Tree species-abundance in forests is a function of geographical area and climate, although it is not clear whether such relationships apply to mass islands. We examined the spatial pattern of tree species in mass islands along the coast of Zhejiang, East China Sea using the Preston model, to identify the relationships between tree communities and climatic conditions. The results show that: (1) the biogeographical distribution of tree species-abundance conformes to Preston’s log-normal pattern, and is in accordance with the findings in both tropical rainforests and estuarine forests; (2) the climatic factors related to tree communities in mass islands are similar to that of the subtropical zone, including the major species of evergreen needle-leaf, broad-leaf and deciduous broad-leaf forests. We conclude that the Preston model can be applied to the trees of mass islands and thus facilitate the systematic ecological researches of vegetation species’ composition in subtropical zone.

Laboratory experiments are performed to explore the response rule of a sandy beach profile under plunging wave on a non-uniform sediment-bed slope. The initial beach slope of combination of 1/10 and 1/20 is exposed to regular waves and cnoidal waves respectively. The free surface elevation, process of wave propagation, wave breaking, uprush and backwash and the change of a cross-shore beach profile are measured and recorded. The beach profile under the regular waves action exhibits two parts: a sandbar profile and a beach berm profile, and only one typical profile transformation under the cnoidal waves action is obtained, which is the beach berm profile. In the laboratory experiments, it is found that the beach states under wave action related to the previous factors. In addition, they are related to the characteristic of breaking waves such as the breaking intensity of the plunging wave. A concept about the characteristic angle of the plunging wave has been put forward through the observation and analysis of the phenomenon of the laboratory experiment. A qualitative analysis about the sediment transport carrying by currents generated from the plunging wave and the state of beach profile under the wave action has been done. The quantitative analysis about the relationship between the characteristic angle and Irribarren number has been done. An available formula of equilibrium states for the sandy beach induced by the plunging wave has been established based on the relationship between Irribarren number and the beach profile. By fitting these experimental results and others' experimental results to three lines, the three fitting coefficients can be calculated in their formula respectively. The recommended empirical formulas can divide three states of a beach morphology profile obviously, which include a depositive beach, an erosive beach and an intermediate beach.

To estimate the sea state bias (SSB) for radar altimeter, two nonparametric models, including a Nadaraya-Watson (NW) kernel estimator and a local linear regression (LLR) estimator, are studied based on the Jason-2 altimeter data. Selecting from different combinations of the Gaussian kernel function, spherical Epanechnikov kernel function, a fixed bandwidth and a local adjustable bandwidth, it is observed that the LLR method with the spherical Epanechnikov kernel function and the local adjustable bandwidth is the optimal nonparametric model for the SSB estimation. The comparisons between the nonparametric and parametric models are conducted and the results show that the nonparametric model performs relatively better at high-latitudes of the Northern Hemisphere. This method has been applied to the HY-2A altimeter as well and the same conclusion can be obtained.

Sea ice in the Arctic has been reducing rapidly in the past half century due to global warming. This study analyzes the variations of sea ice extent in the entire Arctic Ocean and its sub regions. The results indicate that sea ice extent reduction during 1979–2013 is most significant in summer, following by that in autumn, winter and spring. In years with rich sea ice, sea ice extent anomaly with seasonal cycle removed changes with a period of 4–6 years. The year of 2003–2006 is the ice-rich period with diverse regional difference in this century. In years with poor sea ice, sea ice margin retreats further north in the Arctic. Sea ice in the Fram Strait changes in an opposite way to that in the entire Arctic. Sea ice coverage index in melting-freezing period is an critical indicator for sea ice changes, which shows an coincident change in the Arctic and sub regions. Since 2002, Region C2 in north of the Pacific sector contributes most to sea ice changes in the central Aarctic, followed by C1 and C3. Sea ice changes in different regions show three relationships. The correlation coefficient between sea ice coverage index of the Chukchi Sea and that of the East Siberian Sea is high, suggesting good consistency of ice variation. In the Atlantic sector, sea ice changes are coincided with each other between the Kara Sea and the Barents Sea as a result of warm inflow into the Kara Sea from the Barents Sea. Sea ice changes in the central Arctic are affected by surrounding seas.

A slowdown of sea surface height (SSH) rise occurred in the Nordic (GIN) seas around 2004. In this study, SSH satellite data and constructed steric height data for the decades before and after 2004 (i.e., May 1994 to April 2014) were used for comparative analysis. The findings indicate that the rate of slowdown of SSH rises in the GIN seas (3.0 mm/a) far exceeded that of the global mean (0.6 mm/a). In particular, the mean steric height of the GIN seas increased at a rate of 4.5 mm/a and then decreased at a slower pace. This was the main factor responsible for the stagnation of the SSH rises, while the mass factor only increased slightly. The Norwegian Sea particularly experienced the most prominent slowdown in SSH rises, mainly due to decreased warming of the 0–600 m layer. The controlling factors of this decreased warming were cessation in the increase of volume of the Atlantic inflow and stagnation of warming of the inflow. However, variations in air-sea thermal flux were not a major factor. In the recent two decades, mean halosteric components of the GIN seas decreased steadily and remained at a rate of 2 mm/a or more because of increased flow and salinity of the Atlantic inflow during the first decade, and reduction in freshwater inputs from the Arctic Ocean in the second decade.

Large parts of North America, Europe, Siberia, and East Asia have experienced cold snaps and heavy snowfalls for the past few winters, which have been linked to rapid decline of Arctic sea ice. Although the role of reduction in Arctic sea ice in recent cold and snowy winters is still a matter of debate, there is considerable interest in determining whether such an emerging climate feedback will persist into the future in a warming environment. Here we show that increased winter snowfall would be a robust feature throughout the 21st century in the northeastern Europe, central and northern Asia and northern North America as projected by current-day climate model simulations under the medium mitigation scenario. We argue that the increased winter snowfall in these regions during the 21st century is due primarily to the diminishing autumn Arctic sea ice (largely externally forced). Variability of the winter Arctic Oscillation (dominant mode of natural variability in the Northern Hemisphere), in contrast, has little contribution to the increased winter snowfall. This is evident in not only the multi-model ensemble mean, but also each individual model (not model-dependent). Our findings reinforce suggestions that a strong sea ice-snowfall feedback might have emerged, and would be enhanced in coming decades, increasing the chance of heavy snowfall events in northern high-latitude continents.

The Arctic near-surface air temperatures are increasing more than twice as fast as the global average–a feature known as Arctic amplification (AA). A modified AA index is constructed in this paper to emphasize the contrast of warming rate between polar and mid-latitude regions, as well as the spatial and temporal characteristics of AA and their influence on atmospheric circulation over the Northern Hemisphere. Results show that AA has a pronounced annual cycle. The positive or negative phase activities are the strongest in autumn and winter, the weakest in summer. After experiencing a remarkable decadal shift from negative to positive phase in the early global warming hiatus period, the AA has entered into a state of being enlarged continuously, and the decadal regime shift of AA in about 2002 is affected mainly by decadal shift in autumn. In terms of spatial distribution, AA has maximum warming near the surface in almost all seasons except in summer. Poleward of 20°N, AA in autumn has a significant influence on the atmospheric circulation in the following winter. The reason may be that the autumn AA increases the amplitude of planetary waves, slows the wave speeds and weakens upper-level zonal winds through the thermal wind relation, thus influencing surface air temperature in the following winter. The AA correlates to negative phase of the Arctic oscillation (AO) and leads AO by 0–3 months within the period 1979–2002. However, weaker relationship between them is indistinctive after the decadal shift of AA.

The recent decline in the Arctic sea ice has coincided with more cold winters in Eurasia. It has been hypothesized that the Arctic sea ice loss is causing more mid-latitude cold extremes and cold winters, yet there is lack of consensus in modeling studies on the impact of Arctic sea ice loss. Here we conducted modeling experiments with Community Atmosphere Model Version 5 (CAM5) to investigate the sensitivity and linearity of Eurasian winter temperature response to the Atlantic sector and Pacific sector of the Arctic sea ice loss. Our experiments indicate that the Arctic sea ice reduction can significantly affect the atmospheric circulation by strengthening the Siberian High, exciting the stationary Rossby wave train, and weakening the polar jet stream, which in turn induce the cooling in Eurasia. The temperature decreases by more than 1°C in response to the ice loss in the Atlantic sector and the cooling is less and more shifts southward in response to the ice loss in the Pacific sector. More interestingly, sea ice loss in the Atlantic and Pacific sectors together barely induces cold temperatures in Eurasia, suggesting the nonlinearity of the atmospheric response to the Arctic sea ice loss.

An increasing amount of freshwater has been observed to enter the Arctic Ocean from the six largest Eurasian rivers over the past several decades. The increasing trend is projected to continue in the twenty-first century according to Coupled Model Intercomparison Project Phase 5 (CMIP5) coupled models. The present study found that water flux from rivers to the Arctic Ocean at the end of the century will be 1.4 times that in 1950 according to CMIP5 projection results under Representative Concentration Pathway 8.5. The effect of increasing Arctic river runoff on the Atlantic meridional overturning circulation (AMOC) was investigated using an ocean-ice coupled model. Results obtained from two numerical experiments show that 100, 150 and 200 years after the start of an increase in the Arctic river runoff at a rate of 0.22%/a, the AMOC will weaken by 0.6 (3%), 1.2 (7%) and 1.8 (11%) Sv. AMOC weakening is mainly caused by freshwater transported from increasing Arctic river runoff inhibiting the formation of North Atlantic Deep Water (NADW). As the AMOC weakens, the deep seawater age will become older throughout the Atlantic Basin owing to the increasing of Arctic runoff.

Sea ice and the snow pack on top of it were investigated using Chinese National Arctic Research Expedition (CHINARE) buoy data. Two polar hydrometeorological drifters, known as Zeno^® ice stations, were deployed during CHINARE 2003. A new type of high-resolution Snow and Ice Mass Balance Arrays, known as SIMBA buoys, were deployed during CHINARE 2014. Data from those buoys were applied to investigate the thickness of sea ice and snow in the CHINARE domain. A simple approach was applied to estimate the average snow thickness on the basis of Zeno^® temperature data. Snow and ice thicknesses were also derived from vertical temperature profile data based on the SIMBA buoys. A one-dimensional snow and ice thermodynamic model (HIGHTSI) was applied to calculate the snow and ice thickness along the buoy drift trajectories. The model forcing was based on forecasts and analyses of the European Centre for Medium-Range Weather Forecasts (ECMWF). The Zeno^® buoys drifted in a confined area during 2003–2004. The snow thickness modelled applying HIGHTSI was consistent with results based on Zeno^® buoy data. The SIMBA buoys drifted from 81.1°N, 157.4°W to 73.5°N, 134.9°W in 15 months during 2014–2015. The total ice thickness increased from an initial August 2014 value of 1.97 m to a maximum value of 2.45 m before the onset of snow melt in May 2015; the last observation was approximately 1 m in late November 2015. The ice thickness based on HIGHTSI agreed with SIMBA measurements, in particular when the seasonal variation of oceanic heat flux was taken into account, but the modelled snow thickness differed from the observed one. Sea ice thickness derived from SIMBA data was reasonably good in cold conditions, but challenges remain in both snow and ice thickness in summer.