Comparison of melt pond parameterization schemes in CICE model

Wang Chuanyin; Su Jie

doi:10.3969/j.issn.0253-4193.2015.11.005

Article Contents

Article Navigation > Haiyang Xuebao > 2015 > 37(11): 41-56

Wang Chuanyin, Su Jie. Comparison of melt pond parameterization schemes in CICE model[J]. Haiyang Xuebao, 2015, 37(11): 41-56. doi: 10.3969/j.issn.0253-4193.2015.11.005

Citation:

Wang Chuanyin, Su Jie. Comparison of melt pond parameterization schemes in CICE model[J]. Haiyang Xuebao, 2015, 37(11): 41-56. doi: 10.3969/j.issn.0253-4193.2015.11.005

Wang Chuanyin, Su Jie. Comparison of melt pond parameterization schemes in CICE model[J]. Haiyang Xuebao, 2015, 37(11): 41-56. doi: 10.3969/j.issn.0253-4193.2015.11.005

Citation:

Wang Chuanyin, Su Jie. Comparison of melt pond parameterization schemes in CICE model[J]. Haiyang Xuebao, 2015, 37(11): 41-56. doi: 10.3969/j.issn.0253-4193.2015.11.005

PDF( 14446 KB)

Comparison of melt pond parameterization schemes in CICE model

doi: 10.3969/j.issn.0253-4193.2015.11.005

Key Laboratory of Physical Oceanography, Ministry of Education, Ocean University of China, Qingdao 266100, China

Received Date: 2015-05-15

Abstract

Abstract

The albedo of melt ponds is greater than open water but less than bare sea ice. It's important to obtain accurate melt pond fraction information for the study of heat budget in the atmosphere-ice-ocean system. In numerical model, melt pond fractions impact the calculation of sea ice surface albedo significantly. In this paper, comparison is carried out among the three melt pond parameterization schemes in CICE5.0. The results show that each scheme owns strengths and weaknesses. The freezing conditions of the cesm scheme are more reasonable. Comparatively, for the topo scheme, with freezing conditions changed, the amplitude of inter-annual variability of averaged pond fractions, the melt ponds coverage extent and the length of peak season agree with MODIS results best. In addition, by fixing bugs in CICE5.0, melt water permeating through sea ice is analyzed. This process could cause some side effect; for example, nearly no ponds exist on multi-year ice in the lvl scheme. This indicates that the evolution of sea ice permeability or other physical processes remains to be improved in CICE model. Lastly, we gave some discussions for the improvement mainly on the topo scheme.
- CICE sea ice model,
- melt pond,
- parameterization

FullText(HTML)

References(40)

References

Krouse H R, Kadko D, Perovich D K, et al. Tracer studies of pathways and rates of meltwater transport through Arctic summer sea ice[J]. Journal of Geophysical Research: Oceans (1978-2012), 2002, 107(C10): C108046.

Eicken H, Grenfell T C, Perovich D K, et al. Hydraulic controls of summer Arctic pack ice albedo[J]. Journal of Geophysical Research: Oceans (1978-2012), 2004, 109(C8):C08007.

Skyllingstad E D, Paulson C A, Perovich D K. Simulation of melt pond evolution on level ice[J]. Journal of Geophysical Research: Oceans (1978-2012), 2009, 114(C12).

Schröder D, Feltham D L, Flocco D, et al. September Arctic sea-ice minimum predicted by spring melt-pond fraction[J]. Nature Climate Change, 2014, 4(5): 353-357.

National Research Council. Enhancing NASA's Contribution to Polar Science: A Review of Polar Geophysical Data Sets[M]. Washington: Natl Academy Press, 2002.

Scharien R K, Yackel J J. Analysis of surface roughness and morphology of first-year sea ice melt ponds: Implications for microwave scattering[J]. Geoscience and Remote Sensing, IEEE Transactions on, 2005, 43(12): 2927-2939.

Polashenski C, Perovich D, Courville Z. The mechanisms of sea ice melt pond formation and evolution[J]. Journal of Geophysical Research: Oceans (1978-2012), 2012, 117(C1):C01001.

Hanesiak J M, Barber D G, De Abreu R A, et al. Local and regional albedo observations of Arctic first-year sea ice during melt ponding[J]. Journal of Geophysical Research: Oceans (1978-2012), 2001, 106(C1): 1005-1016.

Fetterer F, Untersteiner N. Observations of melt ponds on Arctic sea ice[J]. Journal of Geophysical Research: Oceans (1978-2012), 1998, 103(C11): 24821-24835.

Perovich D K, Tucker W B, Ligett K A. Aerial observations of the evolution of ice surface conditions during summer[J]. Journal of Geophysical Research: Oceans (1978-2012), 2002, 107(C10): SHE 24-1-SHE 24-14.

Rösel A, Kaleschke L, Birnbaum G. Melt ponds on Arctic sea ice determined from MODIS satellite data using an artificial neural network[J]. The Cryosphere, 2012, 6(2): 431-446.

Istomina L, Heygster G, Huntemann M, et al. The melt pond fraction and spectral sea ice albedo retrieval from MERIS data: validation and trends of sea ice albedo and melt pond fraction in the Arctic for years 2002-2011[J]. The Cryosphere Discussions, 2014, 8: 5227-5292.

SIDARUS Validation and calibration of the MPD retrieval using sea ice and melt pond albedo spectra measured during Polarstern cruise IceArc2012. 2014. Sea Ice Downstream services for Arctic and Antarctic Users and Stakeholders

Taylor P D, Feltham D L. A model of melt pond evolution on sea ice[J]. Journal of Geophysical Research: Oceans (1978-2012), 2004, 109(C12): C12007.

Lüthje M, Feltham D L, Taylor P D, et al. Modeling the summertime evolution of sea-ice melt ponds[J]. Journal of Geophysical Research: Oceans (1978-2012), 2006, 111(C2):C02001.

Scott F, Feltham D L. A model of the three-dimensional evolution of Arctic melt ponds on first-year and multiyear sea ice[J]. Journal of Geophysical Research: Oceans (1978-2012), 2010, 115(C12).

Flocco D, Feltham D L. A continuum model of melt pond evolution on Arctic sea ice[J]. Journal of Geophysical Research: Oceans (1978-2012), 2007, 112(C8): C08016.

Hunke E C, Lipscomb W H, Turner A K, et al. CICE: the Los Alamos Sea Ice Model Documentation and Software User's Manual Version 4.0 LA-CC-06-012[J]. Los Alamos National Laboratory, Los Alamos NM, 2008, 87545: 115.

Holland M M, Bailey D A, Briegleb B P, et al. Improved sea ice shortwave radiation physics in CCSM4: the impact of melt ponds and aerosols on Arctic sea ice[J]. Journal of Climate, 2012, 25(5): 1413-1430.

Pedersen C A, Roeckner E, Lüthje M, et al. A new sea ice albedo scheme including melt ponds for ECHAM5 general circulation model[J]. Journal of Geophysical Research: Atmospheres (1984-2012), 2009, 114:D8.

Roeckner E, Mauritsen T, Esch M, et al. Impact of melt ponds on Arctic sea ice in past and future climates as simulated by MPI-ESM[J]. Journal of Advances in Modeling Earth Systems, 2012, 4(3):M00A02.

Flocco D, Feltham D L, Turner A K. Incorporation of a physically based melt pond scheme into the sea ice component of a climate model[J]. Journal of Geophysical Research: Oceans (1978-2012), 2010, 115(C8):C08012.

Flocco D, Schroeder D, Feltham D L, et al. Impact of melt ponds on Arctic sea ice simulations from 1990 to 2007[J]. Journal of Geophysical Research: Oceans (1978-2012), 2012, 117(C9).

Hunke E C, Hebert D A, Lecomte O. Level-ice melt ponds in the Los Alamos sea ice model, CICE[J]. Ocean Modelling, 2013, 71: 26-42.

Hunke E C. Weighing the importance of surface forcing on sea ice: a September 2007 modelling study[J]. Quarterly Journal of the Royal Meteorological Society, 2014, 140(642).

Hunke E C, Lipscomb W H, Turner A K, et al. CICE: the Los Alamos Sea Ice Model Documentation and Software User's Manual Version 5.0 LA-CC-06-012[S]. Los Alamos National Laboratory, Los Alamos NM, 2013, 87545: 115.

Griffies S M, Biastoch A, Böning C, et al. Coordinated ocean-ice reference experiments (COREs)[J]. Ocean Modelling, 2009, 26(1): 1-46.

Hunke E C, Holland M M. Global atmospheric forcing data for Arctic ice-ocean modeling[J]. Journal of Geophysical Research: Oceans (1978-2012), 2007, 112(C4): C04S14.

Parkinson C L, Washington W M. A large-scale numerical model of sea ice[J]. Journal of Geophysical Research, 1979, 84(C1): 311-337.

Hunke E C. Thickness sensitivities in the CICE sea ice model[J]. Ocean Modelling, 2010, 34(3): 137-149.

Steele M, Morley R, Ermold W. PHC: A global ocean hydrography with a high-quality Arctic Ocean[J]. Journal of Climate, 2001, 14(9): 2079-2087.

National Snow and Ice Data Center. Sea Ice Concentrations from Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data[OL]. http://nsidc.org/data/docs/daac/nsidc0051_gsfc_seaice.gd.html

Hunke E C, Bitz C M. Age characteristics in a multidecadal Arctic sea ice simulation[J]. Journal of Geophysical Research: Oceans (1978-2012), 2009, 114(C8): C08013.

Rösel A, Kaleschke L. Exceptional melt pond occurrence in the years 2007 and 2011 on the Arctic sea ice revealed from MODIS satellite data[J]. Journal of Geophysical Research: Oceans (1978-2012), 2012, 117(C5):C05018.

Lecomte O, Fichefet T, Flocco D, et al. Interactions between wind-blown snow redistribution and melt ponds in a coupled ocean-sea ice model[J]. Ocean Modelling, 2014, 87: 67-80.

Laine V, Manninen T, Riihelä A. High temporal resolution estimations of the Arctic sea ice albedo during the melting and refreezing periods of the years 2003-2011[J]. Remote Sensing of Environment, 2014, 140: 604-613.

Perovich D, Richter-Menge J, Polashenski C, et al. Sea ice mass balance observations from the North Pole Environmental Observatory[J]. Geophysical Research Letters, 2014, 41(6): 2019-2025.

Notz D. Sea-ice extent and its trend provide limited metrics of model performance[J]. The Cryosphere, 2014, 8(2): 229-243.

Bitz C M, Holland M M, Hunke E C, et al. Maintenance of the sea-ice edge[J]. Journal of Climate, 2005, 18(15):2903-2921.

Petrich C, Eicken H, Polashenski C M, et al. Snow dunes: A controlling factor of melt pond distribution on Arctic sea ice[J]. Journal of Geophysical Research: Oceans (1978-2012), 2012, 117, C09029:1-10

Relative Articles

Supplements(0)

Cited By

Proportional views