A non-stationary bias adjustment method for improving the inter-annual variability and persistence of projected precipitation.

ABSTRACT: Hydrological studies depend heavily on environmental variables, such as precipitation and resulting runoff, which exhibit highly seasonal and intermittent behaviour in semiarid basins. In these basins, the use of traditional methods to adjust biases in time series projections can lead to inaccurate results regarding the impacts of climate change. This study introduces a non-stationary bias adjustment methodology (NS) specifically designed for environmental variables characterized by sporadic events and substantial intensity variability, such as precipitation. The methodology involves establishing a probability threshold to adapt the occurrence of precipitation events and utilizes a quantile mapping method based on a non-stationary theoretical and parametric distribution to adjust biases as

SUBMITTER: Cantalejo M 

PROVIDER: S-EPMC11522466 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature