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.
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
) 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
) 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
, RH and prevailing wind distribution have been simulated. Model simulated T
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
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.
The present study investigates the accelerating factors for extreme flash flood at Chamoli district of Uttarakhand on 7 February 2021. The Sentinel-2A and 2B satellite data have been used to depict ...changes in pre-flood (16th of January) i.e., 5 years of 2016 to 2021 to post-flood (10 February, 2021) situation over the study domain. Vegetation and snow-cover from 2016 to 2021 has been obtained using Normalized Difference Vegetation Index (NDVI) classification over study area. Normalized Difference Water Index (NDWI) is used to extract the pre and post-flood water pixels for flood inundation mapping. The Cartosat-1 digital elevation model (DEM) product is used for drainage pattern and stream order mapping. Correlation between the meteorological parameters such as snowfall, wind speed and wind direction of Nanda Gunti peak during the time of flood with the flood event is analysed. The overall results indicate heavy snowfall (4.22 mm/day) over Nanda Gunti hills followed by high wind speed (23 km/hr.) that might have led to initiation of avalanche/landslide, giving rise to massive flash flood and eroded approximately 0.0263 km
3
volume of landmass along with snow cover. Further, the 5 years NDVI analysis shows decrease in vegetation near Rishiganga and Alaknanda, a higher order river streams, is also crucial factor for flood intensification that caused massive destruction within the study area. The work highlights the importance of mapping of intense events and underline factors to reduce the impact and losses in case of future events.
We have examined the air quality over China, India and demonstrated marked differences in levels of air pollution resulted from the COVID-19 restrictions during December-April, 2019-20 to that of 11 ...years mean of 2009-19. The criteria air quality indicators i.e., nitrogen dioxide (NO_2), sulphur dioxide (SO_2), Aerosol Index (AI) and aerosol optical depth (AOD) data are retrieved from the Ozone Monitoring Instrument (OMI), TROPOspheric Monitoring Instrument (TROPOMI), and MODerate Resolution Imaging Spectroradiometer (MODIS) sensor on the Terra and Aqua satellites, respectively. Over China, during COVID-19 lockdown a significant drop in columnar abundances of tropospheric NO_2 (-37%), SO_2 (-64%) and AOD (-8%) for 2020 in comparison to 11 years mean (2009-19) has been observed. A noticeable difference in NO_2 column burden is seen over SE (-35%), NE (-33%), NW (-13%) and SW (-5%) China. Over the SE and NE China, both NO_2 and SO_2 levels decreased dramatically in 2020 from that of 2009-19, by more than 40% and 65%, respectively, because of both stricter regulations of emissions and less traffic activity due to reduced social and industrial activities during COVID-19 restrictions. In contrast, the curve of monthly mean tropospheric columnar burden of NO_2 and SO_2 over India has shown moderate reduction of 16% and 20%, respectively because lockdown came into effect much later in March 2020. The mean NO_2 and SO_2 over IGP region is found to be 25% higher than whole India's mean concentration due to large scale urban settlement and crop burning events. The statistical t-test analysis results confirm significant (p ＜ 0.05) improvements in AQ during lockdown. The COVID-19 pandemic provided an unprecedented opportunity to investigate such large-scale reduction in emissions of trace gases and aerosols. Therefore, it is important to further strengthen environmental policies to tackle air quality, human health, and climate change in this part of the world.
This study aimed to identify the impact of an annular solar eclipse i.e., 21 June 2020 on the variation of meteorological parameters along with trace gases using statistical analyses. The study site ...is located at Poornima University, Jaipur (26.7796°N, 75.8771°E), Rajasthan, India. The observational analysis indicates a rapid decrease in solar direct radiation (SDR) which varied between 706 and 79 W/m
2
during the eclipse. SDR was reduced to 79 W/m
2
at the maximum peak of the solar eclipse at 11:55 a.m. at the study location. The comparative analysis shows the variation of SDR during the solar eclipse day, the previous day, and the day after the event. A strong dip was observed in SDR during the annular eclipse day concerning before (734.31 W/m
2
) and after (734.375 W/m
2
) eclipse event. Furthermore, the impact of the solar eclipse on temperature (Ts) and Relative Humidity (RH) was analyzed over Jaipur. The statistical analyses demonstrate an apparent decrease in temperature of about 2°C while RH shows a slight increment (3.45%) during the solar eclipse event. The results show an inverse correlation between the solar eclipse and trace gases variations during the eclipse due to the changes in solar radiation, surface temperature, and variation in winds that might affect the photochemical processes.
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 ground-based 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.
The prediction of fog onset remains difficult despite the progress in numerical weather prediction. It is a complex process and requires adequate representation of the local perturbations in weather ...prediction models. It mainly depends upon microphysical and mesoscale processes that act within the boundary layer. This study utilizes a multirule based diagnostic (MRD) approach using postprocessing of the model simulations for fog predictions. The empiricism involved in this approach is mainly to bridge the gap between mesoscale and microscale variables, which are related to mechanism of the fog formation. Fog occurrence is a common phenomenon during winter season over Delhi, India, with the passage of the western disturbances across northwestern part of the country accompanied with significant amount of moisture. This study implements the above cited approach for the prediction of occurrences of fog and its onset time over Delhi. For this purpose, a high resolution weather research and forecasting (WRF) model is used for fog simulations. The study involves depiction of model validation and postprocessing of the model simulations for MRD approach and its subsequent application to fog predictions. Through this approach model identified foggy and nonfoggy days successfully 94% of the time. Further, the onset of fog events is well captured within an accuracy of 30–90 minutes. This study demonstrates that the multirule based postprocessing approach is a useful and highly promising tool in improving the fog predictions.
During recent decades, India experienced more frequent and severe floods due to increasing extreme rainfall events over different Indian River Basins (IRBs). The present study uses Generalized ...Extreme Value distribution, Expert Team on Climate Change and Detection Indices, and Standardized Precipitation Index to examine the trend in extreme rainfall events over the IRBs using long‐term observed high‐resolution gridded rainfall data (1901‐2019) obtained from India Meteorological Department. The analysis depicts a marked shifting trend in extreme rainfall events from northeastern Indian river basins toward the western Indian river basins during the recent decades of 1981‐2019. The spatial variations in the annual maximum rainfall for the 10‐, 30‐, and 100‐year return levels show statistically significant increasing trends over the IRBs. The observed decadal changes of rainfall during wet and dry conditions showed the shifting and increasing (15%–58.74%) pattern in extreme rainfall events during the last decades of the 20th and current twenty first century over the west‐flowing river basins. This research highlights the significant increasing trend in extreme rainfall events, which may pose a grave risk to agriculture, human life, and infrastructure, predominantly on the vulnerable sections of the society.
Key Points
High‐resolution gridded data sets used for the assessment of the rainfall extremes over the Indian River Basins (IRBs)
A western shift in a significantly increasing trend of extreme rainfall events was observed over the western part of the IRBs in the last four decades
West and North‐east flowing river basins were found to be highly flood‐prone regions resulting in vulnerable hazards
The western disturbances (WD) form over the Mediterranean region as extra-tropical low-pressure systems and lose the frontal structure while moving eastward to reach India. These systems bring cold ...waves, snowfalls, hailstorms and rain over north and north-west India during post monsoon and winter months. The first part (Part A) of the present paper investigates the performance of Advanced Research WRF (ARW) model with 8 combinations of cloud microphysics and cumulus convection schemes in simulating 20 WD cases. These 20 cases were simulated using a single-domain WRF model of horizontal resolution 27 km. The combination of Lin et al. cloud microphysics scheme and Betts–Miller–Janjic cumulus convection scheme (mp2cu2) performs better than other combinations in simulating temperature at 2 m height and precipitation. The performance of the combination of Ferrier (new Eta) microphysics scheme and Betts-Miller-Janjic cumulus convection scheme (mp3cu2) is very close to that of mp2cu2 combination. Analysis of box-whisker plot also shows that the combinations mp2cu2 and mp3cu2 perform better than others. In the second part (Part B) 10 cases are simulated using a double-nested WRF model with inner and outer domain resolutions 9 km and 27 km, respectively. Four cases of part B are simulated with (mp2cu2 and mp3cu2) and without (mp2cu0 and mp3cu0) cumulus convection schemes to understand the response of cloud microphysics to explicit convection and also to select the best combination of cloud microphysics and cumulus convection scheme. The combination mp2cu2 has lower RMSE of precipitation than other combinations. Remaining six cases were then simulated with the combination of mp2cu2 using the double-nested model. Spatial distribution of model simulated and TRMM estimated precipitation agree well in most of the cases. The domain-averaged RMSE of model-simulated precipitation with respect to TRMM 3B42 V7 estimated precipitation varies from 2.89 to 4.12 cm for the six WD cases. The box-whisker diagram shows that the model overestimates the maximum rainfall amount in most of the cases but it is consistent in simulating precipitation over the model domain for all the six cases.
The focus of present study is to quantify the radiation budget of aerosols over Jaipur (Northwestern, India) from 2011 to 2015. The Aerosol radiative forcing (ARF) has been determined for shortwave ...spectrum (0.3-3.0 μm) individually for the top of the atmosphere (TOA), bottom of the atmosphere (BOA) and within the atmosphere (ATM) over study region. Santa Barbara DISORT Atmospheric Radiative Transfer model (SBDART) is used to simulate the aerosols radiative effect. The inter-annual monthly average of ARF at TOA during 2011-2015 is found between -11.40 to -5.60 W m^(-2), while the ARF at BOA is found to be between -32.2 to -22.49 W m^(-2). Likewise, the ARF within the atmosphere (ATM) comes between 14.04 to 22.47 W m^(-2) over Jaipur. The SBDART model is run discretely for Dust period (DSP) and non-Dust Period (NDP) during the year 2012 to inspect the change in ARF during extreme events over the Jaipur site. During DSP, the net TOA and BOA forcing are found in the range -20.71 to -16.81 W m^(-2) and -45.15 to -39.6 W m^(-2), respectively, and net ATM forcing varies in the range 22.7 to 24.4 W m^(-2). For the NDP, the corresponding value varies in the range -10.1 to -6.6 W m^(-2) and -23.6 to -22.3 W m^(-2). The net ATM forcing during NDP is between 12.2 to 17.05 W m^(-2). The value of BOA increases more than ~67% during DSP than NDP. The more increase (-ve) in surface forcing represents the cooling of the surface during DSP. The results depict that dust over Jaipur in the vicinity of the Thar Desert is scattering in nature with high value (＞ 0.95) of SSA. The scattering is mostly high during summer and low in winter.
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