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The Chukchi Sea shelf (CSS) is a highly productive region in the Arctic Ocean and it is highly efficient for absorbing atmospheric carbon dioxide and exporting and retaining carbon in the deep sea. However, with global warming, the carbon retention time in CSS may decrease, leading to less efficient carbon export. Here, we investigate the seasonal variability of carbonate chemistry in CSS using three sets of late‐ vs. early‐summer reoccupations of the same transect. Our findings demonstrate substantially increased and rapid degradation of biologically produced organic matter and therefore acidification over time in the southern CSS due to earlier sea‐ice retreat, resulting in significantly shorter carbon retention time. In sharp contrast, no increased degradation has been observed in the northern CSS where photosynthesis has just commenced. In the future, climate change would further diminish the carbon export capacity and exacerbate seasonal acidification not only within CSS but also across other polar coastal oceans. [ABSTRACT FROM AUTHOR]

To investigate patterns of horizontal atmospheric latent energy (LE) transport toward the Arctic, we applied the self-organizing maps (SOM) method to the daily vertically integrated horizontal LE flux from ERA5 in winter (January–March) during 1979–2021. A clear picture depicting the LE transport to the Arctic at a synoptic scale then emerged, with four primary transport pathways identified: the northern Europe, the Davis Strait, the Greenland Sea, and the Bering Strait pathways. The four primary pathways occurred at a comparable frequency, and noticeable interannual variability was observed in their time series of frequency during 1979–2021. Further analysis suggested that the northward LE transport through all these pathways is significantly modulated by cyclones, with the northern Europe and the Greenland Sea pathways being mostly affected. Generally, more frequent and stronger cyclones were observed near the entry regions of LE transport compared to other regions. Moreover, this study provides a comprehensive picture of how atmospheric LE transport is related to air temperature, moisture, surface heat flux, and sea ice anomalies over the Arctic Ocean in winter. Through a thermodynamic perspective, we argue that the deleterious impacts of poleward LE transport on Arctic sea ice are to a large extent attributable to the enhanced local atmosphere–ice interactions, which increase downward longwave radiation (DLR) plus turbulent fluxes, consequently warming the surface and promoting the loss of sea ice. According to the quantitative results, among the four primary pathways, LE transport through the Davis Strait and the Greenland Sea could cause the loss of Arctic sea ice most efficiently. [ABSTRACT FROM AUTHOR]

In recent years, noticeable subsidence depressions have occurred along the coastal zone of the Yellow River Delta. In some coastal areas, the average annual subsidence varies from tens of millimeters to hundreds of millimeters. Although some studies have discovered a significant land subsidence funnel in the coastal zone of the Yellow River Delta, it has rarely been reported in recent years. Using Sentinel-1A/1B images from the last five years and permanent scatterers interferometric synthetic aperture radar technology, we found a typical subsidence bowl in the northeastern part of the delta, with a cumulative settlement of nearly 1 m over five years. In addition, we used the approach of soil mechanics to simulate the settlement of confined brine layers with different thicknesses under drainage conditions. We found that the 15 m thick confined aquifer can produce 1 m of settlement for every 15% decrease in water content. The simulation results explain the large settlement of the brine industrial area. This study can provide guidance for brine mining in the future. If we continue to overexploit underground brine, there will be more severe land subsidence in the delta in the future. [ABSTRACT FROM AUTHOR]

A distinguishing feature of Arctic sea ice is the rapid declining in the Pacific Arctic Sector (PAS) in recent years. The atmospheric variability during spring (March‐May) plays a critical role in determining the sea ice extent (SIE) during the following summer. The summertime (June‐August) SIE reduction in the eastern part of PAS, including the East Siberian Sea and the Laptev Sea, is strongly related to the first two leading atmospheric circulation modes in spring, the Arctic Oscillation and the Arctic Dipole, retrieved from empirical orthogonal function analysis. Here, we show that the third leading mode of atmospheric circulation in spring, namely the Barents‐Beaufort Oscillation (BBO), can also change the summer SIE, especially on the western regime of the PAS across the Beaufort and Chukchi Seas. We find that a positive phase of springtime BBO (i.e., BBO+), relative to the BBO−, acts to decrease sea ice thickness via advection and generate sea ice deformation through divergence and shear processes, thereby preconditioning for a rapid sea ice loss within the PAS in the following summer. Furthermore, the occurrence of BBO is state‐dependent and potentially modulated by the phase shift of the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO). Since the mid‐1990s, the AMO (PDO) index has changed from a dominant negative (positive) to a positive (negative) phase. These phase shifts in AMO and PDO would have contributed to the subsequently increased appearance of anomalous BBO+ after 2000 and enhanced the summertime sea ice loss in the western regions of the PAS in recent years. Plain Language Summary: Large‐scale atmospheric circulation plays a vital role in regulating the Arctic sea ice extent (SIE) changes in summer. Spring atmospheric circulation anomaly could precondition for a noticeable decline in SIE in the following summer. Arctic Oscillation and Arctic Dipole anomaly modes are well demonstrated in previous studies. In this study, we outline the effectiveness in leading to sea ice reduction by another important circulation pattern, namely the Barents‐Beaufort Oscillation (BBO). The spring BBO in its positive phase can change the summer SIE over the western Pacific‐Arctic sector, including Beaufort and Chukchi Seas. The two seas are the regions undergoing the rapidest shrinkage over the past decades. We also found that the decadal variability of BBO seems to be associated with the ocean activities at low latitudes. The frequent occurrence after 2000 is partly attributable to the phase shift by the Pacific Decadal Oscillation and Atlantic Multidecadal Oscillation since mid‐1990s. Key Points: A special connection of summer Arctic sea ice extent shrinkage to spring Barents‐Beaufort Oscillation (BBO) is outlinedThe dynamic impacts on ice thickness decline through diverging and shearing processes linked to BBO are identified over the Pacific‐Arctic sectorThe effectiveness of BBO on Arctic sea ice changes depends on the states of Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation [ABSTRACT FROM AUTHOR]

This study investigates the thermodynamical and dynamical influences of the intense cyclone in the Arctic Ocean in August 2012 on the synoptic‐scale sea ice evolution, using the Arctic Ice Ocean Prediction System (ArcIOPS). As it is hard to fully isolate sea ice loss owing to extreme cyclone from that owing to background atmospheric state in most previous studies on this topic, this study introduces a newly developed algorithm to remove the cyclone component in atmospheric forcing, and conducts sea ice and heat budget analyses in two simulations driven by atmospheric forcing with and without the cyclone. Strong impact of the intense cyclone on sea ice locates on the east side of the cyclone's path, that is, Pacific Arctic for this case. The cyclone affects sea ice in two ways. First, cyclone‐induced enhancement in ice‐ocean interaction leads to increased sea ice basal melt in the Pacific Arctic and part of the Atlantic Arctic, which induces strong sea ice area and volume loss when the cyclone's intensity peaks. Second, as the cyclone strengthens, the increases in air temperature, humidity and wind speed accelerate turbulent heat exchange at the air‐ocean and air‐ice interfaces, leading to enhanced local sea ice surface melt in the Chukchi Sea and northern Beaufort Sea. The cyclone‐induced strong winds stir sea ice leading to enhanced gradients in sea ice velocity field and thus increased sea ice deformation, which further induces strong sea ice area loss. This study also demonstrates a precise atmospheric forcing field is essential for sea ice modeling. Plain Language Summary: We use a numerical model to study the effects of a strong Arctic cyclone on sea ice. First, we use a newly developed "cyclone removal algorithm" to remove the cyclone from the atmospheric data that is used to force the model. We can then compare how the sea ice changes between the model runs with and without the cyclone. We find that the cyclone has a strong local impact on sea ice, and sea ice losses are different on the two sides of the cyclone's path. The cyclone results in warm, moist air and strong wind, which leads to strong sea ice surface melting. At the same time, the cyclone increases the transfer of heat from the ocean to the sea ice, causing strong sea ice bottom melting. The strong wind also leads to more sea ice ridging and a reduction in sea ice area. Our study indicates that the effects of cyclones on sea ice are complex and that atmospheric data must accurately represent cyclones if we want to correctly model changes in the Arctic sea ice. Key Points: Removing a cyclone from the atmospheric forcing in an Arctic model reveals its contributions to sea ice loss along its trajectoryOceanic and turbulent heat fluxes are the key factors driving enhanced ice basal and surface melt during an intense cyclone in the ArcticStrong sea ice loss locates on the east side of the trajectory of an intense cyclone [ABSTRACT FROM AUTHOR]

Arctic sea ice, especially the multiyear ice (MYI), is decreasing rapidly, partly due to melting triggered by global warming, in turn partly due to the possible acceleration of ice export from the Arctic Ocean to southern latitudes through identifiable gates. In this study, MYI and total sea ice areal flux through six Arctic gateways over the winters (October–April) of 2002–2021 were estimated using daily sea ice motion and MYI/total sea ice concentration data. Inconsistencies caused by different data sources were considered for the estimate of MYI flux. Results showed that, there is a slight declining trend in the Arctic MYI areal flux over the past two decades, which is attributable to the decrease in MYI concentration. Overall speaking, MYI flux through Fram Strait accounts for ~87% of the Arctic MYI outflow, with an average of ~325.92 × 103 km2 for the winters of 2002–2021. The monthly MYI areal flux through Fram Strait is characterized with a peak in March (~55.56 × 103 km2) and a trough in April (~40.97 × 103 km2), with a major contribution from MYI concentration. The connections between sea ice outflow and large-scale atmospheric circulations such as Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and Dipole Anomaly (DA) were investigated. High correlation coefficients (CCs) were found in winter months such as January and February. While AO and NAO (especially NAO) exhibited generally weak correlations with the MYI/total sea ice flux, DA presented strong correlations with the areal flux, especially for MYI (CC up to 0.90 in January). However, the atmospheric circulation patterns are sometimes not fully characterized by the specific indices, which could have different effects on sea ice flux and its correlation with the atmospheric indices. [ABSTRACT FROM AUTHOR]

Revealing the changes in the Fram Strait (FS) multiyear ice (MYI) export is crucial due to their climate relevance in the context of the loss rate of MYI being faster than that of the total ice in the Arctic. Here, we estimated winter (October–April) MYI area export through the FS over the last 2 decades by using updated MYI concentration data retrieved from active and passive microwave satellite observations. We divided the period into two regimes relative to the ice index: D1 (2002/03–2010/11) and D2 (2012/13–2019/20). The observed variations of winter MYI exports D2 were compared with those of the previous decade D1. The results show that the MYI area exports display strong interannual variability. A significant decrease in MYI export for the periods between D1 and D2 is noted. On average, the wintertime MYI area exports declined sharply by 22% from 3.82 × 105 km2 in D1 to 3.00 × 105 km2 in D2. In addition, the percentage of MYI in the total sea ice outflow through the FS (PCM) also decreased distinctly from 72% in D1 to 59% in D2. Statistics show that weekly sea ice drift across the strait can explain 76% of the MYI area export variability. Furthermore, the dominant atmospheric drivers contributing to the decline in MYI area export during D2 were examined. In the last decade (D2), the strengthened low pressure in the North Atlantic sector, combined with an eastward shift in the axis of dipole anomaly (DA), resulted in reduced MYI advection from the Beaufort Sea and Siberian Coast toward the FS. Moreover, weakened cyclonic activity south of the FS also contributed to the reduction in MYI export during D2. [ABSTRACT FROM AUTHOR]

With the new-generation reanalysis product (ERA5), the spatiotemporal characteristics of poleward atmospheric moisture and energy transport over the past four decades (1979–2020) were examined. The main channels of atmospheric transport entering the Arctic in the Northern Hemisphere include the Chukchi Sea at 170° W, Baffin Bay at 50° W, North Atlantic at 0° E, and central Siberia at 90° E. Summer (winter) is characterized by high moisture (energy) transport across 70° N. No clear trend in moisture transport was found, whereas the winter and spring energy transport are declining significantly at a rate of −7.31 × 105 W/m/a (99% confidence) and −6.04 × 105 W/m/a (95% confidence), respectively. Meanwhile, an increasing trend was found in summer (4.48 × 105 W/m/a, 95% confidence) and autumn (3.61 × 105 W/m/a, not significant). The relationship between atmospheric moisture and energy transport and different large-scale atmospheric circulation patterns, including the Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Dipole Anomaly (DA), was explored. Among them, DA was identified as the most favorable pattern in relation to moisture and/or energy intrusion into the Arctic. As a result, the surface air temperature increases are more pronounced over most of the central Arctic under the regulation of DA. [ABSTRACT FROM AUTHOR]

The satellite observations unveiled that the July sea ice extent of the Arctic shrank to the lowest value, since 1979, in 2020 with a major ice retreat in the Eurasian shelf seas including Kara, Laptev, and East Siberian seas. Based on the ERA-5 reanalysis products, we explored the impacts of warm and moist air-mass transport on this extreme event. The results revealed that anomalously high energy and moisture converged into these regions in the spring months (April to June) of 2020, leading to a burst of high moisture content and warming within the atmospheric column. The convergence is accompanied by local enhanced downward longwave surface radiation and turbulent fluxes, which is favorable for initiating an early melt onset in the region with severe ice loss. Once the melt begins, solar radiation plays a decisive role in leading to further sea ice depletion due to ice–albedo positive feedback. The typical trajectories of the synoptic cyclones that occurred on the Eurasian side in spring 2020 agree well with the path of atmospheric flow. Assessments suggest that variations in characteristics of the spring cyclones are conducive to the severe melt of sea ice. We argue that large-scale atmospheric circulation and synoptic cyclones acted in concert to trigger the exceptional poleward transport of total energy and moisture from April to June to cause this record minimum of sea ice extent in the following July. [ABSTRACT FROM AUTHOR]

In this study, a regional linear Markov model is developed to assess seasonal sea ice predictability in the Pacific-Arctic sector. Unlike an earlier pan-Arctic Markov model that was developed with one set of variables for all seasons, the regional model consists of four seasonal modules with different sets of predictor variables, accommodating seasonally varying driving processes. A series of sensitivity tests are performed to evaluate the predictive skill in cross-validated experiments and to determine the best model configuration for each season. The prediction skill, as measured by the sea ice concentration (SIC) anomaly correlation coefficient (ACC) between predictions and observations, increased by 32 % in the Bering Sea and 18 % in the Sea of Okhotsk relative to the pan-Arctic model. The regional Markov model's skill is also superior to the skill of an anomaly persistence forecast. SIC trends significantly contribute to the model skill. However, the model retains skill for detrended sea ice extent predictions for up to 7-month lead times in the Bering Sea and the Sea of Okhotsk. We find that subsurface ocean heat content (OHC) provides a crucial source of prediction skill in all seasons, especially in the cold season, and adding sea ice thickness (SIT) to the regional Markov model has a substantial contribution to the prediction skill in the warm season but a negative contribution in the cold season. The regional model can also capture the seasonal reemergence of predictability, which is missing in the pan-Arctic model. [ABSTRACT FROM AUTHOR]

The acidification of coastal waters is distinguished from the open ocean because of much stronger synergistic effects between anthropogenic forcing and local biogeochemical processes. However, ocean acidification research is still rather limited in polar coastal oceans. Here, we present a 17‐year (2002–2019) observational data set in the Chukchi Sea to determine the long‐term changes in pH and aragonite saturation state (Ωarag). We found that pH and Ωarag declined in different water masses with average rates of −0.0047 ± 0.0026 years−1 and −0.017 ± 0.009 years−1, respectively, and are ∼2–3 times faster than those solely due to increasing atmospheric CO2. We attributed the rapid acidification to the increased dissolved inorganic carbon owing to a combination of ice melt‐induced increased atmospheric CO2 invasion and subsurface remineralization induced by a stronger surface biological production as a result of the increased inflow of the nutrient‐rich Pacific water. Plain Language Summary: Anthropogenic CO2 absorbed by the ocean leads to a lower pH and the calcium carbonate saturation state (Ω) and threatens the marine ecosystems state of healthiness via a process called ocean acidification (OA). The Arctic Ocean is particularly sensitive to OA because more CO2 can be dissolved in cold water. This study used the observations collected over 17 years from 2002 to 2019 to estimate long‐term trends of Ωarag and pH in the Chukchi Sea. The results show that rapid acidification occurred throughout all water masses from 2002 to 2019, leading to or approaching aragonite undersaturation. The rapid acidification is attributed to the enhanced increasing concentration of dissolved inorganic carbon. While sea ice melt induced uptake of anthropogenic CO2 partly explains the long‐term acidification, the remainder is due to the increased nutrient‐rich Pacific inflow water which promotes the high biological CO2 utilization in the surface waters but leads to stronger subsurface acidification due to the regenerated CO2. We suggest that the acidity in Chukchi Arctic Shelf waters will increase in the future if the increased inflow of Pacific water continues. Key Points: pH and Ωarag declined at −0.0047 ± 0.0026 years−1 and −0.017 ± 0.009 years−1 from 2002 to 2019, 2–3 times greater than atmospheric CO2 projectedThe enhanced acidification in Chukchi Sea is mainly driven by enhanced dissolved inorganic carbon, owing to atmospheric CO2 uptake and biological activityAragonite undersaturation in Pacific Winter Water has been observed from 2010; other water masses are expected to encounter Ωarag < 1 within 15 years [ABSTRACT FROM AUTHOR]

The extreme Arctic sea ice minima in the twenty-first century have been attributed to multiple factors, such as anomalous atmospheric circulation, excess solar radiation absorbed by open ocean, and thinning sea ice in a warming world. Most likely it is the combination of these factors that drives the extreme sea ice minima, but how the factors rank in setting the conditions for these events has not been quantified. To address this question, the sea ice budget of an Arctic regional sea ice–ocean model forced by atmospheric reanalysis data is analyzed to assess the development of the observed sea ice minima. Results show that the ice area difference in the years 2012, 2019, and 2007 is driven to over 60% by the difference in summertime sea ice area loss due to air–ocean heat flux over open water. Other contributions are small. For the years 2012 and 2020 the situation is different and more complex. The air–ice heat flux causes more sea ice area loss in summer 2020 than in 2012 due to warmer air temperatures, but this difference in sea ice area loss is compensated by reduced advective sea ice loss out of the Arctic Ocean mainly caused by the relaxation of the Arctic dipole. The difference in open water area in early August leads to different air–ocean heat fluxes, which distinguishes the sea ice minima in 2012 and 2020. Further, sensitivity experiments indicate that both the atmospheric circulation associated with the Arctic dipole and extreme storms are essential conditions for a new low record of sea ice extent. [ABSTRACT FROM AUTHOR]

Recently, many of the world's major river deltas have been sinking, making them increasingly vulnerable to floods and storm surges, salinization and permanent inundation. For the Yellow River delta, annual subsidence rates of several to dozens of centimeters have been reported in the past few years. The extraction of a considerable amount of groundwater due to continuous pumping is suggested as the main driver of the groundwater depression cone. Despite its scale and severity, methods to quantify subsidence are scarce. We introduce a soil mechanics approach to quantify subsidence due to the compaction of soft soil. The largest reduction in soft soil thickness, which is more than 2.6 m, occurred in the salt field area to the north of the Yellow River. Furthermore, by estimating the primary consolidation of soft soil, the subsidence caused by groundwater exploitation is quantified. In the coastal area of the delta, due to excessive exploitation of shallow underground brine resources, the maximum accumulated subsidence is as high as 2 m. Since the natural consolidation of these deltaic sediments has ended, if the current groundwater exploitation intensity is maintained, major subsidence disasters, such as subsidence depressions and ground fissures, will occur. [ABSTRACT FROM AUTHOR]

Atmospheric circulation associated with the Arctic dipole (AD) pattern plays a crucial role in modulating the variations of summertime sea ice concentration (SIC) within the Pacific Arctic sector (PAS). Based on reanalysis data and satellite observations, we found that the impacts of atmospheric circulation associated with a positive AD (AD+) on SIC change over different regions of the PAS [including the East Siberian Sea (ESS), Beaufort and Chukchi Seas (BCS), and Canadian Arctic Archipelago (CAA)] are dependent on the phase shifts of Pacific decadal oscillation (PDO). Satellite observations reveal that SIC anomalies, influenced by AD+ during PDO− relative to that during PDO+, varies significantly in summer by 4.9%, −7.3%, and −6.4% over ESS, BCS, and CAA, respectively. Overall, the atmospheric anomalies over CAA and BCS in terms of specific humidity, air temperature, and thereby downward longwave radiation (DLR), are enhanced (weakened) in the atmospheric conditions associated with AD+ during PDO− (PDO+). In these two regions, the larger (smaller) increases in specific humidity and air temperature, associated with AD+ during PDO− (PDO+), are connected to the increased (decreased) poleward moisture flux, strengthened (weakened) convergence of moisture and heat flux, and in part to adiabatic heating. As a consequence, the DLR and surface net energy flux anomalies over the two regions are reinforced in the atmospheric scenarios associated with AD+ during PDO− compared with that during PDO+. Therefore, smaller SIC anomalies are identified over CAA and BCS in the cases related to AD+ during PDO− than during PDO+. Essentially, the changes of the DLR anomaly in CAA and BCS are in alignment with geopotential height anomalies, which are modulated by the anticyclonic circulation pattern in association with AD+ during varying PDO phases. In contrast, the SIC changes over ESS is primarily attributed to the variations in mechanical wind forcing and sea surface temperature (SST) anomalies. The cloud fraction anomalies associated with AD+ during different PDO phases are found not to be a significant contributor to the variations of sea ice anomaly in the studied regions. Given the oscillatory nature of PDO, we speculate that the recent shift to the PDO+ phase may temporarily slow the observed significant decline trend of the summertime SIC within PAS of the Arctic. [ABSTRACT FROM AUTHOR]

A cyclone is an intensive synoptic activity that occurs frequently over Baffin Bay. By modifying the large‐scale distribution pattern of sea level pressure, a passing cyclone can serve as an important regulator of sea ice outflow via the Davis Strait. We obtain a nearly 40‐year‐long record (1979/1980–2017/2018) of the sea ice area flux (SIAF) through the Davis Strait and Arctic cyclone activities in winter. A case study and statistical results indicate that the sea ice concentration and motion fields can be greatly altered by the occurrence of cyclones, thereby contributing to changes in sea ice export. Moreover, the effects of cyclones on sea ice export in Baffin Bay are dependent on the spatial distribution pattern of the storms. In terms of the cyclone center count and intensity, the key regions with significant impacts on sea ice export out of Baffin Bay are identified, one around Baffin Island (80°W–60°W, 60°N–70°N) and the other over the southern Labrador Peninsula (70°W–50°W, 40°N–60°N). A robust correlation exists between the winter‐accumulated SIAF via the Davis Strait and the average winter cyclone intensity (center count) in the critical regions with R = −0.57 (+0.49), affirming the vital role of cyclone activity in modulating the interannual variability of sea ice export in Baffin Bay. Key Points: The wintertime sea ice area flux through the Davis Strait and cyclone activities nearby over the period 1979/1980–2017/2018 are acquiredStrong winds induced by cyclones can change the characteristics of sea ice and thus can impact sea ice export through the Davis StraitThe effects of cyclones on sea ice export through the Davis Strait are spatially dependent, and the key regions are identified [ABSTRACT FROM AUTHOR]

Sea ice export through the Baffin Bay plays a vital role in modulating the sea ice cover variability in the Labrador Sea. In this study, satellite-derived sea ice products are used to obtain the sea ice area flux (SIAF) through the three passages in the Baffin Bay (referred to as A, B, and C for the north, middle, and south passages, respectively). The spatial variability of the monthly sea ice drift in the Baffin Bay is presented. The interannual variability and trends in SIAF via the three passages are outlined. The connection to several large-scale atmospheric circulation modes is assessed. Over the period of 1988–2015, the average annual (October to the following September) SIAF amounts to 555×103 km2, 642×103 km2, and 551×103 km2 through Passages A, B, and C, respectively. These quantities are less than that observed through the Fram Strait (FS, 707×103 km2) of the corresponding period. The positive trends in annual SIAF, on the order of 53.1×103 km2/(10 a) and 43.2×103 km2/(10 a) (significant at the 95% confidence level), are identified at Passages A and B, respectively. The trend of the south passage (C), however, is slightly negative (−13.3×103 km2/(10 a), not statistically significant). The positive trends in annual SIAF through the Passages A and B are primarily attributable to the significant increases after 2000. The connection between the Baffin Bay sea ice export and the North Atlantic Oscillation is not significant over the studied period. By contrast, the association with the cross-gate sea level pressure difference is robust in the Baffin Bay (R equals 0.69 to 0.71, depending on the passages considered), but relatively weaker than that over FS (R=0.74). [ABSTRACT FROM AUTHOR]

The spatial structure of the Arctic sea ice concentration (SIC) variability and the connection to atmospheric as well as radiative forcing during winter and summer for the 1979–2017 period are investigated. The interannual variability with different spatial characteristics of SIC in summer and winter is extracted using the empirical orthogonal function (EOF) analysis. The present study confirms that the atmospheric circulation has a strong influence on the SIC through both dynamic and thermodynamic processes, as the heat flux anomalies in summer are radiatively forced while those in winter contain both radiative and "circulation-induced" components. Thus, atmospheric fluctuations have an explicit and extensive influence to the SIC through complex mechanisms during both seasons. Moreover, analysis of a variety of atmospheric variables indicates that the primary mechanism about specific regional SIC patterns in Arctic marginal seas are different with special characteristics. [ABSTRACT FROM AUTHOR]

In comparison with seasonal sea ice (first-year ice, FY ice), multiyear (MY) sea ice is thicker and has more opportunity to survive through the summer melting seasons. Therefore, the variability of wintertime MY ice plays a vital role in modulating the variations in the Arctic sea ice minimum extent during the following summer. As a response, the ice-ocean-atmosphere interactions may be significantly affected by the variations in the MY ice cover. Satellite observations are characterized by their capability to capture the spatiotemporal changes of Arctic sea ice. During the recent decades, many active and passive sensors onboard a variety of satellites (QuikSCAT, ASCAT, SSMIS, ICESat, CryoSat-2, etc.) have been used to monitor the dramatic loss of Arctic MY ice. The main objective of this study is to outline the advances and remaining challenges in monitoring the MY ice changes through the utilization of multiple satellite observations. We summarize the primary satellite data sources that are used to identify MY ice. The methodology to classify MY ice and derive MY ice concentration is reviewed. The interannual variability and trends in the MY ice time series in terms of coverage, thickness, volume, and age composition are evaluated. The potential causes associated with the observed Arctic MY ice loss are outlined, which are primarily related to the export and melting mechanisms. In addition, the causes to the MY ice depletion from the perspective of the oceanic water inflow from Pacific and Atlantic Oceans and the water vapor intrusion, as well as the roles of synoptic weather, are analyzed. The remaining challenges and possible upcoming research subjects in detecting the rapidly changing Arctic MY ice using the combined application of multisource remote sensing techniques are discussed. Moreover, some suggestions for the future application of satellite observations on the investigations of MY ice cover changes are proposed. [ABSTRACT FROM AUTHOR]

The Pacific sector of the Arctic Ocean (PA, hereafter) is a region sensitive to climate change. Given the alarming changes in sea ice cover during recent years, knowledge of sea ice loss with respect to ice advection and melting processes has become critical. With satellite-derived products from the National Snow and Ice Center (NSIDC), a 38-year record (1979–2016) of the loss in sea ice area in summer within the Pacific-Arctic (PA) sector due to the two processes is obtained. The average sea ice outflow from the PA to the Atlantic-Arctic (AA) Ocean during the summer season (June–September) reaches 0.173×106 km 2 , which corresponds to approximately 34 % of the mean annual export (October to September). Over the investigated period, a positive trend of 0.004×106 km 2 yr -1 is also observed for the outflow field in summer. The mean estimate of sea ice retreat within the PA associated with summer melting is 1.66×106 km 2 , with a positive trend of 0.053×106 km 2 yr -1. As a result, the increasing trends of ice retreat caused by outflow and melting together contribute to a stronger decrease in sea ice coverage within the PA (0.057×106 km 2 yr -1) in summer. In percentage terms, the melting process accounts for 90.4 % of the sea ice retreat in the PA in summer, whereas the remaining 9.6 % is explained by the outflow process, on average. Moreover, our analysis suggests that the connections are relatively strong (R=0.63), moderate (R=-0.46), and weak (R=-0.24) between retreat of sea ice and the winds associated with the dipole anomaly (DA), North Atlantic Oscillation (NAO), and Arctic Oscillation (AO), respectively. The DA participates by impacting both the advection (R=0.74) and melting (R=0.55) processes, whereas the NAO affects the melting process (R=-0.46). [ABSTRACT FROM AUTHOR]

Unlike the rapid decline of Arctic sea ice in the warming climate, Antarctic sea‐ice extent exhibits a modest positive trend in the period of near four decades. In recent years, the fluctuation in Antarctic sea ice has been strengthened, including a decrease toward the lowest sea‐ice extent in February 2011 for the period of 1978–2016 and a strong rebound in the summer of 2012. The sea‐ice recovery mainly occurs in the Weddell Sea, Bellingshausen Sea, Amundsen Sea, southern Ross Sea, and the eastern Somov Sea. This study offers a new mechanism for this summertime sea‐ice rebound. We demonstrate that cloud‐fraction anomalies in winter 2011 contributed to the positive Antarctic sea‐ice anomaly in summer 2012. The results show that the negative cloud‐fraction anomalies in winter 2011 related to the large‐scale atmospheric circulation resulted in a substantial negative surface‐radiation budget, which cooled the surface and promoted more sea‐ice growth. The sea‐ice growth anomalies due to the negative cloud forcing propagated by sea‐ice motion vectors from September 2011 to January 2012. The distribution of the sea‐ice anomalies corresponded well with the sea‐ice concentration anomalies in February 2012 in the Weddell Sea and eastern Somov Sea. Thus, negative cloud‐fraction anomalies in winter can play a vital role in the following summer sea‐ice distribution. Key Points: Wintertime cloud fraction anomalies in 2011 contributed significantly to the summertime sea‐ice rebound in 2012 in the AntarcticLess cloud fraction in winter 2011 related to large‐scale atmospheric circulation resulted in a strong negative surface‐radiation budgetCloud forcing in winter 2011 cooled the surface, promoted more sea‐ice growth, and resulted in more sea‐ice survival in summer 2012 [ABSTRACT FROM AUTHOR]

Baffin Bay serves as a huge reservoir of sea ice which would provide the solid freshwater sources to the seas downstream. By employing satellite-derived sea ice motion and concentration fields, we obtain a nearly 40-year-long record (1978–1979 to 2016–2017) of the sea ice area flux through key fluxgates of Baffin Bay. Based on the estimates, the Baffin Bay sea ice area budget in terms of inflow and outflow are quantified and possible causes for its interannual variations and trends are analyzed. On average, the annual (September–August) inflows through the northern gate and Lancaster Sound are on the order of 205.8(±74.7)×103 km 2 and 55.2(±17.8)×103 km 2. In particular, a comparison with published results seems to suggest that about 75 %–85 % of the inflow through the northern gates is newly formed ice produced in the recurring North Water Polynya (NOW), in addition to the inflow via Nares Strait and Jones Sound. Meanwhile, the mean outflow via the southern gate approaches 394.3(±110.2)×103 km 2. The distinct interannual variability for ice area flux through the northern gate and southern gate is partly explained by wind forcing associated with cross-gate sea level pressure difference, with correlations of 0.62 and 0.68, respectively. Also, significant increasing trends are found for the annual sea ice area flux through the three gates, amounting to 38.9×103 , 82.2×103 , and 7.5×103 km 2 decade -1 for the northern gate, southern gate, and Lancaster Sound. These trends are chiefly related to the increasing ice motion, which is associated with thinner ice owing to the warmer climate (i.e., higher surface air temperature and shortened freezing period) and increased air and water drag coefficients over the past decades. [ABSTRACT FROM AUTHOR]

The Yellow River Delta, which is the second-largest delta in China, has experienced varying degrees of land subsidence since the late 1970s. Although recent studies have identified the natural consolidation and compaction of sediment among the most important contributors to geologic processes, their processes have rarely been quantified. We estimated the sediment compaction over different time ranges to determine the temporal evolution of subsidence parameters (i.e., cumulative compaction). Estimates of primary consolidation, secondary consolidation, and the degree of consolidation in 152 boreholes revealed the spatial–temporal characteristics of sediment compaction and consolidation using geotechnical parameters collected from 152 boreholes, soil mechanics equations and the Kriging interplolation method. In addition, these estimates were partially constrained and cross-validated using the interferometric synthetic aperture radar (InSAR) results from early 2007 to late 2010 which were provided in a previous study. By performing a comparison analysis between theoretical evaluations of compaction for borehole data and InSAR observations, we were able to quantify subsidence due to sediment compaction. The comparison results suggest that the theoretical solutions agreed well with the measurements recorded by the well-validated, advanced InSAR method and that the deviations between the InSAR technique and geotechnical evaluations ranged from −22 to 3 mm. The results reveal that the land subsidence of the chosen borehole sites during the investigative period was dominated by the primary consolidation and compaction of sediment. The underprediction of subsidence may be explained by fluid withdrawal, oil exploitation and engineering construction. To speculate, more geological disasters may occur if the current subsidence condition extends into the future. [ABSTRACT FROM AUTHOR]

Arctic sea ice cover has decreased dramatically over the last three decades. This study quantifies the sea ice concentration (SIC) trends in the Arctic Ocean over the period of 1979–2016 and analyzes their spatial and temporal variations. During each month the SIC trends are negative over the Arctic Ocean, wherein the largest (smallest) rate of decline found in September (March) is -0.48%/a (-0.10%/a). The summer (-0.42%/a) and autumn (-0.31%/a) seasons show faster decrease rates than those of winter (-0.12%/a) and spring (-0.20%/a) seasons. Regional variability is large in the annual SIC trend. The largest SIC trends are observed for the Kara (-0.60%/a) and Barents Seas (-0.54%/a), followed by the Chukchi Sea (-0.48%/a), East Siberian Sea (-0.43%/a), Laptev Sea (-0.38%/a), and Beaufort Sea (-0.36%/a). The annual SIC trend for the whole Arctic Ocean is -0.26%/a over the same period. Furthermore, the infl uences and feedbacks between the SIC and three climate indexes and three climatic parameters, including the Arctic Oscillation (AO), North Atlantic Oscillation (NAO), Dipole anomaly (DA), sea surface temperature (SST), surface air temperature (SAT), and surface wind (SW), are investigated. Statistically, sea ice provides memory for the Arctic climate system so that changes in SIC driven by the climate indices (AO, NAO and DA) can be felt during the ensuing seasons. Positive SST trends can cause greater SIC reductions, which is observed in the Greenland and Barents Seas during the autumn and winter. In contrast, the removal of sea ice (i.e., loss of the insulating layer) likely contributes to a colder sea surface (i.e., decreased SST), as is observed in northern Barents Sea. Decreasing SIC trends can lead to an in-phase enhancement of SAT, while SAT variations seem to have a lagged infl uence on SIC trends. SW plays an important role in the modulating SIC trends in two ways: by transporting moist and warm air that melts sea ice in peripheral seas (typically evident inthe Barents Sea) and by exporting sea ice out of the Arctic Ocean via passages into the Greenland and Barents Seas, including the Fram Strait, the passage between Svalbard and Franz Josef Land (S-FJL), and the passage between Franz Josef Land and Severnaya Zemlya (FJL-SZ). [ABSTRACT FROM AUTHOR]

The Fram Strait (FS) is the primary region of sea ice export from the Arctic Ocean and thus plays an important role in regulating the amount of sea ice and fresh water entering the North Atlantic seas. A 5 a (2011-2015) sea ice thickness record retrieved from CryoSat-2 observations is used to derive a sea ice volume flux via the FS. Over this period, a mean winter accumulative volume flux (WAVF) based on sea ice drift data derived from passivemicrowave measurements, which are provided by the National Snow and Ice Data Center (NSIDC) and the Institut Francais de Recherche pour d’Exploitation de la Mer (IFREMER), amounts to 1 029 km3 (NSIDC) and 1 463 km3 (IFREMER), respectively. For this period, a mean monthly volume flux (area flux) difference between the estimates derived from the NSIDC and IFREMER drift data is-62 km3 per month (-18×106 km2 per month). Analysis reveals that this negative bias is mainly attributable to faster IFREMER drift speeds in comparison with slower NSIDC drift data. NSIDC-based sea ice volume flux estimates are compared with the results from the University of Bremen (UB), and the two products agree relatively well with a mean monthly bias of (5.7±45.9) km3 per month for the period from January 2011 to August 2013. IFREMER-based volume flux is also in good agreement with previous results of the 1990s. Compared with P1 (1990/1991-1993/1994) and P2 (2003/2004-2007/2008), the WAVF estimates indicate a decline of more than 600 km3 in P3 (2011/2012-2014/2015). Over the three periods, the variability and the decline in the sea ice volume flux are mainly attributable to sea ice motion changes, and second to sea ice thickness changes, and the least to sea ice concentration variations. [ABSTRACT FROM AUTHOR]

Satellite remote sensing provides new insight into the large-scale changes within the Arctic sea ice cover. In this study, satellite-derived sea ice parameters (thickness and age) were explored to investigate age-dependent Arctic sea ice volume changes. Between 2003–2008 (ICESat) and 2011–2015 (CyroSat-2), Arctic Ocean sea ice experienced a net depletion of roughly ${\text{4.68}}\times {\text{10}}^{3}\,{\text{km}}^{3}$ during autumn (October–November) and about 87% (or ${\text{4.11}}\times {\text{10}}^{3}\,{\text{km}}^{3}$ ) is caused by the removal in multiyear ice (two years and older). In spring (February–March), the net ice depletion amounts to ${\text{1.46}}\times {\text{10}}^{3}\,{\text{km}}^{3}$ , with the multiyear ice loss of ${\text{3.74}}\times {\text{10}}^{3}\,{\text{km}}^{3}$ and seasonal ice increment of ${\text{2.24}}\times {\text{10}}^{3}\,{\text{km}}^{3}$. Among multiyear ice loss, about 74% (autumn) and 93% (spring) of the loss were attributable to the depletion of the oldest ice type (5 years and older). Analyses also affirm that the marvelous volume loss of multiyear ice during cold months (October–May) in 2006/2007 and 2011/2012, along with the low replenishment of perennial ice as noted in the following autumns in 2007 and 2012, plays a major role in leading to a younger Arctic sea ice cover. Consequently, these processes together favors for the overall substantial volume loss observed in the Arctic sea ice cover. [ABSTRACT FROM AUTHOR]

Sea ice is a quite sensitive indicator in response to regional and global climate changes. Based on monthly mean Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) sea ice thickness fields, we computed the conductive heat flux (CHF) in the Arctic Ocean in the four winter months (November-February) for a long period of 36 years (1979-2014). The calculated results for each month manifest the increasing extension of the domain with high CHF values since 1979 till 2014. In 2014, regions of roughly 90% of the central Arctic Ocean have been dominated by the CHF values larger than 18 W m (November-December) and 12 W m (January-February), especially significant in the shelf seas around the Arctic Ocean. Moreover, the population distribution frequency (PDF) patterns of the CHF with time show gradually peak shifting toward increased CHF values. The spatiotemporal patterns in terms of the trends in sea ice thickness and other three geophysical parameters, surface air temperature (SAT), sea ice thickness (SIT), and CHF, are well coupled. This suggests that the thinner sea ice cover preconditions for the more oceanic heat loss into atmosphere (as suggested by increased CHF values), which probably contributes to warmer atmosphere which in turn in the long run will cause thinner ice cover. This represents a positive feedback mechanism of which the overall effects would amplify the Arctic climate changes. [ABSTRACT FROM AUTHOR]

By combing satellite-derived ice motion and concentration with ice thickness fields from a popular model PIOMAS we obtain the estimates of ice volume flux passing the Fram Strait over the 1979-2012 period. Since current satellite and field observations for sea ice thickness are limited in time and space, the use of PIOMAS is expected to fill the gap by providing temporally continued ice thickness fields. Calculated monthly volume flux exhibits a prominent annual cycle with the peak record in March (roughly 145 km/month) and the trough in August (10 km/month). Annual ice volume flux (1 132 km) is primarily attributable to winter (October through May) outflow (approximately 92%). Uncertainty in annual ice volume export is estimated to be 55 km (or 5.7%). Our results also verified the extremely large volume flux appearing between late 1980s and mid- 1990s. Nevertheless, no clear trend was found in our volume flux results. Ice motion is the primary factor in the determination of behavior of volume flux. Ice thickness presented a general decline trend may partly enhance or weaken the volume flux trend. Ice concentration exerted the least influences on modulating trends and variability in volume flux. Moreover, the linkage between winter ice volume flux and three established Arctic atmospheric schemes were examined. Compared to NAO, the DA and EOF3 mechanism explains a larger part of variations of ice volume flux across the strait. [ABSTRACT FROM AUTHOR]

The Yellow River delta, the second largest oil and gas base of China, has been subsiding due to the combination effects of human and natural factors. Increasing anthropogenic activities, like hydrocarbon exploitation, accelerate the subsidence, gradually threatening the stability of infrastructures and causing the inhabitants more vulnerable to natural hazards. Interferometric synthetic aperture radar (InSAR) techniques can measure ground movements in high resolution. The purpose of this study is to map the spatial and temporal variations in surface deformation over the Yellow River delta using a Small Baseline Subset InSAR technique and to assess the role of hydrocarbon exploitation in subsidence. The Stanford Method for Persistent Scatterers/Multi-Temporal InSAR (StaMPS/MTI) package is employed to process ENVISAT ASAR images collected from 2007 to 2010. InSAR-derived surface deformation measurements are then compared to geological and petroleum geologic data, oil field data and hydrocarbon reservoir inversion information to address the causes of the observed subsidence. Spirit leveling data and standard deviation maps are used to verify the InSAR results and measurement accuracy. Consistent results of the two descending tracks indicate subsidence up to 40 mm/yr over oil field. The time-series deformation manifests that subsidence area and peak broaden over time and subsidence rate are approximately constant in Shikou oil field, while the rate decreases in Dongying oil field since 2009. Moreover, our results indicate that the land subsidence pattern is concentrated in hydrocarbon exploration field and has a good consistency with faults distributions. In addition, a multiple finite prolate ellipsoid sources model is implemented to model the InSAR-derived deformation in Shikou oil field. The model manifests that land subsidence and hydrocarbon exploitation can be quantitatively linked to each other. The intimate connection of surface deformation with reservoir change suggests that land subsidence over oil field in the Yellow River delta is primarily caused by hydrocarbon exploitation. The results provide new insights into the land subsidence mechanism in the Yellow River delta. [ABSTRACT FROM AUTHOR]

In this study, changes in Arctic sea ice thickness for each ice age category were examined based on satellite observations and modelled results. Interannual changes obtained from Ice, Cloud, and Land Elevation Satellite (ICESat)-based results show a thickness reduction over perennial sea ice (ice that survives at least one melt season with an age of no less than 2 year) up to approximately 0.5-1.0 m and 0.6-0.8 m (depending on ice age) during the investigated winter and autumn ICESat periods, respectively. Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS)-based results provide a view of a continued thickness reduction over the past four decades. Compared to 1980s, there is a clear thickness drop of roughly 0.50 m in 2010s for perennial ice. This overall decrease in sea ice thickness can be in part attributed to the amplified warming climate in north latitudes. Besides, we figure out that strongly anomalous southerly summer surface winds may play an important role in prompting the thickness decline in perennial ice zone through transporting heat deposited in open water (primarily via albedo feedback) in Eurasian sector deep into a broader sea ice regime in central Arctic Ocean. This heat source is responsible for enhanced ice bottom melting, leading to further reduction in ice thickness. [ABSTRACT FROM AUTHOR]

The culture of suspended kelp, such as Laminaria japonica Aresch, has arisen in nearshore areas for approximately 30 years since the 1980s. This long-term activity has significant impact on the regional hydrodynamic and sedimentary environments. In this study the impact was investigated, based on synchronized multi-station data from continuous observations made within and around the culture area. In total, three current velocity profiles were identified inside and on the landward side of the culture area. Based on the current velocity profiles we calculated the boundary layer parameters, the fluxes of erosion/deposition, and the rate of sediment transport in different times at each observation site. Comparison between culture and non-culture periods showed that the presence of suspended kelp caused the reduction in the average flow velocity by approximately 49.5%, the bottom friction velocity by 24.8%, the seabed roughness length by 62.7%, and the shear stress and the flux of resuspended sediment by approximately 50%. From analyses in combination with the corresponding vertical variation of the suspended sediment distribution, it is revealed that the lifted sediments by resuspension is mixed with the upper suspended material, which will modify the regional distribution of suspended sediment. These changes in flow structure and sediment movement will accelerate seabed siltation, which corresponds to the changes in seabed erosion/deposition. However, under the influences of the seasonal changes in kelp growth the magnitude of change with the seabed siltation was not obvious inside the culture area, but a fundamental change was apparent around the culture area. [ABSTRACT FROM AUTHOR]

By combing ice motion and concentration fields, we obtain the estimates of ice area flux passing the Fram Strait over a 25-year period (1988–2012). Mean monthly area flux exhibits a prominent cycle with the peak in March \rm(78 \times 10^3\,\textkm^2\text/month) and the trough in August \rm(5 \times 10^3\,\textkm^2/\textmonth). Mean net annual ice area flux \rm(644.1 \times 10^3\,\textkm^2\,\textkm^2\rm) is primarily/slightly attributable to winter (October–May)/summer (June–September) outflow of \rm598.7\times 10^3\,\textkm^2 \rm(or\; 93.0\%)/ 45.4 \times 10^3\,\textkm^2 (\rmor 7\%) . However, these quantities need to be considered with great prudence since comparisons with preceding studies indicate distinct difference may exist between calculated Fram Strait sea ice outflow based on varied ice motion datasets. In particular, major bias emerged during winter rather than summer. Trends are also affected due to this bias. Despite the clear disparity in magnitude, we found a good agreement with preceding estimates in terms of temporal variability. The linkage between ice area flux via the Fram Strait and various atmospheric circulation indices, such as the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), a west-east dipole anomaly pattern (DA), as well as a seesaw structure between Beaufort and Barents Sea (BBO), was examined. Results show that atmospheric circulation patterns linked to the DA and BBO possess a relatively stronger influence on Fram Strait ice export over the 25-year period. By contrast, the AO- and NAO-related atmospheric circulation pattern exhibit weaker connections with ice outflow through the strait. In addition, correlation analysis further justify the robust connection with a cross-strait surface level pressure gradient index. Depending on months, it is suggested that a manifold of aforementioned atmospheric indices may jointly or alone impose a significant influence on sea ice export through the Fram Strait. [ABSTRACT FROM PUBLISHER]

Sea-ice outflow from the Laptev Sea is of considerable importance in maintaining the Arctic Ocean sea-ice budget. In this study, a method exclusively using multiple satellite observations is used to calculate sea-ice volume flux across the eastern boundary (EB) and northern boundary (NB) of the Laptev Sea during the October–November and February–March or March–April periods (corresponding to the ICESat autumn and winter campaigns) between 2003 and 2008. Seasonally, the mean total ice volume flux (i.e., NB+EB) over the investigated autumn period (1.96 km3/day) is less than that over the winter period (2.57 km3/day). On the other hand, the large standard deviations of the total volume flux, 3.45 and 0.91 km3/day for the autumn and winter campaigns, indicate significant interannual fluctuations in the calculated quantities. A statistically significant (P>0.99) positive correlation, R=0.88 (or 0.81), is obtained between volume flux across the EB (or NB) and mean ice-drift speed over the boundary for the considered 11 ICESat campaigns. In addition, statistics show that a large fraction of the variability in volume flux across the NB over the 11 investigated campaigns, roughly 40%, is likely explained by ice thickness variability. On average, flux through the Laptev Sea amounts to approximately one-third of that across Fram Strait during the autumn and winter campaigns. These large contributions of sea ice from the Laptev Sea demonstrate its importance as an ice source, affecting the entire sea-ice mass balance in the Arctic Ocean. [ABSTRACT FROM AUTHOR]

A modified algorithm taking into account the first year (FY) and multiyear (MY) ice densities is used to derive a sea ice thickness from freeboard measurements acquired by satellite altimetry ICESat (2003-2008). Estimates agree with various independent in situ measurements within 0.21 m. Both the fall and winter campaigns see a dramatic extent retreat of thicker MY ice that survives at least one summer melting season. There were strong seasonal and interannual variabilities with regard to the mean thickness. Seasonal increases of 0.53 m for FY the ice and 0.29 m for the MY ice between the autumn and the winter ICESat campaigns, roughly 4-5 month separation, were found. Interannually, the significant MY ice thickness declines over the consecutive four ICESat winter campaigns (2005-2008) leads to a pronounced thickness drop of 0.8 m in MY sea ice zones. No clear trend was identified from the averaged thickness of thinner, FY ice that emerges in autumn and winter and melts in summer. Uncertainty estimates for our calculated thickness, caused by the standard deviations of multiple input parameters including freeboard, ice density, snow density, snow depth, show large errors more than 0.5 m in thicker MY ice zones and relatively small standard deviations under 0.5 m elsewhere. Moreover, a sensitivity analysis is implemented to determine the separate impact on the thickness estimate in the dependence of an individual input variable as mentioned above. The results show systematic bias of the estimated ice thickness appears to be mainly caused by the variations of freeboard as well as the ice density whereas the snow density and depth brings about relatively insignificant errors. [ABSTRACT FROM AUTHOR]

The traditional method of Synthetic Aperture Radar (SAR) wind field retrieval is based on an empirical relation between the near surface winds and the normalized radar backscatter cross section to estimate wind speeds, where this relation is called the geophysical model function (GMF). However, the accuracy rapidly decreases due to the impact of rainfall on the measurement of SAR and the saturation of backscattered intensity under the condition of tropical cyclone. Because of no available instrument synchronously monitoring rain rate on the satellite platform of SAR, we have to derive the precipitation of the SAR observation time from non-simultaneous passive microwave observations of rain in combination with geostationary IR images, and then use the model of rain correction to remove the impact of rain on SAR wind field measurements. For the saturation of radar backscatter cross section in high wind speed conditions, we develop an approach to estimate tropical cyclone parameters and wind fields based on the improved Holland model and the SAR image features of tropical cyclone. To retrieve the low-to-moderate wind speed, the wind direction of tropical cyclone is estimated from the SAR image using wavelet analysis. And then the maximum wind speed and the central pressure of tropical cyclone are calculated by a least square minimization of the difference between the improved Holland model and the low-to-moderate wind speed retrieved from SAR. In addition, wind fields are estimated from the improved Holland model using the above-mentioned parameters of tropical cyclone as input. To evaluate the accuracy of our approach, the SAR images of typhoon Aere, typhoon Khanun, and hurricane Ophelia are used to estimate tropical cyclone parameters and wind fields, which are compared with the best track data and reanalyzed wind fields of the Joint Typhoon Warning Center (JTWC) and the Hurricane Research Division (HRD). The results indicate that the tropical cyclone center, maximum wind speed, and central pressure are generally consistent with the best track data, and wind fields agree well with reanalyzed data from HRD. [ABSTRACT FROM AUTHOR]

Sea-ice concentration is a key item in global climate change research. Recent progress in remotely sensed sea-ice concentration product has been stimulated by the use of a new sensor, advanced microwave scanning radiometer for EOS (AMSR-E), which offers a spatial resolution of 6 km×4 km at 89GHz. A new inversion algorithm named LASI (linear ASI) using AMSR-E 89GHz data was proposed and applied in the antarctic sea areas. And then comparisons between the LASI ice concentration products and those retrieved by the other two standard algorithms, ASI (arctic radiation and turbulence interaction study sea-ice algorithm) and bootstrap, were made. Both the spatial and temporal variability patterns of ice concentration differences, LASI minus ASI and LASI minus bootstrap, were investigated. Comparative data suggest a high result consistency, especially between LASI and ASI. On the other hand, in order to estimate the LASI ice concentration errors introduced by the tie-points uncertainties, a sensitivity analysis was carried out. Additionally an LASI algorithm error estimation based on the field measurements was also completed. The errors suggest that the moderate to high ice concentration areas (>70%) are less affected (never exceeding 10%) than those in the low ice concentration. LASI and ASI consume 75 and 112 s respectively when processing the same AMSR-E time series thourghout the year 2010. To conclude, by using the LASI algorithm, not only the seaice concentration can be retrieved with at least an equal quality as that of the two extensively demonstrated operational algorithms, ASI and bootstrap, but also in a more efficient way than ASI. [ABSTRACT FROM AUTHOR]

The affiliations of the authors of this article unfortunately contained a mistake. [ABSTRACT FROM AUTHOR]

The power law particle size distribution (PSD) slope parameter is commonly used to characterize sediment fluxes, resuspension, aggregates, and settling rates in coastal and estuarine waters. However, particle size distribution metrics are also very useful for understanding sediment source and dynamic processes. In this study, a method was proposed to employ the particle size parameters commonly used in sedimentary geology (average particle size (ø), sorting, skewness, and kurtosis) as indicators of changes in sediment dynamic processes, and MODIS images were used to estimate these parameters. The particle size parameters were estimated using a Mie scattering model, Quasi-Analytical Algorithm (QAA) analysis algorithm, and least squares QR decomposition (LSQR) solution method based on the relationship between the power law distribution of the suspended particles and their optical scattering properties. The estimates were verified by field measurements in the Yellow Sea and Bohai Sea regions of China. This method provided good estimates of the average particle size (ø), sorting, and kurtosis. A greater number of wavebands (39) was associated with more accurate particle size distribution curves. Furthermore, the method was used to monitor changes in suspended particulate matter in the vicinity of the Heini Bay of China before and after the passage of a strong storm in August 2011. The particle size parameters represented the influence of a strong typhoon on the distribution of the near-shore sediment and, together with the PSD slope, comprehensively reflected the changes in the near-shore suspended particulate matter. This method not only established the relationship between remote sensing monitoring and the historical sediment record, it also extends the power law model to the application of sediment source and dynamic processes in coastal waters. [ABSTRACT FROM AUTHOR]