Improving medium-range streamflow forecasts over South Korea with a dual-encoder transformer model.

Accurate and reliable hydrological forecasts play a pivotal role in ensuring water security, facilitating flood preparedness, and supporting agriculture activities. This study investigates the potential of hydrological forecasting in South Korea, focusing on medium-range lead times ranging from 1 to 10 days. The methodology involves leveraging a Transformer neural network, a model entirely based on attention mechanisms.

Interannual variability of heat waves over the Korean Peninsula based on integrated approach.

Heat waves can provide detrimental impacts on human society and the environmental system, and thus have received substantial attention in scientific research. Since heat waves are relevant to a wide range of stakeholders, definitions for heat wave events vary in terms of threshold values, durations, and utilized variables. While there is a value in this diversity of perspectives, the various definitions often complicate the assessment of heat wave risk, thereby underscoring the improved utility of a unified definition.