Abstract Analysis of high‐resolution data offers greater opportunity to understand the nature
of data variability, behaviours, trends and to detect small changes. Climate studies often …

Time series data is of great value in data mining and analysis, but it often comes with the
problem of data partly missing in many fields. So it is necessary to impute missing values …

This study evaluated the performance of 07 gridded datasets viz. Asian Precipitation Highly-
resolved Observational Data Integration towards Evaluation of Water Resources …

The dry spells and rainfall deficit within crop season, play vital role in determining
productivity of rainfed crops. Dry Spell Index (DSI) was formulated to quantify cumulative …

This study discusses the observed long-term (1991–2015) and short-term (1991–2000 and
2001–2015) trends in winter temperature and precipitation over Northwestern Himalaya …

Meteorological data from ground stations suffer from temporal discontinuities caused by
missing values and short measurement periods. Gap-filling and reconstruction techniques …

The data driven time series forecasting is a key concern for the digital modeling and health
management of energy equipment. However, due to various issues, eg, sensor failures in …

Station-based serially complete datasets (SCDs) of precipitation and temperature
observations are important for hydrometeorological studies. Motivated by the lack of serially …

This study aims to assess the glaciers change status in Shyok basin, East Karakoram in
terms of area and mass balance, and to ascertain if glaciers in this part of Karakoram also …

The results of metrological, hydrological, and environmental data analyses are mainly
dependent on the reliable estimation of missing data. In this study, 21 classical methods …