Impact model: GLM-LER

GLM (General Lake Model) is a one-dimensional hydrodynamic lake model, employing a flexible vertical layer structure. Vertical layers can merge or split depending on their respective densities and surface mixing is calculated based on an energy balance approach. GLM-LER is the version of GLM that is incorporated in the GLM3r R package, and is run as part of an ensemble by the LakeEnsemblR (LER) package.

ISIMIP3b

Person responsible for model simulations in this simulation round

Johannes Feldbauer: johannes.feldbauer@tu-dresden.de, 0000-0002-8238-5375, Institute of Hydrobiology, TU Dresden (Germany)

Jorrit Mesman: jorrit.mesman@ebc.uu.se, 0000-0002-4319-260X, Evolutionary Biology Centre, Uppsala University (Sweden)

Output Data

Experiments: ssp370_2015soc_default, ssp126_2015soc_default, ssp585_2015soc_default, historical_2015soc_default, picontrol_2015soc_default
Climate Drivers: GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL
Date: 2023-09-27

Basic information

Model Version: GLM-3.1.1

Model Output License: CC0

Model Homepage: https://aed.see.uwa.edu.au/research/models/GLM/

Model License: GPL-3.0

Reference Paper: Main Reference: Hipsey M, Bruce L, Boon C, Busch B, Carey C, Hamilton D, Hanson P, Read J, de Sousa E, Weber M, Winslow L et al. A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON). Geoscientific Model Development,12,473-523,2019

Reference Paper: Other References: Moore T, Mesman J, Ladwig R, Feldbauer J, Olsson F, Pilla R, Shatwell T, Venkiteswaran J, Delany A, Dugan H, Rose K, Read J et al. LakeEnsemblR: An R package that facilitates ensemble modelling of lakes. Environmental Modelling & Software,143,105101,2021

Resolution

Spatial aggregation: lake

Horizontal resolution: The model was applied to specific case study lakes, forced with meteorology for the 0.5 x 0.5 degree grid cell in which the respective lake is located

Vertically resolved: Yes

Number of vertical layers: Layers of fixed thickness, variable per lake

Additional spatial aggregation & resolution information: The original GLM output is generated for layers that vary over time in depth and number of layers. In LakeEnsemblR, these outputs are interpolated to a fixed grid.

Temporal resolution of input data: climate variables: daily

Input data

Simulated atmospheric climate data sets used: MRI-ESM2-0, IPSL-CM6A-LR, MPI-ESM1-2-HR, UKESM1-0-LL, GFDL-ESM4

Other data sets used: Lakes static information

Climate variables: hurs, sfcWind, tas, rlds, rsds, ps, pr

Spin-up

Was a spin-up performed?: Yes

Spin-up design: First year of meteorological forcing was repeated and placed before simulation period. Only exceptions were lakes Kivu (5 years) and Tahoe (30 years), due to their large depth. In these cases, the first 5 years were repeated multiple times, to avoid creating a climatic trend before start of the actual simulation.

Vegetation

Is co2 fertilisation accounted for?: No

Calibration

Was the model calibrated?: Yes

Which years were used for calibration?: All years for which water temperature observations were provided, were used for calibration. This amount differed per lake.

Which dataset was used for calibration?: GSWP3-W5E5