scholarly journals Hemispheric sea ice extent dynamics as observed from MSMR

MAUSAM ◽  
2021 ◽  
Vol 60 (3) ◽  
pp. 295-308
Author(s):  
NILAY SHARMA ◽  
M. K. DASH ◽  
P. C. PANDEY ◽  
N. K. VYAS

The ice covered regions of the polar seas influence the global climate in several ways. Any perturbation in the polar oceanic cryosphere affects the local weather and the global climate through modulation of the radiative forcing, the bottom water formation and the mass & the momentum transfer between Atmosphere-Cryosphere-Ocean System. The cold, harsh and inhospitable conditions in the polar regions prohibit the collection of extensive in situ data with sufficient spatial and temporal variation. However, satellite remote sensing is an ideal technique for studying the areas like the polar regions with synoptic and repetitive coverage.  This paper discusses the analysis of the data obtained over the polar oceanic regions during the period June 1999 – September 2001 through the use of Multi-channel Scanning Microwave Radiometer (MSMR), onboard India’s first oceanographic satellite Oceansat-1. The MSMR observation shows that all the sectors in the Antarctic behave differently to the melting and formation of the sea ice. Certain peculiar features like the increase in sea ice extent during the melt season of 1999 – 2000 in the Indian Ocean sector, 15 – 20% decrease in the sea ice extent in the western Pacific sector during the ice formation period for the year 2000, melting spell within the formation phase of sea ice in B & A sector in the year 2000 were observed. On the other hand the northern polar sea ice extent is seen to be more dominated by the land characteristics. The ice formation in Kara and the Barent Sea sector is dominated by the ocean currents, where as the ice covered in the Japan and the Okhotsk Sea is dominated by the land processes. The sea ice extent in the Arctic Ocean show fluctuations from July to October and remain almost steady over other months. The global sea ice cover shows a formation phase from March to June and melting phase from November to February. In other months, i.e., from July – October the global sea ice cover is dominated by the hemispheric asymmetry of the ice growth and retreat.

2018 ◽  
Author(s):  
Monica Ionita ◽  
Klaus Grosfeld ◽  
Patrick Scholz ◽  
Renate Treffeisen ◽  
Gerrit Lohmann

Abstract. Sea ice in both Polar Regions is an important indicator for the expression of global climate change and its polar amplification. Consequently, a broad interest exists on sea ice coverage, variability and long term change. However, its predictability is complex and it depends on various atmospheric and oceanic parameters. In order to provide insights into the potential development of a monthly/seasonal signal of sea ice evolution, we developed a robust statistical model based on oceanic and different atmospheric variables to calculate an estimate of the September sea ice extent (SSIE) on monthly time scale. Although previous statistical attempts of monthly/seasonal SSIE forecasts show a relatively reduced skill, when the trend is removed, we show here that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' atmospheric and oceanic conditions. Our statistical model skillfully captures the interannual variability of the SSIE and could provide a valuable tool for identifying relevant regions and atmospheric parameters that are important for the sea ice development in the Arctic and for detecting sensitive and critical regions in global coupled climate models with focus on sea ice formation.


2020 ◽  
Vol 12 (18) ◽  
pp. 2880
Author(s):  
Shuang Liang ◽  
Jiangyuan Zeng ◽  
Zhen Li ◽  
Dejing Qiao ◽  
Ping Zhang ◽  
...  

Sea ice concentration (SIC) plays a significant role in climate change research and ship’s navigation in polar regions. Satellite-based SIC products have become increasingly abundant in recent years; however, the uncertainty of these products still exists and needs to be further investigated. To comprehensively evaluate the consistency of the SIC derived from different SIC algorithms in long time series and the whole polar regions, we compared four passive microwave (PM) satellite SIC products with the ERA-Interim sea ice fraction dataset during the period of 2015–2018. The PM SIC products include the SSMIS/ASI, AMSR2/BT, the Chinese FY3B/NT2, and FY3C/NT2. The results show that the remotely sensed SIC products derived from different SIC algorithms are generally in good consistency. The spatial and temporal distribution of discrepancy among satellite SIC products for both Arctic and Antarctic regions are also observed. The most noticeable difference for all the four SIC products mostly occurs in summer and at the marginal ice zone, indicating that large uncertainties exist in satellite SIC products in such period and areas. The SSMIS/ASI and AMSR2/BT show relatively better consistency with ERA-Interim in the Arctic and Antarctic, respectively, but they exhibit opposite bias (dry/wet) relative to the ERA-Interim data. The sea ice extent (SIE) and sea ice area (SIA) derived from PM and ERA-Interim SIC were also compared. It is found that the difference of PM SIE and SIA varies seasonally, which is in line with that of PM SIC, and the discrepancy between PM and ERA-Interim data is larger in Arctic than in Antarctic. We also noticed that different algorithms have different performances in different regions and periods; therefore, the hybrid of multiple algorithms is a promising way to improve the accuracy of SIC retrievals. It is expected that our findings can contribute to improving the satellite SIC algorithms and thus promote the application of these useful products in global climate change studies.


2021 ◽  
Vol 13 (8) ◽  
pp. 1570
Author(s):  
Sarah B. Hall ◽  
Bulusu Subrahmanyam ◽  
Ebenezer S. Nyadjro ◽  
Annette Samuelsen

Freshwater (FW) flux between the Arctic Ocean and adjacent waterways, predominantly driven by wind and oceanic currents, influences halocline stability and annual sea ice variability which further impacts global circulation and climate. The Arctic recently experienced anomalous years of high and low sea ice extent in the summers of 2013/2014 and 2012/2016, respectively. Here we investigate the interannual variability of oceanic surface FW flux in relation to spatial and temporal variability in sea ice concentration (SIC), sea surface salinity (SSS), and sea surface temperature (SST), focusing on years with summer sea–ice extremes. Our analysis between 2010–2018 illustrate high parameter variability, especially within the Laptev, Kara, and Barents seas, as well as an overall decreasing trend of FW flux through the Fram Strait. We find that in 2012, a maximum average FW flux of 0.32 × 103 ms−1 in October passed over a large portion of the Northeast Atlantic Ocean at 53°N. This study highlights recent changes in the Arctic and Subarctic Seas and the importance of continued monitoring of key variables through remote sensing to understand the dynamics behind these ongoing changes. Observations of FW fluxes through major Arctic routes will be increasingly important as the polar regions become more susceptible to warming, with major impacts on global climate.


2012 ◽  
Vol 25 (5) ◽  
pp. 1431-1452 ◽  
Author(s):  
Alexandra Jahn ◽  
Kara Sterling ◽  
Marika M. Holland ◽  
Jennifer E. Kay ◽  
James A. Maslanik ◽  
...  

To establish how well the new Community Climate System Model, version 4 (CCSM4) simulates the properties of the Arctic sea ice and ocean, results from six CCSM4 twentieth-century ensemble simulations are compared here with the available data. It is found that the CCSM4 simulations capture most of the important climatological features of the Arctic sea ice and ocean state well, among them the sea ice thickness distribution, fraction of multiyear sea ice, and sea ice edge. The strongest bias exists in the simulated spring-to-fall sea ice motion field, the location of the Beaufort Gyre, and the temperature of the deep Arctic Ocean (below 250 m), which are caused by deficiencies in the simulation of the Arctic sea level pressure field and the lack of deep-water formation on the Arctic shelves. The observed decrease in the sea ice extent and the multiyear ice cover is well captured by the CCSM4. It is important to note, however, that the temporal evolution of the simulated Arctic sea ice cover over the satellite era is strongly influenced by internal variability. For example, while one ensemble member shows an even larger decrease in the sea ice extent over 1981–2005 than that observed, two ensemble members show no statistically significant trend over the same period. It is therefore important to compare the observed sea ice extent trend not just with the ensemble mean or a multimodel ensemble mean, but also with individual ensemble members, because of the strong imprint of internal variability on these relatively short trends.


2022 ◽  
Author(s):  
Qing-Bin Lu

Abstract Time-series observations of global lower stratospheric temperature (GLST), global land surface air temperature (LSAT), global mean surface temperature (GMST), sea ice extent (SIE) and snow cover extent (SCE), together with observations reported in Paper I, combined with theoretical calculations of GLSTs and GMSTs, have provided strong evidence that ozone depletion and global climate changes are dominantly caused by human-made halogen-containing ozone-depleting substances (ODSs) and greenhouse gases (GHGs) respectively. Both GLST and SCE have become constant since the mid-1990s and GMST/LSAT has reached a peak since the mid-2000s, while regional continued warmings at the Arctic coasts (particularly Russia and Alaska) in winter and spring and at some areas of Antarctica are observed and can be well explained by a sea-ice-loss warming amplification mechanism. The calculated GMSTs by the parameter-free warming theory of halogenated GHGs show an excellent agreement with the observed GMSTs after the natural El Niño southern oscillation (ENSO) and volcanic effects are removed. These results provide a convincing mechanism of global climate change and will make profound changes in our understanding of atmospheric processes. This study also emphasizes the critical importance of continued international efforts in phasing out all anthropogenic halogenated ODSs and GHGs.


2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet

Abstract. Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the Radiative Concentration Pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all 9 models. RCP4.5 demonstrates continued summer Arctic sea ice decline due to continued warming on longer time scales. These two scenarios imply that summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in 7 of 9 models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and reversibility of declines in seasonal sea ice extent.


Geology ◽  
2019 ◽  
Vol 47 (10) ◽  
pp. 963-967 ◽  
Author(s):  
Steffen Hetzinger ◽  
Jochen Halfar ◽  
Zoltán Zajacz ◽  
Max Wisshak

Abstract The fast decline of Arctic sea ice is a leading indicator of ongoing global climate change and is receiving substantial public and scientific attention. Projections suggest that Arctic summer sea ice may virtually disappear within the course of the next 50 or even 30 yr with rapid Arctic warming. However, limited observational records and lack of annual-resolution marine sea-ice proxies hamper the assessment of long-term changes in sea ice, leading to large uncertainties in predictions of its future evolution under global warming. Here, we use long-lived encrusting coralline algae that strongly depend on light availability as a new in situ proxy to reconstruct past variability in the duration of seasonal sea-ice cover. Our data represent the northernmost annual-resolution marine sea-ice reconstruction to date, extending to the early 19th century off Svalbard. Algal records show that the decreasing trend in sea-ice cover in the high Arctic had already started at the beginning of the 20th century, earlier than previously reported from sea-ice reconstructions based on terrestrial archives. Our data further suggest that, although sea-ice extent varies on multidecadal time scales, the lowest sea-ice values within the past 200 yr occurred at the end of the 20th century.


2020 ◽  
Author(s):  
Shuang Liang ◽  
Jiangyuan Zeng ◽  
Zhen Li

<p>Evaluating the performance and consistency of passive microwave (PM) sea ice concentration (SIC) products derived from different algorithms is critical since a good knowledge of the quality of the satellite SIC products is essential for their application and improvement. To comprehensively evaluate the performance of satellite SIC in long time series and the whole polar regions (both Arctic and Antarctic), in the study we examined the spatial and temporal distribution of the discrepancy between four PM satellite SIC products with the ERA-Interim sea ice fraction dataset (ERA SIC) during the period of 2015-2018. The four PM SIC products include the DMSP SSMIS with Arctic Radiation and Turbulence Interaction Study Sea Ice (ASI) algorithm (SSMIS/ASI), the GCOM-W AMSR2 with NASA Bootstrap (BT) algorithm (AMSR2/BT), the Chinese Feng Yun-3B with enhanced NASA Team (NT2) sea ice algorithm (FY3B/NT2), and the Chinese Feng Yun-3C with NT2 (FY3C/NT2) at a spatial resolution of 12.5 km.</p><p>The results show the spatial patterns of PM SIC products are generally in good agreement with ERA SIC. The comparison of monthly and annual SIC shows that the largest bias and root mean square difference (RMSD) for the PM SIC products mainly occur in summer and the marginal ice zone, indicating that there are still many uncertainties in PM SIC products in such period and region. Meanwhile, the daily sea ice extent (SIE) and sea ice area (SIA) derived from the four PM SIC products can generally well reflect the variation trend of SIE and SIA in Arctic and Antarctic. The largest bias of SIE and SIA are above 4×10<sup>6</sup> km<sup>2</sup> when the sea ice reaches the maximum and minimum value, and the daily bias of SIE and SIA vary seasonally and regionally, which is mainly concentrated from June to October in Arctic. In general, among the four PM SIC products, the SSMIS/ASI product performs the best compared with ERA SIC though it usually underestimates SIC with a negative bias. The FY3B/NT2 and FY3C/NT2 products show more significant discrepancy with higher RMSD and bias in Arctic and Antarctic compared with the SSMIS/ASI and AMSR2/BT. The AMSR2/BT product performs much better in Antarctic than in Arctic and it always overestimates ERA SIC with a positive bias. The consistency of the four PM products concerning ERA SIC in the Antarctic region is generally superior to that in Arctic region.</p>


2006 ◽  
Vol 52 (178) ◽  
pp. 433-439 ◽  
Author(s):  
Larissa Nazarenko ◽  
Nickolai Tausnev ◽  
James Hansen

AbstractUsing a global climate model coupled with an ocean and a sea-ice model, we compare the effects of doubling CO2 and halving CO2 on sea-ice cover and connections with the atmosphere and ocean. An overall warming in the 2 × CO2 experiment causes reduction of sea-ice extent by 15%, with maximum decrease in summer and autumn, consistent with observed seasonal sea-ice changes. The intensification of the Northern Hemisphere circulation is reflected in the positive phase of the Arctic Oscillation (AO), associated with higher-than-normal surface pressure south of about 50° N and lower-than-normal surface pressure over the high northern latitudes. Strengthening the polar cell causes enhancement of westerlies around the Arctic perimeter during winter. Cooling, in the 0.5 × CO2 experiment, leads to thicker and more extensive sea ice. In the Southern Hemisphere, the increase in ice-covered area (28%) dominates the ice-thickness increase (5%) due to open ocean to the north. In the Northern Hemisphere, sea-ice cover increases by only 8% due to the enclosed land/sea configuration, but sea ice becomes much thicker (108%). Substantial weakening of the polar cell due to increase in sea-level pressure over polar latitudes leads to a negative trend of the winter AO index. The model reproduces large year-to-year variability under both cooling and warming conditions.


2001 ◽  
Vol 33 ◽  
pp. 457-473 ◽  
Author(s):  
Josefino C. Comiso

AbstractRecent observations of a decreasing ice extent and a possible thinning of the ice cover in the Arctic make it imperative that detailed studies of the current Arctic environment are made, especially since the region is known to be highly sensitive to a potential change in climate. A continuous dataset of microwave, thermal infrared and visible satellite data has been analyzed for the first time to concurrently study in spatial detail the variability of the sea-ice cover, surface temperature, albedo and cloud statistics in the region from 1987 to 1998. Large warming anomalies during the last four years (i.e. 1995−98) are indeed apparent and spatially more extensive than previous years. The largest surface temperature anomaly occurred in 1998, but this was confined mainly to the western Arctic and the North American continent, while cooling occurred in other areas. The albedo anomalies show good coherence with the sea-ice concentration anomalies except in the central region, where periodic changes in albedo are observed, indicative of interannual changes in duration and areal extent of melt ponding and snow-free ice cover. The cloud-cover anomalies are more difficult to interpret, but are shown to be well correlated with the expected warming effects of clouds on the sea-ice surface. The results from trend analyses of the data are consistent with a general warming trend and an ice-cover retreat that appear to be even larger during the last dozen years than those previously reported.


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