Nansen gjesteforelesning 10.07.2024

Dr. Guokun Dai, Department of Atmospheric and Oceanic Science & Institute of Atmospheric Sciences, Fudan University, China

«Influence of Arctic sea ice concentration on extreme Ural blocking predictability in subseasonal timescales»

The linkage between the Arctic and midlatitudes has received much attention recently due to the rapidly changing climate. Many investigations have been conducted to reveal the relationship between the Arctic sea ice concentration and Eurasian extreme events from the perspective of climatological statistics. Utilizing the Community Atmospheric Model version 4, the influence of Arctic sea ice concentration (SIC) on the predictability of the Ural Blocking (UB) in subseasonal timescale is investigated. Taking the zonal flows as the reference states, the optimal Arctic SIC perturbations that trigger zonal flows into UB events on subseasonal timescale are obtained with the conditional nonlinear optimal perturbation (CNOP) approach. It shows that the Arctic SIC decline in the Greenland, Barents and Okhotsk Seas can trigger zonal flows into UB events on a timescale of four pentads (20 days). After that, the optimal Arctic SIC perturbations that have great influences on subseasonal UB predictions are also obtained with CNOP approach. It is found that SIC increase in the Greenland Sea, Barents Sea, and Okhotsk Sea would weaken the UB intensity while SIC decline in these regions would strengthen it. Further diagnoses show that the physical mechanisms are similar to those triggering UB formation. Moreover, utilizing the observing system simulation experiments, it is shown that targeted observations in the Barents Sea, Greenland Sea, and Okhotsk Sea can remarkably improve the prediction skills of UB in the fourth pentad. Further diagnosis shows that the improvement is related to the well-described westerly winds in the Ural region and its adjacent regions, corresponding to the more skillful predictions of blocking circulations. The above results supply a theoretical base for the design of Arctic SIC observations and more skillful subseasonal predictions for mid-latitude extreme weather.

Når og hvor?

Onsdag, 10.07.24 kl. 10:45 – 11:30.

Copernicus forelesningsrom, 1. etasje, Nansensenteret, Jahnebakken 3, Bergen

Om Dr. Guokun Dai

Dr. Guokun Dai is an associated research scientist in the department of Atmospheric and Oceanic Science & Institute of Atmospheric Sciences at Fudan University in China. He obtained his Ph.D. in meteorology from the Institute of Atmospheric Physics, Chinese Academy of Sciences, and conducted postdoctoral research at Fudan University. His research interests encompass the predictability of extreme Eurasian events, the linkage between the Arctic and Eurasia and the application of machine learning in geosciences.