Effects of Climate change on temperature and precipitation in the Lake Toba region, Indonesia, based on ERA5-land data with quantile mapping bias correction

Abstract

Climate change is a serious problem that can cause global variations in temperature and rainfall patterns. This global variation can affect the water availability of lakes. In this study, trends in temperature and rainfall in the Lake Toba area for 40 years (1981–2020) were analyzed using ERA5-Land data corrected with observation station data utilizing the quantile mapping bias correction method. Corrected ERA5-Land data were used in this study to show spatial patterns and trends. The Mann–Kendall and Sen slope tests were carried out to see the magnitude of the trend. A comparison of temperature and rainfall against their baseline period (1951–1980) was also investigated. The results of this study show that climate change has affected the trend of increasing temperature and rainfall in the Lake Toba area, with an increase in temperature of 0.006 °C per year and an average rainfall of 0.71 mm per year. In general, significant changes in the increase of temperature and rainfall occurred in the last decade, with an increase in temperature of 0.24 °C and rainfall of 22%. The study of the impact of climate change expected to be useful for policymakers in managing water resources in the Lake Toba area.

Drought Atlas of India, 1901–2020

“…We used the distribution (Quantile-Quantile) mapping bias correction method to reduce the bias in these datasets and making them consistent with the observed datasets. The distribution mapping method efficiently reduces bias for mean and interannual variations and also for extreme events 48 . Aadhar & Mishra 27 compared linear scaling 27 , 49 , 50 and distribution mapping 43 , 50 for the bias correction of precipitation and temperature over South Asia and demonstrated that distribution mapping performs better than the linear scaling.…”

“…ERA5-Land reanalysis is also a combined product of weather models and observations from the satellite and in-situ measurements 37 . Compared to the observed datasets, ERA5-Land reanalysis consists of bias in air temperature 48 . Therefore, the bias correction of ERA5-Land temperature (Raw data) was performed using the observed IMD temperature data (Reference data) at the spatial resolution of 0.25°.…”

Cambio climático y variabilidad espacio-temporal (serie 1980-2020) de la temperatura en Tolima, Colombia

“…Posteriormente se realizó un análisis de tendencia de la temperatura en la serie de tiempo continuo desde 1980 hasta 2020, con el método Mann-Kendall (Irwandi, Rosid y Mart 2023;Shigute et al, 2023) y usando el nivel de programación de Python, con la librería pymannkendall (Hussain y Mahmud, 2019). La implementación en Python tomó los datos en archivos csv, con columnas como: fecha, época (seca o lluvia), periodo (Niño o Niña) en cada estación estudiada.…”

Water Resources Evaluation and Sustainability Considering Climate Change and Future Anthropic Demands in the Arequipa Region of Southern Peru

“…However, the complex human development dynamics make it harder to predict future water availability under unpredictable climatic changes [8]. While climate change analysis is usually focused on evaluating precipitation and temperature trends (e.g., [9]), authors around the world are now including human activities when predicting water resources availability (e.g., [10][11][12]).…”