Introduction
Climate resilience is defined as the capacity of an individual site to perform according to its regulatory requirements while impacted by potential stresses imposed by climate variability, weather extremes, and related impacts projected by future climate scenarios. As highlighted in the US Global Change Research Program’s recent National Climate Assessment, the impacts of climate change are broadly distributed across the United States, with regionally-specific effects potentially threatening sites and site infrastructure under remediation or with waste disposal cells. Therefore, we developed the climate-resilience package (https://pypi.org/project/climate-resilience/) to aid the long-term climate resilience and vulnerability assessment for soil and groundwater-contaminated sites.
climate-resilience
Download Examples
This file requires a download_params.yml file to specify the download configurations.
We cannot directly download the data from the Google Earth Engine directly onto the local machine. So the best option is to download to the drive and then download that data to the local drive.
Preprocess Examples
The preprocessing functions will expect that the local data drive contains the downloaded data.
If the data is on drive, the drive needs to be mounted. This is easier to do in a google colab session. Once the drive is mounted, the path of the mounted drive can be used with the functions as normal.
Expected file and directory structure:
The input file and directory structure for functions calculate_Nth_percentile(), calculate_pr_count_amount(), and calculate_temporal_mean() in the preprocessing code should be as follows:
datadir
├── scenario1_variable1_ensemble
│ ├── name1_state1_scenario1_variable1.csv
│ └── name2_state2_scenario1_variable1.csv
├── scenario1_variable2_ensemble
│ ├── name1_state1_scenario1_variable2.csv
│ └── name2_state2_scenario1_variable2.csv
├── scenario2_variable1_ensemble
│ ├── name1_state1_scenario2_variable1.csv
│ └── name2_state2_scenario2_variable1.csv
└── scenario2_variable2_ensemble
├── name1_state1_scenario2_variable2.csv
└── name2_state2_scenario2_variable2.csv
Visualization Examples
The visualization code will be easier to be used in a notebook as inline visualizations can be used.
Map visualization notebook
Below is a screenshot of the interactive map with the sites marked.
Box plot visualization notebook
Below is a screenshot of boxplot of annual precipitation in different regions of the United States.
Library Features:
Downloader
Class SiteDownloader member functions: