Dynamics of Muddy Rain of 15 June 2018 in Nepal

atmosphere

Article Dynamics of Muddy Rain of 15 June 2018 in Nepal

Ashok Kumar Pokharel 1,2,*, Tianli Xu 1, Xiaobo Liu 1 and Binod Dawadi 1,3 1 Kathmandu Center for Research and Education, Chinese Academy of Sciences-Tribhuvan University, Kathmandu 44613, Nepal; [email protected] (T.X.); [email protected] (X.L.); [email protected] (B.D.) 2 Weather Extreme Ltd., Incline Village, NV 89451, USA 3 Central Department of Hydrology and Meteorology, Tribhuvan University, Kathmandu 44613, Nepal * Correspondence: [email protected]

Received: 13 April 2020; Accepted: 15 May 2020; Published: 21 May 2020

Abstract: It has been revealed from the Modern-Era Retrospective analysis for Research and Applications MERRA analyses, Moderate Resolution Imaging Spectroradiometer MODIS/Terra satellite imageries, Naval Aerosol Analysis and Prediction System NAAPS model outputs, Cloud –Aerosol Lidar and Infrared Pathfinder Satellite Observations CALIPSO imageries, Hybrid Single Particle Lagrangian Integrated Trajectory HYSPLIT model trajectories, atmospheric soundings, and observational records of dust emission that there were multiple dust storms in the far western parts of India from 12 to 15 June 2018 due to thunderstorms. This led to the lifting of the dust from the surface. The entry of dust into the upper air was caused by the generation of a significant amount of turbulent kinetic energy as a function of strong wind shear generated by the negative buoyancy of the cooled air aloft and the convective buoyancy in the lower planetary boundary layer. Elevated dust reached a significant vertical height and was advected towards the northern/northwestern/northeastern parts of India. In the meantime, this dust was carried by northwesterly winds associated with the jets in the upper level, which advected dust towards the skies over Nepal where rainfall was occurring at that time. Consequently, this led to the muddy rain in Nepal.

Keywords: thunderstorm; dust storm; muddy rain; transport; convection; buoyancy; turbulent kinetic energy

1. Introduction It has been found that the lofted dust from wind erosion causes environmental effects at regional and global scales. Atmospheric dust affects climate globally by altering the radiation balance of the atmosphere [1,2]. Similarly, high concentrations of dust cause negative health effects [3,4] as well as, on a regional scale, lower economic status by deteriorating visibility with an increase in the cost of visibility impairment on national parks and wilderness areas. A positive correlation has been indicated between drought years and increased dust lofting [5], whereas others indicated that the intrusion of dust into the atmosphere occurs when freshly deposited sediment caused by the intense storms becomes dried up [6]. A dust climatology study over the southwestern US mentioned that the annual mean number of dust events, the annual mean duration of dust events, and the ratio of duration to number of dust events was directly proportional to the visibility range [7]. This study also found that the higher the percentage of total seasonal precipitation, the lower the total dust events percentage in the summer and the winter, and the lower the percentage of total seasonal precipitation, the higher the total dust event percentage in the spring and the autumn. It has been stated that the capability of the wind to deflate the dust particles (erosivity), the soil’s susceptibility to entrainment (erodibility), and the supply of erodible sediment are three major controlling factors on the dust emission process [8]. It is found that the downslope winds and the

Atmosphere 2020, 11, 529; doi:10.3390/atmos11050529 www.mdpi.com/journal/atmosphere Atmosphere 2020, 11, 529 2 of 13 unbalanced adjustment processes in the lee of the mountain ranges are the terrain-induced wind storms that also lift the dust from the surface, and produce larger-scale dust aerosol mobilization, and transport [9–13]. On the other hand, there are some examples that show thunderstorms produce very strong downburst winds leading to dust storms (i.e., strong and turbulent wind events by which dust is lofted from the surface and carries clouds of fine dust, soil, and sand over a large area) [14]. In happening thus, the wall of dust created by this kind of storm can be miles long and several thousand feet high [15]. In southwest Asia, dust storm activity is also controlled by thunderstorm occurrence, lifting dust from the ground surface. Though the highest frequency of thunderstorms is during the wet months—July and August,—there is also substantial thunderstorm activity in May and June, prior to major precipitation occurrence over this region [16]. Similarly, dust storms are most frequent in the afternoon, when turbulent mixing is most pronounced, due to the abundant insolation. This was found in Mexico Basin, where events were associated with strong downdraughts generated by the convective process-dry thunderstorms [17]. As far as the thunderstorm over Nepal is concerned, lightning activity starts in March; it intensifies quickly, reaching its peak in May, while in June the activity decreases rapidly as the southwest monsoon starts [18]. Due to extreme dust storms of 28 March 2016 over Kathmandu, Nepal and its surrounding areas there was a significant reduction in visibility (2 km), effects in aviation and ground transportation, and air quality deterioration. This reveals how vulnerable Nepal is to dust storm and how severely dust storms affect Nepal. On the other hand, unfortunately there are a lack of studies about the origin of dust storms, transport and deposition of dust, and a detailed understanding of the climatological and meteorological characteristics that influence dust event frequency and dust rain dynamics in Nepal. This type of knowledge is necessary to understand the regional, local dust climatology, and the atmospheric phenomena that affect the transport and deposition of the dust in Nepal. In this regard, the study of recent muddy rain (a kind of rain which contains enough dust (e.g., desert dust) to be clearly visible. This occurs when dust and dirt particles mix with the rain [19] of 15 June 2018 in Nepal, which might have increased the pH of rain water, has become quite a newsworthy issue as it is a quite unusual activity over Nepal and its neighbors, and the dust particles can neutralize acid rain in a manner similar to the way antacids counteract excess acid in an upset stomach [20]. For example, the increased level of pH was observed in southern Corsica in 1984 when the chemistry of precipitation mixed with Saharan dust was analyzed [21]. It is to be noted here that based on the findings of previous studies increase of pH has been suspected during this particular muddy rain. However, this study does not incorporate any discussion of the possible impacts of pH caused by this particular event due to beyond the scope of the study. According to Meteorological Forecasting Division (MFD) of Nepal, there was a muddy rain over Nepal on 15 June 2018 [22], which was also observed by the public, as shown in Figure1. They did not discuss the detailed atmospheric dynamics regarding the processes responsible for causing that muddy rain. To address these issues, this study is accomplished, which describes different processes below. As far as the previous studies of detail atmospheric dynamics of muddy rain in Nepal are concerned, no such studies have been carried out in Nepal. For the first time, this study will reveal the scientific understanding of muddy rain dynamics over Nepal. Nepal is situated between China in the north and India to the south, east and west (i.e., 26.37◦–30.07◦ N and 80.07◦–88.20◦ E). It is a country of tremendous geographic diversity. Elevation ranges from 59 m in Terai to Earth’s highest point, the 8848 m Mount Everest. It has a warm temperate climate with dry winters and hot summers. Average annual precipitation ranges from 160 to 5500 mm. Atmosphere 2020, 11, 529 3 of 13 Atmosphere 2020, 11, x FOR PEER REVIEW 3 of 13

Figure 1. RedRed arrow arrow indicates deposited dust on leaves [23]. [23].

2. Methodology Methodology For this study, surface meteorological data and a map of regional overview of Indian subcontinent werewere collected collected from from the Departmentthe Depart ofment Meteorology of Meteorology and Hydrology, and NepalHydrology, (DHM-Nepal) Nepal (DHM-Nepal)and weatherunderground.com and weatherunderground.com [24,25]. Satellite [24,25]. imagery Satellite from imagery Moderate from Moderate Resolution Resolution Imaging ImagingSpectroradiometer Spectroradiometer (MODIS) /Terra(MODIS)/Terra [26] were collected[26] were and collected analyzed and in depth.analyzed For in the depth. synoptic For scale the synopticobservational scale atmospheric observational processes atmospheric analysis, processes the reanalysis analysis, datasets the ofre surfaceanalysis pressure, datasets geopotential of surface pressure,height, air geopotential temperature, height, precipitable air temperature, water, wind pr speedecipitable and direction,water, wind and speed vertical and motion direction, obtained and verticalfrom the Modernmotion Eraobtained Retrospective-Analysis from the Modern for ResearchEra Retrospective-Analysis and Applications (MERRA) for Research (0.50 0.67and) ◦ × ◦ wereApplications used to (MERRA) make horizontal (0.50° × cross 0.67°) sections were used [27 ].to Vertical make horizontal cross sections cross ofsections wind speed[27]. Vertical components cross sectionsand potential of wind temperature speed components were plotted and from potentia the selectedl temperature reanalysis were datasets. plotted An from evolution the selected of the reanalysisdust by an datasets. aerosol modelling An evolution system of atthe 1 dust1 byhorizontal an aerosol resolution modelling from system the Navy at 1° Aerosol × 1° horizontal Analysis ◦ × ◦ resolutionand Prediction fromSystem the Navy (NAAPS) Aerosol [ 28Analysis] was considered. and Prediction In addition System to(NAAPS) this, Modern-Era [28] was considered. Retrospective In Analysisaddition forto this, Research Modern-Era and Applications-2 Retrospective (MERRA-2) Analysis modelfor Research (spatial and resolution Applications-2 0.5 0.625 (MERRA-2)) hourly ◦ × ◦ modeldatasets (spatial were usedresolution to analyze 0.5 × the 0.625°) dust hourly scattering datasets aerosol were optical used thickness to analyze (AOT) the 550dust nm scattering of 1 µm aerosolparticulate optical matter thickness [29] over (AOT) this region 550 nm of interest.of 1 μm Rawinsondeparticulate matter data were [29] obtainedover this from region the of University interest. Rawinsondeof Wyoming, data USA were [30]. obtained Similarly, from the dustthe Universi backwardty trajectoriesof Wyoming, were USA analyzed [30]. Similarly, using the the Hybrid dust backwardSingle Particle trajectories Lagrangian were Integrated analyzed Trajectory using (HYSPLIT)the Hybrid model Single [31 Particle]. To analyze Lagrangian the vertical Integrated reach of Trajectorydust, imageries (HYSPLIT) of Cloud-Aerosol model [31]. Lidar To analyze and Infrared the vertical Pathﬁnder reach Satelliteof dust, Observationimageries of (CALIPSO)Cloud-Aerosol [32] wereLidar alsoand takenInfrared into Pathfinder account. Satellite Observation (CALIPSO) [32] were also taken into account.

3. Results Results and and Discussion Discussion

3.1. Observation of Dust Storms from Some Surface Stations 3.1. Observation of Dust Storms from Some Surface Stations Locations of surface stations clos closee to the area of dust storms is shown in the regional overview of Indian subcontinent (Figure 22))[ [24,25].24,25]. Observational data of Safdarjung Airport, India (28.58(28.58°◦ N 77.21°77.21◦ E) and Sardar Vallabhbhai Patel International Airport, India (23.07° (23.07◦ N 72.63° 72.63◦ E) archived by Weather Underground (Table1 1)) indicatedindicated thatthat dustdust stormsstorms hithit SafdarjungSafdarjung Airport,Airport, IndiaIndia atat 5:455:45 toto 8:45 a.m. (local (local time) time) on on 12 12 June June 2018 2018 with with westerly/west-northwesterly westerly/west-northwesterly winds winds ranging ranging from from 6.26 6.26 to 1 8.05to 8.05 ms m−1 speed; s− speed; at 5:45 at 5:45to 11:45 to 11:45 a.m. a.m.on 13 on June 13 June2018 2018with withwesterly westerly wind wind ranging ranging from from7.60 to 7.60 9.39 to 1 ms9.39−1 ; m at s −3:45; at to 3:45 8:45 to a.m. 8:45 on a.m. 14 on June 14 June2018 2018with withwest-southwesterly west-southwesterly wind wind ranging ranging from from4.47 to 4.47 7.15 to 1 ms7.15−1; m and s− at; and 3:45 at to 3:45 5:45 to a.m. 5:45 on a.m. 15 onJune 15 2018 June wi 2018th west/west-southwesterly with west/west-southwesterly winds winds ranging ranging fromfrom 6.26 1 to6.26 7.60 to 7.60ms−1m speed. s− speed. Similarly, Similarly, Sardar Sardar Vallab Vallabhbhaihbhai Patel Patel Intl IntlAirport, Airport, India India experienced experienced dust dust storms storms at 6:45at 6:45 to 11:45 to 11:45 a.m. a.m. (local (local time) time) of 12 ofJune 12 2018 June with 2018 westerly/southwesterly/west-southwesterly with westerly/southwesterly/west-southwesterly winds ranging from 4.02 to 5.36 ms−1; at 4:15 a.m. to 11:15 p.m. (local time) of 13 June 2018 with westerly/southwesterly/west-southwesterly winds ranging from 2.68 to 6.26 ms−1; at 12:45 a.m. to

Atmosphere 2020, 11, x FOR PEER REVIEW 4 of 13

11:15 p.m. (local time) of 14 June 2018 with south-southwesterly/west-southwesterly winds ranging from 2.68 to 7.15 ms−1; and at 5:45 a.m. to 5:45 p.m. (local time) of 15 June 2018 with southwesterly/south-southwesterly/west-southwesterly winds ranging from 2.68 to 7.70 ms−1. Hence, this clearly shows that there were multiple dust storms in the far western parts of India from 12 to 15 June of 2018. It is to be noted here that prior to these event days (e.g., 10–11 June 2018), there was no precipitation and the flow of strong wind at Safdarjung Airport and Sardar Vallabhbhai Patel International Airport, India.

Table 1. Surface weather data observed at two stations of India [24].

Date of Wind Name of Surface Local Dust Speed Wind Direction Stations Time Storms (ms−1) 5:45 Am 12 June 6.26 to to 8:45 Westerly/West-northwesterly 2018 8.05 Am 5:45 Am 13 June 7.60 to to 11:45 Westerly Safdarjung Airport, 2018 9.39 Am India 3:45 Am 14 June 4.47 to to 8:45 West-southwesterly 2018 7.15 Am 15 June 3:45 Am 6.26 to Atmosphere 2020, 11, 529 West/west-southwesterly 4 of 13 2018 5:45 Am 7.60 6:45 Am 12 June 4.02 to to 11:45 Westerly/Southwesterly/West-southwesterly winds ranging from 4.022018 to 5.36 m s 1; at 4:155.36 a.m. to 11:15 p.m. (local time) of 13 June 2018 with Am− 1 westerly/southwesterly/west-southwesterly4:15 Am winds ranging from 2.68 to 6.26 m s− ; at 12:45 a.m. 13 June 2.68 to to 11:15 p.m. (local time) of 14 Juneto 11:15 2018 with south-southwesterlyWesterly/Southwesterly/West-southwesterly/west-southwesterly winds Sardar Vallabhbhai 2018 6.26 1 Pm rangingPatel International from 2.68 to 7.15 m s− ; and at 5:45 a.m. to 5:45 p.m. (local time) of 15 June 2018 with 12:45 Am southwesterlyAirport, India/south-southwesterly 14 June /west-southwesterly2.68 to winds ranging from 2.68 to 7.70 m s 1. Hence, to 11:15 South-southwesterly/West-southwesterly − 2018 7.15 this clearly shows that there were multiplePm dust storms in the far western parts of India from 12 to 15 June of 2018. It is to be noted here5:45 that Am prior to these event days (e.g., 10–11 June 2018), there was 15 June 2.68 to to 5:45 Southwesterly/South-southwesterly/West-southwesterly no precipitation and the2018 ﬂow of strong wind7.70 at Safdarjung Airport and Sardar Vallabhbhai Patel International Airport, India. Pm

FigureFigure 2.2. Observation of dust storms from some surface stations are shownshown byby redred colouredcoloured trianglestriangles in the map of regional overview of Indian subcontinent [24,25]. A triangle, which is shown in the side in the map of regional overview of Indian subcontinent [24,25]. A triangle, which is shown in the side of Himalyas, represents Safdarjung Airport, India, and another triangle represents Sardar Vallabhbhai of Himalyas, represents Safdarjung Airport, India, and another triangle represents Sardar Patel International Airport, India. Rawinsonde sounding station at Ahamadabad in India is also shown by a yellow coloured star.

Table 1. Surface weather data observed at two stations of India [24].

Name of Surface Date of Wind Speed Local Time 1 Wind Direction Stations Dust Storms (m s− ) 12 June 2018 5:45 a.m. to 8:45 a.m. 6.26 to 8.05 Westerly/West-northwesterly

Safdarjung Airport, 13 June 2018 5:45 a.m. to 11:45 a.m. 7.60 to 9.39 Westerly India 14 June 2018 3:45 a.m. to 8:45 a.m. 4.47 to 7.15 West-southwesterly 15 June 2018 3:45 a.m. 5:45 a.m. 6.26 to 7.60 West/west-southwesterly 12 June 2018 6:45 a.m. to 11:45 a.m. 4.02 to 5.36 Westerly/Southwesterly/West-southwesterly Sardar Vallabhbhai 13 June 2018 4:15 a.m. to 11:15 p.m. 2.68 to 6.26 Westerly/Southwesterly/West-southwesterly Patel International Airport, India 14 June 2018 12:45 a.m. to 11:15 p.m. 2.68 to 7.15 South-southwesterly/West-southwesterly 15 June 2018 5:45 a.m. to 5:45 p.m. 2.68 to 7.70 Southwesterly/South-southwesterly/West-southwesterly

3.2. Dust Storms and the Dust Advection The MODIS/Terra images [26] captured useful images of massive dust storms of thick dust over the far West to Northwest to North of India from 12 June to 15 June 2018, as shown in Figure3a–d, respectively. Although these ﬁgures are not able to indicate the exact location and the time of the initiation of the dust storm, based on the earliest available images among them and observational Atmosphere 2020, 11, x FOR PEER REVIEW 5 of 13

Vallabhbhai Patel International Airport, India. Rawinsonde sounding station at Ahamadabad in India is also shown by a yellow coloured star.

3.2. Dust Storms and the Dust Advection The MODIS/Terra images [26] captured useful images of massive dust storms of thick dust over Atmosphere 2020, 11, 529 5 of 13 the far West to Northwest to North of India from 12 June to 15 June 2018, as shown in Figure 3a–d, respectively. Although these figures are not able to indicate the exact location and the time of the initiation of the dust storm, based on the earliest available images among them and observational information, it can be inferred that the ﬁrst lifting of dust was initiated around 26.3◦ N 73.01◦ E on information,12 June 2018 it can (Figure be inferred3a). that the first lifting of dust was initiated around 26.3° N 73.01° E on 12 June 2018 (Figure 3a).

(a) (b)

Figure 3. Dust storms images captured by moderate resolution imaging spectroradiometer Figure 3. Dust storms images captured by moderate resolution imaging spectroradiometer (MODIS)/Terra(MODIS)/Terra (1 km (1 resolution) km resolution) on 12–15 on 12–15 June 2018 June (( 2018a), ( ((b)a, –(dc)),, and respectively (d), respectively [26]). Pink [26]). colored Pink circles area coloredshow circles the area dust show plume the areas dust ofplume western areas to of northwesternwestern to northwestern to northern to partsnorthern of India.parts of India. 3.3. Synoptic Overview from the MERRA

Based on the 0.50 0.67 MERRA reanalysis datasets [27], a meso-α/synoptic observational ◦ × ◦ analysis was carried out to find out the roles of different atmospheric processes from the surface to the mid-troposphere at different time intervals that may have generated this particular favorable muddy rain environment. The mid tropospheric synoptic overview from the MERRA shows that there was a positively tilted trough (oriented along a southwest-northeast axis) in the far western/southwestern parts of India and southwestern/southern parts of Nepal from 12 June 2018 (Figure4a). Over time, the geopotential height consistently showed a positively tilted trough (the presence of trough indicates the condition of static instability below it, the generation of strong positive vorticity advection, and the Atmosphere 2020, 11, 529 6 of 13 creation of differential temperature advection (i.e., upper level and low-level fronts)) with falling heights rotated cyclonically to be oriented more southern to southwestern across Nepal till 15 June 2018 (Figure4b). On 0630 UTC of 12 June 2018 a jet at 500 hPa (causes the upper level forcing) was propagating from northwest of India to western to southern to eastern parts of Nepal, respectively, with further amplification over time; therefore, it was continuously advancing on its way, influencing the trough. The baroclinic amplification of the jet streak was consistent with the deepening of the trough at that time. Similarly, on 0000 UTC of 15 June 2018, there were a juxtaposition of the jet with lower level mesoscale jetlet between 700 and 850 hPa, referring to a possible coupling between the upper and lower level wind maxima. Due to the presence of the upper level trough and the strong jet over our region of interest it can be inferred that the combination of these lift mechanisms played significant roles for occurrence of thunderstorms leading to downburst, kicking up the dust (Figure3a–d), and carrying the lofted dust into Nepal for causing a muddy rainfall over there. These processes are also discussed in different sub-sections below.

3.4. Evolution of the Dust by an Aerosol Modeling of Navy Aerosol Analysis and Prediction System (NAAPS) and Dust Scattering AOT by MERRA-2 The NAAPS model is an additional supporting information regarding the occurrence of dust storm data in aforesaid region of few observations. It is a 1 1 resolution aerosol model that depicts ◦ × ◦ dust predictions at 6-h intervals [28], is also used to diagnose the beginning and subsequent multiple occurrences of dust storms over our region of interest. This model reveals the evolution of the dust, including the concentration of sulfate over the region, and it can be related to the strength and track of the dust transport over time. It is important to note that sulfate was associated with the initial emission of the dust into the atmosphere, and over time, due to the lower density associated with sulfate compared with dust it remains for a relatively long period of time in the environment. Though the concentration of sulfate is lower than the dust in the composite form of the initial emission of the total material from the surface, over time, sulfate can be recognized due to its longevity in the atmosphere more than the dust due to its lower density. Here, we analyzed the NAAPS aerosol modeling image from 0000 UTC of June 12 to 15, 2018. NAAPS shows that the strongest signal of dust and sulfate emission into the atmosphere was largely over the 20–22◦ N 68–74◦ E region at 0600 to 1800 UTC of 13 June 2018 (Figure5a–b). At 1800 UTC of 14 June 2018 and onwards, the strength and areal extension of the dust and sulfate materials increased and mostly advected towards the northwest/north/northeast region of India and its neighbors, 22–35◦ N 68–88◦ E (Figure5c). Similarly, MERRA-2 model shows that the dust-scattering AOT reached up to 0.874 when the intrusion of dust reached in maximum vertical height in early of 14 June 2018 in the western parts of Nepal; and over time this value was diluted [29] when the dust was advected towards the eastern parts of Nepal. Atmosphere 2020, 11, 529 7 of 13 Atmosphere 2020, 11, x FOR PEER REVIEW 7 of 13

(a) (b)

FigureFigure 4. (a) 4.Geopotential(a) Geopotential height and height wind and speed/direction wind speed/ directionat 500 hPa at at500 0630 hPa UTC at on 0630 12 June UTC 2018. on 12 The June yellow 2018. colored The yellow circle shows colored the circle flow showsof jet and the the ﬂow white of jet and the white dotteddotted line indicates line indicates a trough a axis trough from axis the Modern-Era from the Modern-Era Retrospective Retrospective analysis for Research analysis and for Applications Research and MERRA Applications reanalysis MERRA with horizontal reanalysis resolution with horizontalof 0.5 × resolution of 0.67°0.5 [27]. The0.67 light[27 blue]. The colored light bluecircle colored shows the circle area shows of dust the storm area ofand dust the stormthunderstorm and the outbreak; thunderstorm (b) Geopotential outbreak; ( bheight) Geopotential and wind heightspeed/direction and wind at speed 500 hPa/direction at 500 hPa ◦ × ◦ on 0930on 0930UTC on UTC 15 onJune 15 2018. June The 2018. yellow The colored yellow circle colored shows circle the shows flow of the jet ﬂowand the of white jet and dotted the white line indicates dotted linea trough indicates axis from a trough the Modern-Era axis from theRetrospective Modern-Era Retrospective analysisanalysis for Research for Research and Applications and Applications (MERRA) (MERRA) reanalysis reanalysis with horizontal with horizontal resolution of resolution 0.5 × 0.67°[27]. of 0.5 0.67 [27]. ◦ × ◦

Atmosphere 2020, 11, 529 8 of 13 Atmosphere 2020, 11, x FOR PEER REVIEW 8 of 13

(a) (b)

(c)

FigureFigure 5. 5.( a(a)) Dust Dust concentration concentration ((µμgg/m/m33)) atat 00600060 UTCUTC on 13 June 2018 (Green and and yellow yellow show show the the dustdust and and red red shows shows sulfatesulfate (horizontal(horizontal resolution of of 1 1 × 1°))1 ))[28]; [28 (];b) ( bDust) Dust concentration concentration (μg/m (µg3/)m at3 ) ◦ × ◦ at1200 1200 UTC UTC on on 13 13 June June 2018 2018 (Green (Green and and yellow yellow show show the the dust dust and and red red show showss sulfate sulfate (horizontal (horizontal resolutionresolution 1 1 × 1°))1 )) [28]; [28]; ( (cc)) Dust Dust concentration concentration ( (μµg/mg/m33)) at at 1800 1800 UTC UTC on on 14 14 June June 2018 2018 (Green (Green and and yellow yellow ◦ × ◦ showshow the the dust dust and and red red shows shows sulfate sulfate ( ( horizontal horizontal resolutionresolution ofof 11 × 1°))1 )) [28]. [28 ]. ◦ × ◦ 3.5.3.5. Rawinsonde Rawinsonde Soundings Soundings AnalysesAnalyses ToTo observe observe the the vertical vertical temperature temperature andand windwind speedspeed/direction/direction profiles profiles at different different atmospheric atmospheric pressurepressure levels levels closeclose toto thethe time period of of the the mu muddyddy rainfall rainfall in in Nepal, Nepal, the the rawinsonde rawinsonde sounding sounding of ofAhamadabad Ahamadabad (23.06° (23.06 ◦N,N, 72.63° 72.63 ◦E)E) in in India India obtained obtained from from University University of of Wyoming, Wyoming, USA USA [30] [30 ]was was analyzedanalyzed from from 12–15 12–15 JuneJune 20182018 (Figure(Figure6 ).6). SinceSince thisthis soundingsounding stationstation isis closeclose toto thethe possiblepossible dust sourcessources we we expect expect thatthat thethe informationinformation regardingregarding thethe verticalvertical profilesprofiles of different different meteorological variablesvariables from from these these stations stations could could bebe wellwell representedrepresented inin thisthis analysis.analysis. A sounding at at Ahamadabad Ahamadabad (23.06(23.06°◦ N N 72.63 72.63°◦ E), E), which which is closeis close to theto the possible possible area ar ofea a of dust a dust storm, storm, at 1200 at 1200 UTC UTC of June of 12,June 2018 12, shows 2018 theshows likely the condition likely condition of a thunderstorm of a thunderstorm because of thebeca valueuse ofof thethe convective value of availablethe convective potential available energy (CAPE)potential (1438 energy J/kg) (CAPE) and the (1438 lifted J/kg) index and ( 9.76)the lifted at that index time ( (i.e.,−9.76) responsible at that time for (i.e., lifting responsible mechanism), for − generationlifting mechanism), of the trigger generation effect due of tothe the trigger presence effect of due warm to the air andpresence moisture of warm at a lowerair and level moisture (shown at bya thelower value level of the(shown dew by point, the value which of is the greater dew thanpoint, 21 which◦C and is greater veering than directional 21 °C and change veering of winddirectional 45◦ or morechange from of wind surface 45° to or 700 more hPa, from 850 surface to 700 hPato 700 wind hPa, was 850 10.3to 700 m hPa/s (i.e., wind low-level was 10.3 jet) m/s or (i.e., greater low-level in the observedjet) or greater sounding), in the andobserved the presence sounding), of the and trough the presence and jet asof discussedthe trough in an thed jet earlier as discussed section. Hence,in the thereearlier was section. a combination Hence, there of high was planetary a combination boundary of layerhigh (PBL)planetary moisture, boundary strong layer directional (PBL) moisture, and wind shear,strong low directional convective and inhibition, wind shear, CAPE, low convec and liftingtive inhibition, mechanisms. CAPE, and lifting mechanisms.

Atmosphere 2020, 11, 529 9 of 13 Atmosphere 2020, 11, x FOR PEER REVIEW 9 of 13

Figure Figure6. Atmospheric 6. Atmospheric sounding sounding observed observed at at Ahamad Ahamadabad,abad, India India at at 1200 1200 UTC UTC on 12 on June 12 June 2018 [201830]. [30].

In addition to this, the sounding, which is presented in Figure6, is inverted and “V”-shaped and In addition to this, the sounding, which is presented in Figure 6, is inverted and “V”-shaped is also showing that the dew point depression decreased significantly with height, dry air (low RH) in and is thealso lower showing troposphere that the with dew nearly point saturated depression air (high decreased RH) in the significantly middle troposphere, with height, the presence dry air (low RH) inof the inversion lower separatingtroposphere the with dry air nearly aloft andsatura theted moist air air(high near RH) the surface,in the middle and the troposphere, convective the presencecondensation of inversion level (CCL)separating at a high the elevation. dry air Hence, aloft this and “V”-shaped the moist sounding air near reveals the that surface, there was and the convectivea quite condensation appropriate condition level (CCL) for the at generation a high elev of a strongation. downdraftHence, this from “V”-shaped the severe thunderstorm. sounding reveals that thereFor example, was a whenquite anappropriat inversion (alsoe condition known as for cap) the existed generation from the surfaceof a strong to a certain downdraft height, heat, from the severemoisture, thunderstorm. and instability For example, could have when built an under invers thision “capping” (also known inversion. as cap) Over existed time, once from the the cap surface broke due to the addition of daytime sensible heating, then explosive convection occurred resulting in to a certain height, heat, moisture, and instability could have built under this “capping” inversion. wind gusts. This was due to the entrain of dry air aloft into the downdraft. This promoted evaporative Over time,cooling once and furtherthe cap enhanced broke due the negative to the buoyancyaddition ofof adaytime parcel. In sensible this case, heating, a cold parcel then of explosive air convectionsurrounded occurred by warm resulting air descended in wind faster gusts. than This the was surrounding due to airthe sinceentrain the coldof dry air wasair aloft denser, into the downdraft.and cooler This air promoted is often noticed evaporative at the surface cooling when an thed downburstfurther enhanced air reaches the the observer.negative When buoyancy this of a parcel.cooler In this air interacted case, a withcold the parcel warm buoyantof air airsurrounded column present by inwarm the lower air troposphere,descended as faster indicated than the surroundingby the sounding air since above, the cold there air was was a lifting denser, of the and dust co tooler 740 hPaair is and often upward noticed caused at by the the surface generation when the downburstof the significantair reaches amount the observer. of turbulent When eddies. this This cooler turbulence air interacted was the result with of the the summationwarm buoyant of air the strong wind shear and the buoyancy, as suggested by [33]. All these aforesaid processes were column present in the lower troposphere, as indicated by the sounding above, there was a lifting of consequences of the thunderstorm and its effect in Ahamadabad and its surroundings. This is consistent the dust to 740 hPa and upward caused by the generation of the significant amount of turbulent with the observation of dust storm observed at Sardar Vallabhbhai Patel Intl Airport, India (23.07◦ N, eddies.72.63 This◦ E), turbulence which is very was close the toresult this soundingof the summa stationtion in Ahamadabad, of the strong as wind already shear mentioned and the in buoyancy, the as suggestedearlier section. by [33]. All these aforesaid processes were consequences of the thunderstorm and its effect in Ahamadabad and its surroundings. This is consistent with the observation of dust storm 3.6. Analyses of Backward Trajectory and Vertical Reach of Dust observed at Sardar Vallabhbhai Patel Intl Airport, India (23.07° N, 72.63° E), which is very close to this soundingThe station HYSPLIT in modelAhamadabad, is run with as fullalready ensemble mentioned set-up, in producing the earlier a variety section. of parcel back trajectories [31], as shown in Figure7. It is used here to compute air parcel trajectories and the deposition or dispersion of lofted dust from the source of dust to recipient of it (e.g., to find out where 3.6. Analyses of Backward Trajectory and Vertical Reach of Dust did the dust come from to Nepal). In other words, this is used here to establish whether a high level of Thedust HYSPLIT at one location model (e.g., is Nepal) run iswith caused full by ensemble the transport set-up, of aircontaminants producing froma variety another of location. parcel back trajectoriesFor this [31], analysis, as shown Kathmandu in Figure (27.72◦ 7.N, It 85.32 is ◦usE)ed in Nepalhere to is consideredcompute asair a recipientparcel trajectories point. and the deposition or dispersion of lofted dust from the source of dust to recipient of it (e.g., to find out where did the dust come from to Nepal). In other words, this is used here to establish whether a high level of dust at one location (e.g., Nepal) is caused by the transport of air contaminants from another location. For this analysis, Kathmandu (27.72° N, 85.32° E) in Nepal is considered as a recipient point.

Atmosphere 2020, 11, 529 10 of 13 Atmosphere 2020, 11, x FOR PEER REVIEW 10 of 13

Figure 7. FigureBackward 7. Backward Trajectory Trajectory by by thethe Hybrid Hybrid Single ParticleSingle LagrangianParticle IntegratedLagrangian Trajectory Integrated (HYSPLIT) Trajectory (HYSPLIT)model model [31] [31] ending ending at 2300 at UTC 2300 on 15UTC June on 2018. 15 June 2018.

HYSPLIT back trajectories of 10 to 16 June of 2018 combined with MODIS satellite imageries have HYSPLITprovided back insight trajectories into whether of high10 to muddy 16 June rain was of caused2018 combined by local air pollution with MODIS sources orsatellite whether imageries have provideddust was insight blown into in the whether wind. Further, high the muddy backward rain trajectories was caused (Figure by7) clearlylocal inferair pollution that the air sources or whether dustparcel was laden blown with dust in the was wind. transported Further, from thethe western backward parts trajectories (between 22◦ N(Figure 72◦ E and 7) 27clearly◦ N to infer that the air parcel77◦ E) laden of India with toNepal dust (e.g.,was Kathmandu),transported as fr shownom the by western the higher parts air currents. (between This also22° revealsN 72° E and 27° that Thar desert of both Rajasthan and Gujarat states of India, which lie in the western part of India, N to 77° E)served of asIndia a dust to source Nepal in this (e.g., particular Kathmandu), event. as shown by the higher air currents. This also reveals that TharThis desert is also supported of both by Rajasthan CALIPSO images and Gujarat [32], which states show thatof India, the vertical which reach lie of in dust the was western 6 km part of India, served(Figure as8 aa,b). dust This source infers that in this when particular the dust reached event. such a height, the strong westerly /northwesterly This iscurrent also ofsupported air at that height, by CALIPSO as discussed images in an earlier [32], section, which advected show dustthat towards the vertical the sky reach of Nepal, of dust was where the precipitable water was present at that time (Figure9), leading to muddy rain in Nepal. 6 km (Figure 8a,b). This infers that when the dust reached such a height, the strong westerly/northwesterly current of air at that height, as discussed in an earlier section, advected dust towards the sky of Nepal, where the precipitable water was present at that time (Figure 9), leading to muddy rain in Nepal.

Atmosphere 2020, 11, 529 11 of 13 Atmosphere 2020, 11, x FOR PEER REVIEW 11 of 13 Atmosphere 2020, 11, x FOR PEER REVIEW 11 of 13

(a) (a)

(b) (b)

Figure 8. (a) Vertical stretch of dust at 20:42:26.8 to 20:55:55.4 UTC on 13 June 2018 captured by FigureFigure 8.8. ((a)) Vertical stretch of dustdust atat 20:42:26.820:42:26.8 toto 20:55:55.420:55:55.4 UTC on 1313 JuneJune 20182018 capturedcaptured byby CALIPSO [32]. The red circled area shows vertical reach of dust; (b) Vertical stretch of dust at CALIPSOCALIPSO [32[32].]. The The red red circled circled area area shows shows vertical vertical reach reach of dust; of (bdust;) Vertical (b) Vertical stretch of stretch dust at of 20:30:08.0 dust at 20:30:08.0 to 20:43:36.7 UTC on 15 June 2018 captured by CALIPSO. The red circled area shows to20:30:08.0 20:43:36.7 to UTC20:43:36.7 on 15 UTC June 2018on 15 captured June 2018 by capt CALIPSO.ured by The CALIPSO. red circled The area red shows circled vertical area shows reach vertical reach of dust. ofvertical dust. reach of dust.

Figure 9.9. TotalTotal precipitable water in mm (shown in legend at upper part of Figure) over Nepal Figure 9. Total precipitable water in mm (shown in legend at upper part of Figure) over Nepal (shown(shown by aa redred colouredcoloured circlecircle area)area) atat 18301830 UTCUTC on 15 JuneJune 20182018 from thethe MERRAMERRA reanalysis with (shown by a red coloured circle area) at 1830 UTC on 15 June 2018 from the MERRA reanalysis with horizontal resolution of 0.50.5◦ × 0.67°.0.67◦ . horizontal resolution of 0.5 ×× 0.67°.

Atmosphere 2020, 11, 529 12 of 13

4. Conclusions There were big surges of dust storms in the far western parts of India, especially Ahamadabad and its surroundings, caused by thunderstorms from 12 to 15 June 2018, intermittently. There was a lifting of dust into the upper air caused by the generation of significant amount of turbulent kinetic energy as a function of strong gust wind, which had strong wind shear, and the convective buoyancy at the lower boundary layer during the descending outflow of cold air caused by the generation of a severe thunderstorm. When this lofted dust in the upper air came into contact with prevailing winds, such as northwesterly/westerly associated with the jets, as discussed in the earlier sections, upper air dust was advected towards Nepal, where rainfall was occurring, led to the muddy rain in Nepal. Hence, the study of this particular event reveals that western parts of India were dust source regions (i.e., Thar desert of both Rajasthan and Gujarat states of India, which plays a significant role as a source of emission of dust caused by the dust storms during the months of March–June every year [34]) from which dust was transported to Nepal as a long range transport. As this finding is still based on the low-resolution datasets, it would be better if it could be done on the high-resolution datasets so that the details of finer temporal and spatial processes, such as emission to transport to the deposition of dust in this particular event, could be further understood. In addition to this, there is a need for more cases in order to establish the representativeness of the event presented here.

Author Contributions: Conceptualization, methodology, software, validation, formal analysis, investigation, and writing, A.K.P.; resources and project administration, T.X., X.L., and B.D. All authors have read and agreed to the published version of the manuscript. Funding: This research is funded by Kathmandu Center for Research and Education (KCRE), Chinese Academy of Sciences (CAS)—Tribhuvan University (TU). Acknowledgments: We would like to thank Tandong Yao and Tao Wang for their helpful advice and support. Also, thanks goes to Kathmandu Center for Research and Education, Chinese Academy of Sciences-Tribhuvan University, Kathmandu, Nepal for providing financial support for this study. Conflicts of Interest: The authors declare no conflict of interest.

References

1. Seinfeld, J.; Carmichael, G.; Arimoto, R.; Conant, W.; Brechtel, F.; Bates, T.; Cahill, T.; Clarke, A.; Doherty, S.; Flatau, P.; et al. ACE-ASIA: Regional climatic and atmospheric chemical eﬀects of Asian dust and pollution. Bull. Am. Meteor. Soc. 2004, 85, 367–380. [CrossRef] 2. Tegen, I. Modeling the mineral dust aerosol cycle in the climate system. Quat. Sci. Rev. 2003, 22, 1821–1834. [CrossRef] 3. Appel, B.; Tokiwa, Y.; Hsu, J.; Kothny, E.; Hahn, E. Visibility as related to atmospheric aerosol constituents. Atmos. Environ. 1985, 19, 1525–1534. [CrossRef] 4. Chan, Y.; Simpson, R.; Mctainsh, G.; Vowles, P.; Cohen, D.; Bailey, G. Sourceapportionment of visibility degradation problems in Brisbane (Australia)—Using the multiple linear regression techniques. Atmos. Environ. 1999, 33, 3237–3250. [CrossRef] 5. Okin, G.S.; Reheis, M.C. An ENSO predictor of dust emission in the southwestern United States. Geophys. Res. Lett. 2002, 29.[CrossRef] 6. Reheis, M.; Kihl, R. Dust deposition in southern Nevada and California, 1984 1989: Relations to climate, source area, and source lithology. J. Geophys. Res. 1995, 100, 8893–8918. [CrossRef] 7. Pokharel, A.; Kaplan, M. Dust Climatology of the NASA Dryden Flight Research Center (DFRC) in Lancaster, California, USA. Climate 2017, 5, 15. [CrossRef] 8. Okin, G.S.; Gillette, D.A.; Herrick, J.E. Multi scale controls on and consequences of Aeolian process in landscape change in arid and semi-arid environments. J. Arid Environ. 2006, 65, 253–275. [CrossRef] 9. Pokharel, A.; Kaplan, M.; Fiedler, S. Subtropical Dust Storms and Downslope Wind Events. J. Geophys. Res. Atmos. 2017, 122, 10. [CrossRef] 10. Pokharel, A.; Kaplan, M. Organization of dust storms and synoptic scale transport of dust by Kelvin waves. Earth Syst. Dynam. 2019, 10, 651–666. [CrossRef] Atmosphere 2020, 11, 529 13 of 13

11. Pokharel, A.; Kaplan, M.; Fiedler, S. The Role of Jet Adjustment Processes in Subtropical Dust Storms. J. Geophys. Res. Atmos. 2017, 122, 12. [CrossRef] 12. Pokharel, A.; Kaplan, M.; Fiedler, S. Atmospheric Dynamics of the Harmattan Surge on March 2, 2004. In Proceedings of the 2nd International Conference on Atmospheric Dust–DUST 2016, Taranto, Italy, 12–17 June 2016; pp. 85–93. [CrossRef] 13. Pokharel, A. Atmospheric Dynamics of Sub-Tropical Dust Storms. Ph.D. Thesis, University of Nevada, Reno, USA, 2016. Available online: https://ui.adsabs.harvard.edu/abs/2016PhDT98P/abstract (accessed on 3 February 2020). 14. Brazel, A.; HSU, S. The climatology of hazardous Arizona dust storms. Desert Dust 1981, 186, 293–303. [CrossRef] 15. SciJinks. Available online: https://scijinks.gov/dust-storm/ (accessed on 3 February 2020). 16. Goudie, A.; Middleton, N. Dust storms in South West Asia. Acta Universitatis Carilinae Suppl. 2000, 73–83. 17. Jauregui, E. The dust storms of Mexico City. Int. J. Climatol. 1989, 9, 169–180. [CrossRef] 18. Baral, K.N.; Mackerras, D. The cloud flash-to-ground flash ratio and other lightning occurrence characteristics in Kathmandu thunderstorms. J. Geophys. Res. 1992, 97, 931–938. [CrossRef] 19. Zifa, W.; Hiromasa, U. Modelling of Long Range Transport of Yellow Sand and Muddy Rain in East Asia; Annuals of Disasters Prevention Research Institute, Kyoto University: Kyoto, Japan, 1999; No. 42 B-1. 20. Hedin, L.; Likens, G. Atmospheric Dust and Acid Rain. Sci. Am. 1996, 275, 88–92. [CrossRef] 21. Loÿe-Pilot, M.D.; Martin, J.M.; Morelli, J. Influence of Saharan dust on the rain acidity and atmospheric input to the Mediterranean. Nature 1986, 321, 427–428. [CrossRef] 22. The Himalayan. Available online: http://thehimalayantimes.com/nepal/kathmandu-valley-receives-muddy- rain/ (accessed on 3 February 2020). 23. Twitter. Available online: https://twitter.com/rupajoshi/status/1007806022805700608/photo/1 (accessed on 3 February 2020). 24. Weather Underground. Available online: Weatherunderground.com (accessed on 3 February 2020). 25. Stolbova, V.; Martin, P.; Bookhagen, B.; Marwan, N.; Kurths, J. Topology and seasonal evolution of the network of extreme precipitation over the Indian subcontinent and Sri Lanka. Nonlin. Processes Geophys. 2014, 21, 901–917. [CrossRef] 26. MODIS/Terra. Available online: https://worldview.earthdata.nasa.gov (accessed on 3 February 2020). 27. MERRA. Available online: https://disc.sci.gsfc.nasa.gov/mdisc/data-holdings/merra/merra_products_nonjs. shtml (accessed on 3 February 2020). 28. NAAPS. Available online: https://www.nrlmry.navy.mil/aerosol_web/ (accessed on 3 February 2020). 29. MERRA-2/Giovanni. Available online: https://giovanni.gsfc.nasa.gov/giovanni/ (accessed on 3 February 2020). 30. University of Wyoming sounding. Available online: http://weather.uwyo.edu/upperair/sounding.html (accessed on 3 February 2020). 31. HYSPLIT. Available online: https://www.ready.noaa.gov/HYSPLIT.php (accessed on 5 March 2020). 32. CALIPSO. Available online: https://www-calipso.larc.nasa.gov/tools/data_avail/index.php?d=2018 (accessed on 5 March 2020). 33. Stull, R. Meteorology for Scientists and Engineers, 2nd ed.; Brooks Cole: Pacific Grove, CA, USA, 1999. 34. Sarkar, S.; Chauhan, A.; Kumar, R.; Singh, R.P. Impact of deadly dust storms (May 2018) on air quality, meteorological, and atmospheric parameters over the northern parts of India. GeoHealth 2019, 3, 67–80. [CrossRef][PubMed]

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).