Tracking Summer Greenland Blocking: the Upstream Pathway Shapes Historical Extremes and Future Change

TL;DR

This study uses a novel Lagrangian approach with the blocktrack tool to analyze Greenland atmospheric blocking, revealing its types, drivers, and future changes under climate scenarios, with implications for understanding extreme weather patterns.

Contribution

Introduces a new Python package 'blocktrack' for tracking Greenland blocking events and analyzes their characteristics and future projections using reanalysis and climate model data.

Findings

Upstream Greenland blocks are linked to increased moisture and temperature anomalies.

Recent increase in Greenland blocking is mainly due to upstream blocks.

Climate models underestimate Greenland blocking variability and future changes.

Abstract

The representation and future evolution of summer Greenland atmospheric blocking is here investigated from a Lagrangian perspective using a novel python package \textit{blocktrack}. By applying the blocktrack algorithm to ERA5 reanalysis and a CMIP6 model ensemble, we identify and track blocking events over Greenland, and obtain their trajectories, intensities, durations and wave-breaking characteristics. Two types of Greenland Blocking (GB) are identified in ERA5 via the Wave Breaking Index, respectively characterized by anticyclonic and cyclonic wave breaking. These correspond to the previously identified upstream and retrograding GBs. Upstream blocks, which originate in Northern Canada, exhibit stronger moisture transport before and during the blocking onset and higher temperature anomalies than retrograding blocks, which follow a east-to-west trajectory and originate in the Northern Atlantic. Our analyses show how the recent observed increase in the frequency of GB, particularly in 2012, is primarily driven by upstream blocks. CMIP6 models generally fail to capture the increase seen in observations and underestimate GB variability. Future projections under the SSP370 scenario show a decline in retrograding blocks but a possible increase in upstream blocks, depending on the detection index used. We discuss possible drivers of these changes, which include jet stream position shifts, increased frequency of high moisture transport events from the equator to the high latitudes, surface temperature increases due to Atlantic Multidecadal Variability and Arctic Amplification. By analyzing block trajectories, this study demonstrates how Lagrangian diagnostics can provide novel insights into the dynamics of blocking events over Greenland.