Spatiotemporal analysis of sea ice in the Weddell Sea of Antarctic based on GTWR DOI
Yi Ding, Xin Liu, Xiaofeng Dai

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 19, 2024

Abstract The Geographical and Temporal Weighted Regression (GTWR) method is employed to assess the impact of various environmental factors on sea ice concentration (SIC) in Weddell Sea. Initially, MODIS-derived SIC was used evaluate accuracy six products derived from different satellite sensors algorithms. MWRI/NT2 product demonstrated highest correlation with MODIS data, validating its reliability for further analysis. Using product, along ERA5 NCEP/NCAR reanalysis datasets, we investigated interannual seasonal trends extent (SIE) 2011 2023. results indicate a declining trend SIE at rate -6.2 ± 1.9×10³ km²/yr, most significant loss occurring autumn. GTWR analysis highlights spatial temporal variability influencing Latent heat flux (LH) emerged as influential factor, median standardized regression coefficient 1.44. LH primarily promotes growth by cooling surface through condensation atmospheric water vapor. Zonal winds also played critical role, particularly promoting formation Ekman transport cold water. However, wind speed had minimal SIC, likely due lack directional data dataset. In contrast, net radiation (NR) varied significantly across region, complicating overall influence dynamics. Sensible (SH) generally supported growth, except central Sea, where local conditions caused SH inhibit formation. These findings underscore complex interplay shaping SIC.

Language: Английский

Antarctica in 2025: Drivers of deep uncertainty in projected ice loss DOI
H. A. Fricker, Benjamin K. Galton‐Fenzi, C. C. Walker

et al.

Science, Journal Year: 2025, Volume and Issue: 387(6734), P. 601 - 609

Published: Feb. 6, 2025

Antarctica is a vital component of Earth’s climate system, influencing global sea level, ocean circulation, and planetary albedo. Major knowledge gaps in critical processes—spanning the atmosphere, ocean, ice sheets, underlying beds, shelves, ice—create uncertainties future projections, hindering adaptation risk assessments intervention strategies. Antarctica’s sheet could contribute 28 centimeters to level by 2100, potentially more if we surpass warming thresholds that trigger instabilities rapid retreat. We review recent advances understanding changing stability margins identify key processes require further research. Progress requires high-resolution satellite data, targeted field campaigns, improved modeling, refined theory. Increased investment interdisciplinary collaboration are essential uncovering hidden reducing projections.

Language: Английский

Citations

1
Spatiotemporal analysis of sea ice in the Weddell Sea of Antarctic based on GTWR DOI Creative Commons
Yi Ding, Xin Liu, Xiaofeng Dai

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 18, 2025

This study investigates the spatiotemporal dynamics of Antarctic sea ice concentration (SIC) and its interactions with environmental factors from 2011 to 2023, focusing on Weddell Sea. SIC products derived MODIS data were assessed compared six widely used datasets, including AMSR2/NT2 MWRI/NT2. Among these, MWRI/NT2 exhibited highest consistency MODIS-derived SIC, achieving a correlation coefficient 0.94, lowest bias (0.23%), smallest mean absolute deviation (MAD) root square (RMSD), making it preferred dataset for further analysis. Seasonal trends reveal that experienced most significant decline during autumn (–10.7 ± 2.3 × 10³ km² yr⁻¹) reduction in winter (–1.3 0.5 yr⁻¹). Correlation analysis identified surface temperature (SST), wind speed, latent heat flux (LHF) as primary drivers seasonal variability, SST exhibiting strong negative correlations across all seasons (r = –0.81, p < 0.01). Spatially, Sea displayed heterogeneity relationship factors. demonstrated particularly western Sea, lags –3 –5 months. LHF consistently promoted growth, strongest influence along eastern coast. Zonal meridional winds both promoting suppressing effects depending region time period, reflecting complex wind-sea interactions. Mean level pressure (MSLP) showed opposing effects: northern southern The use geographically temporally weighted regression (GTWR) allowed quantification spatial temporal these factors, influential variable (median standardized 1.44). These findings highlight intricate interplay between atmospheric, oceanic, provide framework understanding variability under changing climatic conditions.

Language: Английский

Citations

0
Biases in Climate Model Global Warming Trends Related to Deficiencies in Southern Ocean Sea Ice Evolution Over Recent Decades DOI Creative Commons
Harry Mutton, Timothy Andrews

Geophysical Research Letters, Journal Year: 2025, Volume and Issue: 52(7)

Published: April 4, 2025

Abstract Between 1985 and 2014 observations show an expansion of Southern Ocean sea‐ice. This phenomena is not simulated in CMIP6 Atmosphere‐Ocean General Circulation Models (AOGCMs). Here we quantify the impact this discrepancy on radiative feedback global temperature trends. We find that both satellite reconstructions Earth's energy budget atmosphere‐only GCM simulations forced with observed Sea Surface Temperature (SST) sea‐ice trends support hypothesis a negative surface albedo over Ocean. In contrast, declining AOGCMs gives rise to positive feedback. estimate had evolution their parameter would be less by 0.07–0.23 (which 12%–29% total difference between AOGCM SST sea‐ice) trend 30 year period reduced 0.01–0.06 K .

Language: Английский

Citations

0
Antarctic Sea ice distribution detection based on improved ant colony algorithm DOI Creative Commons

Xingdong Wang,

Zehao Sun

Frontiers in Marine Science, Journal Year: 2024, Volume and Issue: 11

Published: Dec. 4, 2024

The changes in the Antarctic sea ice area are directly related to atmosphere and oceans. Determining distribution is of great significance global climate change analysis. ant colony algorithm adopts a positive feedback mechanism continuously converge search process ultimately approaches optimal solution, making it easy find segmentation threshold for detecting distribution. However, has problems high computational complexity getting stuck local optima. In order better apply detection, an improved was proposed, which improves selection initial clustering centers update pheromone volatilization factors algorithm. We compared with iterative algorithm, maximum entropy basic results showed that proposed feasible. To further validate accuracy we obtained from MODIS data 4.99%, 3.66%, 5.46% higher than other three algorithms, respectively.

Language: Английский

Citations

1
Spatiotemporal analysis of sea ice in the Weddell Sea of Antarctic based on GTWR DOI
Yi Ding, Xin Liu, Xiaofeng Dai

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 19, 2024

Abstract The Geographical and Temporal Weighted Regression (GTWR) method is employed to assess the impact of various environmental factors on sea ice concentration (SIC) in Weddell Sea. Initially, MODIS-derived SIC was used evaluate accuracy six products derived from different satellite sensors algorithms. MWRI/NT2 product demonstrated highest correlation with MODIS data, validating its reliability for further analysis. Using product, along ERA5 NCEP/NCAR reanalysis datasets, we investigated interannual seasonal trends extent (SIE) 2011 2023. results indicate a declining trend SIE at rate -6.2 ± 1.9×10³ km²/yr, most significant loss occurring autumn. GTWR analysis highlights spatial temporal variability influencing Latent heat flux (LH) emerged as influential factor, median standardized regression coefficient 1.44. LH primarily promotes growth by cooling surface through condensation atmospheric water vapor. Zonal winds also played critical role, particularly promoting formation Ekman transport cold water. However, wind speed had minimal SIC, likely due lack directional data dataset. In contrast, net radiation (NR) varied significantly across region, complicating overall influence dynamics. Sensible (SH) generally supported growth, except central Sea, where local conditions caused SH inhibit formation. These findings underscore complex interplay shaping SIC.

Language: Английский

Citations

0