Improving the simulation of convective dust storms in regional‐to‐global models

Foroutan, Hosein; Pleim, Jonathan

doi:10.1002/2017ms000953

Cited by 12 publications

(13 citation statements)

References 49 publications

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“…Simulated hourly PM10 surface concentrations (μg m − 3 ) at 06:00 UTC on 6 July 2011 (23,00 local time on 5 July 2011) from three runs (left to right) (1) (control --no lightning assimilation (LTGA) and no subgrid wind variability (SGWV), (2) with SGWV, and (3) with SGWV and LTGA), overlaid with the observations of 11 PM10 monitoring sites. (this is lowest panel from Figure6of[12]).…”

mentioning

confidence: 87%

“…One instructive example of the difficulties in performing these simulations and of what improvements might be forthcoming, can be found in the work of [12]. The authors assert that "regional-to-global models generally do not accurately simulate these storms", for two reasons: "(1) using a single mean value for wind speed per grid box, i.e., not accounting for subgrid wind variability and (2) using convective parametrizations that poorly simulate cold pool outflows".…”

Section: Forecasting and Simulating Dust Stormsmentioning

confidence: 99%

“…Last, the paper explores modern-day dust storm magnitudes and frequencies, as well as their meteorological and landscape causes [11]. The paper goes further into this subject by describing how weather forecasters predict these storms and how atmospheric scientists come to understand their formation, transport, and eventual dissipation, [12,13].…”

Section: Introductionmentioning

confidence: 99%

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Bowing Sand, Dust, and Dunes, Then and Now–A North American Perspective

Hyde¹,

Mahalov²

2022

Deserts and Desertification

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Dune fields of the present day, the Dust Bowl disaster of the 1930s U.S. Great Plains, and contemporary efforts to forecast, simulate, and understand dust storms have a striking, uniform commonality. What these apparently diverse phenomena have in common is that they all result from blowing sand and dust. This review paper unifies these three disparate but related phenomena. Its over-arching goal is to clearly explain these manifestations of windblown sand and dust. First, for contemporary dune fields, we offer reviews of two technical papers that explain the eolian formation and the continuing development of two major dune fields in southeastern California and northwestern Sonora, Mexico: the Algodones Dunes and the Gran Desierto de Altar. Second, historical, geological, meteorological, and socioeconomic aspects of the 1930s Great Plains Dust Bowl are discussed. Third, and last, we return to the present day to summarize two lengthy reports on dust storms and to review two technical papers that concern their forecasting and simulation. The intent of this review is to acquaint the interested reader with how eolian transport of sand and dust affects the formation of present-day dune fields, human agricultural enterprises, and efforts to better forecast and simulate dust storms. Implications: Blowing sand and dust have drastically affected the geological landscape and continue to shape the formation of dune fields today. Nearly a century ago the U.S. Great Plains suffered through the Dust Bowl, yet another consequence of blowing sand and dust brought on by drought and mismanagement of agricultural lands. Today, this phenomenon adversely affects landscapes, transportation, and human respiratory health. A more complete understanding of this phenomenon could (and has) led to more effective mitigation of dust sources, as well as to a more accurate predictive system by which the public can be forewarned.

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mentioning

confidence: 87%

Section: Forecasting and Simulating Dust Stormsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Bowing Sand, Dust, and Dunes, Then and Now–A North American Perspective

Hyde¹,

Mahalov²

2022

Deserts and Desertification

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“…Also, in Europe, a study by Chervenkov and Jajobs (2011) implemented the EURAD model for understanding the processes involved in dust storms. When sufficient data are available, the incorporation of a probability distribution function for surface wind in distributed parameter modeling approaches is a suitable way to account for wind variability due to dry and moist convection (Foroutan and Pleim, 2017). Due to the lack of field infrastructure for the assessment of wind erosion in Mexico, simple indirect methods are used for obtaining the parameters that define this process.…”

Section: Introductionmentioning

confidence: 99%

Potential of wind erosion and dust emission in an arid zone of northern Mexico: A simple assessment method

Macias-Corral

Arriaga²,

Sánchez-Cohen³

2020

Revista Brasileira De Ciência Do Solo

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Wind erosion is the main problem that arid lands in northern Mexico are facing. Quantification of this phenomenon is crucial for planning purposes and to scale its impact. The challenge is to assess the problem under limited availability of climatic information. This study aimed to identify potential areas of dust emissions in an arid zone of Northern Mexico. Wind direction and intensity were characterized through a robust index that involves rainfall and evaporation as well as the climatic factor of the general wind erosion equation. A method for assessing the likelihood of dust emission associated with wind erosion was applied. Data from twelve weather stations within the region of the study was analyzed. The variables considered were wind velocity and direction, temperature, and precipitation. A wind rose of wind direction and intensity was obtained. Results showed that the Thornthwaite's method for computing the Soil Moisture Index (SMI) is a good approach when computing the climatic factor C of the general function of the potential average annual soil loss. Given the lack of local evaporation data, the precipitation-evaporation ratio (P E) for each weather station was computed as an intermediate step towards the computation of C. Three of the analyzed climatic stations had intermediate C values (36-71 %) in the scale of wind erosion climatic factor. The wind velocities registered in these climatic stations ranged from 15 to 30 km h-1. The magnitude-frequency analysis of the P E parameter for the stations showed the differences in rainfall and evaporation regimes. Dust pollution prone areas were identified, showing areas where conservation strategies should be directed.

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“…The uncertainty in the dust emission modeling is the main reason for such large differences (Gong & Zhang, ; Uno et al, ). The high levels of uncertainties in dust emission parametrization are due to insufficient knowledge about the dust lifting itself, the lack of input data on the soil characteristics and the impossibility for the models to resolve the fine‐scale variability in wind fields that drive the dust emission (Escribano et al, ; Foroutan & Pleim, ; Foroutan et al, ).…”

Section: Introductionmentioning

confidence: 99%

Dust Emission Inversion Using Himawari‐8 AODs Over East Asia: An Extreme Dust Event in May 2017

Jin

Segers²,

Heemink

et al. 2019

J Adv Model Earth Syst

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Aerosol optical depths (AODs) from the new Himawari-8 satellite instrument have been assimilated in a dust simulation model over East Asia. This advanced geostationary instrument is capable of monitoring the East Asian dust storms which usually have great spatial and temporal variability. The quality of the data has been verified through a comparison with AErosol RObotic NETwork AODs. This study focuses on extreme dust events only when dust aerosols are dominant; promising results are obtained in AOD assimilation experiments during a case in May 2017. The dust emission fields that drive the simulation model are strongly improved by the inverse modeling, and consequently, the simulated dust concentrations are in better agreements with the observed AOD as well as ground-based observations of PM 10 . However, some satellite AODs show significant inconsistence with the simulations and the PM 10 and AErosol RObotic NETwork observations, which might arise from retrieval errors over a partially clouded scene. The data assimilation procedure therefore includes a screening method to exclude these observations in order to avoid unrealistic results. A dust mask screening method is designed, which is based on selecting only those observations where the deterministic model produces a substantial amount of dust. This screen algorithm is tested to give more accurate result compared to the traditional method based on background covariance in the case study. Note that our screen method would exclude valuable information in case the model is not able to simulate the dust plume shape correctly; hence, applications in related studies require inspections of simulations and observations by user.

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Improving the simulation of convective dust storms in regional‐to‐global models

Cited by 12 publications

References 49 publications

Bowing Sand, Dust, and Dunes, Then and Now–A North American Perspective

Bowing Sand, Dust, and Dunes, Then and Now–A North American Perspective

Potential of wind erosion and dust emission in an arid zone of northern Mexico: A simple assessment method

Dust Emission Inversion Using Himawari‐8 AODs Over East Asia: An Extreme Dust Event in May 2017

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