Articles | Volume 15, issue 12
https://doi.org/10.5194/gmd-15-4739-2022
https://doi.org/10.5194/gmd-15-4739-2022
Model evaluation paper
 | 
21 Jun 2022
Model evaluation paper |  | 21 Jun 2022

Validation of turbulent heat transfer models against eddy covariance flux measurements over a seasonally ice-covered lake

Joonatan Ala-Könni, Kukka-Maaria Kohonen, Matti Leppäranta, and Ivan Mammarella

Related authors

A field study on ice melting and breakup in a boreal lake, Pääjärvi, in Finland
Yaodan Zhang, Marta Fregona, John Loehr, Joonatan Ala-Könni, Shuang Song, Matti Leppäranta, and Zhijun Li
The Cryosphere, 17, 2045–2058, https://doi.org/10.5194/tc-17-2045-2023,https://doi.org/10.5194/tc-17-2045-2023, 2023
Short summary

Related subject area

Atmospheric sciences
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025,https://doi.org/10.5194/gmd-18-1989-2025, 2025
Short summary
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025,https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025,https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025,https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025,https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary

Cited articles

Aalto, J., Aalto, P., Keronen, P., Kolari, P., Rantala, P., Taipale, R., Kajos, M., Patokoski, J., Rinne, J., Ruuskanen, T., Leskinen, M., Laakso, H., Levula, J., Pohja, T., Siivola, E., and Kulmala, M.: SMEAR II Hyytiälä forest meteorology, greenhouse gases, air quality and soil, University of Helsinki, Institute for Atmospheric and Earth System Research [data set], https://doi.org/10.23729/2001890a-2f0b-4e37-8c70-4d2cb5f40273, 2019. a
Andreas, E.: A Bulk Turbulent Flux Algorithm for Sea Ice, Based on the SHEBA Data Set (2.0), Zenodo [code], https://doi.org/10.5281/zenodo.5534911, 2014. a
Andreas, E. L., Persson, P. O. G., Grachev, A. A., Jordan, R. E., Horst, T. W., Guest, P. S., and Fairall, C. W.: Parameterizing turbulent exchange over sea ice in winter, J. Hydrometeorol., 11, 87–104, 2010. a
Aubinet, M., Vesala, T., and Papale, D.: Eddy covariance: a practical guide to measurement and data analysis, Springer Science & Business Media, https://doi.org/10.1007/978-94-007-2351-1, 2012. a
Barskov, K., Stepanenko, V., Repina, I., Artamonov, A., and Gavrikov, A.: Two regimes of turbulent fluxes above a frozen small lake surrounded by forest, Bound.-Lay. Meteorol., 173, 311–320, 2019. a, b, c
Download
Short summary
Properties of seasonally ice-covered lakes are not currently sufficiently included in global climate models. To fill this gap, this study evaluates three models that could be used to quantify the amount of heat that moves from and into the lake by the air above it and through evaporation of the ice cover. The results show that the complex nature of the surrounding environment as well as difficulties in accurately measuring the surface temperature of ice introduce errors to these models.
Share