Climate models have been key for assessing the impact of climate change and simulating
future climate scenarios. The machine learning (ML) community has taken an increased …

Using climate model ensembles containing members that exhibit very high climate
sensitivities to increasing CO2 concentrations can result in biased projections. Various …

Efforts to diagnose the risks of a changing climate often rely on downscaled and bias-
corrected climate information, making it important to understand the uncertainties and …

Scenario planning has emerged as a widely used planning process for resource
management in situations of consequential, irreducible uncertainty. Because it explicitly …

Abstract Changes in patterns of meteorological parameters, like precipitations, temperature,
wind, etc., are causing significant increases in various extreme events. And these extreme …

Regions with high productivity of agriculture, such as the Beqaa Plain, Lebanon, often rely
on groundwater supplies for irrigation demand. Recent reports have indicated that …

Heatwave events over Guangdong have attracted recent attention under changing climate
conditions. It is desired to explore the future changes of heatwave due to its associated …

Taking into account natural and climatic factors in various regions of the Far North and the
Arctic is extremely important for organizing the successful pickup and delivery of various …

Given the increasing use of climate projections and multi-model ensemble weighting for a
diverse array of applications, this project assesses the sensitivities of climate model …

This study aims to improve local-scale climate simulations by developing a Multi-Model
Ensemble using selected General Circulation Models (GCMs). Bayesian Networks were …