Sea Ice Anomalies Research Articles

Seasonal Prediction of Arctic Summer Sea Ice Concentration from a Partial Least Squares Regression Model

The past decade has witnessed a rapid decline in the Arctic sea ice and therefore has raised a rising demand for sea ice forecasts. In this study, based on an analysis of long-term Arctic summer sea ice concentration (SIC) and global sea surface temperature (SST) datasets, a physical–empirical (PE) partial least squares regression (PLSR) model is presented in order to predict the summer SIC variability around the key areas of the Arctic shipping route. First, the main SST modes closely associated with sea ice anomalies are found by the PLSR method. Then, a prediction model is reasonably established on the basis of these PLSR modes. We investigate the performance of the PE PLSR model by examining its reproducibility of the seasonal SIC variability. Results show that the proposed model turns out promising prediction reliability and accuracy for Arctic summer SIC change, thus providing a reference for the further study of Arctic SIC variability and global climate change.

Eurasian cooling in response to Arctic sea-ice loss is not proved by maximum covariance analysis

The extent to which the ongoing decline in Arctic sea ice affects mid-latitude climate has received great attention and polarised opinions. The basic issue is whether the inter-annual variability in Arctic sea ice is the cause of, or the response to, variability in mid-latitude atmospheric circulation. Mori et al. (M19) claims to have reconciled previous conflicting studies by showing that a consistent mid-latitude climate response to inter-annual sea-ice anomalies can be identified between the ERA-Interim reanalysis, taken as observations, and an ensemble of atmosphere-only (AMIP) climate model simulations. Here we demonstrate that such a conclusion cannot be drawn, due to issues with the interpretation of the maximum covariance analysis performed. After applying the M19 approach to the output from a simple statistical model, we conclude that a predominant atmospheric forcing of the sea-ice variability, rather than the converse, is a more plausible explanation of the results presented in M19.

Causes and impacts of sea ice variability in the sea of Okhotsk using CESM-LE

This study provides a holistic view of the coupled ocean-atmosphere-sea ice processes responsible for generating interannual variability in sea ice coverage in the Sea of Okhotsk as well as the atmospheric response to this variability. Simulations from the Community Earth System Model Large Ensemble project are analyzed, providing the ability to elucidate the time evolution of these relationships through weekly lead-lag composite analysis, while maintaining a large number of samples to provide robust conclusions. We find that thermodynamic processes involving anomalous ocean-atmosphere heat fluxes affect the timing of initial sea ice growth in the Sea of Okhotsk as early as November. Low-level wind anomalies in the winter affect the extent to which sea ice fully develops, both through advection of the sea ice itself and through changes in the transport of air masses over the Sea of Okhotsk. In this study, the results synthesize and support a diverse set of mechanisms identified in previous observational studies to be responsible for anomalous sea ice conditions, but in a coupled global climate model framework with a large sample size. We also find evidence that anomalous ocean-atmosphere heat fluxes in the winter can trigger an atmospheric response comprised of a local negative sea-level pressure anomaly and Rossby wave that extends over North America. The sign of the turbulent heat fluxes relative to the sea ice anomalies confirm that this is indeed a lagged response of the atmosphere forced by sea ice anomalies. This validates the Rossby wave train response identified in more idealized model simulations with prescribed sea ice and sea surface temperature by demonstrating that this process also occurs in a more realistic coupled model framework.

Global Drivers on Southern Ocean Ecosystems: Changing Physical Environments and Anthropogenic Pressures in an Earth System

The manuscript assesses the current and expected future global drivers of Southern Ocean (SO) ecosystems. Atmospheric ozone depletion over the Antarctic since the 1970s, has been a key driver, resulting in springtime cooling of the stratosphere and intensification of the polar vortex, increasing the frequency of positive phases of the Southern Annular Mode (SAM). This increases warm air-flow over the East Pacific sector (Western Antarctic Peninsula) and cold air flow over the West Pacific sector. SAM as well as El Niño Southern Oscillation events also affect the Amundsen Sea Low leading to either positive or negative sea ice anomalies in the west and east Pacific sectors, respectively. The strengthening of westerly winds is also linked to shoaling of deep warmer water onto the continental shelves, particularly in the East Pacific and Atlantic sectors. Air and ocean warming has led to changes in the cryosphere, with glacial and ice sheet melting in both sectors, opening up new ice free areas to biological productivity, but increasing seafloor disturbance by icebergs. The increased melting is correlated with a salinity decrease particularly in the surface 100 m. Such processes could increase the availability of iron, which is currently limiting primary production over much of the SO. Increasing CO2is one of the most important SO anthropogenic drivers and is likely to affect marine ecosystems in the coming decades. While levels of many pollutants are lower than elsewhere, persistent organic pollutants (POPs) and plastics have been detected in the SO, with concentrations likely enhanced by migratory species. With increased marine traffic and weakening of ocean barriers the risk of the establishment of non-indigenous species is increased. The continued recovery of the ozone hole creates uncertainty over the reversal in sea ice trends, especially in the light of the abrupt transition from record high to record low Antarctic sea ice extent since spring 2016. The current rate of change in physical and anthropogenic drivers is certain to impact the Marine Ecosystem Assessment of the Southern Ocean (MEASO) region in the near future and will have a wide range of impacts across the marine ecosystem.

Autumn Arctic Pacific Sea Ice Dipole as a Source of Predictability for Subsequent Spring Barents Sea Ice Condition

AbstractThis study uses observational and reanalysis datasets in 1980–2016 to show a close connection between a boreal autumn sea ice dipole in the Arctic Pacific sector and sea ice anomalies in the Barents Sea (BS) during the following spring. The September–October Arctic Pacific sea ice dipole variations are highly correlated with the subsequent April–May BS sea ice variations (r = 0.71). The strong connection between the regional sea ice variabilities across the Arctic uncovers a new source of predictability for spring BS sea ice prediction at 7-month lead time. A cross-validated linear regression prediction model using the Arctic Pacific sea ice dipole with 7-month lead time is demonstrated to have significant prediction skills with 0.54–0.85 anomaly correlation coefficients. The autumn sea ice dipole, manifested as sea ice retreat in the Beaufort and Chukchi Seas and expansion in the East Siberian and Laptev Seas, is primarily forced by preceding atmospheric shortwave anomalies from late spring to early autumn. The spring BS sea ice increases are mostly driven by an ocean-to-sea ice heat flux reduction in preceding months, associated with reduced horizontal ocean heat transport into the BS. The dynamical linkage between the two regional sea ice anomalies is suggested to involve positive stratospheric polar cap anomalies during autumn and winter, with its center slowly moving toward Greenland. The migration of the stratospheric anomalies is followed in midwinter by a negative North Atlantic Oscillation–like pattern in the troposphere, leading to reduced ocean heat transport into the BS and sea ice extent increase.

A new approach to classification of 40 years of Antarctic sea ice concentration data

AbstractIn this paper, we present a characterization of Antarctic sea ice based on the classification of annual sea ice concentration (SIC) data from 1979 to 2018. A clustering algorithm was applied to provide a climatological description of significant annual cycles of SIC and their spatial distribution around the Southern Ocean. Based on these classification results, we investigate the variability of SIC cycles on decadal and inter‐annual time scales. First, we discuss significant spatial shifts of SIC cycles during 1979–1998 and 1999–2018. In the Weddell Sea and in large parts of the Ross Sea, we observed higher SIC during the summer season, and an extension of sea ice cover in winter compared to the long‐term average. Second, we introduce the Climatological Sea Ice Anomaly Index (CSIAI), which is an annual measure for year‐round sea ice anomalies of the Southern Ocean and its regional sub‐sectors. By relating selected years of significant sea ice conditions (1981, 2007 and 2014) with atmospheric influences, we demonstrate that the CSIAI is very useful for assessing inter‐annular Antarctic SIC variability. Positive and negative sea ice anomalies can be qualitatively explained by atmospheric circulation anomalies in the years 1981 and 2007. However, in 2014, the year with the largest observed sea ice extent in our time series, we found that this positive sea ice anomaly was surprisingly not associated with a stationary and inter‐seasonally persistent pattern of circulation anomaly. This suggests that sub‐seasonal to seasonal circulation anomalies and ocean‐related processes favoured the formation of the sea ice maximum in 2014. With this study we provide additional information on the long‐term annual SIC variability around Antarctica. Furthermore, our classification approach and its results have potential for application in the evaluation of sea ice model results.

Current likelihood and dynamics of hot summers in the UK

Summer 2018 in the United Kingdom (UK) was its joint hottest on record and the associated impacts raise questions over societal resilience to extremes of this magnitude or greater occurring in upcoming years. Better information on the current likelihood of extreme and unprecedented events feeds into improved understanding of risk, relevant for policy and contingency planning. However, making robust estimates of likelihood is difficult given that extremes in the historical record are few by definition. We overcome this by using a large ensemble of initialised climate model simulations to assess the chance of exceeding summer 2018 temperatures in the current climate and find it to be ∼11% each year, although a weak circulation bias may mean this estimate is conservative. This likelihood has increased sharply over the last few decades. A one in 100-year event would bring summertime temperatures to the UK of approximately 1 °C above 2018, an anomaly similar to that of the notable hot summer of 1976. Subsetting the large ensemble enables characterisation of the dynamics around hot summers, and investigation of possible remote influences. Several circulation patterns bring warm temperatures to the UK, and it is likely that influences from different remote regions are active or dominant in different years. We present evidence suggesting roles for tropical precipitation anomalies via extratropical wave trains. Circulation anomalies associated with wet conditions in the Caribbean project particularly strongly onto the hot UK summer conditions, with a weaker signal from the tropical Pacific consistent with developing La Niña. We also highlight possible influence in some years from springtime high sea ice anomalies in the Sea of Okhotsk and low anomalies in the Barents/Kara seas. Building on this, we use new experiments that isolate the effects of opposing springtime sea ice anomalies in the two regions and find a causal relationship with the summertime circulation over the North Atlantic and northern Europe.

Prolonged Periodicity and Eastward Shift of the January North Pacific Oscillation Since the Mid‐1990s and Its Linkage With Sea Ice Anomalies in the Barents Sea

AbstractThe present study mainly investigates changes in the periodicity and location of the January North Pacific Oscillation (NPO) and the underlying mechanisms during 1980–2018. The periodicity of the January NPO prolongs from 2–3 years to 5–8 years around the mid‐1990s. Corresponding to the prolonged periodicity, both the southern and northern lobes of the January NPO shift eastward, and their meridional movement is relatively weak. As a result, the impacts of the January NPO on surface air temperature in North America are enhanced. The changes in the periodicity and location of the January NPO differ from those of the NPO of other winter months. Further study shows that the changes in the January NPO are closely related to the sea ice anomalies in the Barents Sea in the preceding November‐December and January. The sea ice anomalies also display a periodicity of 5–8 years after the mid‐1990s, and their impacts on the January NPO are enhanced. The January NPO is significantly and negatively correlated with the sea ice anomalies after the mid‐1990s. The sea ice anomalies contribute to the prolonged periodicity and eastward shift of the January NPO by exciting a quasi‐stationary Rossby wave propagating eastward along the coast of northern Eurasia and resultant atmospheric dynamic processes. The physical mechanism is reasonably reproduced by the numerical experiment with observed sea ice anomalies in the Barents Sea prescribed. In addition, possible reasons for the enhanced impacts of the sea ice anomalies on the January NPO are discussed.

What Leads to Persisting Surface Air Temperature Anomalies from Winter to Following Spring over Mid- to High-Latitude Eurasia?

AbstractSurface air temperature (SAT) anomalies tend to persist from winter to the following spring over the mid- to high latitudes of Eurasia. The present study compares two distinct cases of Eurasian SAT anomaly evolution and investigates the reasons for the persistence of continental-scale mid- to high-latitude Eurasian SAT anomalies from winter to following spring (termed persistent cases). The persisting SAT anomalies are closely associated with the sustenance of large-scale atmospheric circulation anomaly pattern over the North Atlantic and Eurasia, featuring a combination of the North Atlantic Oscillation/Arctic Oscillation (NAO/AO) and the Scandinavian pattern, from winter to spring. The combined circulation anomalies result in SAT warming over most of mid- to high-latitude Eurasia via anomalous wind-induced temperature advection. The sustenance of atmospheric circulation anomaly pattern is related to the maintenance of the North Atlantic triple sea surface temperature (SST) anomaly pattern due to air–sea interaction processes. The Barents Sea ice anomalies, which form in winter and increase in spring, also partly contribute to the sustenance of atmospheric circulation anomalies via modulating thermal state of the lower troposphere. In the cases that notable SAT warming (cooling) in winter is replaced by pronounced SAT cooling (warming) in the subsequent spring—termed reverse cases—the North Atlantic SST anomalies become small and the Greenland Sea ice change is a response to atmospheric change in spring. Without the support of lower boundary forcing, the atmospheric circulation anomaly pattern experiences a reverse in the spatial distribution from winter to spring likely due to internal atmospheric processes.

North Pacific Gyre Oscillation Closely Associated With Spring Arctic Sea Ice Loss During 1998–2016

AbstractThe relative importance of the factors contributing to Arctic spring sea ice decline remains an open question. Here we suggest a new major factor. In spring the North Pacific Gyre Oscillation (NPGO) shows a significantly increasing trend during 1998–2016, in contrast to the insignificant trend of the Pacific Decadal Oscillation (PDO) index. Nearly 40% of Arctic springtime sea ice concentration trend is statistically related to the increase of the NPGO index but only 4% to the PDO trend. Through the destructive linear interference with climatological Aleutian low, the increasing NPGO index tends to weaken the upward propagation of planetary waves, which enhances the strength of the stratospheric Arctic vortex and the Arctic Oscillation (AO). The positive AO anomalies influence the surface wind field and temperature pattern anomalies, contributing to negative sea ice anomalies in the Arctic.

Climate anomalies contributed to the rebound of PM2.5 in winter 2018 under intensified regional air pollution preventions

Rigorous air pollution managements since 2013 resulted in decreasing trend in fine particulate matter (PM2.5) in China. Regional air pollution prevention measures were extra implemented in the “2 + 26” region since 2017. However, haze pollution dramatically rebounded in the winter of 2018. Both of the observed analyses and the numerical results (basing on a global 3-D chemical transport model) demonstrated that, although intensified prevention measures existed, atmospheric circulation and local meteorological conditions still significantly influenced the variation in haze pollution. The simulated PM2.5 concentrations (with fixed emissions) driven by meteorology in 2018 were 12–15% higher than those with atmospheric circulations in 2017 both under a low and a high emission level, close to the observed 10% PM2.5 rebound. In 2018, positive sea ice anomalies around Beaufort Sea and “triple pattern” anomalies of sea surface temperature in the North Pacific and North Atlantic enhanced the anomalous anticyclonic circulations over the air-polluted region, and thus resulted in minimum surface wind speed during 1979–2018 and 16.8% shallower boundary layer than those in 2017. In the stagnated air of winter 2018, the transported dispersion of pollutant particles was weakened, however more secondary aerosols were produced by enhanced chemical reactions, which jointly contributed to the PM2.5 rebound in 2018.

Characteristics of stratospheric polar vortex fluctuations associated with sea ice variability in the Arctic winter

The leading two modes of winter (November–February) Arctic sea ice cover variability and their linkage to stratospheric polar vortex variations are analyzed based on the cyclostationary EOF techniques. The first mode represents an accelerating trend of Arctic sea ice decline associated with Arctic amplification, particularly in the Barents and Kara Seas. The second mode is associated with decadal-scale phase shifts of dipole sea ice anomalies in the North Atlantic caused by NAO circulation. The first two modes of sea ice variability represent respectively a forced climate change and internal variability, and result in temporally and spatially distinct stratospheric polar vortex weakening. Sea ice reduction in the Barents and Kara Seas for the first mode is linked to a stratospheric vortex weakening during mid January–late February. The second mode with the dipole structure of positive sea ice anomalies in the Barents and Greenland Seas and negative anomalies in the Hudson Bay and Labrador Sea is related to a stratospheric vortex weakening during December–early February. The spatial evolutionary structure of anomalous polar vortex also exhibits differences between the two modes. When stratospheric anomalies are fully developed, stratospheric vortex is shifted to Eurasia in the first mode and to Europe in the second mode.

Seasonal prediction of the northern and southern temperature modes of the East Asian winter monsoon: the importance of the Arctic sea ice

Previous research work found that two distinct surface air temperature (SAT) modes—the northern (N-) and the southern (S-) modes dominate the East Asian winter monsoon (EAWM) region. The inter-annual variations of these two modes were mainly attributed to preceding Siberian snow cover anomalies and El Nino–Southern Oscillation (ENSO). Observed evidence in this study shows that sea ice anomalies on Barents–Kara (BK) and Laptev Seas and those on Chukchi–Beaufort (CB) Sea in autumn have co-mingled effects on the two abnormal EAWM modes. If negative sea ice anomalies appear in the BK and northern CB Sea in September–October (SO), the following winter SAT anomaly over East Asia is featured by an obvious cooling north of 40° N, which highly resembles the SAT N-mode of EAWM. If negative sea ice anomalies occur in BK–Laptev Sea but positive anomalies in the southern CB Sea, the East Asia winter SAT anomaly exhibits a salient cold condition over the south of 40° N and corresponds to the EAWM S-mode. The above results indicate that autumn Arctic sea ice can provide another predictability source for the EAWM, besides Siberian snow cover and ENSO. To further verify its contribution to seasonal prediction of the EAWM, a series of physical–empirical models are established using the combinations of SO Arctic sea ice, autumn Siberian snow cover and ENSO. Hindcast experiment output shows when adding autumn Arctic sea ice into the predictors, the cross-validated prediction skill is significantly improved. The possible physical mechanisms on how preceding Arctic sea ice anomalies impact on the N- and S- modes are also discussed.

Influence of sea-ice anomalies on Antarctic precipitation using source attribution in the Community Earth System Model

Abstract. We conduct sensitivity experiments using a general circulation model that has an explicit water source tagging capability forced by prescribed composites of pre-industrial sea-ice concentrations (SICs) and corresponding sea surface temperatures (SSTs) to understand the impact of sea-ice anomalies on regional evaporation, moisture transport and source–receptor relationships for Antarctic precipitation in the absence of anthropogenic forcing. Surface sensible heat fluxes, evaporation and column-integrated water vapor are larger over Southern Ocean (SO) areas with lower SICs. Changes in Antarctic precipitation and its source attribution with SICs have a strong spatial variability. Among the tagged source regions, the Southern Ocean (south of 50∘ S) contributes the most (40 %) to the Antarctic total precipitation, followed by more northerly ocean basins, most notably the South Pacific Ocean (27%), southern Indian Ocean (16 %) and South Atlantic Ocean (11 %). Comparing two experiments prescribed with high and low pre-industrial SICs, respectively, the annual mean Antarctic precipitation is about 150 Gt yr−1 (or 6 %) more in the lower SIC case than in the higher SIC case. This difference is larger than the model-simulated interannual variability in Antarctic precipitation (99 Gt yr−1). The contrast in contribution from the Southern Ocean, 102 Gt yr−1, is even more significant compared to the interannual variability of 35 Gt yr−1 in Antarctic precipitation that originates from the Southern Ocean. The horizontal transport pathways from individual vapor source regions to Antarctica are largely determined by large-scale atmospheric circulation patterns. Vapor from lower-latitude source regions takes elevated pathways to Antarctica. In contrast, vapor from the Southern Ocean moves southward within the lower troposphere to the Antarctic continent along moist isentropes that are largely shaped by local ambient conditions and coastal topography. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies associated with natural variability on Antarctic precipitation. Our analyses of the seasonal contrast in changes of basin-scale evaporation, moisture flux and precipitation suggest that the impact of SIC anomalies on regional Antarctic precipitation depends on dynamic changes that arise from SIC–SST perturbations along with internal variability. The latter appears to have a more significant effect on the moisture transport in austral winter than in summer.

The impact of wintertime sea-ice anomalies on high surface heat flux events in the Iceland and Greenland Seas

The gyres of the Iceland and Greenland Seas are regions of deep-water formation, driven by large ocean-to-atmosphere heat fluxes that have local maxima adjacent to the sea-ice edge. Recently these regions have experienced a dramatic loss of sea ice, including in winter, which begs the question have surface heat fluxes in the adjacent ocean gyres been affected? To address this a set of regional atmospheric climate model simulations has been run with prescribed sea ice and sea surface temperature fields. Three 20-year model experiments have been examined: Icemax, Icemed and Icemin, where the surface fields are set as the year with maximum, median and minimum sea-ice extents respectively. Under conditions of reduced sea-ice extent there is a 15% (19 W m−2) decrease in total wintertime heat fluxes in the Iceland Sea. In contrast, there is an 8% (9 W m−2) increase in heat fluxes in the Greenland Sea primarily due to higher local SSTs. These differences are manifest as changes in the magnitude of high heat flux events (such as cold air outbreaks). In the Iceland Sea, 76% of these events are lower in magnitude during reduced sea-ice conditions. In the Greenland Sea, 93% of these events are higher in magnitude during reduced sea-ice conditions as a result of higher SSTs coincident with retreating sea ice. So, in these experiments, the reduced wintertime sea-ice conditions force a different response in the two seas. In both gyres, large-scale atmospheric circulation patterns are key drivers of high heat flux events.

Month-to-Month Variability of Autumn Sea Ice in the Barents and Kara Seas and Its Relationship to Winter Air Temperature in China

The variation of autumn Arctic sea ice is a critical indicator of temperature anomalies over the Eurasian continent during winter. The retreat of autumn Arctic sea ice is typically accompanied by negative anomalous winter temperatures over the Eurasian and North American continents. However, such sea ice temperature linkages notably change from month to month. The variation of the autumn Arctic sea ice area and the relationship between the month-to-month sea ice and winter temperature anomalies in China are investigated using the Hadley Centre’s sea ice dataset (HadiSST) and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset (ERA-Interim) during 1979–2018. We present the following results: The sea ice in the Barents and Kara seas (BK) during the autumn and winter seasons shows notable low-frequency variability. The retreat of sea ice in the BK from September to November is significantly associated with negative temperature anomalies in the following winter in China. However, the linkage between the sea ice in the BK in September and the winter temperatures is stronger than that in both October and November. An anomalous positive surface pressure is exhibited over the northwestern part of Eurasia in the winter that is linked to decreasing sea ice in the BK in the preceding September. This surface pressure favors the persistence and intensification of synoptic perturbations, such as blocking highs and surface cold highs, as well as the intensification of the Siberian High and the East Asian winter monsoon. These favorable conditions ultimately contribute to the formation of large-scale winter cold anomalies in China. Compared to low sea ice cover in October and November, a more oceanic heat storage in the upper BK induced by low sea ice cover in the BK leads to a larger heat release to tropospheric atmosphere in winter by surface heat flux and upward longwave radiation in the BK. This regional tropospheric warming results in a higher barotropic positive height anomaly over the Ural Mountains, and then more active cold advection from the high latitude affects East Asia.

Assessment of Arctic sea ice simulations in CMIP5 models using a synthetical skill scoring method

The Arctic sea ice cover has declined at an unprecedented pace since the late 20th century. As a result, the feedback of sea ice anomalies for atmospheric circulation has been increasingly evidenced. While climatic models almost consistently reproduced a decreasing trend of sea ice cover, the reported results show a large distribution. To evaluate the performance of models for simulating Arctic sea ice cover and its potential role in climate change, this study constructed a reasonable metric by synthesizing both linear trends and anomalies of sea ice. This study particularly focused on the Barents Sea and the Kara Sea, where sea ice anomalies have the highest potential to affect the atmosphere. The investigated models can be grouped into three categories according to their normalized skill scores. The strong contrast among the multi-model ensemble means of different groups demonstrates the robustness and rationality of this method. Potential factors that account for the different performances of climate models are further explored. The results show that model performance depends more on the ozone datasets that are prescribed by the model rather than on the chemical representation of ozone.

Different contributions of Arctic sea ice anomalies from different regions to North China summer ozone pollution

AbstractSurface ozone pollution is the main form of summer air pollution in North China and damages human and ecosystem health. Long‐term meteorological observations show that late spring Arctic sea ice and ozone‐related meteorological conditions are positively correlated; this result was further verified by numerical experiments. The Eurasia teleconnection pattern bridged the sea ice over Gakkel Ridge to the local meteorological conditions associated with O3. The sea ice anomalies over the Canada Basin and the Beaufort Sea mainly influenced the O3 pollution in North China via the summer west Pacific pattern. Furthermore, changes in the relationships were also included. The anticyclonic circulation over North China, that is, the joint centre of the Eurasia teleconnection and west Pacific patterns, could significantly lead to suitable weather conditions to accelerate the photochemical reactions to transfer the precursors to surface ozone. This finding helps to improve the understanding of the interannual variation in ozone pollution in North China.

Impact of the Madden-Julian oscillation on Antarctic sea ice and its dynamical mechanism

The influence of the Madden-Julian oscillation (MJO) on Antarctic sea ice extent has not been extensively explored. This study investigates intraseasonal variability of the sea ice extent induced by the MJO and its physical mechanism. During austral winter, the sea ice extent anomaly exhibits considerable melting and freezing as the MJO evolves. Numerical experiments and the Rossby wave theory show that the high-latitude circulation anomalies in response to the MJO are responsible for the sea ice change. The MJO-induced Rossby waves propagate into the Southern Hemisphere through the northerly ducts over the western Indian Ocean–central Africa and the Maritime Continent. The MJO-induced circulation anomalies reach high latitudes and lead to anomalous meridional temperature advection, causing changes in the sea ice extent. The time difference between the meridional wind and sea ice anomalies is ~5 days. As the MJO moves, the sea ice extent anomaly also exhibits eastward-migrating behavior. Strong sea ice melting in the total anomaly is synchronous to the evolution of the MJO, suggesting the practical usefulness of the location of the MJO for the prediction of the sea ice decrease.

Analysis of summer Antarctic sea ice anomalies associated with the spring Indian Ocean dipole

Abstract In this study, we applied the empirical orthogonal function (EOF) to analyze the anomalous characteristics of the summer Antarctic sea ice. Through correlation analysis, it is found that two strong signals existed in the spring Indian Ocean. These two signals constitute the Indian Ocean dipole (IOD). Although the IOD often occurs with El Nino-Southern Oscillation (ENSO), the first mode of the EOF is mainly resultant from the IOD. The IOD can cause sea ice anomalies in the Atlantic and Pacific Oceans, as well as the Weddell and Ross Seas. When the ENSO signal in the IOD was removed, the sea-ice anomalies in the Pacific Ocean and the eastern Ross Sea disappear, and the sea ice in the Atlantic Ocean decreases and moves westward. However, the sea ice anomalies in the Weddell Sea remain almost unchanged. These results demonstrate that the IOD excites geopotential height anomalies, causing anomalous atmospheric circulation, resulting in an increase (decrease) in sea ice caused by cold (warm) meridional flow.