README

Brief Overview

This is a quick reference to understand the files used in the UCLA Mono Lake Model (UCLA-MLM) User Interface.

File Descriptions

• UCLA_MLM_User_Interface.ipynb: This is the primary user interface, which allows users to interactively set-up and simulate how Mono Lake Water Level responds to a different export criteria and climate scenarios

• Mono_Lake_Interface_lib_v4.py: This contains the bulk of python code functions used to represent the Mono Lake Water Budget (MLWB) and used to create figures in the user interface (this file is loaded into UCLA_MLM_User_Interface.ipynb). Within this file, a function called predict_Mono_Lake_Water_Level_Added_Policies contains the water budget model code. The creation of export criteria and figures depend on a variety of functions within the python file. If comfortable with python, you can add flexibility to the export criteria and figure creation.

• data.tar: This contains the climate projections across Mono Basin that are required as critical components for the Mono Lake Water Budget (e.g. precipitation on Mono Lake). It is unpacked in Step 0 of the notebook.

• Mono_Lake_Area_Storage_Elev.txt: This contains the relationship between Mono Lake storage, water level, and surface area

• details_for_model.csv: This contains a few fine-tuned parameters that are used by the UCLA-MLM

• colab_requirements.txt: Pinned Python package versions used for Google Colab deployment. This ensures the Colab environment matches the versions tested during development. It is installed automatically in Step 0 of the notebook.

• local_requirements.txt: Full pip freeze of the local development environment, used for setting up a local Python environment to run the notebook outside of Colab.

• For_Running_Model The wrapped run and climate projection atmospheric and flow data can be viewed by opening this folder.Inside this folder, the historical reconstruction of observed weather conditions, which is used for the wrapped runs, can be found in "ERA5_Historical_Data". The climate model data can be found in "Dynamic_RYT_SEF". Note, each climate model and emission scenario has its own file in "Dynamic_RYT_SEF"...The actual water levels are determined later when the water budget model is simulated against the export criteria that are of interest.

Overview of Shared Socioecononomic Pathways (SSPs)

CMIP6 simulates GCMs under historical emissions and different greenhouse gas emission trajectories, known as Shared Socioeconomic Pathways (SSPs). Different SSPs exist to allow for assessments of how varying levels of emissions related to different societal choices may influence future climate change.

The UCLA-MLM focuses on the three SSPs available from CA5: SSP2-4.5, SSP3-7.0, and SSP5-8.5. These scenarios were selected because they span a range of plausible future emissions pathways, from moderate (SSP2-4.5) to very high (SSP5-8.5), relative to historical levels (Fifth National Climate Assessment, 2023). There is substantial uncertainty associated with which emission scenario will be realized; however, SSP2-4.5 and SSP3-7.0 are generally considered more likely than SSP5-8.5 (Huard, 2022).

• SSP2-4.5 includes moderate efforts to mitigate climate change and reflects a world with gradual progress toward sustainability.
• SSP3-7.0 is often considered an intermediate-high or "business as usual" pathway, where global efforts to reduce greenhouse gas emissions are limited.
• SSP5-8.5 is often referred to as the "worst-case scenario" and assumes rapid economic growth fueled by intensive fossil fuel use.

Overview of Export Criteria

Pre-Loaded Transition Export Criteria

Pre-Loaded Post-Transition Export Criteria

Existing Transition Export Criteria and Post-Transition Export Criteria

More background information on Mono Lake and further details associated with the UCLA-MLM can be found in the accompanying report delivered to the SWRCB.