SUMMA (Structure for Unifying Multiple Modeling Alternatives)

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Forcing Data Description Features Workflow

Hydrological Model

SUMMA (Structure for Unifying Multiple Modeling Alternatives)

Required Data

1. precipitation rate [kg m-2 s-1] 2. incoming shortwave radiation [W m-2] 3. incoming longwave radiation [W m-2] 4. air temperature [K] 5. wind speed [m s-1] 6. air pressure [Pa] 7. specific humidity [g g-1]

Data Sources

● Currently being set up for ERA5 (global) and SNOTEL network (point scale) Note: See https://github.com/CH-Earth/summaWorkflow_public which contains source code and exemplifies how to configure the model

Spatial Resolution

Flexible

Temporal Resolution

Flexible

File Format

● Forcing must be provided in .nc files, with a time and HRU dimension

Strengths and Limitations

● Not limited to a given spatial or temporal resolution

External and Internal Tools

● Python CANDEX package to convert forcing to the required spatial domain (e.g. spatial interpolation ● Python METSIM package for temporal disaggregation, estimating missing forcing variables. TBD_STEPHEN best possible links here-above-to

Source Code Availability

● External tools available on github with examples TBD_STEPHEN best possible links on github

Model Workflow

1. Download raw forcing data 2. [Optional] construct and/or disaggregate missing forcing data 3. [Optional] re-sample data from native spatial resolution to desired configuration (grid or irregular shapes) 4. [Optional] re-sample data from native temporal resolution to desired time step size 5. Convert forcing data to .nc file with dimensions time and hru.

Notes

Detailed Model Setup: https://github.com/CH-Earth/summaWorkflow_public Above link contains scripts to install, set up and run the Structure for Unifying Multiple Modeling Alternatives (SUMMA, Clark et al., 2015a,b) and mizuRoute (Mizukami et al., 2016) to generate hydrologic simulations for a given domain. Documentation: https://ral.ucar.edu/projects/summa https://summa.readthedocs.io/en/latest/ https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2015WR017198