The unusual severe dust storm of May 2018 over Northern India: Genesis, propagation and associated conditions

2021 ◽  
Author(s):  
Priyanka Banerjee ◽  
Sreedharan Krishnakumari Satheesh ◽  
Krishnaswamy Krishna Moorthy
Keyword(s):  
Dust Storm ◽  
Northern India ◽  
Associated Conditions ◽  
Severe Dust Storm

Revisiting Andhi in northern India: A case study of severe dust-storm over the urban megacity of New Delhi

Urban Climate ◽  
2021 ◽  
Vol 37 ◽  
pp. 100825
Author(s):  
Kaustav Chakravarty ◽  
Vineetha Vincent ◽  
Ramesh Vellore ◽  
A.K. Srivastava ◽  
Arpita Rastogi ◽  
...  
Keyword(s):  
Dust Storm ◽  
New Delhi ◽  
Northern India ◽  
Severe Dust Storm

scholarly journals Measurements and modelling of particulate matter building ingress during a severe dust storm event

2020 ◽  
Vol 167 ◽  
pp. 106441 ◽  
Author(s):  
Christos D. Argyropoulos ◽  
Hala Hassan ◽  
Prashant Kumar ◽  
Konstantinos E. Kakosimos
Keyword(s):  
Particulate Matter ◽  
Dust Storm ◽  
Storm Event ◽  
Dust Storm Event ◽  
Severe Dust Storm

scholarly journals An Ensemble Kalman Filter for severe dust storm data assimilation over China

2008 ◽  
Vol 8 (11) ◽  
pp. 2975-2983 ◽  
Author(s):  
C. Lin ◽  
Z. Wang ◽  
J. Zhu
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Dust Storm ◽  
Ensemble Kalman Filter ◽  
Deposition Velocity ◽  
Dust Storms ◽  
Initial Time ◽  
Model Errors ◽  
The Impact ◽  
Severe Dust Storm

Abstract. An Ensemble Kalman Filter (EnKF) data assimilation system was developed for a regional dust transport model. This paper applied the EnKF method to investigate modeling of severe dust storm episodes occurring in March 2002 over China based on surface observations of dust concentrations to explore the impact of the EnKF data assimilation systems on forecast improvement. A series of sensitivity experiments using our system demonstrates the ability of the advanced EnKF assimilation method using surface observed PM10 in North China to correct initial conditions, which leads to improved forecasts of dust storms. However, large errors in the forecast may arise from model errors (uncertainties in meteorological fields, dust emissions, dry deposition velocity, etc.). This result illustrates that the EnKF requires identification and correction model errors during the assimilation procedure in order to significantly improve forecasts. Results also show that the EnKF should use a large inflation parameter to obtain better model performance and forecast potential. Furthermore, the ensemble perturbations generated at the initial time should include enough ensemble spreads to represent the background error after several assimilation cycles.

Investigation of aerosol optical, physical, and radiative characteristics of a severe dust storm observed over UAE

2015 ◽  
Vol 169 ◽  
pp. 404-417 ◽  
Author(s):  
Ghouse Basha ◽  
D.V. Phanikumar ◽  
K. Niranjan Kumar ◽  
T.B.M.J. Ouarda ◽  
P.R. Marpu
Keyword(s):  
Dust Storm ◽  
Radiative Characteristics ◽  
Severe Dust Storm

Characterization and radiative impact of dust aerosols over northwestern part of India: a case study during a severe dust storm

2016 ◽  
Vol 128 (6) ◽  
pp. 779-792 ◽  
Author(s):  
Atinderpal Singh ◽  
Shani Tiwari ◽  
Deepti Sharma ◽  
Darshan Singh ◽  
Suresh Tiwari ◽  
...  
Keyword(s):  
Dust Storm ◽  
Northwestern Part ◽  
Dust Aerosols ◽  
Radiative Impact ◽  
Severe Dust Storm

scholarly journals Changes in Aerosol Optical and Micro-Physical Properties over Northeast Asia from a Severe Dust Storm in April 2014

2016 ◽  
Vol 8 (5) ◽  
pp. 394 ◽  
Author(s):  
Li Fang ◽  
Shupeng Wang ◽  
Tao Yu ◽  
Xingfa Gu ◽  
Xingying Zhang ◽  
...  
Keyword(s):  
Physical Properties ◽  
Dust Storm ◽  
Northeast Asia ◽  
Severe Dust Storm
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