Browsing by Author "Usha Devi"

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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.
Methodological application of quantile mapping to generate precipitation data over Northwest Himalaya
(John Wiley and Sons Ltd, 2019) Usha Devi; Manorama S. Shekhar; Gyan P. Singh; Nalamasu N. Rao; Uma S. Bhatt
Continuous high quality data are critical for weather and climate investigations. Numerous data gaps exist particularly over mountainous regions which limits the ability to construct climatologies and perform trend analysis. This study addresses the issue of sparse precipitation data over Northwest Himalaya (NWH) and fills data voids by applying the quantile mapping (QM) method. QM is applied to observed winter precipitation for a period of 25 years (1991–1992 to 2015–2016) to construct a continuous reliable data set. The first 20 years (1991–1992 to 2010–2011) are used for training and the remaining 5 years (2011–2012 to 2015–2016) are used for validation. In total, 10 stations are available for this study and each one is considered serially as a reference to generate daily precipitation values at the other stations. The mean precipitation of NWH region is constructed by considering the mean of all the stations. Standard statistical measures like root mean square errors, standard deviation, skill score and its decompositions are applied to evaluate the generated datasets. Based on statistical analysis, the Kanzalwan station, located in Great Himalaya range, is one of the best performing reference stations for generating precipitation values over NWH. The statistical measures of this station show the highest skill scores, lowest root mean square error and lowest standard mean errors for all winter months except January. This study provides a successful application of QM to generate precipitation data for climate analysis over the complex terrain of the Himalaya region. © 2019 Royal Meteorological Society
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.
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.