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Impact model: air2water6par

Sector
Lakes (local)
Region
local

air2water6par is a hybrid physically-based/statistical model to predict Lake Surface Water Temperature (LSWT) and epilimnion thickness relying solely on air temperature as external forcing.
https://github.com/spiccolroaz/air2water/blob/master/README.txt

Information for the model air2water6par is provided for the simulation rounds shown in the tabs below. Click on the appropriate tab to get the information for the simulation round you are interested in.

Person responsible for model simulations in this simulation round
Sebastiano Piccolroaz: s.piccolroaz@unitn.it, Free University in Bolzano (Italy)
Bronwyn Woodward: bronwyn.woodward@uwa.edu.au, University of Western Australia (Australia)
Richard Iestyn Woolway: riwoolway@gmail.com, Dundalk Institute of Technology (Ireland)
Additional persons involved: Sebastiano Piccolroaz (s.piccolroaz@unitn.it)
Person responsible for model simulations in this simulation round
Sebastiano Piccolroaz: s.piccolroaz@unitn.it, Free University in Bolzano (Italy)
Bronwyn Woodward: bronwyn.woodward@uwa.edu.au, University of Western Australia (Australia)
Richard Iestyn Woolway: riwoolway@gmail.com, Dundalk Institute of Technology (Ireland)
Additional persons involved: Sebastiano Piccolroaz (s.piccolroaz@unitn.it)
Output Data
Experiments: I, II, III, VIII
Climate Drivers: None
Date: 2020-04-01
Basic information
Model Version: 2.0.0
Model Output License: CC BY 4.0
Simulation Round Specific Description: ISIMIP2b simulation round
Reference Paper: Main Reference: Piccolroaz S, Toffolon M, Majone B et al. A simple lumped model to convert air temperature into surface water temperature in lakes. Hydrology and Earth System Sciences,17,3323–3338,2013
Reference Paper: Other References:
Resolution
Spatial aggregation: lake
Temporal resolution of input data: climate variables: daily
Additional temporal resolution information: The model needs daily air temperature data, which can be provided by daily observed/modeled values or reconstructed through daily interpolation of coarser resolution averages (e.g., weekly, monthly)
Input data
Simulated atmospheric climate data sets used: IPSL-CM5A-LR, HadGEM2-ES, GFDL-ESM2M, MIROC5
Observed atmospheric climate data sets used: EWEMBI
Spin-up
Was a spin-up performed?: Yes
Spin-up design: The first year of each simulation period was run starting from LSWT at 4°C, and the LSWT at the end of this period was used to initialize the simulation runs.
Vegetation
Is co2 fertilisation accounted for?: No
Calibration
Was the model calibrated?: Yes
Which years were used for calibration?: Dependent on experiment period and period covered by water temperature observations
Which dataset was used for calibration?: Dependent on experiment period




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