Abstract
Dust particle studies in ice cores from the tropical Andes provide important information about climate dynamics. We investigated dust concentrations from a 22.7 m ice-core recovered from the Quelccaya Ice Cap (QIC) in 2018, representing 14 years of snow accumulation. The dust seasonality signal was still preserved with homogenization of the record due to surface melting and percolation. Using a microparticle counter, we measured the dust concentration from 2 to 60 µm and divided the annual dust concentration into three distinct groups: fine particle percentage (FPP, 2–10 µm), coarse particle percentage (CPP, 10–20 μm), and giant particle percentage (GPP, 20–60 μm). Increased dust was associated with the warm stage of the Pacific Decadal Oscillation index (PDO) after 2013 with significant increases in FPP and a relative decrease in CPP and GPP. There was a positive correlation between PDO and FPP (r = 0.70, p-value < 0.005). CPP and GPP were dominant during the mainly PDO cold phase (2003–2012). The FPP increase record occurs during the positive phase of PDO and snow accumulation decrease. We also revealed a potential link between QIC record and Madeira River during the wet season through two relationships: between QIC snow accumulation and runoff during transitional season, QIC dust, and suspended sediments during high-water discharge. The snow accumulation (during September-November) and runoff (during November-January) relationship present similar variability using a time-lag (60 days) while total dust and FPP group are associated with average suspended sediments concentration during February-April. Assessing dust record variability by distinct size groups can help to improve our knowledge of how the Pacific ocean influence dust record in the QIC. In addition, the association of snow accumulation and dust variability with dynamic changes in suspended sediments load and runoff in the Madeira River system demonstrates the potential for future investigation of linkages between QIC record and Amazon basin rivers.
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