Work Description

Title: FVCOM-UGCICE source codes and model results for assessment of precipitation impact on Great Lakes ice cover and water temperature Open Access Deposited

http://creativecommons.org/licenses/by/4.0/
Attribute Value
Methodology
  • This dataset includes the representative model results for the Laurentuan Great Lakes from the Finite-Volume Community Ocean Model coupled with the unstructured grid version of the Los Alamos Sea Ice Model (FVCOM-UGCICE), the model source codes, and namelist files that were used for the simulations. In the source codes, the updates are made so that the model can take account of the precipitation heat flux at the ice/water surface.
Description
  • Precipitation impacts on ice cover and water temperature in the Laurentian Great Lakes were examined using state-of-art coupled ice-hydrodynamic models. Numerical experiments were conducted for the recent anomalously cold (2014-2015) and warm (2015-2016) winters that were accompanied by high and low ice coverage over the lakes, respectively. The results of numerical experiments showed that, snow cover on the ice, which is the manifestation of winter precipitation, reduced the total ice volume (or mean ice thickness) in all of the Great Lakes, shortened the ice duration, and allowed earlier warming of water surface. The reduced ice volume was due to the thermal insulation of snow cover. The surface albedo was also increased by snow cover, but its impact on the delay the melting of ice was overcome by the thermal insulation effect. During major snowstorms, snowfall over the open lake caused notable cooling of the water surface due to latent heat absorption. Overall, the sensible heat flux from rain in spring and summer was found to have negligible impacts on the water surface temperature. Although uncertainties remain in over-lake precipitation estimates and model’s representation of snow on the ice, this study demonstrated that winter precipitation, particularly snowfall on the ice and water surfaces, is an important contributing factor in Great Lakes ice production and thermal conditions from late fall to spring.
Creator
Depositor
  • ayumif@umich.edu
Contact information
Discipline
Funding agency
  • Other Funding Agency
Other Funding agency
  • National Oceanic and Atmospheric Administration
ORSP grant number
  • NA12OAR4320071
Keyword
Citations to related material
  • Fujisaki-Manome, A., E.J. Anderson, J.A. Kessler, P.Y. Chu, J. Wang, and A.D. Gronewold, Simulating impacts of precipitation on ice cover and surface water temperature across large lakes, Journal of Geophysical Research Oceans, in revision.
Resource type
Last modified
  • 04/30/2020
Published
  • 04/30/2020
Language
DOI
  • https://doi.org/10.7302/4mpr-4364
License
To Cite this Work:
Ayumi Fujisaki-Manome. FVCOM-UGCICE source codes and model results for assessment of precipitation impact on Great Lakes ice cover and water temperature [Data set], (2020). University of Michigan - Deep Blue. https://doi.org/10.7302/4mpr-4364

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Files (Count: 7; Size: 4.66 GB)

Date April 30, 2020

Dataset Title: FVCOM-UGCICE source codes and model results for assessment of precipitation impact on Great Lakes ice cover and water temperature

Dataset Creators: Ayumi Fujisaki-Manome

Dataset Contact: Ayumi Fujisaki-Manome, ayumif@umich.edu

Key Points:
• Precipitation impacts on Great Lakes ice cover and water temperature were evaluated using a coupled ice-hydrodynamic model.
• The model results showed that snow cover on the ice reduced the net production of ice, which resulted in earlier decay of ice cover.
• The model results showed that snowfall cooled the water surface notably through latent heat absorption during storms.

Research Overview:
Precipitation impacts on ice cover and water temperature in the Laurentian Great Lakes were examined using state-of-art coupled ice-hydrodynamic models. Numerical experiments were conducted for the recent anomalously cold (2014-2015) and warm (2015-2016) winters that were accompanied by high and low ice coverage over the lakes, respectively. The results of numerical experiments showed that, snow cover on the ice, which is the manifestation of winter precipitation, reduced the total ice volume (or mean ice thickness) in all of the Great Lakes, shortened the ice duration, and allowed earlier warming of water surface. The reduced ice volume was due to the thermal insulation of snow cover. The surface albedo was also increased by snow cover, but its impact on the delay the melting of ice was overcome by the thermal insulation effect. During major snowstorms, snowfall over the open lake caused notable cooling of the water surface due to latent heat absorption. Overall, the sensible heat flux from rain in spring and summer was found to have negligible impacts on the water surface temperature. Although uncertainties remain in over-lake precipitation estimates and model’s representation of snow on the ice, this study demonstrated that winter precipitation, particularly snowfall on the ice and water surfaces, is an important contributing factor in Great Lakes ice production and thermal conditions from late fall to spring.

Methodology:
This dataset includes the representative model results for the Laurentuan Great Lakes from the Finite-Volume Community Ocean Model coupled with the unstructured grid version of the Los Alamos Sea Ice Model (FVCOM-UGCICE), the model source codes, and namelist files that were used for the simulations. In the source codes, the updates are made so that the model can take account of the precipitation heat flux at the ice/water surface.

Instrument and/or Software specifications: N/A

Files contained here:

- FVCOM4.3.1_icealbedo_precip.tar:
The updated model source codes of the Finite-Volume Community Ocean Model coupled with the unstrucutured grid version of Los Alamos Sea Ice Model (FVCOM-UGCICE). This model source codes are based on the official FVCOM version 4.3.1 available at the website of the Marine Ecosystem Dynamics Modeling laboratory at the University of Massachusetts (http://fvcom.smast.umassd.edu/FVCOM/Source/code.htm). The updates were made for this particular study to include the precipitation-induced heat fluxes.

- namelists.tar:
The namelist files that were used for the study. The model was configures for Lake Superior, Michigan-Huron, Erie, and Ontario with 3 numerical experiments for each of the lakes, resulting in 12 cases. The extension (.expt[1-3]) indicates the numerical experiment number, where Expt.1, Expt.2 and Expt. 3 correspond to experiments with no precipitation, precipitation, precipitaiton with prescribed heat fluxes, respectively.

The meteorological forcing dataset used in this study was the High-Resolution Rapid Refresh (HRRR). The HRRR surface meteorological dataset can be publicly accessible at the University of Utah HRRR Download page (http://home.chpc.utah.edu/~u0553130/Brian_Blaylock/cgi-bin/hrrr_download.cgi) and NOAA National Centers for Environmental Prediction (https://www.nco.ncep.noaa.gov/pmb/products/hrrr/).

- sup_expt2.nc.gz, mhs_expt2.nc.gz, erie_expt2.nc.gz, ontario_expt2.nc.gz:
Representative model results containing variables used in the graphics in the reference paper (e.g. ice concentration, ice thickness, precipitation heat fluxes) for Lake Superior, Michigan-Huron, Erie, and Ontario, respectively. The results are from Expt.2 (precipitation experiment).

Related publication:
- Fujisaki-Manome, A., E.J. Anderson, J.A. Kessler, P.Y. Chu, J. Wang, and A.D. Gronewold, Simulating impacts of precipitation on ice cover and surface water
temperature across large lakes, Journal of Geophysical Research Oceans, in revision.

Use and Access:
This data set is made available under a Creative Commons License Attribution 4.0 International (CC BY 4.0).

To Cite Data:
- Ayumi Fujisaki-Manome FVCOM-UGCICE source codes and model results for assessment of precipitation impact on Great Lakes ice cover and water temperature [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/4mpr-4364

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