Estimates of Global Coastal Losses Under Multiple Sea Level Rise Scenarios ...

• Main Authors: Bolliger, Ian, Depsky, Nicholas, Allen, Daniel, Choi, Jun Ho, Delgado, Michael, Greenstone, Michael, Hamidi, Ali, Houser, Trevor, Hsiang, Solomon, Kopp, Robert E.
• Format: Dataset
• Language: English
• Published: Zenodo 2023
• Subjects: climate change; climate adaptation; economics; climate impacts; migration; sea level rise; natural hazards; Diaz; Ice Sheet
• Online Access: https://dx.doi.org/10.5281/zenodo.8229860; https://zenodo.org/record/8229860

Results from the Python Coastal Impacts and Adaptation Model (pyCIAM), along with the inputs and source code necessary to replicate these outputs and the results presented in Depsky et al. 2023 (under review). All zipped Zarr stores can be downloaded and accessed locally or can be directly accessed via code similar to the following: <code class="language-python">from fsspec.implementations.zip import ZipFileSystem import xarray as xr xr.open_zarr(ZipFileSystem(url_of_file_in_record}}).get_mapper()) File Inventory Products pyCIAM_outputs.zarr.zip : Outputs of the pyCIAM model, using the SLIIDERS dataset to define socioeconomic and extreme sea level characteristics of coastal regions and the 17th, 50th, and 83rd quantiles of local sea level rise as projected by various modeling frameworks (LocalizeSL and FACTS) and for multiple emissions scenarios and ice sheet models. diaz2016_outputs.zarr.zip : A replication of the results from Diaz 2016 - the model upon which pyCIAM was built, using an identical ...