Stanford University
Giant plumes of Sahara Desert dust that gust across the Atlantic can suppress hurricane formation over the ocean and affect weather in North America.
But thick dust plumes can also lead to heavier rainfall – and potentially more destruction – from landfalling storms, according to a July 24 study in Science Advances. The research shows a previously unknown relationship between hurricane rainfall and Saharan dust plumes.
“Surprisingly, the leading factor controlling hurricane precipitation is not, as traditionally thought, sea surface temperature or humidity in the atmosphere. Instead, it’s Sahara dust,”
said the corresponding author Yuan Wang, an assistant professor of Earth system science at the Stanford Doerr School of Sustainability.
Previous studies have found that Saharan dust transport may decline dramatically in the coming decades and hurricane rainfall will likely increase due to human-caused climate change.
However, uncertainty remains around the questions of how climate change will affect outflows of dust from the Sahara and how much more rainfall we should expect from future hurricanes. Additional questions surround the complex relationships among Saharan dust, ocean temperatures, and hurricane formation, intensity, and precipitation. Filling in the gaps will be critical to anticipating and mitigating the impacts of climate change.
“Hurricanes are among the most destructive weather phenomena on Earth,” said Wang. Even relatively weak hurricanes can produce heavy rains and flooding hundreds of miles inland. “For conventional weather predictions, especially hurricane predictions, I don’t think dust has received sufficient attention to this point.”
Competing effects
Dust can have competing effects on tropical cyclones, which are classified as hurricanes in the North Atlantic, central North Pacific, and eastern North Pacific when maximum sustained wind speeds reach 74 miles per hour or higher.
“A dust particle can make ice clouds form more efficiently in the core of the hurricane, which can produce more precipitation,” Wang explained, referring to this effect as microphysical enhancement. Dust can also block solar radiation and cool sea surface temperatures around a storm’s core, which weakens the tropical cyclone.
Wang and colleagues set out to first develop a machine learning model capable of predicting hurricane rainfall, and then identify the underlying mathematical and physical relationships.
The researchers used 19 years of meteorological data and hourly satellite precipitation observations to predict rainfall from individual hurricanes.
The results show a key predictor of rainfall is dust optical depth, a measure of how much light filters through a dusty plume. They revealed a boomerang-shaped relationship in which rainfall increases with dust optical depths between 0.03 and 0.06, and sharply decreases thereafter. In other words, at high concentrations, dust shifts from boosting to suppressing rainfall.
“Normally, when dust loading is low, the microphysical enhancement effect is more pronounced. If dust loading is high, it can more efficiently shield [the ocean] surface from sunlight, and what we call the ‘radiative suppression effect’ will be dominant,” Wang said.
Additional authors are affiliated with Western Michigan University, Purdue University, University of Utah, and California Institute of Technology
Journal
Science Advances
DOI
Article Title
Leading Role of Saharan Dust on Tropical Cyclone Rainfall in the Atlantic Basin
Article Publication Date
24-Jul-2024
Abstract
Tropical cyclone rainfall (TCR) extensively affects coastal communities, primarily through inland flooding. The impact of global climate changes on TCR is complex and debatable. This study uses an XGBoost machine learning model with 19-year meteorological data and hourly satellite precipitation observations to predict TCR for individual storms. The model identifies dust optical depth (DOD) as a key predictor that enhances performance evidently. The model also uncovers a nonlinear and boomerang-shape relationship between Saharan dust and TCR, with a TCR peak at 0.06 DOD and a sharp decrease thereafter. This indicates a shift from microphysical enhancement to radiative suppression at high dust concentrations. The model also highlights meaningful correlations between TCR and meteorological factors like sea surface temperature and equivalent potential temperature near storm cores. These findings illustrate the effectiveness of machine learning in predicting TCR and understanding its driving factors and physical mechanisms.
INTRODUCTION
Tropical cyclones (TCs) are extreme weather events that have caused catastrophic damages globally (1, 2). According to global and regional climate models, TC rainfall (TCR) is expected to increase with global warming, following the increased water vapor holding capacity in the atmosphere with rising temperature (3–5). A recent study (6) compared the sea surface temperature (SST)–TCR relationships and discovered that the climate scaling (changing ratio between rainfall and rising temperature) under future warmer climate (5% per K) is smaller than the Clausius-Clapeyron scaling (7% per K) and apparent scaling under current climate. In addition, recent satellite observations revealed a decreasing trend of rain rate in the core part of TCs but increasing trend in outer bands (7, 8). Besides ocean surface temperature and water vapor in the atmosphere, other environmental factors regulate the regional variations of TCR, including vertical wind shear (9–11), surface roughness change (12–14), and atmospheric aerosols (15, 16). How the environment and climate influence the TCR remains unresolved, especially over multiyear to decadal time scales.
Saharan dust, transported across the Atlantic Ocean by trade winds, is the predominant aerosol type during summer and early fall over the tropical Atlantic (17). It can efficiently alter atmospheric radiative fluxes in both shortwave and longwave bands and participate in cloud formation by serving as cloud condensation nuclei (CCN) and/or ice nuclei (IN) (18). It has been reported that Saharan dust tends to suppress the formation of tropical cyclones via a cooling effect on SST that consequently cuts the energy supply for TCs (19, 20). This phenomenon was evident during the peak of European air pollution in the 1970s and 1980s, which is believed to have amplified the Sahel dust emissions due to the prevalent drought conditions. This intensified dust transport coincided with a noticeable downturn in Atlantic hurricane activity (8). Another study (21) has highlighted a close association between the North Atlantic’s dust and considerable spatial shifts in factors such as zonal wind shear, midlevel moisture, and SST. However, they found a minimal correlation between dust optical depth (DOD) and the Atlantic’s accumulated cyclone energy. As Saharan dust-laden air masses move westward, they can introduce dry and stable air into the tropical environment. This dry air inhibits the moisture and convection required for tropical cyclone formation. Moreover, by blocking solar radiation from reaching the surface, dust can reduce SST. The dust effects on TCR can be more complicated and multifaceted. Similar to the anthropogenic aerosols (e.g., sulfate or hygroscopic organics) that provide more CCN to TC systems (22), dust can foster the hydrometeor formation in the cloud tower, enhance the vertical motion of rain bands via elevated latent heat release, and result in more surface precipitation (23). In a nutshell, there is no consensus on the sign of the dust effect on TCR, and it remains uncertain what is the relative importance of dust effect compared to the other meteorological factors.
Current climate models still do not have sufficient spatial resolution to resolve the complex microphysical processes of cloud and precipitation, particularly how aerosol microphysics affects deep convective clouds. While cloud-resolving numerical models were adopted to capture the complex air-sea and aerosol-TC interactions (14, 24), it remains challenging to run these models over multiyear to decadal climate time scales, given their computational expense. Therefore, a combination of big data and machine learning (ML) offers a promising alternative method for untangling those complex relationships between environment forcings and TC activities. Previous studies have demonstrated that ML has robust predictive capabilities in TC genesis, intensity, precipitation, and rapid intensification (14, 25–27). While current ML research on TCs primarily centers on enhancing forecasting and prediction capabilities, ML models also have the potential to unveil intricate and nonlinear relationships between features and response variables. Recent advancements in interpretable ML further bolster the interpretability of these models. Therefore, in this research, we first derive a long-term record of TCR, which is defined as the average tropical cyclone rain rate within 600 km of each TC position (see Materials and Methods), and then aim to: (i) develop an ML model capable of predicting TCR variabilities across the Atlantic Ocean using environmental forcing variables; (ii) pinpoint the most influential environmental forcing variables within the ML model and explore their interactions; and (iii) specifically, elucidate the role of Saharan dust in TCR. This will be achieved by contrasting various ML models with and without the dust variable and interpreting their physical significance through the lens of ML interpretability techniques.
RESULTS
Model performance and overall effect of dust
A correlation analysis first shows very low correlations (coefficient generally smaller than 0.06) between individual environmental factors and TCR (fig. S1). It indicates that conventional statistical methods such as linear regression may not work well to model TCR, likely due to the nonlinear relationships between environmental features and TCR. Therefore, we use a more sophisticated ML approach, the Extreme Gradient Boosting (XGBoost) based on an ensemble of decision trees, to build our TCR models. Two distinct models were developed, one only including the traditional meteorological factors and geoinformation and the other adding DOD as another predictor. Results from fivefold cross-validation demonstrate that both DOD and non-DOD models offer decent out-of-sample prediction capabilities (with ~0.6 R2, as in Fig. 1, A and B), without overfitting the training data. Notably, the DOD model surpasses its counterpart, as evidenced by a higher R2 and a reduced root mean squared error (RMSE). The differences in conditional median values further highlight the DOD model’s superiority across most TCR spectrums, with pronounced error reduction observed for both light and heavy TCR extremes (as illustrated in Fig. 1C). Both models tend to have a larger magnitude of underestimates for heavy TCR than the overestimates for light TCR. With respect to the spatial distribution, we can also observe systematic improvement from the non-DOD to DOD models (Fig. 1D). On average, the absolute error (AE) of the non-DOD model is approximately fourfold that of the DOD model. This is underscored by the more frequent appearance of an AE ratio exceeding 1, indicating that the non-DOD model’s AE is consistently larger than that of the DOD model.
Read the rest of the open access article here.
It is all part of a global energy balancing act.
Whatever seeks to alter the baseline system energy content set by gravity and atmospheric mass will be neutralised by a subtle change in the general air circulation.
It’s almost as if the earth has land, air and ocean and more than one greenhouse gas and substance .
“greenhouse gas” is not a scientific expression, unless you are within a hot house.
The atmosphere is not and does not create a greenhouse.
I will repeat the message again. We have to stop using the hijacked language and repurposed definitions of the Climate Syndicate. To win this war, we much use accurate, concise, and correct vocabulary.
To do otherwise increases, needlessly, the credibility of the fear mongerers.
How about “non-condensing radiative gases” and “condensing radiative gases”? Then we could also stop saying “carbon” when we mean “carbon dioxide”.
Correct.
To your point, yes, there is no single “control knob.”
Weather is the result of a non-deterministic, chaotic system involving so many different things it may be impossible to determine the sensitivities of even a few of the factors.
The system energy content is set by solar insolation, nothing else. The amount absorbed is modified by cloud albedo and most of the stored energy is held in the oceans. The equilibrium temperature of the energy balance depends upon the rate that the absorbed surface energy can escape to space and balance energy in with energy out. And yes, there is an effect of gravity that creates the lapse rate, but that has nothing to do with total surface energy which is entirely a function of solar insolation. THat like saying PV = nRT creates the Lapse rate which it does not, where does the energy come from? PV = nRT defines the thermodynamic lapse rate energy density over the gradient to space, but creates no energy….how could it? It really isn’t that hard.
Gravity and convection within atmospheric mass determine the proportion of solar energy retained in the system as convectively available potential energy. It is the constant recycling of CAPE that causes the greenhouse effect not atmospheric composition.
In other words, weather is Gaia balancing the energy when out of equilibrium.
“Giant plumes of Sahara Desert dust that gust across the Atlantic can suppress hurricane formation over the ocean”
For some reason the first thought that came to mind was: does this mean that when the Sahara was green hurricanes were…. far worse than scientists thought? Who knows? Anyhow, I thought they said the science was settled years ago.
“Wang and colleagues set out to first develop a machine learning model “
That will be quite ignorant of… clouds. But nonetheless, one still has to remember to put the cart before the horse before pontificating on any climate issue.
“Despite the fact that clouds envelop two-thirds of the planet at any given time, transport water on the wind, and shield the Earth from the sun, surprisingly little is known about how climate change affects them.”
https://grist.org/science/earthcare-to-solve-cloud-climate-mystery/
See what they did there! Forget cosmic rays, particulates etc etc etc – and all those unknown unknowns. It’s climate change.
“parts of the UK woke up to hazy skies and a thin layer of orange dust covering many things outside – like cars and windows. The dust is from the Sahara desert in northern Africa, it’s moved through the air across Europe and all the way to the UK.”
https://www.bbc.co.uk/newsround/66734529
To quote from “Predator“: “S__t happens”.
Good comment. Right on the money.
“when the Sahara was green”
something like 200 times in the past 2 million years- there ought to be some way to estimate past hurricanes when it was green?
But the model-predicted is boomerang-shaped, so much more dust will reduce rainfall, just much less dust.
As the Sahara is becoming smaller, will that lead to reduced dust and, therefore, reduced precipitation?
Cliamte science is always covered with a layer of green pseudo science bullshit.
Which they simply reverse when its wrong, …….
because they are the scientists that say Ni!
“Return with a Shrubbery, and not too expensive….”
makes as much sense as Under Assistant Professor Wong.
Wonder if kids get a computer model for Christmas now instead of a Chemistry set? Don’t want to fill their minds with empirical reality, now, do we…… FFS
Defines what the climate syndicate is all about.
Does “Climate Change” affect clouds, or do clouds affect “Climate Change”? In a coupled system, the answer is “yes”.
From the article: “Previous studies have found that Saharan dust transport may decline dramatically in the coming decades and hurricane rainfall will likely increase due to human-caused climate change. ”
LOL!
These Idiots never give up, do they.
And this is why I LOL.
From the article: “However, uncertainty remains around the questions of how climate change will affect outflows of dust from the Sahara and how much more rainfall we should expect from future hurricanes. Additional questions surround the complex relationships among Saharan dust, ocean temperatures, and hurricane formation, intensity, and precipitation. Filling in the gaps will be critical to anticipating and mitigating the impacts of climate change.”
So the climate alarmists make claims and then say “uncertainty remains”. Well, it certainly does. Making claims like this in the face of such uncertainty makes these claims climate change propaganda.
Making ludicrous claims is an industry now
Climate change does not affect anything. Climate change is a record of past weather.
According to the article, “The results show a key predictor of rainfall is dust optical depth, a measure of how much light filters through a dusty plume. They revealed a boomerang-shaped relationship in which rainfall increases with dust optical depths between 0.03 and 0.06, and sharply decreases thereafter. In other words, at high concentrations, dust shifts from boosting to suppressing rainfall.”
This implies that there is a certain dust concentration that results in maximum rainfall from hurricanes, and that either less dust or more dust results in lower rainfall from hurricanes.
But why would climate change from CO2 result in less dust transport from the Sahara over the Atlantic? In my experience in modeling dispersion of pollutants (including particulates) in the atmosphere, the amount of dust (or sand, in the case of the Sahara) entrained into the atmosphere is a function of wind speed and particle size, where higher wind speeds result in higher entrainment. How would climate change affect the speed of winds blowing dust over the Atlantic?
Even if climate change did reduce the wind speed and the dust loading, on which side of the dust loading which causes maximum rainfall would this fall, and would this increase or decrease rainfall? Also, if the winds were weaker, wouldn’t this also reduce the probability of forming a vortex which could develop into a hurricane?
“But why would climate change from CO2 result in less dust transport from the Sahara over the Atlantic?”
More water in the air due to higher temperature leads to less dust in the air due to wetter Sahara leads to less water in the air to wet the Sahara. Therefor the world will be warmer, colder, wetter, drier, dustier, clearer, … hey it got published and maybe some kids got degrees that will get them jobs. They can disavow it all later.
The first red flag is “The Stanford Doerr School of Sustainability” reference.
The first signal that, it might be, is possibly, in all likelihood, (see how they do that) anxiety porn created to induce governments to direct obscene levels of taxpayer funding in the direction of the cabal generating the fear. Its the 21st century school of I publish, your perish.
it has a vision to “vision to create a future where people and nature thrive in concert and perpetuity”
good luck with that- in other words, a utopia
I was trying to find out who Doerr is or was- there was a forestry economist with that name- but probably not him.
now I see there:
“At the core of the school from the start were six departments, three interdisciplinary degree programs, a new Accelerator, two institutes, and dozens of associated centers and programs.”
wow, we’ll be further enlightened by them /s
with so many entities, it’s a good opportunity to tap into the gazillions of dollars to save the planet! /s
John Doerr is one of the foremost Silicon Valley venture capitalists (Kleiner Perkins) who helped start-ups get their funding and establish their ownership and governance structure. Unfortunately, he succumbed to the “climate crisis” myth, using his usefully-gained wealth on useless efforts to prove man-made CO2 is an existential threat. He could have used his money for much more valuable outcomes.
Stanford is not the school it used to be when I would attend Peninsula Geological Society monthly meetings hosted by the Stanford geology department. Once, I found myself sitting next to Dallas Peck, the newly appointed director of the USGS, during a presentation on the Mount St. Helens eruption.
The more we learn, the more it is apparent that the warmunists were full of poopoo when they claimed “the science is settled”.
Real science is never settled. Science is the search for information and understanding. If you don’t search, you don’t find. If it is all “settled” then why bother searching?
I wonder if NOAA took into account Saharan dust before they made their latest hurricane forecast?
Not many hurricanes out there at present. NOAA seemed to think there would be many. Above average, is their claim. But then, that’s always their claim, every year. There’s no moderation at NOAA.
Unfortunately in a litigation happy society, NOAA has to over predict. If there are more storms than predicted, NOAA will spend countless hours in courts and expending huge piles of cash on settlements.
Unfortunately the consequence of over predicting is loss of credibility.
Perfection is unobtainium.
There are no absolutes.
There are hundreds of thousands of lawyers.
Dust also delivers iron to the surface of the ocean. This causes phytoplankton blooms. Phytoplankton produce cloud condensation nuclei and can change how light is absorbed in the ocean surface – more stuff in the water makes it less clear, so more light is absorbed at shallower depth, causing more surface heating and more evaporation.
Their model should include satellite data on Ocean primary productivity to see if this effect is contributing.
So this is the Marxist narrative re alignment, because instead of drought and desertification more CO2 plus slight warming causes de-desertification and less sand, so the government scribes need to invent a new problem that compensates for their lies being exposed, and they flip reality, again. As long as there is a grant for it.
All this is noise in the global picture, only affects the USA that’s only 2 % of Earth’s surface and it’s the oceans that control Earth’s energy balance, mostly in the SH, its about the Southern oceans, nearly half the plante where most of the stored heat and control feedback to solar warming is, not the US weather on land.
Wang is wong.
“uncertainty remains”
nice that SOME researchers admit that!
A correction:
There may be some dust from the Sahara Desert, but most of it comes from the Asian deserts, as shown in the attached image.
I don’t think that you can use that image to determine where the dust is coming from, without a wind direction overlay it could equally show where the dust is going to.
Nansar07:
Although you do have a point, common sense tells us that it is not coming from over the Atlantic.
The image at the top of this thread shows the dust streaming from the East, and windy.com shows the same wind direction.
Ground molecules trying to move, air molecules trying not to, friction.
Just like the “Observations” sections of the IPCC reports, measurements show (almost) none of the predicted trends, but darn it all, they’re certain it’s going to get bad because the climate models say so.
Except rainfall hasn’t increased, but why let the inaccuracy of the climate models stop you from making unsupported claims?
In other words, the models are inaccurate, when compared with observations of tropical cyclone rainfall.
But the model adjusted to include dust optical depth—discovered as a (possible) correlation to tropical cyclone rainfall by machine learning analysis of 19 years of cyclone rainfall records—is less inaccurate.
But ultimately, they’re certain that cyclones are going to get worse in the future. Because, why not?
Another example of the state of the art in modern climate “science” haruspicy: a mix of math, models, measurements, and scientific wild-ass guess (SWAG), heavily influenced by the chronically gloomy doomsayers.
A more interesting read:
Blood rain – Wikipedia
I guess, in this post, they had to mention “Climate Change”™ to get a grant and be published.
This is new?
Oh! Wait! They used models.
this.
Thought this well established. And since storms are suppressed during these episodes, water temps in the region continue to rise. Look for the next storm or two, when they finally do form, to grow into doozies.
There is much we do not know.
There are ongoing research and studies trying to determine how water affects storm intensity.
We always knew dust from Africa along with thermally active air was involved.
There is nothing said about the thermal energy in evaporation (phase change) and how it affects storms.
My point is, to repeat again, models are not science. Models are tools to help understand, of course, but models cannot predict. Use case inputs can generate families of projections, but again, only to understand not to predict.
No mention of the fact that Saharan Dust is PM 2.5 material and is always circling the world.
The next time the EPA talks about the danger of inhaling PM 2.5 someone should tell them that Africa should be banned.
Where are the error bars for the numbers presented?
“can also lead to”
“can efficiently alter”
“It has been reported”
“tends to suppress“
“is believed to have amplified“
“can introduce“
“can reduce“
“can be more complicated and multifaceted”
“can foster”
…stopped at about half way.
I “can keep going” but decided the point is made.
Yes, those ambiguous phrases are what make up all of Alamist Climate Science. They have nothing else. It’s all speculation, assumptions, and unsubstantiated assertions.
It’s a scandal.
Plausible deniability.
Would there not be a similar effect if atmospheric dust content was inversely related to relative humidity and wind speed?