Examining Hydroclimate Extremes Over the Columbia River Basin in a 50km Global Climate Model

Rivers have long provided resources as cultural, economic and ecological agents in society. As a result, people have congregated along river banks and in river valleys throughout history, from the earliest settlements to contemporary metropoles. The close proximity of civilization and rivers, however, poses a serious threat when extreme flooding occurs. Understanding how climate change will affect the flow of rivers in the future is imperative for risk mitigation and infrastructural planning. GFDL’s Seamless System for Prediction and Earth System Research (SPEAR) model employs LM4.0, a 50km land model, which contains a global river and lake network. We use the Columbia River as a case study in the identification and explanation of biases in the SPEAR river system. When comparing annual cycles for observational and model river discharge, we found that the model discharge peak occurs one month earlier and about two times greater in magnitude than the observational data. Excess precipitation in the Pacific Northwest (PNW) region contributes to the magnitude bias, while the timing bias is likely due to model percolation transporting water from mountainous regions to the river too quickly. We test this hydroclimate variability in a short 25 km model run to explore the role of increased resolution and topographic fidelity in runoff magnitude and timing. To best inform stakeholders of the future conditions of the Columbia River flow we explore the effects of climate change on precipitation, a main driver of extreme flooding in the Columbia River Basin.