the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Using Icepack to reproduce Ice Mass Balance buoy observations in landfast ice: improvements from the mushy layer thermodynamics
- 1Recherche en prévision numérique environnementale, Environnement et Changement Climatique Canada, Dorval, Québec, Canada
- 2Department of Atmospheric and Oceanic Sciences, McGill University, Montréal, Québec, Canada
- 3Canadian Ice Service, Environment and Climate Change Canada, Ottawa, Ontario, Canada
- 4Nunatsiavut Research Center, Nain, Labrador, Canada
- 5Service Météorologique Canadien, Environnement et Changement Climatique Canada, Dorval, Québec, Canada
- 1Recherche en prévision numérique environnementale, Environnement et Changement Climatique Canada, Dorval, Québec, Canada
- 2Department of Atmospheric and Oceanic Sciences, McGill University, Montréal, Québec, Canada
- 3Canadian Ice Service, Environment and Climate Change Canada, Ottawa, Ontario, Canada
- 4Nunatsiavut Research Center, Nain, Labrador, Canada
- 5Service Météorologique Canadien, Environnement et Changement Climatique Canada, Dorval, Québec, Canada
Abstract. The column thermodynamics package (Icepack v1.1.0) of the Community Ice Code (CICE) version 6 is used to reproduce observations from two Ice Mass Balance (IMB) buoys co-deployed in the landfast ice close to Nain (Labrador) in February 2017. A new automated surface retrieval algorithm is used to determine the ice thickness and snow depths from the measured vertical temperature profiles. The buoys recorded heavy snow precipitation over relatively thin ice, negative ice freeboards and delayed snow flooding. Icepack simulations are produced to evaluate the performance of the Bitz and Lipscomb (1999) thermodynamics used in the Environment and Climate Change Canada (ECCC) ice-ocean systems and to investigate the improvements associated with the use of mushy layer physics. Results show that the Bitz and Lipscomb (1999) scheme produces a smooth thermodynamics growth that fails to capture the observed variability in bottom sea ice congelation rates. The mushy layer physics produces similar temperature profiles but better captures the variability in congelation rates at the ice bottom interface, with periods of rapid ice growth that coincide with IMB observations. Large differences are also found associated with the snow-ice parameterization: the volume of snow-ice formed during flooding is largely underestimated when using a mass conserving snow-formation scheme, but largely improved when using the mushy layer parameterization in which sea-water is filling the porosity of the snow layer. Both schemes are however unable to reproduce the delayed snow-ice formation, as they rely on the hydrostatic balance and do not allow for negative freeboards. This calls for added brine fraction or ice porosity dependencies in the snow-ice parameterizations.
Mathieu Plante et al.
Status: open (until 28 Feb 2023)
-
RC1: 'Comment on tc-2022-266', Anonymous Referee #1, 26 Jan 2023
reply
Review on “Using Icepack to reproduce Ice Mass Balance buoy observations in land-fast ice: improvements from the mushy layer thermodynamics” by Plante et al.,
This manuscript needs a major revision or possible resubmission to the TC.
Undoubtedly, this research subject is important and is of potential interest to TC readers. This manuscript contains the following key elements: a) Icepack (v1.1.0); b) ice mass balance buoy (SAMS IMB), c) land-fast sea ice in Canadian Arctic Archipelago (CAA) and d) mushy layer~ slush layer (mixture of snow and ice).
By the way, please use “SIMBA (snow and ice mass balance apparatus)” in the revised manuscript to present SAMS IMB since this acronym has been used in many papers to name SAMS IMB.
The authors presented the Icepack model; processed the SIMBA data (observations) using a newly developed automatic SIMBA algorithm based on existing methods; simulated ice thickness (calculations) using the Icepack model; Summarized results (observations and calculations); Concluded that the modelled ice thickness is better when applying a mushy layer parameterization; pointed out the simulation errors and give suggestions on further actions. The storyline of this manuscript seems ok, but the presentation suffers various ambiguities and makes it difficult to follow and understand.
Several major comments:
1 What is the relationship between Icepack1.1.0 and Bitz and Lipscomb's (1999) thermodynamics model? To my understanding, CICE is a 2D dynamic-thermodynamic sea ice model developed by the Los Alamos National Laboratory. Icepack 1.1.0 is the one-dimensional module of the CICE model. Bitz and Lipscomb (1999) is an independent one-dimensional thermodynamic sea ice model. Please clarify those models and present clearly how they support each other.
2) Are you trying to develop Icepack or simply to validate Icepack using SIMBA observations? Why is Bitz and Lipscomb's (1999) scheme mentioned separately?
3a) The paper structure is not clear. The current chapters 2 and 3 mixture of many things and need to be reconstructed. One possibility could be
2 Data
Describe the data used in this study
2.1 Weather data
Describe weather conditions
2.2 SIMBA data
Describe SIMBA deployment and data
3 Method
Describe the model/algorithm used in the study
3.1 Icepack model
Surface energy budget
Heat conduction in snow and ice
Bottom heat and mass balance
Snow-ice interaction
3.2 SIMBA algorithm
I would like to see a sub-section dealing with the weather data.
3b) The result chapter needs significant updates too.
I would like to see a sub-section presenting analyses of weather data. This is very important for readers to understand your model performance and the snow-ice interactions. The weather part is missing entirely both in the data and result sections.
Do you have ice core samples to show how the snow ice was distributed vertically? It would be interesting to add some on-site photos.
4) Several figures can be improved.
- a) Figure 1 is not very representative. Please show a much larger domain so readers can better understand the region's geography. What is the distance between those two SIMBAs? What are the air temperatures and precipitation patterns of those two sites?
- b) Figure 7-12 need revisions. Can authors make those figures to be consistent with the SIMBA figures? The figure captions need improvement for better clarity. Some of the results lines need to be smoothed, e.g., 5-day running mean.
5) Surface retrieval algorithm validation: Could authors perform some statistical analyses to give a concrete assessment of your algorithm performance?
6) section 4.2 (In situ ice mass balance conditions) should be moved to the data section.
7) Icepack simulations section looks weak. I see a description of the results, but please carry out some in-depth analyses.
8) The discussion section looks weak too. I would like to see some tables and comparisons with other studies. I am sure there are a lot of land-fast sea ice modelling papers and snow-ice simulations. Please make some concrete discussions.
9) “Code and data availability. All codes (model and analysis) are available on github upon request. The buoy data are available upon request.” I think this statement is not acceptable to the TC. Please make your code and data available with doi link or weblink.
Mathieu Plante et al.
Mathieu Plante et al.
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 157 | 50 | 9 | 216 | 2 | 2 |
- HTML: 157
- PDF: 50
- XML: 9
- Total: 216
- BibTeX: 2
- EndNote: 2
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1