Tag: Dust storms

Frequency of Dust Storms: Increases Due to Climate Change (WHO, 2025) vs Decreases Due to Complex Factors in the Sahara-Sahel Region (Yeo et al., 2026)!

Dust storms (also called sandstorms) are meteorological events where strong winds lift loose sand, dust, and dirt from dry surfaces into the air, creating clouds or walls of particles that reduce visibility and can travel long distances.

Haboobs are intense dust storms triggered by thunderstorm downdrafts. They appear as dramatic advancing walls of dust, sometimes thousands of feet high and miles long.

The most infamous is the Dust Bowl of the 1930s in the U.S. Great Plains.

From CO2- Coalition´s Substack

By Ganapathy Shanmugam, Ph.D.

The prevailing climate narrative is that the frequency of dust storms (Fig. 1) tends to increase with global warming (Fig. 2). But the empirical datasets from the Sahara-Sahel region (Fig. 3) reveal that the opposite trend is true for the period 1984-2023 (Fig. 4).

Dust storms

A dust storm, also called a sand storm, is a meteorological phenomenon common in arid and semi-arid regions. Dust storms arise when a gust front or other strong wind blows loose sand and dirt from a dry surface. Fine particles are transported by both saltation and suspension.

Dust storms commonly begin when:

· A dry cold front sweeps through.

· A thunderstorm collapses, creating a powerful downdraft.

· Strong pressure gradients generate high winds.

The most dramatic type—a haboob—forms when a thunderstorm’s downdraft hits desert soil and spreads outward like a giant broom, lifting a massive wall of dust. These dust storms can reduce visibility, disrupt transportation, and pose serious health risks. The arid regions (Fig. 1) of North Africa, the Middle East, Central Asia and China are the main terrestrial sources of airborne dust (Wikipedia https://en.wikipedia.org/wiki/Dust_storm). A major desert dust storm can rise 1,500–2,000 m high and advance at 60–80 km/h, with some gust fronts exceeding 100 km/h. Visibility often drops to zero. They can stretch hundreds of kilometers, with rare events spanning up to 1,000 km.

Climate-Change Narrative

The World Health Organization (WHO, 2025) states that “Climate change contributes to desertification, which in turn may increase the frequency and spread of sand and dust storms. Recently, the WHO Eastern Mediterranean Region and other areas have observed a surge in frequency, duration and intensity of sand and dust storms.” However, WHO (2025) did not explain the details of how Climate Change can increase the frequency of dust storms.

Empirical Data from North Africa

In a comprehensive regional study of dust storms in the Sahara-Sahel region of North Africa, Yeo et al. (2026) have documented that North African dust storms have undergone marked variability, reflecting complex interactions between regional climate processes and environmental change. These authors, using four decades (1984–2023) of visibility‐based observational records, have examined regional and seasonal trends in dust storm frequency across the Sahel and the Sahara, capturing their distinct dust dynamics.

Results reveal a significant decline in dust activity in both regions (Fig. 4), most pronounced during pre‐monsoon (MAM) and monsoon (JJA) seasons in the Sahel, and during post‐monsoon (SON) and dry season (DJF) in the Sahara. Integrating surface observations with local meteorology (precipitation, surface wind speed, vegetation) and climate indices (AMO, NAO, MEI), Yeo et al. (2026) find the Atlantic Multidecadal Oscillation (AMO) as the primary driver, with region‐specific effects: in the Sahel, AMO‐driven warming and rainfall increase vegetation, suppressing dust; in the Sahara, AMO intensifies the Saharan Heat Low (SHL) and elevates temperatures, modulating dust through atmospheric stability and wind patterns. Local meteorology further differentiates responses, with precipitation and Leaf Area Index (LAI) dominating dust variability in the Sahel, while SHL strength and surface winds are most influential in the Sahara. By explicitly separating the Sahel and Sahara and integrating multiple drivers, this study provides a more spatially resolved understanding of dust–climate link and suggests continued declines in North African dust storm activity under future warming.

In light of the Climate Narrative, it is worth noting that “Desertification and dust productions are caused by low CO2 concentrations” (Palmer and Elias, 2016).

Implications

Clearly, available empirical datasets from North Africa do not validate the notion that Fossil Fuels and related CO2 emissions (as implied by the WHO narrative) are the cause of increasing frequency of dust storms. Dust storms are products of meteorological factors. In this context, humans are utterly impotent when it comes to controlling Forces of Nature (e.g., Dust storms, Cyclones, Tsunamis, Volcanoes, Meteorite Impacts, and Earthquakes). Humans can neither create nor stop Extreme Weather Events!

Figure 1

Figure 2

Figure 3

Figure 4

Acknowledgements

I thank Angela Wheeler, Executive Director of the CO2 Coalition, for inviting me to present this contribution and Ethan Otte for helping. I also thank William Happer for valuable suggestions. I am grateful to Jean Shanmugam for her comments.

References

Christy, J. R. (2022). Data shows there’s no climate catastrophe looming – climatologist Dr J Christy debunks the narrative. BizNewsTv. https://www.youtube.com/watch? v=qJv1IPNZQao Retrieved May 2, 2023. 

NOAA (2024). Global Monitoring Laboratory. Earth System Research Laboratories. Trends in Atmospheric Carbon Dioxide (CO2). https://gml.noaa.gov/ccgg/trends/ Retrieved August 16, 2024

Palmer, M. and Elias, R. (2016). Modulation of ice ages via precession and dust-albedo feedbacks. Geoscience Frontiers, Volume 7, Issue 6, November 2016, Pages 891-909.

WHO (World Health Organization) (2025). Sand and Dust Storms. https://www.who.int/news-room/fact-sheets/detail/sand-and-dust-storms

Yeo, K., Oluleye, A., Yoroba, F., Hamidi, M., & Shao, Y. (2026). Trend of North African dust storms and potential link to climate change. Journal of Geophysical Research: Atmospheres, 131, e2025JD043630. https://doi.org/10.1029/2025JD043630

Citation

Shanmugam, G., (2026). Frequency of Dust Storms: Increases due to Climate Change (WHO, 2025) vs Decreases due to Complex Factors in the Sahara-Sahel Region (Yeo et al., 2026)! 5 p. CO2 Coalition Substack. July 22, 2026

Dr. Ganapathy Shanmugam is a CO2 Coalition Member, a petroleum geologist, and a sedimentologist with more than 50 years of experience in geology and energy research. He earned a Ph.D. from the University of Tennessee and worked for Mobil (1978-2000) before becoming an independent consultant. He has published extensively on deep-water sediments and petroleum reservoirs. His 317 published works on ResearchGate have reached 250,518 (over one-quarter million) reads from 32 countries as of July 19, 2026. He has also lectured and conducted workshops around the world.

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Dust Storms: Hidden Drivers of Extreme Rainfall and Global Precipitation Shifts

Dust storm activity exhibits pronounced global variability characterized by strong regional contrasts and interdecadal oscillations rather than a uniform worldwide trend. Analyses spanning 1979–2023 using reanalysis datasets and ground observations reveal cycles of approximately 10–14 years in global dusty weather frequency, with a general decline from the late 1970s to the late 1990s, followed by fluctuating patterns.

Dust storm activity exhibits pronounced global variability characterized by strong regional contrasts and interdecadal oscillations rather than a uniform worldwide trend. Analyses spanning 1979–2023 using reanalysis datasets and ground observations reveal cycles of approximately 10–14 years in global dusty weather frequency, with a general decline from the late 1970s to the late 1990s, followed by fluctuating patterns. Atlantic climate mode, particularly the North Atlantic Oscillation (NAO) and the South Atlantic Subtropical Dipole, play significant roles in modulating surface winds, energy convergence, and dust emission over major source regions.

Regional trends further underscore this heterogeneity. Declining dust activity has been observed in recent decades over the Taklimakan Desert, southwestern Sahara, and much of northern China, often linked to reduced strong wind days, increased vegetation cover, and improved soil moisture conditions. In contrast, increasing trends have been reported in the northern Sahara, Arabian Desert, Gobi, and Thar Desert. Visibility-based records from 1984–2023 indicate overall declines in dust storm frequency across both the Sahara and Sahel, with the Atlantic Multidecadal Oscillation (AMO) identified as a key driver through its influence on regional rainfall, vegetation dynamics, and the Saharan Heat Low.

Beyond their direct socioeconomic and health impacts, dust storms exert substantial broader atmospheric effects. Mineral dust aerosols influence the Earth’s radiative balance through scattering and absorption of solar and terrestrial radiation and can modify atmospheric circulation patterns. A particularly important recent advance highlights their active role in the global water cycle. Liu et al. (2026) demonstrate that dust storms act as hidden drivers of extreme rainfall and global precipitation shifts. Using global observations, they found that 7-day accumulated precipitation following dust storms can exceed that under dust-free conditions by up to 9.6 mm. This enhancement is primarily attributed to dust aerosols serving as effective ice nuclei, promoting cloud glaciation, the formation of larger ice crystals, and more efficient precipitation processes.

These dust–precipitation interactions have significant implications for regional water resources, agricultural productivity, and the frequency of extreme weather events in both source regions and distant receptor areas. As climate change continues to alter wind regimes, vegetation cover, and moisture availability, understanding the complex feedback between global dust storm variability and atmospheric processes will be critical for improving predictions of transboundary dust impacts and associated hydrological risks.

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Dust storms: Hidden drivers of extreme rainfall and global precipitation shifts

Dust storms: Hidden drivers of extreme rainfall and global precipitation shifts is the name of a new 2026 study in Science Advances.

The study directly addresses aspects of global dust storm variability and its broader atmospheric impacts, making it highly relevant.

Science Advances

DOI: 10.1126/sciadv.adw686

Authors: Yuzhi Liu, Weiqi Tang, Tianbin Shao, Run Luo, Ziyuan Tan, Dan Li, and Jianping Huang

Abstract

Dust storms, while often seen as harmful, can play an unexpected role in enhancing rainfall. Global observations show that 7-day accumulated precipitation after dust storms exceeds dust-free conditions by up to 9.6 millimeters. Numerical simulations further confirm that dust particles act as ice nuclei, thereby promoting cloud formation and increasing rainfall through the ice crystal effect. Moreover, in regions with rising anthropogenic aerosols, dusts determine precipitation patterns. While elevated levels of anthropogenic aerosols alone tend to boost weak rainfall, the presence of dust aerosols reduces light precipitation and enhances heavier precipitation. Collectively, these findings reveal a dual role of dust storms in shaping global precipitation patterns while adversely affecting the human living environment. This research establishes a mechanistic framework for understanding how dust affects extreme precipitation at the global scale, advancing predictive capabilities for heavy precipitation.

Recent Dust Storm Panic Is Just More Hot Air From Climate Alarmists

In Inside Climate News’ article, “Dust Storms Surprise the Midwest and Raise Worries About Climate Risks”, published September 21, 2025, Nikita Ponomarenko reports on recent dust storms in Illinois and Kansas that resulted in tragic accidents. The story frames these storms as a possible “new normal” tied to climate change, warning that the Midwest faces rising risks as warming intensifies.

A towering dust storm billowing into the sky over a dry landscape, with large clouds of dust and debris creating a dramatic scene.

From Watts Up With That?

By Anthony Watts

A radar tower stands alongside a building and a fenced area, with a dust storm creating a brown haze in the background under a blue sky.

In Inside Climate News’ article, “Dust Storms Surprise the Midwest and Raise Worries About Climate Risks”, published September 21, 2025, Nikita Ponomarenko reports on recent dust storms in Illinois and Kansas that resulted in tragic accidents. The story frames these storms as a possible “new normal” tied to climate change, warning that the Midwest faces rising risks as warming intensifies.

The article declares that “dust storms have always swirled through parts of North America, but they are becoming more unexpected and destructive and landing in places unfamiliar with the danger, scientists warn”. It goes on to link drought, wind, and farming practices with climate change, quoting one researcher as saying, “there’s no question that climate change is one of the major drivers of dust”.

Dust storms, however, are not new phenomena. They have long been part of the weather in the Great Plains and Midwest, often tied to spring planting, dry fields, and high winds. The most famous example remains the Dust Bowl of the 1930s, when prolonged drought and poor land management created catastrophic storms across Oklahoma, Kansas, Texas, and beyond.

A black and white photograph of a deserted road leading towards a dark, looming dust storm, with a lone vehicle visible in the distance.
Arthur Rothstein, Public domain, via Wikimedia Commons

Dust storms in the Midwest have been documented repeatedly since then, including major events in Illinois in 1985 and again in the early 2000s. NOAA’s storm event database shows dust storms occurring sporadically across the Plains for over a century. To imply that their appearance in 2023 or 2025 is something new is to disregard both meteorological history and common sense.

It is also misleading to claim climate change “drives” dust storms. Dust storms are weather events, not climate trends. They occur when specific conditions align: dry soils, freshly tilled fields, and strong winds. As the National Weather Service explains, the mechanism is mechanical, not thermal—winds lift loose soil into the air, reducing visibility. While drought may be one precondition, the leap from a seasonal drought to anthropogenic climate change as the driver of a dust storm is unjustified. Blaming CO₂ for a 60 mph wind gust sweeping across a dry field confuses correlation with causation.

Historical context matters. The tragic 2023 Illinois dust storm cited by Inside Climate News was deadly, but it pales in scale compared to the storms of the 1930s. On May 11, 1934, a dust storm carried an estimated 350 million tons of soil across the Plains, darkening skies as far east as Washington, D.C., and New York City. In 1935, the infamous “Black Sunday” storm turned day into night across the Plains, forcing thousands from their homes.

Historic newspaper clipping reporting on a large dust storm affecting multiple states, with descriptions of cancellations and public health precautions. Features images of masked individuals and a map highlighting erosion impact areas.

Those events were far more severe than today’s short-lived traffic accidents, and they occurred decades before “climate change” was a political talking point.

Moreover, agricultural practices—not global temperature trends—remain the key driver of modern dust storms. As Inside Climate News itself notes, “dry-tilled fields, notably before spring plantings, are vulnerable to more intense seasonal winds”. When farmers leave fields bare, soil is exposed. Strong spring storms can then whip the ground into the air. By contrast, conservation tillage, cover crops, and windbreaks dramatically reduce dust risk. The difference between dust storm or no dust storm often comes down to farming practices, not carbon dioxide levels in the atmosphere.

The article further cites speculative links between dust storms and climate change-driven megadroughts. But again, this is an attempt to shoehorn ordinary weather into an apocalyptic narrative. The Midwest is not undergoing desertification, nor is it experiencing anything resembling the 1930s multi-year droughts that fueled the Dust Bowl. U.S. Department of Agriculture drought records show year-to-year variability, with wet and dry cycles alternating as they always have. To elevate one bad season into evidence of a “new normal” is narrative-driven journalism, not science.

Even Inside Climate News concedes that “complex factors” caused the 2023 Illinois storm: a cold spring, late planting, drought, high winds, and even the positioning of a tree line. Yet despite listing all these local, mechanical drivers, the story insists on pivoting back to climate change. That leap requires ignoring the fact that significant dust storms also occurred in 1901, 1934, 1955, 1977, and many other years with no connection to modern carbon dioxide emissions.

In the end, dust storms are tragic when they claim lives, but they are not proof of a “climate crisis”. They are part of the natural variability of weather, exacerbated at times by land use and farming decisions. By attributing them to global warming, Inside Climate News misinforms readers and deflects attention from practical, local solutions such as conservation tillage, soil moisture management, and windbreak planting.

Rather than educating the public on how to mitigate dust risk, Inside Climate News offered yet another attempt to force a local weather event into the climate change narrative. The result is not journalism, but agenda-driven storytelling. Readers deserve to know the difference.

Saharan dust regulates hurricane rainfall

Giant plumes of Sahara Desert dust that gust across the Atlantic can suppress hurricane formation over the ocean and affect weather in North America.

From Watts Up With That?

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

10.1126/sciadv.adn6106

Article Title

Leading Role of Saharan Dust on Tropical Cyclone Rainfall in the Atlantic Basin

Article Publication Date

24-Jul-2024

From EurekAlert!

https://www.science.org/doi/10.1126/sciadv.adn6106

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.