Benchmark decadal forecast skill for terrestrial water storage estimated by an elasticity framework

Area of Science:

• Hydrology and Climate Science
• Earth System Science
• Water Resource Management

Background:

• Reliable decadal prediction of terrestrial water storage (TWS) is crucial for managing freshwater resources and infrastructure.
• The dependency of TWS forecast skill on initial hydrological conditions and decadal climate forecast accuracy remains unclear.
• A baseline skill for decadal TWS prediction has not been established.

Purpose of the Study:

• To establish a benchmark decadal forecast skill for TWS over global major river basins.
• To investigate the influence of initial hydrological conditions and decadal climate forecasts on TWS prediction skill.
• To assess the potential for improving decadal TWS forecasts using dynamical climate prediction.

Main Methods:

• Utilized decadal climate hindcasts and performed hydrological ensemble simulations.
• Employed an elasticity framework to analyze the varying skill of initial conditions and climate forecasts.
• Estimated a benchmark decadal forecast skill for TWS across global river basins.

Main Results:

• Initial condition skill elasticity dominates over climate forecast skill elasticity at short leads (1-4 years) in many basins.
• The established benchmark TWS skill significantly exceeds initial conditions-based forecast skill in 25% (1-4 years lead) and 31% (3-6 years lead) of basins.
• Incorporating climate prediction substantially enhances TWS prediction skill in over half of the river basins at longer leads, particularly in mid- and high-latitudes.

Conclusions:

• Decadal TWS forecasts can be improved by integrating dynamical climate prediction information.
• The newly established benchmark skill is necessary for verifying the success of future decadal hydrological forecasts.
• Understanding the interplay between initial conditions and climate forecasts is key to advancing decadal water resource prediction.