Swagata Payra - Academia.edu (original) (raw)

Papers by Swagata Payra

Scientific reports, Feb 1, 2024

The evaluation of Weather Research and Forecasting (WRF) model has been performed for simulating ... more 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 (T max) 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 (T max) 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 T max , RH and prevailing wind distribution have been simulated. Model simulated T max 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 T max 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. Weather and climate extremes have become a widely recognized area, it requires further development in climate research field. In recent time, extreme temperature events such as HWs and hot days have become more frequent over the majority of global land areas 1 and their impact on ecosystem and society are significant. Numerous studies have reported regional changes in extreme heat events 2-4. Understanding these regional characteristics of extreme temperature is crucial for developing effective adaptation and mitigation strategies. Manifestation of regional cooling/warming in relation to daytime and night time temperature, as they are linked to humidity, cloudiness, soil moisture, and atmospheric circulation pattern have been studied 5. Further research is necessary to improve our understanding of underlying mechanism driving these events and their regional variations. The development of more advanced modeling techniques and improved observational data can aid in this endeavour. Projection of HWs depends on the capability of regional and global model to exemplify the appropriate land surface and atmospheric processes 6. Therefore, understanding the nature and feedback-driving mechanism i.e., soil moisture/snow or circulation pattern of extreme heat events needed a high-resolution model simulation. The regional climate model (RCM) helps to understand the temperature distribution and its variability or even the climatic events, especially extreme heat and cold wave, 7,8 were among the first to use regional climate models (RCMs) to study the climate extremes. Over the past year, the numerical models have improved substantially to represent microphysics, large-scale advection, vertical mixing, and convection which govern extreme events over a region and time. Though there exist limited number of model studies that can resolve mesoscale processes substantially 9,10 , still there are areas of uncertainties. These uncertainties and errors in RCM may arise due to inadequacies in different physical parameterization schemes including microphysics, convection, radiation, land surface and planetary boundary layer 11-14. Effectiveness of the WRF model, along with its different radiation and urban parameterization schemes, when applied at a 0.5 km resolution for forecasting heatwaves in Odisha have been studied 15 .

Frontiers in Environmental Science, Jun 6, 2023

In the present study, the first systematic performance evaluation of aerosol optical depth (AOD) ... more In the present study, the first systematic performance evaluation of aerosol optical depth (AOD) products retrieved using two satellite sensors i.e., Visible Infrared Imaging Radiometer Suite (VIIRS) and Aqua-Moderate-Resolution Imaging Spectroradiometer (MODIS) is carried out over India. We have used groundbased AOD from AERONET at 550 nm wavelength for inter-comparison with MODIS Aqua version C6.1 (C061) Deep Blue (DB) aerosol product and VIIRS/SNPP collection version 1.1 (V1.1) DB aerosol product over the time span of 7-year (2014-2020) observation periods. For validation, the average value of satellite pixels falling within the box of 50 Km x 50 Km keeping the AERONET station at the center is retrieved. The average daily data from the AERONET sun photometer (2014-2019) were obtained within ±15 min of satellite overpass time. Statistical parameters like correlation coefficient (R), RMSE, MAE, and RMB were calculated. The uncertainty of satellite AOD is evaluated using an envelope of Expected Error (EE = ±0.05 + 0.15 AOD for land). Statistical analysis shows that the MODIS AOD product outperforms VIIRS-retrieved AOD. The AOD retrieved from both sensors yields a high correlation (0.86-Jaipur, 0.79-Kanpur, 0.84-Gandhi College, and 0.74-Pune for MODIS and 0.75-Jaipur, 0.77-Kanpur, 0.49-Gandhi College, and 0.86-Pune for VIIRS) and low MAE (0.12-Jaipur, 0.20-Kanpur, 0.15-Gandhi College, and 0.09-Pune for MODIS and 0.13-Jaipur, 0.13-Kanpur, 0.26-Gandhi College, and 0.10-Pune for VIIRS). Other statistical measures such as RMSE, RMB, and P also suggest similar performance. More than 66% of the total data fall within the range of EE for both the satellite products at each station. Spatial comparison exhibits the same AOD pattern seasonally as well as annually having a minimum bias from −0.3 to +0.3 between MODIS and VIIRS. Slight underestimation and overestimation are observed in all the stations by MODIS, whereas VIIRS continuously underestimates AOD with increase in optical depth, suggesting improvements in the aerosol model and surface reflection in retrieval. Overall, the comparison of ground AERONET AOD reveals better accuracy of MODIS AOD with that of VIIRS satellite datasets over India.

Environmental Monitoring and Assessment, Oct 13, 2022

of PM 10 was observed to be 426.77 µg/m 3 while that of PM 2.5 was observed to be 301.91 µg/m 3 i... more of PM 10 was observed to be 426.77 µg/m 3 while that of PM 2.5 was observed to be 301.91 µg/m 3 in January 2019 for traffic-affected regions. During winters, higher PM 2.5 concentration was observed which can be ascribed to increased local emissions and enhanced secondary particle formations. While the increase in PM 10 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 PM 10 pollution over Delhi.

Environmental Science and Pollution Research, Jan 20, 2023

urban climate, Jul 1, 2022

AGU Fall Meeting Abstracts, Dec 1, 2020

International journal of engineering research and technology, Apr 24, 2018

Model resolution plays an important role in numerical modeling. A coarse model resolution outputs... more Model resolution plays an important role in numerical modeling. A coarse model resolution outputs (i.e. temperature, relative humidity, wind direction etc.) may differ a large from real-time observations. In this paper, a performance evaluation study using Weather Research and Forecasting (WRF) model has been carried out over Jaipur (26.9 N, 75.8 E), a semi arid region in India. The study focus is to determine efficiency of the model over a chosen grid domain centered on Jaipur region using different spatial model resolutions. The model was run using the best physical parameterization scheme with different spatial model resolutions. The performance of the model varies with the different combination of the model resolution. The model simulations show encouraging and better statistical results for 24 km model resolution considering the balance between total computation time and model performance on the same computer configuration.

Advances in Space Research, Aug 1, 2022

Natural Hazards, Feb 12, 2020

Lightning, a climate-related highly localized natural phenomenon, claims lives and damage propert... more Lightning, a climate-related highly localized natural phenomenon, claims lives and damage properties. These losses could only be reduced by the identification of active seasons and regions of lightning. The present study identifies and correlates the lightning-prone regions with the number of casualties reported over India at the state/union territory level. The seasonal and monthly composite satellite data of Lightning Imaging Sensor for the duration of 16 years (1998-2013) have been analyzed in this study for the identification of the major lightning-prone seasons and regions over India. The casualties due to lightning have also been estimated using data from Accidental Deaths and Suicides in India, National Crime Record Bureau report of India. The spatial distribution analysis reveals that lightning occurs mostly in hilly regions over India throughout the year (26 flash/sq. km/yr) and, however, causes lesser casualties because of the sparse population over the hilly terrain. The seasonal analysis reveals the most lightning phenomena occur during the pre-monsoon period (40-45 flash/sq. km/yr) over the northeast region of India. During the winter period, the lightning dominates over the northern parts of India such as Jammu and Kashmir. The state-wise casualties' study reveals that maximum casualties are reported in Madhya Pradesh (313 deaths), Maharashtra (281 deaths) and Orissa (255 deaths) on an average per annum. The favorable climatic conditions, such as availability of moisture content, unstable atmosphere and strong convection, cause severe cases of lightning over the regions of Orissa and Maharashtra.

Atmospheric Pollution Research, Sep 1, 2018

The present study estimates ground-level Respirable Particulate Matter (RSPM) by the combined use... more The present study estimates ground-level Respirable Particulate Matter (RSPM) by the combined use of satellite remote sensing Aerosol Optical Depth (AOD) at 550 nm (AOD MODIS or MODIS AOD) and ground-based meteorological measurements from April-2010 to March-2014 over Jaipur, semi-arid region in Northwestern , India. The satellite MODIS Level 2.0 AOD is used in developing multi-regression statistical models to estimate RSPM values over the study area. The relationship between particulate matter (PM) and AOD relationship depends on size distribution, particle composition and vertical profile of aerosols. Thus, for optimal representation of MODIS AOD, the factors like Height of Planetary Boundary Layer (HPBL) and meteorological parameters has been considered in all regression models in the present study as surrogates. The performance of regression models is analyzed on the basis of descriptive statistical measures i.e. Normalised Mean Square Error (NMSE), Correlation (R), Factor of two observations (FA2), and Fractional Bias (FB). The nonlinear multi-regression model (MODEL V) performed better than other models for our study period and region on the basis of statistical analysis (R = 0.80, NMSE = 0.01, FB = 0.0, FA2 = 100). The coefficients obtained from MODEL V were again used over Jodhpur and found to perform better than other models. The study is further extended to find out the Air Quality Index (AQI) category over Jaipur. The average RSPM obtained from Rajasthan Pollution Control Board (RPCB) observations and those of model estimated values come under the "Moderately Polluted" category as per Indian air quality standards.

Environmental Monitoring and Assessment, Sep 26, 2022

Journal of Earth System Science

The current study discourses the impact of variation in PM 2.5 concentration on the ambient air q... more The current study discourses the impact of variation in PM 2.5 concentration on the ambient air quality of Delhi. The 24-hourly PM 2.5 concentration dataset was obtained from air quality measurement site (Anand Vihar) of Delhi Pollution Control Committee (DPCC) for the duration of April 2015 to December 2018. The annual and seasonal variability in the trend of ambient PM 2.5 along with cumulative impact of meteorological parameters have been analyzed. The overall percentage increase in annual PM 2.5 concentration, compared to National Ambient Air Quality Standards (NAAQS) guidelines, is observed to be 286.09%. The maximum concentration of Bne particulate matter was recorded to be 788.6 lg/m 3 during post-monsoon season and it was found to be associated with lower ambient temperature of 21.34°C and wind speed of 0.33 m/sec. Further, PM 2.5 concentration was found to be correlated with CO (R = 0.6515) and NH 3 (R = 0.6396) indicating similar sources of emission. Further, backward trajectory analysis revealed contribution in PM 2.5 concentration from the states of Punjab and Haryana. The results indicated that particulate pollution is likely to occur in urban atmospheric environments with low temperatures and low wind speeds.

Meteorology and Atmospheric Physics

This study seeks to understand and quantify the changes in tropospheric ozone (O 3) in lower trop... more This study seeks to understand and quantify the changes in tropospheric ozone (O 3) in lower troposphere (LT), middle troposphere (MT) and upper middle troposphere (UMT) over the Indo-Gangetic Plains (IGPs), India during the COVID-19 lockdown 2020 with that of pre-lockdown 2019. The gridded datasets of ozone from the European Centre for Mediumrange Weather Forecasts (ECMWF) reanalysis product, ERA5 in combination with statistical interpolated (IDWs) surface NO 2 observations, present a consistent picture and indicate a significant tropospheric ozone enhancement over IGP during COVID-19 lockdown restrictions in May 2020. The Paper also examines the influencing role of meteorological parameters on increasing ozone concentration. Over LT, an increase in O 3 concentration (23%) is observed and in MT to UMT an enhancement of about 9-18% in O 3 concentration have been seen during May 2020 with respect to May 2019. An investigation on causes of increasing ozone concentration (35-85 ppbv) from MT to UMT during May 2020 reveals that there was significant rise (by 1-6%) in low cloud cover (LCC). Notably, higher LCC increases the backscattering of upward solar radiation from the top of the atmosphere. A positive difference of 5-25 W/m 2 in upward solar radiation (USR) is observed across the entire study region. The result suggests that higher LCC significantly contributed to the enhanced USR. Thereby, resulting in higher photolysis rate that lead to an increase in mid tropospheric ozone concentration during May 2020. The results highlight the importance of LCC as an important pathway in ozone formation and aid in scientific understanding of it.

Environmental Monitoring and Assessment