Browsing by Author "M.S. Shekhar"

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Correction of mesoscale model daily precipitation data over Northwestern Himalaya
(Springer, 2021) Usha Devi; M.S. Shekhar; G.P. Singh
Maximum numerical weather prediction models have their own inherent biases and these biases have high impact on accuracy of weather forecast. Hence, bias correction is an essential part of any study for any model output datasets. The current study uses a weather research and forecasting (WRF) model, simulated daily precipitation of winter season (December to February: DJF) for the period of 2010–2011 to 2016–2017 (7 years) for the bias correction and validated against observed precipitation of Snow and Avalanche Study Establishment (SASE), India. For the first time, three different methods, i.e., empirical quantile mapping (QM), linear scaling (LS), and regression (REG) have been studied for the bias correction over the Northwest Himalaya region. In order to identify the best method out of these three, four statistical measurements, i.e., skill score (SS) and its decompositions, bias in percentage, root mean square errors (RMSE), and percentile values have been examined. Based on the analysis of SS and RMSE, it is worth to note that the QM method is found to be most suitable method for the December and February forecast of WRF model, whereas the LS approach is most suitable for the January forecast. Comparison based on Taylor’s diagram and percentiles via boxplot shows that the quantile mapping approach is most advisable for bias correction to the model simulated precipitation dataset over Northwest Himalaya region. © 2020, Springer-Verlag GmbH Austria, part of Springer Nature.
Forecasting extreme precipitation event over Munsiyari (Uttarakhand) using 3DVAR data assimilation in mesoscale model
(Springer, 2020) N. Narasimha Rao; M.S. Shekhar; G.P. Singh
A localized extreme precipitation event occurred over Munsiyari (Uttarakhand, India) on 2nd July 2018 causing flash floods, landslides and damage to the hydropower project. A preliminary study has been carried out by using Weather Research and Forecasting (WRF) model with three-dimensional variation data assimilation technique (3DVAR) to examine the feasibility of the model to predict the localized phenomena. Sensitivity experiments were carried out with two different microphysics in the model. Results show that P3 1-category plus double moment cloud water microphysics scheme with 3DVAR in WRF simulates the quantity of precipitation closer to the observed precipitation over Munsiyari. The vertical velocity and relative humidity were also simulated well during 3DVAR data assimilation as compared to without data assimilation over study region. © 2019, Indian Academy of Sciences.
Performance of 4D-Var Data Assimilation on Extreme Snowfall Forecasts over the Western Himalaya Using WRF Model
(Korean Meteorological Society, 2021) Narasimha Rao Nalamasu; M.S. Shekhar; Gp Singh
The accurate predictions of extreme precipitation/snowfall events are very helpful in identifying the severe avalanche/landslide prone hazard areas in advance over high mountainous regions. The Weather Research and Forecasting model (WRF) version 3.9 has been used to investigate the performance of Four-Dimensional Variational data assimilation (4D-Var) on Three-Dimensional Variational data assimilation (3D-Var) by considering two extreme snowfall events (23–26 January 2017 and 05–08 February 2019) over the Western Himalaya (WH). The result shows that the 4D-Var performed better than the 3D-Var for both the events by analyzing domain-averaged error and sensitivity parameter analysis. The initial state model variable’s domain-averaged error analysis revealed that 4D-Var has great potential to improve the initial conditions than the 3D-Var from lower to the upper atmosphere. Sensitivity parameter analysis also supports 4D-Var has more sensitive than the 3D-var especially in the lower and upper atmosphere by changing temperature and moisture fields along with winds circulations. From statistical skill scores analysis, 4D-Var performed well to reproduce the extreme snowfall events than the 3D-Var over WH. © 2020, Korean Meteorological Society and Springer Nature B.V.
Statistical Method of Forecasting of Seasonal Precipitation over the Northwest Himalayas: North Atlantic Oscillation as Precursor
(Birkhauser, 2020) Usha Devi; M.S. Shekhar; G.P. Singh; S.K. Dash
Dynamical and Statistical models are operationally used by Snow and Avalanche Study Establishment (SASE) for winter precipitation forecasting over the Northwest Himalayas (NWH). In this paper, a statistical regression model developed for seasonal (December–April) precipitation forecast over Northwest Himalaya is discussed. After carrying out the analysis of various atmospheric parameters that affect the winter precipitation over the NWH two parameters are selected such as North Atlantic Oscillation (NAO) and Outgoing Long wave Radiation (OLR) over specific areas of North Atlantic Ocean for the development of statistical regression model. A set of 27 years (1990–1991 to 2016–2017) of observed precipitation data and parameters (NAO and OLR) are utilized. Out of 27 years of data, first 20 years (1990–1991 to 2009–2010) are used for the development of regression model and remaining 7 years (2010–2011 to 2016–2017) are used for the validation purpose. Precipitation over NWH mainly associated with Western Disturbances (WDs) and the results of the present study reveal that NAO during SON has negative relationship with WDs and also with the winter precipitation over same region. Quantitative validation of the multiple regression model, result shows good Skill Score and RMSE-observations standard deviation ratio (RSR) which is 0.79 and 0.45 respectively and BIAS − 0.92. © 2020, Springer Nature Switzerland AG.
Study of Natural Disaster in Manali Valley (Himachal Pradesh), India on 09 July 2023
(India Meteorological Department, 2024) M.S. Shekhar; Peeyush Gupta; Vartika Sharma; Kritika Nag; Surender Paul; D.R. Saklani; Veluswami Venkatramanan; G.P. Singh; Amreek Singh
Continuous heavy rainfall in July 2023, particularly from the 7th to the 10th, led to devastating flash floods, cloudbursts and landslides in Himachal Pradesh, causing extensive damage to infrastructure and properties and loss of lives. The most severely affected districts were Kullu, Mandi, Sirmaur, Shimla, Solan and nearby areas. The Manali sub-division, located in Himachal Pradesh, spans an altitude range of 1074 to 4017 meters above sea level. The region's climate is shaped by its mountainous terrain, with the Beas Valley's weather influenced by factors like relief, aspect and altitude. The Pir Panjal Range's windward slopes create a barrier to monsoon winds, resulting in heavy rainfall and cloudbursts in the area. The report from the India Meteorological Department (IMD) in Shimla, Himachal Pradesh, on July 12, 2023, highlighted the active monsoon conditions in the state from 7-10 July, exacerbated by a Western Disturbance (WD). This combination led to intense and unprecedented rainfall, causing extensive damage to public and private properties, particularly in hilly regions. The report mentioned that similar disasters have occurred in the past due to heavy rainfall, cloudbursts and landslides, possibly exacerbated by factors like unscientific construction, climate change and increased human activities, including tourism. The report emphasized the need for accurate predictions and proactive planning to mitigate such disasters in the future. © 2024, India Meteorological Department. All rights reserved.
Trends of winter precipitation extremes over Northwest Himalaya
(Taylor and Francis Ltd., 2021) N. Narasimha Rao; Usha Devi; M.S. Shekhar; G.P. Singh
The intensity and frequency of extreme precipitation events are of great concern for water resources over the Indian Himalayas, where climate change is rapidly progressive. The long-term trends of extreme precipitation events have been examined during the winter season (November to April; 1996–2016) using the data of 10 observatories maintained by the Snow and Avalanche Study Establishment (SASE) over the Northwest Himalaya (NWH) region. The extreme events are categorized into seven indices, which are 90th and 95th percentiles, rainy days, and maximum 1-d, 3-d, 5-d and total accumulated precipitation. The analysis shows increasing trends for all seven indices for the peak month of February for all Himalayan ranges and altitudes. The rainy days are significantly increased at a 95% confidence level in the Pir-Panjal Range. The teleconnection study reveals that the negative correlation between the North Atlantic Oscillation and winter precipitation extremes is critical for the inter-monthly precipitation behaviours over the NWH. © 2021 IAHS.
Variability of Diurnal Temperature Range During Winter Over Western Himalaya: Range- and Altitude-Wise Study
(Birkhauser Verlag AG, 2018) M.S. Shekhar; Usha Devi; S.K. Dash; G.P. Singh; Amreek Singh
The current trends in diurnal temperature range, maximum temperature, minimum temperature, mean temperature, and sun shine hours over different ranges and altitudes of Western Himalaya during winter have been studied. Analysis of 25 years of data shows an increasing trend in diurnal temperature range over all the ranges and altitudes of Western Himalaya during winter, thereby confirming regional warming of the region due to present climate change and global warming. Statistical studies show significant increasing trend in maximum temperature over all the ranges and altitudes of Western Himalaya. Minimum temperature shows significant decreasing trend over Pir Panjal and Shamshawari range and significant increasing trend over higher altitude of Western Himalaya. Similarly, sunshine hours show significant decreasing trend over Karakoram range. There exists strong positive correlation between diurnal temperature range and maximum temperature for all the ranges and altitudes of Western Himalaya. Strong negative correlation exists between diurnal temperature range and minimum temperature over Shamshawari and Great Himalaya range and lower altitude of Western Himalaya. Sunshine hours show strong positive correlation with diurnal temperature range over Pir Panjal and Great Himalaya range and lower and higher altitudes. © 2018, Springer International Publishing AG, part of Springer Nature.