Gaoyuan qixiang (Oct 2024)

Error Analysis of Lake Ice Characteristics of ERA5-Land and FLake Model Improvement on the Qinghai-Xizang Plateau

  • Liuyiyi YANG,
  • Lijuan WEN,
  • Mengxiao WANG,
  • Dongsheng SU,
  • Jingwei DONG

DOI
https://doi.org/10.7522/j.issn.1000-0534.2024.00011
Journal volume & issue
Vol. 43, no. 5
pp. 1125 – 1137

Abstract

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The Qinghai-Xizang Plateau, distinguished by its vast array of lakes, exhibits marked seasonal lake ice coverage, which is highly responsive to climatic shifts.This ice coverage plays a crucial role in the dynamic interchange of fluxes between the lake surfaces and the atmosphere.Despite the significance of these ice phenomena, the limited availability of extensive, long-term observational data on plateau lake ice has led to a reliance on reanalyzed ice datasets, particularly ERA5-Land.This study aims to rigorously evaluate the effectiveness and potential enhancements of ERA5-Land's lake ice data in the distinct environment of the Qinghai-Xizang Plateau.Focusing on data collected from 2010 to 2022 for Qinghai Lake and Ngoring Lake, this research meticulously examines the ERA5-Land reanalysis data's ability to accurately capture the intrinsic characteristics of plateau lake ice.The study uncovered that ERA5-Land tends to overestimate the ice thickness by about 0.54~0.62 m and erroneously prolongs the freezing period by roughly 68 days per year for these lakes.This notable discrepancy necessitated an in-depth error analysis, which synthesized ERA5-Land data with direct observational data from Ngoring Lake, revealing that inaccuracies primarily originated from the FLake one-dimensional lake model within the ERA5-Land system.In an effort to address these inaccuracies, the study employed the MCD43A3 surface albedo product for both Qinghai Lake and Ngoring Lake over the same period.This innovative approach significantly refined the FLake model by incorporating both a multi-year average albedo and a dynamic daily average albedo.These methodological improvements led to a substantial reduction in the average bias of ice thickness, by 85% and 90% respectively, and narrowed the deviation in the modeled freezing period by about 6 and 8 days per year.The enhancements were particularly notable in lakes with longer periods of snow cover, where the dynamic albedo adjustment proved to be highly effective.This research has successfully identified the albedo parameter within the FLake model as a key source of error in ERA5-Land's lake ice characterizations and has implemented practical adjustments to rectify this.These enhancements have markedly increased the model's precision in simulating lake ice, thereby significantly improving the accuracy of ERA5-Land reanalyzed lake ice data.This advancement is particularly pertinent for the unique climatic and geographical conditions of Qinghai Lake and Ngoring Lake on the Qinghai-Xizang Plateau and offers invaluable insights for future research and practical applications in this domain.The findings of this study contribute profoundly to our understanding and modeling of lake ice phenomena in high-altitude regions and have broader implications for climatological research and environmental monitoring on the Qinghai-Xizang Plateau.

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