Seasonal and inter-annual variations of Arctic cyclones and their linkage with Arctic sea ice and atmospheric teleconnections

The seasonal and inter-annual variations of Arctic cyclone are investigated. An automatic cyclone tracking algorithm developed by University of Reading was applied on the basis of European Center for Medium-range Weather Forecasts（ECMWF） ERA-interim mean sea level pressure field with 6 h interval for 34 a period. The maximum number of the Arctic cyclones is counted in winter, and the minimum is in spring not in summer.About 50% of Arctic cyclones in summer generated from south of 70°N, moving into the Arctic. The number of Arctic cyclones has large inter-annual and seasonal variabilities, but no significant linear trend is detected for the period 1979–2012. The spatial distribution and linear trends of the Arctic cyclones track density show that the cyclone activity extent is the widest in summer with significant increasing trend in CRU（central Russia）subregion, and the largest track density is in winter with decreasing trend in the same subregion. The linear regressions between the cyclone track density and large-scale indices for the same period and pre-period sea ice area indices show that Arctic cyclone activities are closely linked to large-scale atmospheric circulations, such as Arctic Oscillation（AO）, North Atlantic Oscillation（NAO） and Pacific-North American Pattern（PNA）. Moreover,the pre-period sea ice area is significantly associated with the cyclone activities in some regions.

Assessment of the capability of CMIP6 global climate models to simulate Arctic cyclones

Arctic cyclones are one of the important synoptic-scale systems that affect weather variability over the Arctic and can cause intense weather phenomena and disasters.Thus,research on the assessment of the climate characteristics,activity laws,and variability trends of Arctic cyclones using climate models has practical significance.On the basis of the fifth-generation European Center for Medium-Range Weather Forecasts reanalysis(ERA5)data,the spatiotemporal variations of Arctic cyclones during 1981–2014 are analyzed by detecting and tracking cyclones using the Lagrangian method.Then,the simulation results of 14 global climate models from the Coupled Model Intercomparison Project Phase 6(CMIP5)are compared with the results of ERA5.Both the individual models and their ensemble mean can simulate the spatial distribution of the density of cyclone tracks with reasonable capability,the correlation coefficients of track density are approximately 0.6.Furthermore,in boreal winter,the Atlantic zonal negative bias of track density is stronger than that in summer.By contrast,in boreal summer,the negative bias over the Arctic Ocean region is stronger than that in winter.Moreover,the simulations of density-field-related variables(i.e.,cyclolysis,cyclogenesis,track,and lowest center pressure densities)of Arctic cyclones are generally better in winter than in summer,and the models can simulate well that the number of external Arctic cyclones entering the Arctic region from the midlatitudes is more than the internal Arctic cyclones generated inside the Arctic region(60°‒90°N).Furthermore,we show that the capability of models to capture Arctic cyclones with a short lifespan(<3 d)is somewhat poor.Except for the simulation of the minimum pressure of Arctic cyclones,the performance of high-resolution models is better than that of low-resolution models.The simulation of Arctic cyclone radius is poor among all of the variables related to Arctic cyclones,and the observed trends of intensities are not well simulated.In general,the simulation of location-field-related variables(i.e.,intensity,radius,deepening rate,and center pressure)of Arctic cyclones is better in winter than in summer.

A Modified Algorithm for Identifying and Tracking Extratropical Cyclones

In this study, a modified identification and tracking algorithm for extratropical cyclones is developed. This identification scheme is based on triangular-mesh contouring techniques combined with a connected-component labeling method in order to detect the outer boundaries and spatial domain characteristics of individual cyclones. A new tracking method allowing for the identification of cyclone merging and splitting events, as well as short-lived windstorms, is developed to reduce the uncertainty in the tracking of extratropical cyclones. I also show that this method excludes the tracks of open systems that would have been unnecessarily detected using conventional NCP methods. The climatological features of the distribution of cyclone frequencies are substantially larger over the traditional storm track regions compared to those seen in previous studies. Interestingly, a significant increase in the cyclone density in the Arctic occurs during all four seasons（up to 19%in summer） compared to that seen with a latitude-longitude gridded mesh analysis. I develop two new regional intensity indices（depth and vorticity） based on the cyclonic domain to better quantify the cyclonic activity in the Arctic region, and find that the interannual variabilities in these two indices are highly consistent. The results of this analysis may shed light on high-latitude cyclonic behavior studies via the newly detected 2D cyclone atlas derived from this cyclonic-domain-based algorithm.