Modelling experiments on air-snow-ice interactions over Kilpisjärvi, a lake in northern Finland

The evolution of snow and ice thicknesses and temperature in an Arctic lake was investigated using two models: a high-resolution, time-dependent model (HIGHTSI) and a quasi-steady two-layer model on top of a lake model (FLake). In situ observations and a Numerical Weather Prediction model (HIRLAM) w...

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Bibliographic Details
Main Authors: Yang, Y., Cheng, B., Kourzeneva, E., Semmler, Tido, Rontu, L., Leppäranta, M., Shirasawa, K., Li, Zhijun
Format: Article in Journal/Newspaper
Language:unknown
Published: FINNISH ENVIRONMENT INST 2013
Subjects:
Arctic
Arctic Lake
Kilpisjärvi
albedo
Boreal Environment Research
Northern Finland
Online Access:https://epic.awi.de/id/eprint/33988/
https://epic.awi.de/id/eprint/33988/1/BER.pdf
http://www.borenv.net/BER/pdfs/ber18/ber18-341.pdf
https://hdl.handle.net/10013/epic.42415
https://hdl.handle.net/10013/epic.42415.d001
Description
Summary:The evolution of snow and ice thicknesses and temperature in an Arctic lake was investigated using two models: a high-resolution, time-dependent model (HIGHTSI) and a quasi-steady two-layer model on top of a lake model (FLake). In situ observations and a Numerical Weather Prediction model (HIRLAM) were used for the forcing data. HIRLAM forecasts, after orography correction, were comparable with the in situ data. Both lake-ice models predicted the ice thickness (accuracy 5 cm), surface temperature (accuracy 2–3 °C in winter, better in spring), and ice-breakup date (accuracy better than five days) well. HIGHTSI was better for ice thickness and ice-breakup date, while FLake gave better freezing date. Snow thickness outcome was worse, in particular for the melting season. Surface temperature was highly sensitive to air temperature, stratification and albedo, and the largest errors (positively biased) resulted in strongly stable conditions.

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