Nowhere is climate change more obvious than in the Arctic. Estimates show that over the past few decades the region has warmed twice as fast as the global average, a phenomenon known as Arctic Amplification (AA). Although the exact causes for this phenomenon is still being debated, most researchers agree that poleward energy transport is accelerating the warming process.
In the collaborative ERC project Blue-Action, coordinated by the Danish Meteorological Institute and involving 41 partners, including the Netherlands eScience Center, the aim is to improve our ability to describe, model and predict Arctic climate change and its impact on Northern Hemisphere climate, as well as to deliver valuated climate services for societal benefit.
As one of the project partners, the eScience Center is working on improving climate change forecasts in the Arctic by calculating the meridional energy transport (MET) both in the atmosphere and ocean and making these refined calculations available to researchers. Yang Liu, research engineer at the eScience Center and a PhD researcher at Wageningen University & Research, is closely involved in the project and recently published a joint paper on the outcome of reanalysis data sets used to compute energy transport. The paper was published in the journal Earth System Dynamics.
“In order to make use of available observations and advanced numerical models, we created an open source work package in Python, in which we combined six state-of-the-art data sets”, Liu explains. “These comprised three atmosphere reanalysis data sets and three ocean reanalysis data sets and had a high temporal and spatial resolution, making them extremely suitable for the computation of energy transport.”
The aim, says Liu, was to quantify and intercompare the Atmosphere Meridional Energy Transport (AMET) and the Ocean Meridional Energy Transport (OMET) variability between the different reanalysis data sets. “We know from previous and current studies that there is a strong relationship between meridional energy transport and fluctuations in sea ice. Our objective was therefore to compare a number of previous studies and see how their respective data sets compare with each other and correspond to the latest observation and modeling techniques.”
Arctic sensitivity to variations
After collecting the reanalysis data sets, Yang and his fellow research engineers at the eScience Center calculated the AMET and OMET on Cartesius, the Dutch National Supercomputer. What they found was that the data sets generally agree on the average AMET and OMET in the Northern Hemisphere, and OMET is consistent with the observational results achieved over the past twenty years. Nevertheless, the team’s analysis did reveal anomalies at interannual time scales, with the data sets clearly differing from each other both spatially and temporally. “When compared over a longer period, the data sets are inconsistent in their long-term analysis and do not match up with the latest climate models”, says Liu. “What the data sets do clearly show, however, is that the Arctic climate is quite sensitive to seasonal variations in atmospheric and ocean energy transport.”
The research team has now made their work package and the reanalysis products available to the wider scientific community. Liu: “Although the reanalysis data sets are not specifically designed for studies on energy transport, they can still be of much use for energy transport diagnostics. In the coming period, we will continue to refine the work package and explore the role of energy transport in sea ice forecasts. Given the close relation between sea ice variation and energy transports, it is promising to improve the Arctic sea ice forecasts with a better estimation of energy transport, in combination with novel machine learning techniques.”
Liu, Y., Attema, J., Moat, B., and Hazeleger, W.: ‘Synthesis and evaluation of historical meridional heat transport from midlatitudes towards the Arctic’ in Earth System Dynamics, 11, 77–96, https://doi.org/10.5194/esd-11-77-2020, 2020.