Western Disturbances Research Articles

Characteristics of Western Disturbance intensification and associated induced circulations over the Indian Region

Western Disturbances (WD) are significantly important weather systems causing precipitation in the Western Himalayan region during Indian Winter months. WDs have two major components-the eastward propagating upper-level trough originating in the mid-latitudes and the low-level Induced Circulation (IC) prevailing over the Northern Indo-Pak region. The present work aims to study the genesis and movement of these upper-level systems using composite analysis of 10 WD events during the Indian winter season that caused extreme precipitation over the western Himalayan region with emphasize on associative mechanisms leading to the IC. Further, we find that the Meridional Temperature Gradient (MTG) is responsible for the development of extra-tropical storms initiated by frontal genesis over the mid-latitude regions. The frontal genesis occurs due to the polar cold air outbreak (CAO) over higher latitudes, causing meandering of the jet stream and leading to the development of the upper-level perturbation that intensifies into a trough. Prior to the IC intensification, the upper-level moisture transport dominates, and during the intensification process, the combined effect of the upper-level trough and IC facilitates a drastic increase in moisture flux from the Arabian Sea at the lower levels. The moisture transport from the Arabian Sea is, therefore, a primary precursor to heavy precipitation in the Himalayan vicinity due to rapid vertical ascent and intense cloud formation because of orographic effects.

A 1-D model to retrieve the vertical profiles of minor atmospheric constituents for cloud microphysical modelling: III. Disturbed weather situations

A hybrid Monte-Carlo Gear solver developed earlier has been improvised to retrieve the vertical profiles of CH4 and N2O during disturbed weather situations such as western disturbances, tropical cyclones, and heavy rainfall events over the megacities: Delhi, Kolkata, Chennai, and Mumbai. Due to rapid changes in the temperature during the passage of these systems over megacities, the percentage differences of CH4 and N2O number concentrations were more compared to the Community Long-term Infrared Microwave Coupled Atmospheric Product System (CLIMCAPS). Therefore, the hybrid solver has been modified by improving maximum likelihood estimates of vertical temperature profiles. The number concentrations of CH4 and N2O during these weather events since 2012 are obtained from the CLIMCAPS dataset for bias correction. It is found that the modified methodology has improved the retrieval of CH4 and N2O vertical profiles by reducing the error percentages during daytime and nighttime over these megacities. The percentage error in estimated number concentrations of CH4 and N2O significantly reduced during (i) the passage of the western disturbance and rainy days of August 2020 over Delhi; (ii) the rainy days of June 2020 over Kolkata; (iii) the influence of supercyclonic storm Amphan (24 and 25 Nov 2020) over Chennai and (iv) rainy days of July 2020 over Mumbai. Implementing this solver in the global model may retrieve the number concentrations more accurately.

Severe dust storm/thunderstorm activity over Uttar Pradesh on 13th May, 2018 - A case study

Premonsoon season over Uttar Pradesh is characterized withthunderstorm accompanied with rain, dust storm, gale winds and hail storms etc. These storms generally develop locally in association with convection and moisture convergence and seen as single cells in Doppler Weather Radar, but sometime these thunderstorms are associated with synoptic scale systems viz. Western Disturbance as cyclonic circulation/trough, induced low/ cyclonic circulation or northwest-southeast oriented trough, thereby increasing the spatial extent and severity of these thunderstorms significantly. In the present study, Duststorm/Thunderstorm activity that occurred over the state on large scale on 13th May 2018 and which claimed more than 49 human lives and large number of livestock in Uttar Pradesh has been analyzed. The purpose of this study wasto find out probable dynamic and thermodynamic aspects of this activity. The study indicates that the environment was highly favourable thermodynamically for severe thunderstorm activity with high maximum temperatures (>40C), high CAPE(>1000), high Total Total Index(>50) and high negative Lifted Index values (<-5) over most parts of the northwest Indian plains. The moisture discontinuity line was clearly noticed over south Uttar Pradesh with high moisture contents towards its north. Also 00UTC GFS wind analysis of the day at 925hPa indicated strong southeasterlies of the order of 30-35Kts over Uttar Pradesh resulting high moisture incursion in the lower levels over this region. The Low level wind shear was also high and was about 25-30Kt as evident from Skew-T gram of Lucknow for 12UTC of the day taken from Wyoming site as well as 12UTC wind shear analysis using ERA Interim daily data of ECMWF on 13 May, 2018. These features together with synoptic conditions viz; Western Disturbance (WD) in mid and upper levels and a Cyclonic Circulation (cycir) over south Haryana & neighbourhood as well as an east-west trough extending from this cycir in the lower levels made the environment highly favourable for severe thunderstorm activity over the region.

Spatial and meteorological controls of stable water isotope dynamics of precipitation in Kashmir Valley, Western Himalaya, India

ABSTRACT In the Himalayas, the lives and livelihoods of millions of people are sustained by water resources primarily depending on the moisture brought by Western Disturbances and Indian Summer Monsoon. In the present study, a network of 12 precipitation stations was established across the Kashmir Valley to understand the spatial and meteorological factors controlling precipitation isotopes. Temperature and relative humidity are dominant meteorological factors, whereas altitude, proximity to forest canopy, land use/land cover, windward and leeward sides of the mountains are the main physical factors influencing precipitation isotopes. The study suggests that the Mediterranean Sea and nearby water bodies along with continental recycling are the dominant sources of moisture from October to May, while the Arabian Sea, Bay of Bengal and continental recycling are the main sources of moisture from June to September. However, some precipitation events from October to May collect moisture from the Arabian Sea and some precipitation events from June to September collect moisture from the Mediterranean Sea. The occasional passage of Western Disturbances in summer merging with the Indian Summer Monsoon yields heavy to very heavy precipitation. The study provides a better understanding of complex spatial and meteorological phenomena controlling precipitation isotopes across the Western Himalayas.

Impacts of Aerosol Orographic Precipitation Interaction Associated with Western Disturbances over India Using Satellite Observations

Western disturbances (WDs) develop as extra-tropical low-pressure systems over the Mediterranean and lose their frontal structure as they move eastward toward India. The effect of aerosols on the microphysical characteristics of precipitation and clouds associated with WDs in February 2016 was investigated over the west coast of India and the adjacent Arabian region. This research highly depends on the era interim reanalysis ensemble with back-trajectory simulation. Among the WD event’s pre-mature and mature phases, warm and humid prevailing winds were observed, resulting in substantial aerosol movement. Compared to the ERA-Interim thirty-year mean climatology, the temperature in the simulations was higher during the dissipating phase through to the mature phase. During the dispersing phase, the confluence of easterly and westerly winds was evident in the study region’s eastern and northeastern areas. Over the northern and eastern sections of the country, there was a substantial quantity of high ratios of water-vapor mixing and a significant level of humidity. Precipitation occurred among the northeastern and eastern parts of the research area between the dissipating phases. All the forecasts overstated the precipitation over Odisha, Gujarat, Maharashtra, and West Bengal, whereas the model underestimated it over Kerala, Karnataka, Konkan, and Goa. Between the dissipating phases among the regions where rainfall was observed, the cloud fraction (CF) value of vertical integration was moderate to high. The significant relationship between aerosol optical depth (AOD) and precipitation showed a stimulating effect in the presence of aerosols, which results in enhanced rain during the dissipating phase.

A case study of exceptionally heavy rainfall event over Uttarakhand, India on 18th October, 2021 and its forecasting

The unprecedented rainfall observed over Uttarakhand on 18th October 2021 caused landslides, debris flow and floods over the Kumaun region and adjoining districts of the Garhwal region of Uttarakhand, which resulted in huge damage to life, agriculture, transport, tourism and other sectors. The synoptic and dynamic study of the current event showed the movement of the Low-Pressure Area over central India resulting in the strong southeasterly winds (Atmospheric River) over Indo-Gangetic planes from the Bay of Bengal from 17th to 19th October. The interaction and blocking of the Atmospheric River by the deep trough of eastward-moving Western Disturbance (WD) caused extreme rainfall over Uttarakhand. However, the X-band Doppler Weather Radar and 123 Automatic Weather/raingauge Stations data suggest that the hourly rainfall rate was of light to moderate intensity (10-20 mm/h) over most of the area and at most of the time. The rainfall rate was extremely intense (50-100 m/hour) for around 1-hour duration in 7 stations of Udham Singh Nagar, Champawat, Nainital and Pauri districts. Unlike the June 2013 extremely heavy rainfall event over Uttarakhand which impacted the whole Uttarakhand state, the present event was concentrated over the Kumaun region and the highest ever 24-hours accumulated rainfall was observed on 18th October, 2021 in Kumaon region of Uttarakhand. The expected rainfall as well as the impact of the event over Uttarakhand was forecasted 5 days in advance with good accuracy based on the synoptic analysis and NWP model guidance. The predictability of the IMD-GFS (T-1534) NWP model was found to be up to 10 days for this extreme rainfall event.

The decline in western disturbance activity over Northern India in recent decades

The decline in western disturbance activity over Northern India in recent decades

Western disturbances alter the trend of winter precipitation and its extremes over Northwest Himalayas: Kashmir Himalaya.

The perception of spatio-temporal variability of winter precipitation covering dominant water resources and environment over Kashmir Himalaya is a pre-eminent perspective under current social interests. The main objectives of the study are, firstly, to unriddle the whole (1980-2020) and post-2000 trend in the winter season precipitation (WP), frequency of low-pressure systems (Lp-S), and western disturbances (WDs) to understand the footprints of climate change over the region; secondly, to evaluate the spatio-temporal variability of winter precipitation under the dominance of global teleconnection indices, using both station and reanalysis datasets. Modified Mann-Kendell test and a linear regression model were utilized to extract the trend and significance in WP, Lp-S, and WDs. The results reveal that WP shows an insignificant decreasing trend (1980-2020), with an increasing trend post-2000, while a decreasing trend is seen during post-2000 in the frequency of Lp-S and WDs. The contribution of WP to annual precipitation shows decadal variability with a decreasing trend post-2000. The anatomy of winter extreme precipitation days has shown a decreasing trend (1980-2020), with a robust coupled increasing trend with WP post-2000. The dynamics of ten severe WD-based extreme precipitation events show that a cyclonic circulation and trough connects the Arabian Sea and the Himalayas, bringing additional moisture to the study region and resulting in extreme precipitation. The cogency of global teleconnections on the variability of WP shows that a pattern with positive phase of NAO, ENSO, and a negative phase in Siberian high intensifies the WD-based precipitation. The study discovers its applicability for the regional forecast system in predicting the winters.

Tree-rings stable isotope (δ18O and δ2H) based 368 years long term precipitation reconstruction of South Eastern Kashmir Himalaya

The hydroclimatic variability in Kashmir Himalaya is influenced by the western disturbances and the Indian Summer Monsoon. To investigate long-term hydroclimatic variability, 368 years tree-ring oxygen and hydrogen isotope ratios (δ18O and δ2H) extending from 1648 to 2015 CE were analysed. These isotopic ratios are calculated using five core samples of Himalayan silver fir (Abies pindrow) collected from the south-eastern region of Kashmir valley. The relationship between the long and short periodicity components of δ18O and δ2H suggested that physiological processes had a minimum effect on the tree-ring stable isotopes in Kashmir Himalaya. The δ18O chronology was developed based on the average of five-individual tree-ring δ18O time series covering the time span of 1648–2015 CE. The climate response analysis revealed the strongest and most significant negative correlation between tree ring δ18O and precipitation amount from the previous year's December to current year's August (D2Apre). The reconstructed D2Apre (D2Arec) explains precipitation variability from 1671 to 2015 CE and is supported by historical and other proxy-based hydroclimatic records. The reconstruction has two distinguishing features: first, it is characterized by stable wet conditions during the last phase of Little Ice Age (LIA) i.e., from 1682 to 1841 CE; and second, the southeast Kashmir Himalaya had experienced drier conditions as compared to recent and historical period with intense pluvial events since 1850. The present reconstruction shows, there have been more extreme dry events than extreme wet events since 1921. A tele-connection is observed between D2Arec and Sea Surface Temperature (SST) of the Westerly region.

Western disturbances vs Non-western disturbances days winter precipitation

Western disturbances vs Non-western disturbances days winter precipitation

Evaluation of Satellite Precipitation Products for Estimation of Floods in Data-Scarce Environment

Utilization of satellite precipitation products (SPPs) for reliable flood modeling has become a necessity due to the scarcity of conventional gauging systems. Three high-resolution SPPs, i.e., Integrated Multi-satellite Retrieval for GPM (IMERG), Global Satellite Mapping of Precipitation (GSMaP), and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), data were assessed statistically and hydrologically in the sparsely gauged Chenab River basin of Pakistan. The consistency of rain gauge data was assessed by the double mass curve (DMC). The statistical metrics applied were probability of detection (POD), critical success index (CSI), false alarm ratio (FAR), correlation coefficient (CC), root mean square error (RMSE), and bias (B). The hydrologic evaluation was conducted with calibration and validation scenarios for the monsoon flooding season using the Integrated Flood Analysis System (IFAS) and flow duration curve (FDC). Sensitivity analysis was conducted using ±20% calibrating parameters. The rain gauge data have been found to be consistent with the higher coefficient of determination (R2). The mean skill scores of GSMaP were superior to those of CHIRPS and IMERG. More bias was observed during the monsoon than during western disturbances. The most sensitive parameter was the base flow coefficient (AGD), with a high mean absolute sensitivity index value. During model calibration, good values of performance indicators, i.e., R2, Nash−Sutcliffe efficiency (NSE), and percentage bias (PBIAS), were found for the used SPPs. For validation, GSMaP performed better with comparatively higher values of R2 and NSE and a lower value of PBIAS. The FDC exhibited SPPs’ excellent performance during 20% to 40% exceedance time.

Lightning Development over the Distinct Climate Regions of Uttarakhand, India

Objectives: Lightning activity and its connections with meteorology and aerosol loading over Uttarakhand, with varying topography and climates, is studied using ISS Lightning Imaging Sensor (LIS) aboard international space station (ISS) data during the period 2018–2021. Methods: To understand the variation of lightning activity with meteorology and aerosol loading the correlation of lightning activity with different meteorological parameters such as surface temperature, convective available potential energy (CAPE), aerosol optical depth (AOD), and convective precipitation is studied. Findings: Very poor correlation is observed between lightning flash counts with the meteorological parameters. Annual variation of lightning activity over Uttarakhand shows maximum during the monsoon season (June–September) with a peak during the pre–monsoon season (March–May) month April. The high frequency of western disturbances defined as warm low-pressure systems associated with moisture originated over Mediterranean Sea travelling from west to east across the northern states are responsible for peak lightning activity during pre–monsoon month April and maximum lightning activity in the monsoon season is attributed to the monsoon convection. Novelty: The study made the spatio – temporal variation of lightning over Uttarakhand and also reveals the connection between lightning and different meteorological parameters in different climatic conditions of Uttarakhand which is first defining the importance of large-scale meteorological processes in the development of lightning in Uttarakhand. Keywords: Lightning; Meteorological Parameters; Aerosol optical depth and Convective Available Potential energy (CAPE)

Is survival of Himalayan Cedar (Cedrus deodara) threatened? An evaluation based on predicted scenarios of its growth trend under future climate change

Global warming is likely to become one of the significant drivers of forest losses in the Hindu-Kush Himalaya (HKH) during the 21st century. Better understanding of how forest ecosystem will respond to global warming requires a precise knowledge of site and species specific responses to climate change. We applied dendrochronological technique to quantify and predict future growth trend of Himalayan cedar (Cedrus deodara), a tree of high commercial importance, and explored its spatial growth variability under two different climatic regimes from 17 deodar sites in the HKH. Of the two climate regimes, one is dominated by the monsoon rainfall and the other by the westerly disturbances. Analysis of tree ring width and climate (monthly temperature and precipitation) data reveals that the spring (March–May) temperature and precipitation affect the growth of deodar negatively and positively, respectively. We used Generalized Least Squares (GLS) regression model to forecast future growth of deodar by taking an ensemble of 40 General Circulation Models (GCMs) for emission scenarios RCP 4.5 and RCP 8.5. Predicted growth trends indicate the decline between 34 % and 38 % under RCP 4.5, and between 29 % and 32 % under RCP 8.5 scenarios, for the low and mid latitude sites. In contrast, a moderate increase in growth was observed in high latitude sites under the both climate scenarios. The study shows more drought stress to deodar trees growing in monsoon areas in mid-and low-latitude sites where less snow melt and low precipitation during the spring season are predicted to increase evapotranspiration. In comparison, in the higher latitude sites where there is a high snowfall due to western disturbances, the growth of deodar is predicted to increase. These findings may be used to take suitable migratory steps for the conservation of deodar in the HKH region.

A 1-D model to retrieve the vertical profiles of minor atmospheric constituents for cloud microphysical modeling: I. Formulation and validation

Determining the number concentration of minor constituents in the atmosphere is very important as it determines the whole tropospheric chemistry process. These constituents may act as cloud condensation nuclei (CCN) and ice nuclei (IN), impacting heterogeneous nucleation inside the cloud. However, the estimations of the number concentration of CCN/IN in cloud microphysical parameters are associated with uncertainties. In the present work, a hybrid Monte Carlo Gear solver has been developed to retrieve profiles of CH4, N2O, and SO2. The idealized experiments have been carried out using this solver for retrieving vertical profiles of these constituents over four megacities, viz., Delhi, Mumbai, Chennai, and Kolkata. Community Long-term Infrared Microwave Coupled Atmospheric Product System (CLIMCAPS) dataset around 0800 UTC (2000UTC) has been used for initializing the number concentration of CH4, N2O, and SO2 for daytime (nighttime). The daytime (nighttime) retrieved profiles have been validated using 2000 UTC (next day 0800 UTC) CLIMCAPS products. ERA5 temperature dataset has been used to estimate the kinematic rate of reactions with 1000 perturbations determined using Maximum Likelihood Estimation (MLE). The retrieved profiles and CLIMCAPS products are in very good agreement, as evidenced by the percentage difference between them within the range of 1.3 × 10−5–60.8 % and the coefficient of determination mainly within the range between 81 and 97 %. However, during the passage of tropical cyclone and western disturbance, its value became as low as 27 and 65 % over Chennai and Kolkata, respectively. The enactment of synoptic scale systems such as western disturbances, tropical cyclone Amphan, and easterly waves caused disturbed weather over these megacities—the retrieved profiles during disturbed weather cause large deviations of vertical profiles of N2O. However, the profiles of CH4 and SO2 have less deviation. It is inferred that incorporating this methodology in the dynamical model will be useful to simulate the realistic vertical profiles of the minor constituents in the atmosphere.

Extreme Hydrological Events in January 2022: A Case Study over Telangana and Andhra Pradesh State, India

The study will look at extreme rainfall events in Andhra Pradesh and Telangana, where both the monsoon and post-monsoon seasons significantly contribute to rainfall. The winter season 2022 was highlighted by unusual rainfall in some districts of Andhra Pradesh and Telangana in the 2nd week of January 2022, causing significant damage. In this paper, we identify the observational aspects, main synoptic system, physical process, and thermodynamic features leading to such unusual rainfall during the winter season. According to the study's findings, a hailstorm was recorded over Telangana state on January 13, 2022, heavy rain fell in Telangana due to the most active western disturbance as a cyclonic circulation over Rajasthan and Pakistan; on January 14, 2022, heavy to very heavy rain fell in Vizianagaram (16 cm) due to the convergence of winds from the Arabian Sea and Bay of Bengal at lower tropospheric levels over east and adjoining central India and a trough from north interior Karnataka to north interior Odisha. The diurnal and temporal pattern of the hail storm and heavy rainfall over the Andhra Pradesh and Telangana States shows that late evenings are most conducive for the occurrence of extreme rainfall events due to the accumulation of precipitable water.

Dataset for "Weakening of western disturbances in response to polar sea ice melt in climate model simulations"

Dataset for "Weakening of western disturbances in response to polar sea ice melt in climate model simulations"

Heavy rainfall forecasting for Dehradun capital city during monsoon season 2020

Dehradun city is Uttarakhand's capital and part of the doon valley, which lies between the Himalayas and the Shivaliks. India Meteorological Department has undertaken the Impact Based Forecasting (IBF) of heavy rainfall events for capital/major cities on an experimental basis from the monsoon season 2020. With the improvement in meteorological observation & monitoring network of Uttarakhand and short & medium range Numerical Weather Prediction (NWP) model outputs, it has become possible to provide impact-based forecast at a very small spatial scale with good accuracy. With the help of a dense network of 5 General Packet Radio Service (GPRS) based Automatic Weather Stations (AWS) & 2 Automatic Rain Gauges (ARG) within a 20 Km radius of Dehradun city center, it has become possible to capture & monitor these events. The spatial analysis of these events suggests that the local orographic features rather than large-scale synoptic features played a major role in heavy rainfalls over Dehradun city. The Heidke skill score of 0.63 and 100% probability of detection is found for the capital city forecast of Dehradun. The presence of monsoon trough to the north of its normal position, a cyclonic circulation south of Uttarakhand over Haryana or East-Rajasthan or West Uttar Pradesh and a Western disturbance around 70°E were found to be the synoptic systems favorable for the occurrence of heavy rainfall in Dehradun city. The occasional strong south-westerly wind flow from the Arabian Sea converging over the foothills of the Western Himalayas is also found to be responsible for the heavy downpour.

Future frequency and intensity of Western Disturbance(s)

AbstractWestern Disturbances (WDs) are the primary contributor of winter precipitation over the Western Himalayas (WH). The precipitation falling as snow is essential for Himalayan glaciers accumulation, contributing to Himalayan rivers supporting downstream population of the Indian subcontinent. Climate change has affected the Himalayas, which is noticeable through lesser snowfall and higher melt leading to critical water resource stresses and managements. Available climate models are one of the best available tools to assess precipitation changes over and around the Himalayas. Inherent uncertainties and errors in these numerical models need a certain urge for improvement. Integration of statistical models and methods on top of dynamical models provide better insight and utility in associated processes. Thus, a statistical relationship between various predictors and precipitation over the region is investigated. Available observations from APHRODITE and ERA‐I and model fields from EC‐EARTH‐RCA4 (a CORDEX‐SA member) is used. Multiple linear regression (MLR) model is used to establish statistical estimates using meteorological variables as predictors and precipitation. The correlation between the predictors and precipitation is determined, and a contour depicting maximum correlation is used to estimate regression coefficients. The MLR model is trained during present (1987–2005) and tested during 2006–2007. Higher positive correlations between observations and MLR model are found. This developed MLR model is then implemented for assessing future WDs under RCP8.5 scenario. The intensity and frequency of WDs are calculated during the present and future. Model‐based WDs' intensities slightly deviate from the corresponding observations in present. But the model‐based WDs' frequencies match with the corresponding observations in present. The results indicate that WDs show a decreasing trend in frequency and intensity in the present and near‐future. But in far‐future intensity of WDs shows an increasing trend.

Evaluating Winter Precipitation over the Western Himalayas in a High-Resolution Indian Regional Reanalysis Using Multisource Climate Datasets

Abstract Considerable uncertainties are associated with precipitation characteristics over the western Himalayan region (WHR). These are due to typically small-scale but high-intensity storms caused by the complex topography that are under-resolved by a sparse gauge network. Additionally, both satellite and gauge precipitation measurements remain subject to systematic errors, typically resulting in underestimation over mountainous terrains. Reanalysis datasets provide prospective alternative but are limited by their resolution, which has so far been too coarse to properly resolve orographic precipitation. In this study, we evaluate and cross compare Indian Monsoon Data Assimilation and Analysis (IMDAA), the first high-resolution (12 km) regional reanalysis over India, with various precipitation products during winter season over WHR. We demonstrate IMDAA’s efficiency in representing winter precipitation characteristics at seasonal, diurnal, interannual scales, as well as heavy precipitation associated with western disturbances (WDs). IMDAA shows closer agreement to other reanalyses than to gauge-based and satellite products in error and bias analysis. Although depicting higher magnitudes, its fine resolution allows a much closer insight into localized spatial patterns and the diurnal cycle, a key advantage over other datasets. Mean winter precipitation over WHR shows a significant decreasing trend in IMDAA, despite no significant trend in the frequency of WDs tracked in either IMDAA or ERA5. The study also exhibits the potential use of IMDAA for characterizing winter atmospheric dynamics, both for climatological studies and during WD activity such as localized valley winds. Overall, these findings highlight the potential utility for IMDAA in conducting monitoring and climate change impact assessment studies over the fragile western Himalayan ecosystem.

A Study of Air Pollution Episode Over Delhi National Capital Region, India During October 29, 2016- November 03, 2016

Northern India has an increase in surface air pressure during winter; this causes the atmosphere to clearout, resulting in the production of significant surface inversions. High-pressure zones are also calm andwind direction changes only when a western disturbance enters the area. The wind is substantially strongerwhen there is a low-pressure system. As a result, the pollutants in northern India are regulated by a sequenceof high- and low-pressure weather situations. October 29, 2016, was when the wind direction unexpectedlyshifted from NW to NE and then to N. Wind speeds dropped from 1-6 km/h to near-calm during this time,which indicated the passing of a high-pressure zone, based on the readings of the pressure gauges. Pollutionfrom northern states was brought into the national capital region by a combination of low wind speed andthe wind’s direction. NCR was clogged with high levels of particulate matter during Diwali celebrations,which were exacerbated by heavy traffic, factory production, and firecrackers. The grave situation persisteduntil the wind shifted directions and increased its velocity. On the monostatic acoustic radar installed atREMTech, Shamli, detected the persistence of a substantially raised layer over the region, implying thatvertical mixing of pollutants was severely harmed or limited. As a result of this state, pollutants accumulated,resulting in a severe bout of air pollution. The findings of this study details an incident of such air pollution happened over Delhi NCR.