Prediction of dust storm events over northern parts  of India using NCUM

Dust storms are common over north-west parts of India during the pre-monsoon season. The main objective of this study is to assess the movement of dust over Indian region during a dust event using the dust aerosol optical depth (AOD) forecast from an operational numerical weather prediction model. Observed values of visibility, wind speed are used to identify the dust events over a point location. In addition, satellite observations for the days prior to, during and after dust events are utilized to ascertain the dust event. The performance of operational NCMRWF Unified Model (NCUM) is analyzed in predicting the values of dust AOD during dust events over north west parts of India. Predicted values of dust AOD are compared with observations available from satellite and ground based network of Aerosol Observation Network (Aeronet). The dust event of 25th May, 2016 observed at Jaipur and Lucknow is well captured by NCUM up to Day-3 forecast. The comparison of predicted dust AOD at point locations Jaipur and Kanpur reveals that NCUM is capable in predicting the high values of AODs during dust event.

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Analysis of Severe Elevated Thunderstorms over Frontal Surfaces Using DCIN and DCAPE

Atmosphere ◽

10.3390/atmos10080449 ◽

2019 ◽

Vol 10 (8) ◽

pp. 449

Author(s):

Patrick Market ◽

Kevin Grempler ◽

Paula Sumrall ◽

Chasity Henson

Keyword(s):

Weather Prediction ◽

Convective Available Potential Energy ◽

Numerical Weather Prediction Model ◽

Surface Boundary ◽

Storm Events ◽

Cold Side ◽

Severe Thunderstorms ◽

Stable Surface Layer ◽

Different Populations ◽

Convective Inhibition

A 10-year study of elevated severe thunderstorms was performed using The National Centers for Environmental Information Storm Events Database. A total of 80 elevated thunderstorm cases were identified, verified, and divided into “Prolific” and “Marginal” classes. These severe cases occurred at least 80 km away from, and on the cold side of, a surface boundary. The downdraft convective available potential energy (DCAPE), downdraft convective inhibition (DCIN), and their ratio are tools to help estimate the potential for a downdraft to penetrate through the depth of a stable surface layer. The hypothesis is that as the DCIN/DCAPE ratio decreases, there exists enhanced possibility of severe surface winds. Using the initial fields from the Rapid Refresh numerical weather prediction model, datasets of DCIN, DCAPE, and their ratio were created. Mann-Whitney U tests on the Prolific versus Marginal case sets were undertaken to determine if the DCAPE and DCIN values come from different populations for the two different case sets. Results show that the Prolific cases have values of DCIN closer to zero, suggesting the downdraft is able to penetrate to the surface causing severe winds. Thus, comparing DCIN and DCAPE is a viable tool in determining if downdrafts will reach the surface from elevated thunderstorms.

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Quantification of iron-rich volcanogenic dust emissions and deposition over the ocean from Icelandic dust sources

Biogeosciences ◽

10.5194/bg-11-6623-2014 ◽

2014 ◽

Vol 11 (23) ◽

pp. 6623-6632 ◽

Cited By ~ 25

Author(s):

O. Arnalds ◽

H. Olafsson ◽

P. Dagsson-Waldhauserova

Keyword(s):

Large Scale ◽

Dust Emission ◽

Dust Storms ◽

Dust Event ◽

Dust Deposition ◽

Dust Emissions ◽

Dust Sources ◽

Basaltic Composition ◽

Limiting Nutrient ◽

Dust Events

Abstract. Iceland has extremely active dust sources that result in large-scale emissions and deposition on land and at sea. The dust has a volcanogenic origin of basaltic composition with about 10% Fe content. We used two independent methods to quantify dust emission from Iceland and dust deposition at sea. Firstly, the aerial extent (map) of deposition on land was extended to ocean areas around Iceland. Secondly, surveys of the number of dust events over the past decades and calculations of emissions and sea deposition for the dust storms were made. The results show that total emissions range from 30.5 (dust-event-based calculation) to 40.1 million t yr−1 (map calculation), which places Iceland among the most active dust sources on Earth. Ocean deposition ranges between 5.5 (dust event calculations) and 13.8 million tons (map calculation). Calculated iron deposition from Icelandic dust ranges between 0.567 and 1.4 million tons, which are distributed over wide areas (>370 000 km2) and consist of fine reactive volcanic materials. The paper provides the first quantitative estimate of total dust emissions and oceanic deposition from Iceland. Iron is a limiting nutrient for primary production in the oceans around Iceland, and the dust is likely to affect Fe levels in Icelandic ocean waters.

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PBL height estimation based on lidar depolarisation measurements (POLARIS)

10.5194/acp-2016-718 ◽

2016 ◽

Cited By ~ 3

Author(s):

Juan Antonio Bravo-Aranda ◽

Gregori de-Arruda-Moreira ◽

Francisco Navas-Guzmán ◽

María José Granados-Muñoz ◽

Juan Luís Guerrero-Rascado ◽

...

Keyword(s):

Weather Prediction ◽

Microwave Radiometer ◽

Numerical Weather Prediction Model ◽

Saharan Dust ◽

Night Time ◽

Signal Ratio ◽

Height Estimation ◽

Boundary Layer Height ◽

Lidar Measurements ◽

Dust Events

Abstract. The automatic and non-supervised detection of the planetary boundary layer height (zPBL) by means of lidar measurements was widely investigated during the last years. Despite the considerable advances achieved the experimental detection still present difficulties either because the PBL is stratified (typically, during night-time) either because advected aerosol layers are coupled to the PBL. The coupling uses to produce an overestimation of the zPBL. To improve the detection even in these complex atmospheric situations, we present a new algorithm, called POLARIS (PBL height estimatiOn based on Lidar depolARISation). POLARIS applies the wavelet covariance transform (WCT) to the range corrected signal and to the perpendicular-to-parallel signal ratio (δ) profiles. Different candidates for zPBL are chosen and the attribution is done, based on the WCT applied to the RCS and the δ. We use two ChArMEx campaigns with lidar and microwave radiometer (MWR), conducted on 2012 and 2013, for the POLARIS' adjustment and validation. POLARIS improves the zPBL detection thanks to the consideration of the relative changes in the depolarization capabilities of the aerosol particles in the lower part of the atmospheric column. Taking the advantage of a proper determination of the zPBL determined by POLARIS and by MWR under Saharan dust events, we compare the POLARIS and MWR zPBL with the zPBL provided by the Weather Research and Forecasting (WRF) numerical weather prediction model. WRF underestimates the zPBL during daytime but agrees with the MWR during night-time. The zPBL provided by WRF showed a better temporal evolution during daytime than during night-time.

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Trajectory Calculation as Forecasting Support Tool for Dust Storms

Advances in Meteorology ◽

10.1155/2014/698359 ◽

2014 ◽

Vol 2014 ◽

pp. 1-6 ◽

Cited By ~ 3

Author(s):

Sultan Al-Yahyai ◽

Yassine Charabi

Keyword(s):

Weather Prediction ◽

Dust Storms ◽

Strong Wind ◽

Storm Events ◽

Long Distance ◽

Support Tool ◽

Trajectory Calculation ◽

Research Activities ◽

Supporting Tool

In arid and semiarid regions, dust storms are common during windy seasons. Strong wind can blow loose sand from the dry surface. The rising sand and dust is then transported to other places depending on the wind conditions (speed and direction) at different levels of the atmosphere. Considering dust as a moving object in space and time, trajectory calculation then can be used to determine the path it will follow. Trajectory calculation is used as a forecast supporting tool for both operational and research activities. Predefined dust sources can be identified and the trajectories can be precalculated from the Numerical Weather Prediction (NWP) forecast. In case of long distance transported dust, the tool should allow the operational forecaster to perform online trajectory calculation. This paper presents a case study for using trajectory calculation based on NWP models as a forecast supporting tool in Oman Meteorological Service during some dust storm events. Case study validation results showed a good agreement between the calculated trajectories and the real transport path of the dust storms and hence trajectory calculation can be used at operational centers for warning purposes.

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The Effect of Soil Moisture Perturbations on Indian Monsoon Depressions in a Numerical Weather Prediction Model

Journal of Climate ◽

10.1175/jcli-d-16-0733.1 ◽

2017 ◽

Vol 30 (21) ◽

pp. 8811-8823 ◽

Cited By ~ 7

Author(s):

Kieran M. R. Hunt ◽

Andrew G. Turner

Keyword(s):

Soil Moisture ◽

Indian Monsoon ◽

Monsoon Season ◽

Weather Prediction ◽

Lower Troposphere ◽

Numerical Weather Prediction Model ◽

North India ◽

Peninsular India ◽

Monsoon Depressions

Indian monsoon depressions (MDs) are synoptic-scale cyclonic systems that propagate across peninsular India three or four times per monsoon season. They are responsible for the majority of rainfall in agrarian north India, so constraining precipitation estimates is of high importance. Here, a case study from August 2014 is used to explore the relationship between varying soil moisture and the resulting track and structure of an incident MD using the Met Office Unified Model. This case study is chosen with the view to increasing understanding of the general impact of soil moisture perturbations on monsoon depressions. It is found that increasing soil moisture in the monsoon trough region results in deeper inland penetration and a more developed structure—for example, a warmer core in the midtroposphere and a stronger bimodal potential vorticity core in the mid-to-lower troposphere—with more precipitation, and a structure that in general more closely resembles that found in depressions over the ocean, indicating that soil moisture may enhance the convective mechanism that drives depressions over land. This experiment also shows that these changes are most significant when the depression is deep and negligible when it is weakening. Increasing soil moisture in the sub-Himalayan arable zone, a region with large irrigation coverage, also caused deeper inland penetration and some feature enhancement in the upper troposphere, but no significant changes were found in the track heading or lower-tropospheric structure.

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Dust Events and Indoor Air Quality in Residential Homes in Kuwait

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17072433 ◽

2020 ◽

Vol 17 (7) ◽

pp. 2433 ◽

Cited By ~ 2

Author(s):

Yufei Yuan ◽

Barrak Alahmad ◽

Choong-Min Kang ◽

Fhaid Al-Marri ◽

Venkateswarlu Kommula ◽

...

Keyword(s):

Dust Storm ◽

Fine Particles ◽

Middle Eastern ◽

Dust Storms ◽

Storm Events ◽

Indoor Exposure ◽

Infiltration Rates ◽

Particle Penetration ◽

Dust Events ◽

Indoor And Outdoor

Kuwait is a developed Middle Eastern country that is impacted by frequent dust storms from regional and/or remote deserts. The effectiveness of keeping homes tightly closed during these events to reduce dust exposures was assessed using indoor and outdoor particle samples at 10 residences within the metropolitan Kuwait City area. Specifically, this study compared indoor and outdoor levels of black carbon and 19 trace elements (Na, Mg, Al, Si, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Br, Sr, and Zr) during dust and non-dust events and found that particle penetration efficiencies were lower during dust storm events (less than 20–30%) than during non-dust storm events (40–60%). Coarse particles had lower penetration efficiency compared to fine particles, which is due to differences in infiltration rates and settling velocities between these two size fractions. Our findings suggest that increasing home insulation could be an effective strategy to reduce indoor exposure to crustal particles from dust storm events in residential houses of Kuwait City.

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Geostatistical assessment of summertime rainfall observations in Korea based on composite precipitation and satellite water vapor data

10.5194/hess-2018-83 ◽

2018 ◽

Author(s):

Sojung Park ◽

Seon Ki Park ◽

Jeung Whan Lee ◽

Yunho Park

Keyword(s):

Water Vapor ◽

Monsoon Season ◽

Weather Prediction ◽

Moran’S I ◽

Spatial Correlations ◽

Moran's I ◽

Observation Network ◽

Current Observation ◽

Resolution Observation ◽

Heavy Rainfalls

Abstract. Among the meteorological disasters, heavy rainfalls cause the second largest damage in Korea, following typhoons. To confront with the potential disasters due to heavy rainfalls, understanding the observational characteristics of precipitation is of utmost importance. In this study, we investigate the spatial and temporal characteristics of summertime precipitation in Korea, according to the precipitation types, by conducting the geostatistical analyses such as autocorrelogram, Moran's I and general G, on the composite (radar + station) precipitation data. The e-folding distance of precipitation ranges from 15 to 35 km, depending on the spatial distribution, rather than intensity, of precipitation, whereas the e-folding time ranges from 1 to 2 h. The directional analyses revealed that the summertime precipitation in Korea has high spatial correlations in the southwest–northeast and west–east directions, mainly due to frontal rainfalls during the monsoon season. Furthermore, the cluster versus dispersion patterns and the hot versus cold spots are analyzed through Moran's I and general G, respectively. Water vapor, represented by the brightness temperature, from three Himawari-8 water vapor bands also show similar characteristics with precipitation but with strong spatial correlation over much longer distance (~ 100 km), possibly due to the continuity of water vapor. We found that, under the e-folding-based standard, the current observation network of Korea is sufficient to capture the characteristics of most precipitation systems; however, under a strict standard (e.g., autocorrelation of 0.6), a higher-resolution observation network is essentially required – especially in local areas with frequent heavy rainfalls – depending on the directional features of precipitation systems. Establishing such an observation network based on the characteristics of precipitation enables us to improve monitoring/tracking/prediction skills of high-impact weather phenomena as well as to enhance the utilization of numerical weather prediction.

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