scholarly journals Annually-Averaged Polar Sea-Ice Extents During 1978–1987: Northern Extent Decrease and Southern Extent Oscillation

1990 ◽  
Vol 14 ◽  
pp. 336
Author(s):  
Per Gloersen ◽  
William J. Campbell
Keyword(s):  
Sea Ice ◽  
Goodness Of Fit ◽  
El Nino ◽  
Microwave Radiometer ◽  
Small Oscillation ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
El Niño Events ◽  
El Nino Events

Recently reported observations of a nine-year decrease in global sea-ice extent, obtained from the Scanning Multichannel Microwave Radiometer onboard the Nimbus-7 satellite during 1978–87 and averaged with an annual running mean, have been separated into Arctic and Antarctic components. The annually-averaged global extent decrease was 2.5%. Here it is shown that the greater part of this decrease occurred in the Arctic where there was a decline of 3.5% with a goodness of fit of 0.54. Superimposed on this decline was a small oscillation with a period of about four years and an amplitude of about 1%. A significantly smaller and statistically insignificant decrease of 1.2% with a goodness of fit of 0.03 is observed in the annually averaged Antarctic sea-ice extent. However, three large oscillations with amplitudes of about 4% and periods of about three years occurred in phase with three El Niño events.

scholarly journals Annually-Averaged Polar Sea-Ice Extents During 1978–1987: Northern Extent Decrease and Southern Extent Oscillation

1990 ◽  
Vol 14 ◽  
pp. 336-336
Author(s):  
Per Gloersen ◽  
William J. Campbell
Keyword(s):  
Sea Ice ◽  
Goodness Of Fit ◽  
El Nino ◽  
Microwave Radiometer ◽  
Small Oscillation ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
El Niño Events ◽  
El Nino Events

Recently reported observations of a nine-year decrease in global sea-ice extent, obtained from the Scanning Multichannel Microwave Radiometer onboard the Nimbus-7 satellite during 1978–87 and averaged with an annual running mean, have been separated into Arctic and Antarctic components. The annually-averaged global extent decrease was 2.5%. Here it is shown that the greater part of this decrease occurred in the Arctic where there was a decline of 3.5% with a goodness of fit of 0.54.Superimposed on this decline was a small oscillation with a period of about four years and an amplitude of about 1%. A significantly smaller and statistically insignificant decrease of 1.2% with a goodness of fit of 0.03 is observed in the annually averaged Antarctic sea-ice extent. However, three large oscillations with amplitudes of about 4% and periods of about three years occurred in phase with three El Niño events.

scholarly journals Sea Ice Concentration and Sea Ice Extent Mapping with L-Band Microwave Radiometry and GNSS-R Data from the FFSCat Mission Using Neural Networks

2021 ◽  
Vol 13 (6) ◽  
pp. 1139
Author(s):  
David Llaveria ◽  
Juan Francesc Munoz-Martin ◽  
Christoph Herbert ◽  
Miriam Pablos ◽  
Hyuk Park ◽  
...  
Keyword(s):  
Sea Ice ◽  
Microwave Radiometer ◽  
Cost Effective ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Neural Network Approach ◽  
Ice Concentration ◽  
L Band ◽  
Moderate Cost

CubeSat-based Earth Observation missions have emerged in recent times, achieving scientifically valuable data at a moderate cost. FSSCat is a two 6U CubeSats mission, winner of the ESA S3 challenge and overall winner of the 2017 Copernicus Masters Competition, that was launched in September 2020. The first satellite, 3Cat-5/A, carries the FMPL-2 instrument, an L-band microwave radiometer and a GNSS-Reflectometer. This work presents a neural network approach for retrieving sea ice concentration and sea ice extent maps on the Arctic and the Antarctic oceans using FMPL-2 data. The results from the first months of operations are presented and analyzed, and the quality of the retrieved maps is assessed by comparing them with other existing sea ice concentration maps. As compared to OSI SAF products, the overall accuracy for the sea ice extent maps is greater than 97% using MWR data, and up to 99% when using combined GNSS-R and MWR data. In the case of Sea ice concentration, the absolute errors are lower than 5%, with MWR and lower than 3% combining it with the GNSS-R. The total extent area computed using this methodology is close, with 2.5% difference, to those computed by other well consolidated algorithms, such as OSI SAF or NSIDC. The approach presented for estimating sea ice extent and concentration maps is a cost-effective alternative, and using a constellation of CubeSats, it can be further improved.

Different responses of Central Asian precipitation to strong and weak El Niño events

2021 ◽  
pp. 1-60
Keyword(s):  
Soil Moisture ◽  
Central Asia ◽  
El Niño ◽  
El Nino ◽  
Moisture Flux ◽  
The Arctic ◽  
Central Asian ◽  
El Niño Events ◽  
Sst Anomalies ◽  
El Nino Events

Abstract The present study investigated impacts of strong and weak El Niño events on Central Asian precipitation variability from El Niño developing years to decaying years. It is found that strong El Niño events persistently enhance Central Asian precipitation from the mature winter to decaying summer. Large warm sea surface temperature (SST) anomalies in the tropical central-eastern Pacific induce anomalous upper-level divergence and updraft over Central Asia through large-scale convergence and divergence in the mature winter and decaying spring. Meanwhile, the associated wind anomalies induce anomalous eastward and northeastward moisture flux from the North Atlantic and Arabian Sea to Central Asia. Both anomalous ascent and moisture flux convergence favor above-normal precipitation over Central Asia in the mature winter and decaying spring. The El Niño events induced Central Asian precipitation anomalies are extended to the decaying summer due to the role of soil moisture. Increased rainfall in winter and spring enhances soil moisture in the following summer, which in turn, contributes to more precipitation in summer through modulating regional evaporation. During weak El Niño events, significant wet anomalies are only seen in the developing autumn, which result from anomalous southeastward moisture flux from the Arctic Ocean, and the abnormal signals are weak in the other seasons. The different responses of Central Asian precipitation to strong and weak El Niño events may be attributed to the difference in intensity of tropical SST anomalies between the two types of events.

scholarly journals Antarctic sea ice decline delayed well into the 21st century in a high-resolution climate projection

2020 ◽  
Author(s):  
Thomas Rackow ◽  
Sergey Danilov ◽  
Helge F. Goessling ◽  
Hartmut H. Hellmer ◽  
Dmitry V. Sein ◽  
...  
Keyword(s):  
Global Warming ◽  
High Resolution ◽  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
The Arctic ◽  
Alternative Mechanism ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Sea Ice Decline

<p>Despite ongoing global warming and strong sea ice decline in the Arctic, the sea ice extent around the Antarctic continent has not declined during the satellite era since 1979. This is in stark contrast to existing climate models that tend to show a strong negative sea ice trend for the same period; hence the confidence in projected Antarctic sea-ice changes is considered to be low. In the years since 2016, there has been significantly lower Antarctic sea ice extent, which some consider a sign of imminent change; however, others have argued that sea ice extent is expected to regress to the weak decadal trend in the near future.</p><p>In this presentation, we show results from climate change projections with a new climate model that allows the simulation of mesoscale eddies in dynamically active ocean regions in a computationally efficient way. We find that the high-resolution configuration (HR) favours periods of stable Antarctic sea ice extent in September as observed over the satellite era. Sea ice is not projected to decline well into the 21<sup>st</sup> century in the HR simulations, which is similar to the delaying effect of, e.g., added glacial melt water in recent studies. The HR ocean configurations simulate an ocean heat transport that responds differently to global warming and is more efficient at moderating the anthropogenic warming of the Southern Ocean. As a consequence, decrease of Antarctic sea ice extent is significantly delayed, in contrast to what existing coarser-resolution climate models predict.</p><p>Other explanations why current models simulate a non-observed decline of Antarctic sea-ice have been put forward, including the choice of included sea ice physics and underestimated simulated trends in westerly winds. Our results provide an alternative mechanism that might be strong enough to explain the gap between modeled and observed trends alone.</p>

scholarly journals Sea ice and water classification on dual-polarized Sentinel-1 imagery during melting season

2021 ◽  
Author(s):  
Yu Zhang ◽  
Tingting Zhu ◽  
Gunnar Spreen ◽  
Christian Melsheimer ◽  
Marcus Huntemann ◽  
...  
Keyword(s):  
Sea Ice ◽  
Microwave Radiometer ◽  
The Arctic ◽  
Fram Strait ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Water Classification ◽  
Sar Data ◽  
Ice Water ◽  
Melting Season

Abstract. We provide a new sea ice and water classification product with high spatial and high temporal coverage using Sentinel-1 Synthetic Aperture Radar (SAR) data. The classification is applied in the Fram Strait region in the Arctic during melting seasons, when the contrast between backscatter intensities of different ice types observed by SAR is reduced due to the melted ice surface and wet snow on sea ice. The wet or melted snow strongly reduces the SAR penetration depth and thus suppresses the volume scattering contribution of sea ice. Furthermore, within the marginal sea ice zone (MIZ)ambiguities between ice and water can result from the effects of winds and ocean currents on the ocean SAR backscatter. On the other hand, under calm conditions the contrast between thin ice and flat open water can be reduced, and thusdecrease the separability of some ice. In summary, the melting season represents the most challenging time of the year forreliable ice-water classification from SAR data. We propose here a new approach to overcome these problems by using amixture statistical distribution based conditional random fields (MSTA-CRF) model. To obtain reliable ice-waterclassification whilst maintaining a fast computation time suitable for operational applications, the MSTA-CRF adopts a superpixel approach in the fully connected CRF model. The MSTA-CRF is a semantic model, which integrates statisticaldistributions (Gamma, Weibull, Alpha-Stable, etc.) to model the backscatters of ice and water and overcome the effects ofspeckle noise and wind-roughened water. Dual-polarization Extended Wide (EW) mode Sentinel-1A/1B SAR data with40 m spatial resolution is available several times per day within the Fram Strait region. Observations from June toSeptember during the six years 2015–2020 are collected and classified into ice and water categories. The classification performance of algorithm is evaluated using ice charts from the Ice Service at the Norwegian Meteorological Institute(MET Norway). The methods of training sample selection, and their application to processing large data volumes andautomatic classification of ice-water are discussed. In the experiment part, we demonstrate that the MSTA-CRF can providea good performance with about 90 % accuracy for ice-water classification, which is better than most of other state-of-theart algorithms. Compared with the 89 GHz microwave radiometer ASI sea ice concentration product, the sea ice extent in Fram Strait derived from MSTA-CRF algorithm is lower during melting seasons from 2015 to 2020, and the monthly Juneto September sea ice area does not change so much in 2015–2017 and 2019–2020, but it has a significant decrease in 2018.

scholarly journals A Regime Shift in Seasonal Total Antarctic Sea Ice Extent in the 20th Century

2021 ◽  
Author(s):  
Ryan Fogt ◽  
Amanda Sleinkofer ◽  
Marilyn Raphael ◽  
Mark Handcock
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
Climate Models ◽  
Historical Context ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Coupled Climate Models ◽  
High Degree ◽  
The Antarctic

Abstract In stark contrast to the Arctic, there have been statistically significant positive trends in total Antarctic sea ice extent since 1979, despite a sudden decline in sea ice in 2016(1–5) and increasing greenhouse gas concentrations. Attributing Antarctic sea ice trends is complicated by the fact that most coupled climate models show negative trends in sea ice extent since 1979, opposite of that observed(6–8). Additionally, the short record of sea ice extent (beginning in 1979), coupled with the high degree of interannual variability, make the record too short to fully understand the historical context of these recent changes(9). Here we show, using new robust observation-based reconstructions, that 1) these observed recent increases in Antarctic sea ice extent are unique in the context of the 20th century and 2) the observed trends are juxtaposed against statistically significant decreases in sea ice extent throughout much of the early and middle 20th century. These reconstructions are the first to provide reliable estimates of total sea ice extent surrounding the continent; previous proxy-based reconstructions are limited(10). Importantly, the reconstructions continue to show the high degree of interannual Antarctic sea ice extent variability that is marked with frequent sudden changes, such as observed in 2016, which stress the importance of a longer historical context when assessing and attributing observed trends in Antarctic climate(9). Our reconstructions are skillful enough to be used in climate models to allow better understanding of the interconnected nature of the Antarctic climate system and to improve predictions of the future state of Antarctic climate.

scholarly journals Influence of Arctic sea-ice variability on Pacific trade winds

2020 ◽  
Vol 117 (6) ◽  
pp. 2824-2834 ◽  
Author(s):  
Charles F. Kennel ◽  
Elena Yulaeva
Keyword(s):  
Sea Ice ◽  
El Niño ◽  
El Nino ◽  
Arctic Sea Ice ◽  
Central Pacific ◽  
Central Pacific El Niño ◽  
Trade Winds ◽  
Upper Troposphere ◽  
El Niño Events ◽  
El Nino Events

A conceptual model connecting seasonal loss of Arctic sea ice to midlatitude extreme weather events is applied to the 21st-century intensification of Central Pacific trade winds, emergence of Central Pacific El Nino events, and weakening of the North Pacific Aleutian Low Circulation. According to the model, Arctic Ocean warming following the summer sea-ice melt drives vertical convection that perturbs the upper troposphere. Static stability calculations show that upward convection occurs in annual 40- to 45-d episodes over the seasonally ice-free areas of the Beaufort-to-Kara Sea arc. The episodes generate planetary waves and higher-frequency wave trains that transport momentum and heat southward in the upper troposphere. Regression of upper tropospheric circulation data on September sea-ice area indicates that convection episodes produce wave-mediated teleconnections between the maximum ice-loss region north of the Siberian Arctic coast and the Intertropical Convergence Zone (ITCZ). These teleconnections generate oppositely directed trade-wind anomalies in the Central and Eastern Pacific during boreal winter. The interaction of upper troposphere waves with the ITCZ air–sea column may also trigger Central Pacific El Nino events. Finally, waves reflected northward from the ITCZ air column and/or generated by triggered El Nino events may be responsible for the late winter weakening of the Aleutian Low Circulation in recent years.

Arctic Sea Ice Loss as a Potential Trigger for Central Pacific El Niño Events

2020 ◽  
Vol 47 (7) ◽  
Author(s):  
Hyerim Kim ◽  
Sang‐Wook Yeh ◽  
Soon‐Il An ◽  
Jae‐Heung Park ◽  
Baek‐Min Kim ◽  
...  
Keyword(s):  
Sea Ice ◽  
El Nino ◽  
Arctic Sea Ice ◽  
Central Pacific ◽  
Central Pacific El Niño ◽  
Arctic Sea ◽  
Potential Trigger ◽  
El Niño Events ◽  
Arctic Sea Ice Loss ◽  
El Nino Events

scholarly journals A spurious jump in the satellite record: has Antarctic sea ice expansion been overestimated?

2014 ◽  
Vol 8 (4) ◽  
pp. 1289-1296 ◽  
Author(s):  
I. Eisenman ◽  
W. N. Meier ◽  
J. R. Norris
Keyword(s):  
Sea Ice ◽  
Ice Cover ◽  
Current Data ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Data Set ◽  
Antarctic Sea Ice ◽  
Ice Retreat ◽  
Bootstrap Algorithm ◽  
The Antarctic

Abstract. Recent estimates indicate that the Antarctic sea ice cover is expanding at a statistically significant rate with a magnitude one-third as large as the rapid rate of sea ice retreat in the Arctic. However, during the mid-2000s, with several fewer years in the observational record, the trend in Antarctic sea ice extent was reported to be considerably smaller and statistically indistinguishable from zero. Here, we show that much of the increase in the reported trend occurred due to the previously undocumented effect of a change in the way the satellite sea ice observations are processed for the widely used Bootstrap algorithm data set, rather than a physical increase in the rate of ice advance. Specifically, we find that a change in the intercalibration across a 1991 sensor transition when the data set was reprocessed in 2007 caused a substantial change in the long-term trend. Although our analysis does not definitively identify whether this change introduced an error or removed one, the resulting difference in the trends suggests that a substantial error exists in either the current data set or the version that was used prior to the mid-2000s, and numerous studies that have relied on these observations should be reexamined to determine the sensitivity of their results to this change in the data set. Furthermore, a number of recent studies have investigated physical mechanisms for the observed expansion of the Antarctic sea ice cover. The results of this analysis raise the possibility that much of this expansion may be a spurious artifact of an error in the processing of the satellite observations.

scholarly journals Antarctic summer sea ice concentration and extent: comparison of ODEN 2006 ship observations, satellite passive microwave and NIC sea ice charts

2008 ◽  
Vol 2 (4) ◽  
pp. 623-647 ◽  
Author(s):  
B. Ozsoy-Cicek ◽  
H. Xie ◽  
S. F. Ackley ◽  
K. Ye
Keyword(s):  
Sea Ice ◽  
Linear Trend ◽  
Passive Microwave ◽  
The Arctic ◽  
Poor Correlation ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Ice Concentration ◽  
Ice Edge

Abstract. Antarctic sea ice cover has shown a slight increase in overall observed ice extent as derived from satellite mapping from 1979 to 2008, contrary to the decline observed in the Arctic regions. Spatial and temporal variations of the Antarctic sea ice however remain a significant problem to monitor and understand, primarily due to the vastness and remoteness of the region. While satellite remote sensing has provided and has great future potential to monitor the variations and changes of sea ice, uncertainties remain unresolved. In this study, the National Ice Center (NIC) ice edge and the AMSR-E (Advanced Microwave Scanning Radiometer – Earth Observing System) ice extent are examined, while the ASPeCt (Antarctic Sea Ice Process and Climate) ship observations from the Oden expedition in December 2006 are used as ground truth to verify the two products during Antarctic summer. While there is a general linear trend between ASPeCt and AMSR-E ice concentration estimates, there is poor correlation (R2=0.41) and AMSR-E tends to underestimate the low ice concentrations. We also found that the NIC sea ice edge agrees well with ship observations, while the AMSR-E shows the ice edge further south, consistent with its poorer detection of low ice concentrations. The northward extent of the ice edge at the time of observation (NIC) had mean values varying from 38 km to 102 km greater on different days for the area as compared with the AMSR-E sea ice extent. For the circumpolar area as a whole in the December period examined, AMSR-E therefore underestimates the area inside the ice edge at this time by up to 14% or, 1.5 million km2 less area, compared to the NIC ice charts. These differences alone can account for more than half of the purported sea ice loss between the pre 1960s and the satellite era suggested earlier from comparative analysis of whale catch data with satellite derived data. Preliminary comparison of satellite scatterometer data suggests better resolution of low concentrations than passive microwave, and therefore better fidelity with ship observations and NIC charts of the area inside the ice edge during Antarctic summer.

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