Browsing by Author "S.C. Bhan"

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Effect of unusual dust event on meteorological parameters & aerosol optical and radiative properties
(India Meteorological Department, 2018) V.K. Soni; Sanjay Bist; R. Bhatla; S.C. Bhan; Gajendra Kumar; M. Sateesh; Siddhartha Singh; D.R. Pattanaik
A very unusual dust plume generated from dust-storm activities over the Arabian Peninsula and Southwest Asia affected the north-west region of India between March 20 and 23, 2012, causing significant reductions in air quality and consequently changes in meteorological parameters. Ground based measurements of aerosol optical depth at 500 nm reached 1.015 ± 0.24 and 0.837 ± 0.042 at Jodhpur while Angstrom exponent dropped to-0.030 and-0.065 on March 20 and 21, 2012 respectively. The AOD reached 0.959 in Delhi while Angstrom exponent dropped to 0.006 on March 21, 2012. PM10 concentration peaked at an unusually high value of more than 1800 μgm-3 during dust storm hours of March 20, 2012 at Delhi. Moderate Resolution Imaging Spectrometer (MODIS) retrieved aerosol optical depth also exhibited high values as well along the path of dust storm and dust plume. The intensity of the dust plume was such that it caused significant cooling at the surface. The large reduction in the radiative flux at the surface level had caused a drop in surface temperature by approximately 2-10 °C. Shortwave and longwave Direct Aerosol Radiative Forcing was calculated using SBDART during the dust period. © 2018, India Meteorological Department. All rights reserved.
Regional climate simulation of present day temperature over India using RegCM3: Evaluation and analysis of model performance
(India Meteorological Department, 2017) R.K.S. Maurya; G.P. Singh; U.K. Choudhary; S.C. Bhan
The study has focused on the evaluation of model performance on simulated air temperature at surface and mid atmospheric level over the Indian subcontinent using a Regional Climate Model version 3 (RegCM3). The model is used at 40 km horizontal resolution over the domain approximately 58° E-102.5° E & 5° N-40° N for the period of 1982-2006. The temperatures at lower troposphere (850 hPa) and mid tropospheric level (500 hPa) have been simulated with reanalysis dataset of the National Centre for Environmental Prediction (NCEP). Various statistical measures namely Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE) and Correlation Coefficients (CCs) has been used to test the model results. It has been found that the RegCM3 is able to capture the main features of the observed mean surface climate and also patterns of surface and mid-level air temperatures over India. The model showed that cold biases were -4.29 °C (16.4%) at the lower troposphere, but insignificant at the mid atmospheric level in comparison to the NCEP dataset. The air temperature was well captured at mid tropospheric level. The CC between RegCM3 and NCEP is significantly high (0.82) over India in respect of annual surface air temperature (SAT). The trends of observed SAT were found to be significant increased by 0.32 °C with NCEP and 0.40 °C with RegCM3 over India. The annual SAT of cold biases ranging between -2 °C to -5 °C was found over major parts of India while cold biases of above -5 °C was found in the regions of low elevation or valley regions and below -2 °C in the mountainous regions. The analysis of annual and seasonal trends of maximum air temperature (Tmax),minimum air temperature (Tmin) and average air temperature (Tave) showed that the increasing trend was found over the Indo-Gangetic plain, Western Himalayas (WH) and North East India (NEI) in all seasons while decreasing trend over the North Central India (NCI) in the summer season and over the state of Gujarat in the monsoon season. The RegCM3 showed higher Water Vapour Mixing Ratio (WVMR) at the lower troposphere resulting more cooling at surface rather than at mid tropospheric level. © 2017, India Meteorological Department. All rights reserved.
Rice (Oryza sativa L.) yield gap using the CERES-rice model of climate variability for different agroclimatic zones of India
(Indian Academy of Sciences, 2016) P.K. Singh; K.K. Singh; L.S. Rathore; A.K. Baxla; S.C. Bhan; Akhilesh Gupta; G.B. Gohain; R. Balasubramanian; R.S. Singh; R.K. Mall
The CERES (Crop Estimation through Resource and Environment Synthesis)-rice model incorporated in DSSAT version 4.5 was calibrated for genetic coefficients of rice cultivars by conducting field experiments during the kharif season at Jorhat, Kalyani, Ranchi and Bhagalpur, the results of which were used to estimate the gap in rice yield. The trend of potential yield was found to be positive and with a rate of change of 26, 36.9, 57.6 and 3.7 kg ha-1 year-1 at Jorhat, Kalyani, Ranchi and Bhagalpur districts respectively. Delayed sowing in these districts resulted in a decrease in rice yield to the tune of 35.3, 1.9, 48.6 and 17.1 kg ha-1 day-1 respectively. Finding reveals that DSSAT crop simulation model is an effective tool for decision support system. Estimation of yield gap based on the past crop data and subsequent adjustment of appropriate sowing window may help to obtain the potential yields.
Unprecedented heavy rainfall event over Yamunanagar, India during 14 July 2016: An observational and modelling study
(John Wiley and Sons Ltd, 2021) N. Narasimha Rao; Surender Paul; M.S. Skekhar; G.P. Singh; A.K. Mitra; S.C. Bhan
Extreme rainfall events have posed several serious threats to many populated and urbanized areas in the world including the Indian subcontinent. Therefore, accurate predictions of their intensity and areas of influence are important for flood-prone risk assessments. On 14 July 2016, heavy to exceptionally heavy rainfall occurred in Yamunanagar (30.16° N, 77.29° E), located in the state of Haryana in North India, which led to widespread disruption of communication, electricity, inundation of houses, and so forth. The present paper aims at examining observational, synoptic, thermo-dynamical, and numerical features associated with this devastating rainfall episode. The analysis found that during extreme rainfall episodes, a trough in mid-tropospheric westerlies and a strong low-level atmospheric monsoonal flow seem to have strongly interacted with each other, creating a strong convergence zone near study areas that led to a severe rainstorm. The quasi-stationary supercells were also noticed due to continuous moisture incursions from the Bay of Bengal and orographic uplift over the Himalayas near Yamunanagar. A deep layer of wind shear interacts dynamically with the convergence zone and leads to a potential rainstorm. Thermodynamic indices indicate high instability over the heavy rainfall area. The dynamics of this event were studied in detail by using three-dimensional variational data assimilation within the weather research and forecasting model, configured with triple two-way nesting domains (27, 9, and 3 km). The model results show that the weather research and forecasting model satisfactorily captures the quantitative precipitation (300 mm) in 24 h over the Yamunanagar region as compared with observation (365 mm). © 2021 The Authors. Meteorological Applications published by John Wiley & Sons Ltd on behalf of Royal Meteorological Society.