Physically Based Summer Temperature Reconstruction From Melt Layers in Ice Cores

• Published in: Earth and Space Science
• Main Authors: Koji Fujita, Sumito Matoba, Yoshinori Iizuka, Nozomu Takeuchi, Akane Tsushima, Yutaka Kurosaki, Teruo Aoki
• Format: Article in Journal/Newspaper
• Language: English
• Published: American Geophysical Union (AGU) 2021
• Subjects: summer temperature; ice core; melt layer; energy balance model; Astronomy; QB1-991; Geology; QE1-996.5; Greenland; Ice Sheet; Alaska
• Online Access: https://doi.org/10.1029/2020EA001590; https://doaj.org/article/efa14093fd2e4936bc63b868d36d0204

Abstract Previous reconstructions of summer temperatures from ice cores have relied on a statistical relationship between a melt layer and temperature observed at nearby stations. This study presents a novel method for reconstructing summer temperatures from melt layers in ice cores using an energy balance model that incorporates heat conduction and meltwater refreezing in the firn. We use the seasonal patterns in the ERA‐Interim reanalysis data set for an ice core site to calculate the amounts of refreezing water within the firn under various summer mean temperature (SMT) and annual precipitation conditions, and prepared calibration tables containing these three variables. We then estimate the SMTs from the refreezing amount and annual accumulation, both of which can be obtained from an ice core. We apply this method to four ice cores that were recovered from sites with different climates: two sites on the Greenland Ice Sheet, one in Alaska, and one in Russian Altai. The reconstructed SMTs show comparable variations with those of observed temperatures at nearby stations. The nonlinear relationship between SMT and melt layer thickness differs between sites, indicating that a single linear approximation cannot be employed to estimate SMT. Sensitivity analyses suggest that the annual temperature range, amount of annual precipitation, and firn albedo (which is a time‐invariant value in the model) significantly affect the relationship between SMT and melt layer thickness. This new method provides an alternative to existing approaches and yields an independent estimate of SMT from ice cores that have been affected by melting.