Retrievals of Arctic sea ice melt pond depth and underlying ice thickness using optical data
at : Jun 21, 2021 09:52:21  (view:335)

ZHANG Hang, YU Miao, LU Peng *, ZHOU Jiaru & LI Zhijun

State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology, Dalian 116024, China

Abstract Melt pond is a distinctive characteristic of the summer Arctic, which affects energy balance in the Arctic system. The Delta-Eddington model (BL) and Two-strEam rAdiative transfer model (TEA) are employed to retrieving pond depth Hp and underlying ice thickness Hi according to the ratio X of the melt-pond albedo in two bands. Results showed that when λ1 = 359 nm and λ2 = 605 nm, the Pearson's correlation coefficient r between X and Hp is 0.99 for the BL model. The result of TEA model was similar to the BL model. The retrievals of Hp for the two models agreed well with field observations. For Hi, the highest r (0.99) was obtained when λ1 = 447 nm and λ2 = 470 nm for the BL model, λ1 = 447 nm and λ2 = 451 nm for the TEA model. Furthermore, the BL model was more suitable for the retrieval of thick ice (0 < Hi < 3.5 m, R2 = 0.632), while the TEA model is on the contrary (Hi < 1 m, R2 = 0.842). The present results provide a potential method for the remote sensing on melt pond and ice in the Arctic summer.

Keywords Arctic, melt pond, sea ice, remote sensing, albedo