa.gov/socd/m ... opical.php?

Some relevant links if you want to read more on this:
https://rammb2.cira.colostate.edu/wp-co ... e_v2-1.pdf
https://www.weather.gov/media/nws/IHC20 ... es_IHC.pdf

[JRD]

Seemingly making a run for northernmost hurricane.

EDIT: though extratropical transition should begin soon according to forecasts. It already has a warm front loosely connected to the outermost isobar.

[kevin]

Ernesto is now the northernmost Atlantic hurricane since Larry in 2021 and after Larry & Fabian in 2003 also the northernmost Atlantic hurricane of the 21st century.