There are significant discrepancies between observational datasets of Arctic sea ice concentrations covering the last three decades, which result in differences of over 20% in Arctic summer sea ice extent/area and 5%–10% in winter. Previous modeling studies have shown that idealized sea ice anomalies have the potential for making a substantial impact on climate. In this paper, this theory is fu...

There are significant discrepancies between observational datasets of Arctic sea ice concentrations covering the last three decades, which result in differences of over 20% in Arctic summer sea ice extent/area and 5%–10% in winter. Previous modeling studies have shown that idealized sea ice anomalies have the potential for making a substantial impact on climate. In this paper, this theory is fu...

[1] Monthly sea levels from five Arctic Ocean Model Intercomparison Project (AOMIP) models are analyzed and validated against observations in the Arctic Ocean. The AOMIP models are able to simulate variability of sea level reasonably well, but several improvements are needed to reduce model errors. It is suggested that the models will improve if their domains have a minimum depth less than 10 m...

Based on observational data and Asian monsoon intensity datasets from China, the relationships between the East Asian winter monsoon index and winter temperature, the East Asian summer monsoon index and Meiyu precipitation over the middle and lower reaches of the Yangtze River, were analyzed. We found that the monsoon signals were reflected in the temperature and Meiyu precipitation variations....

Climate variability is simply represented by teleconnection patterns such as the Arctic Oscillation (AO), Antarctic Oscillation (AAO), North Atlantic Oscillation (NAO), Pacific–North American pattern (PNA), and Southern Oscillation (SO) with associated indices. Two approaches can be used to predict the indices: forward and backward methods. The forward method is commonly used to predict the ind...

We use an empirical statistical model to demonstrate significant skill in making extended-range forecasts of the monthly-mean Arctic Oscillation (AO). Forecast skill derives from persistent circulation anomalies in the lowermost stratosphere and is greatest during boreal winter. A comparison to the Southern Hemisphere provides evidence that both the time scale and predictability of the AO depen...

We compare the relationship between Arctic Oscillation (AO) and ozone concentration in lower stratosphere over during 1980–1994 (P1) 2007–2019 (P2) January February using reanalysis datasets. The out-of-phase AO is significant P1 P2, but it insignificant P2 P1. variable links are not caused by changes spatial pattern of related to anomalies planetary wave propagation troposphere stratosphere. u...