The stable water isotopes and snow accumulation from Weddell Sea sector imprint the large-scale atmospheric circulation variability

• Main Authors: Marcher, Andressa, Simões, Jefferson Cardia, Bernardo, Ronaldo Torma, Aquino, Francisco Eliseu, Thoen, Isaías Ullmann, Valente, Pedro Teixeira, Schossler, Venisse
• Format: Text
• Language: English
• Published: 2022
• Subjects: Amundsen Sea; Austral; Möller Ice Stream; Weddell; Weddell Sea; Antarc*; Antarctica; Ice Sheet; Sea ice
• Online Access: https://doi.org/10.5194/tc-2022-161; https://tc.copernicus.org/preprints/tc-2022-161/

Stable water isotopes and accumulation data extracted from polar ice/firn cores provide valuable climate information. Here, we present novel isotopic and accumulation time series from an upstream area of the Möller Ice Stream (MIS) basin, Weddell Sea Sector (WSS), Antarctica – a Brazilian research area (84°00’00’’S; 79°29’39’’W; 1276 m a.s.l.). Our purpose was to understand the depositional history and investigate how much the recent climate signal (21 st century) is stored in the shallowest ice sheet layers in this area. Therefore, we crossed the isotopic (δ 18 O, δD, and d-excess) and snow accumulation data of two shallow firn cores (both ⁓9.0 m deep) with glaciological information, local and regional meteorological data (both ERA5 and AWS), indices of large-scale atmospheric modes (as SAM and ENSO) and the Amundsen Sea Low (ASL). The isotopic records cover 16 years (from 1999 to 2015-austral summer) and the accumulation records cover 20 years (from 1999 to 2018). We find that interannual δs variability is strongly explained by changes in the phase of the SAM (r = 0.74; p < 0.05; α = 0.05) and, consequently, also by changes in pressure of both the WSS (r = -0.57; p < 0.05; α = 0.05) and the ASL (r = -0.56; p < 0.05; α = 0.05). The regional temperature in WSS (r = 0.50; p < 0.05; α = 0.05) and Antarctica Peninsula (r = 0.70; p < 0.05; α = 0.05), as well as the sea ice concentration in the Weddell Sea (r = -0.49; p = 0.05; α = 0.05) are other factors that measurably influence the δs in the study area. In the period covered by our study, the rarest and strongest wind events (SWE; > ⁓15 m/s) and extreme precipitation events (EPE) oscillate almost completely out of phase, and this relationship is largely explained by the sub-decadal changes in the SWE-ENSO relationship and by the SAM variability. This oscillatory pattern between SWE and EPE justifies the non-temporally stable correlation between δs and local temperature in the study area. For the period of 2013–2018, we show that the trigger to ...