Fidelity of WRF model in simulating heat wave events over India.

The evaluation of Weather Research and Forecasting (WRF) model has been performed for simulating episodic Heat Wave (HW) events of 2015 and 2016 with varied horizontal resolutions of 27 km for the entire India (d01), 9 km for the North West (NW (d02)) and South East (SE (d03)) domain. Study compares the maximum temperature (Tmax) simulated by WRF model, using six different combination of parameterization schemes, with observations from the India Meteorological Department (IMD) during the HW events. Among the six experiments, Exp2 (i.e., combination of WSM6 microphysics (MP) together with radiation parameterization CAM, Yonsei (PBL), NOAH land surface and Grell-3D convective schemes) is found closest to the observations in reproducing the temperature. The model exhibits an uncertainty of ± 2 °C in maximum temperature (Tmax) for both the regions, suggesting regional temperature is influenced by the location and complex orography. Overall, statistical results reveal that the best performance is achieved with Exp2. Further, to understand the dynamics of rising HW intensity, two case studies of HW days along with influencing parameters like Tmax, RH and prevailing wind distribution have been simulated. Model simulated Tmax during 2015 reaches up to 44 °C in NW and SE part of India. In 2016, HW is more prevailing towards NW, while in SE region Tmax reaches upto 34-38 °C with high RH (60-85%). The comparative research made it abundantly evident that these episodic events are unique in terms of duration and geographical spread which can be used to assess the WRF performance for future projections of HW.

An evaluation of long-term gridded datasets of total columnar ozone retrieved from MERRA-2 and AIRS over the Indian region.

Accurately determining the spatiotemporal variability of ozone on a regional to intercontinental scale is essential for air quality studies. In the present study, a first systematic evaluation and analysis of long-term (2009-2020) gridded datasets (0.5° × 0.625°) of total columnar ozone (TCO) retrieved from Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2TCO) is evaluated for the Indian region. The MERRA-2TCO is first validated with observations (IMDTCO) and then further compared with the Atmospheric Infrared Sounder (AIRSTCO) satellite datasets. For an in-depth comparison and statistical analysis, the dataset has been segregated into seven distinct regions, i.e., Western Himalaya (WH), North East (NE), North Central (NC), North West (NW), West Peninsula India (WPI), East Peninsula India (EPI), and South Peninsula India (SPI). Descriptive statistics (NMSE, FB, R, FA2, and d) reveals a significant correlation of MERRA-2TCO against IMDTCO for Delhi with NMSE (0.0013), FB (- 0.029) and Varanasi NMSE (0.0008), FB (- 0.014). The results of simple linear regression analysis show an increasing TCO trend value of 0.31% and 0.44% per decade in both the cities, respectively. A comparison of MERRA-2TCO with AIRSTCO shows a significant correlation of 0.62-0.87 in different regions of India. Furthermore, in support of Brewer's circulation pattern, an increasing shift of columnar ozone from low (SPI) to high (WH) latitudinal regions is observed. Our results show that the MERRA-2 ozone dataset can be effectively used for ozone air quality studies over India and this analysis may strengthen the need for independent, high-quality, and consistent ozone measurements with small uncertainties.

An analysis of particulate pollution using urban aerosol pollution island intensity over Delhi, India.

The accent of the present study is determination of Urban Aerosol Pollution Island (UAPI) intensity and spatial variability in particulate matter concentration (PM10 and PM2.5) over Delhi. For analysis, the hourly concentration dataset of PM2.5 and PM10 from January 2019 to December 2020 was obtained from ten air quality monitoring stations of Delhi. Additionally, UAPI Index has been calculated to assess the intensity of particulate pollution. The daily, monthly, and annual variations in the trends of PM10, PM2.5, and UAPI index along with related meteorological parameters have been analyzed. Particulate pollution peaked majorly during two seasons, i.e., summer and winter. The highest concentration of PM10 was observed to be 426.77 µg/m3 while that of PM2.5 was observed to be 301.91 µg/m3 in January 2019 for traffic-affected regions. During winters, higher PM2.5 concentration was observed which can be ascribed to increased local emissions and enhanced secondary particle formations. While the increase in PM10 concentrations led to an increment in pollution episodes during summers over most of the sites in Delhi. The UAPI index was found to be declining in 2020 over traffic affected regions (77.92 and 27.22 for 2019 and 2020, respectively) as well as in the background regions (64.91 and 19.80 for 2019 and 2020, respectively) of Delhi. Low traffic intensity and reduced pollutant emission could have been responsible for the reduction of UAPI intensity in the year 2020. The result indicates that lockdown implemented to control the COVID-19 outbreak led to an unexpected decrease in the PM10 pollution over Delhi.

Climatology and model prediction of aerosol optical properties over the Indo-Gangetic Basin in north India.

The current research focuses on the use of different simulation techniques in the future prediction of the crucial aerosol optical properties over the highly polluted Indo-Gangetic Basin in the northern part of India. The time series model was used to make an accurate forecast of aerosol optical depth (AOD) and angstrom exponent (AE), and the statistical variability of both cases was compared in order to evaluate the effectiveness of the model (training and validation). For this, different models were used to simulate the monthly average AOD and AE over Jaipur, Kanpur and Ballia during the period from 2003 to 2018. Further, the study was aimed to construct a comparative model that will be used for time series statistical analysis of MODIS-derived AOD550 and AE412-470. This will provide a more comprehensive information about the levels of AOD and AE that will exist in the future. To test the validity and applicability of the developed models, root-mean-square error (RMSE), mean absolute error (MAE), mean absolute percent error (MAPE), fractional bias (FB), and Pearson coefficient (r) were used to show adequate accuracy in model performance. From the observation, the monthly mean values of AOD and AE were found to be nearly similar at Kanpur and Ballia (0.62 and 1.26) and different at Jaipur (0.25 and 1.14). Jaipur indicates that during the pre-monsoon season, the AOD mean value was found to be highest (0.32 ± 0.15), while Kanpur and Ballia display higher AOD mean values during the winter season (0.72 ± 0.26 and 0.83 ± 0.32, respectively). Among the different methods, the autoregressive integrated moving average (ARIMA) model was found to be the best-suited model for AOD prediction at Ballia based on fitted error (RMSE (0.22), MAE (0.15), MAPE (24.55), FB (0.05)) and Pearson coefficient r (0.83). However, for AE, best prediction was found at Kanpur based on RMSE (0.24), MAE (0.21), MAPE (22.54), FB (-0.09) and Pearson coefficient r (0.82).

Intercomparison of Aerosol Optical Thickness Derived from MODIS and in Situ Ground Datasets over Jaipur, a Semi-arid Zone in India.

The first detailed seasonal validation has been carried out for the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua satellites Level 2.0 Collection Version 5.1 AOT (τMODIS) with Aerosol Robotic Network (AERONET) Level 2.0 AOT (τAERONET) for the years 2009-2012 over semi-arid region Jaipur, northwestern India. The correlation between τMODIS versus τAERONET at 550 nm is determined with different spatial and temporal size windows. The τMODIS overestimates τAERONET within a range of +0.06 ± 0.24 during the pre-monsoon (April-June) season, while it underestimates the τAERONET with -0.04 ± 0.12 and -0.05 ± 0.18 during dry (December-March) and post-monsoon (October-November) seasons, respectively. Correlation without (with) error envelope has been found for pre-monsoon at 0.71 (0.89), post-monsoon at 0.76 (0.94), and dry season at 0.78 (0.95). τMODIS is compared to τAERONET at three more ground AERONET stations in India, i.e., Kanpur, Gual Pahari, and Pune. Furthermore, the performance of MODIS Deep Blue and Aqua AOT550 nm (τDB550 nm and τAqua550 nm) with τAERONET is also evaluated for all considered sites over India along with a U.S. desert site at White Sand, Tularosa Basin, NM. The statistical results reveal that τAqua550 nm performs better over Kanpur and Pune, whereas τDB550 nm performs better over Jaipur, Gual Pahari, and White Sand High Energy Laser Systems Test Facility (HELSTF) (U.S. site).

Dust events and their influence on aerosol optical properties over Jaipur in Northwestern India.

In this study, we systematically document the link between dust episodes and local scale regional aerosol optical properties over Jaipur located in the vicinity of Thar Desert in the northwestern state of Rajasthan. The seasonal variation of AOT(500 nm) (aerosol optical thickness) shows high values (0.51 ± 0.18) during pre-monsoon (dust dominant) season while low values (0.36 ± 0.14) are exhibited during winter. The Ångström wavelength exponent has been found to exhibit low value (<0.25) indicating relative dominance of coarse-mode particles during pre-monsoon season. The AOT increased from 0.36 (Aprilmean) to 0.575 (May-June(mean)). Consequently, volume concentration range increases from April through May-June followed by a sharp decline in July during the first active phase of the monsoon. Significantly high dust storms were observed over Jaipur as indicated by high values of single scattering albedo (SSA(440 nm) = 0.89, SSA(675 nm) = 0.95, SSA870 nm = 0.97, SSA(1,020 nm) = 0.976) than the previously reported values over IGP region sites. The larger SSA values (more scattering aerosol), especially at longer wavelengths, is due to the abundant dust loading, and is attributed to the measurement site's proximity to the Thar Desert. The mean and standard deviation in SSA and asymmetry parameter during pre-monsoon season over Jaipur is 0.938 ± 0.023 and 0.712 ± 0.017 at 675 nm wavelength, respectively. Back-trajectory air mass simulations suggest Thar Desert in northwestern India as the primary source of high aerosols dust loading over Jaipur region as well as contribution by long-range transport from the Arabian Peninsula and Middle East gulf regions, during pre-monsoon season.

Characterizing the long-range transport of black carbon aerosols during Transport and Chemical Evolution over the Pacific (TRACE-P) experiment.

A major aircraft experiment Transport and Chemical Evolution over the Pacific (TRACE-P) mission over the NW Pacific in March-April 2001 was conducted to better understand how outflow from the Asian continent affects the composition of the global atmosphere. In this paper, a global climate model, GEOS-Chem is used to investigate possible black carbon aerosol contributions from TRACE-P region. Our result depicts that absorbing black carbon ("soot") significantly outflow during lifting to the free troposphere through warm conveyor belt and convection associated with this lifting. The GEOS-Chem simulation results show significant transport of black carbon aerosols from Asian regions to the Western Pacific region during the spring season. As estimated by GEOS-Chem simulations, approximately 25% of the black carbon concentrations over the western pacific originate from SE Asia in the spring.

Influence of aerosol spectrum and air pollutants on fog formation in urban environment of megacity Delhi, India.

Urban areas are facing increasing fog frequencies that may result due to increased air pollution emanating from variety of sources. The increased pollution levels may lead to the atmospheric reactions resulting into the formation of secondary pollutants that may also lead to increased aerosol number concentrations (ANC) in the atmosphere. This could cause enhanced water aerosols in the presence of favourable meteorological conditions and high relative humidity. This study deals with the atmospheric pollution and visibility during winter season of megacity Delhi in order to assess the relationship between the two specifically during fog episodes. Thus, this study analyses the levels of air pollutants, aerosol spectrum and meteorological conditions during one week each in the winter season of the years 2004 and 2006 in order to have an improved understanding of their role in fog formation in mega-city Delhi. More than 300 h of measurements which included episodes of dense, thick and moderate fogs of about 25 h, were studied. The measurements cover most of the accumulation mode and greater size spectrum of aerosols. Thus, the analysis is performed for the entire period, specifically, before the fog sets up, during and afterwards. In general, the relatively small variations in number concentration show larger variations in visibility prior and post dense fog formation than during dense fog episodes. Preliminary analysis of monthly averaged RSPM (Respirable Suspended particulate Matter or PM(10)) concentration values for four winter months for a period of 6 years (1996-2001) and visibility did not show a good correlation with total occurrences of fog. However, daily averaged RSPM concentration showed a good correlation with the occurrences of thick fog. Diurnal variation of Sulfur-dioxide and Nitrogen dioxide were found to have inverse relationship with visibility during fog which may be due to formation of secondary pollutants such as sulfate and to a lesser extent nitrates. Amongst, the daily averaged concentrations of all the criteria pollutants, RSPM was found to be best correlated with the fog in comparison to other pollutants.