Awesome

Impact-Based Forecasting of Tropical Cyclone-Related Human Displacement to Support Anticipatory Action

These scripts reproduce the main results of the paper:

Impact-Based Forecasting of Tropical Cyclone-Related Human Displacement to Support Anticipatory Action.

Pui Man Kam (1,2), Fabio Ciccone (1), Chahan, M. Kropf (1,3), Lukas Riedel (1,3), Christopher Fairless (1), and David N. Bresch (1,3)

Publication status: under revision.

(1) Institute for Environmental Decisions, ETH Zurich, Switzerland

(2) Internal Displacement Monitoring Centre, Geneva, Switzerland

(3) Federal Office of Meteorology and Climatology MeteoSwiss, Switzerland

Contact: Pui Man Kam (mannie.kam@usys.ethz.ch)

Content:

The project is seperated into two main folders. TC_Yasa_case_study contains all the scripts to reproduce the results from the case study of TC Yasa that caused displacement in Fiji. Sensitivity_analysis_events_2017-2020 contains scripts for the sensitivity analysis for all TC displacement events recorded between 2017-2020.

TC_Yasa_case_study

TC_yasa_FJI_2d_leadtime.py: Python script for running the impact forecast for displacement at 2 days leadtime (2020-12-15 00UTC) prior the landfall of TC Yasa at Fiji. This script can be run independantly with the fulfilment of data requirements.

tc_haz_Yasa.py: Python script for calculating the 1-minute maximum sustained wind speed at 10 metres from surface for TC Yasa. The forecast initiate time is ranging from 2020-12-13 12UTC to 2020-12-17 00UTC with time interval of 12 hours. The output hdf5 files are the hazard sets, which are further used for the impact calculation.

calc_unc_Yasa_FJI.py: Python script for computing the uncertainty and sensitivity analysis for the TC Yasa case study. Make sure to run this after tc_haz_Yasa.py.

Sensitivity_analysis_events_2017-2020

create_NETCDF_from_TIGGE_n2o_matched_ibtracs.py: Python script for extracting archived TC track forecast incxml format from TIGGE project NetCDF files for later computation. Original data can be retrived from NCAR Data Research Archive.

unc_sen_analysis_events_2017-2020.py: Python script for computing the uncertainty and sensitivity analysis for all TC displacement events recorded between 2017-2020. The output hdf5 files are the CLIMADA UncOutput objects. Make sure to run this after create_NETCDF_from_TIGGE_n2o_matched_ibtracs.py, and load_TIGGE_tracks.py which contains the function to read TC tracks in NetCDF into CLIMADA is placed in the same working directory,

unc_output_to_xlsx.py: Python script for reading the hdf5 files output from unc_sen_analysis_events_2017-2020.py into xlsx files.

load_TIGGE_tracks.py: Python script that contains function to process TC tracks in NetCDT file (output from create_NETCDF_from_TIGGE_n2o_matched_ibtracs.py) into climada.hazard.TCTracks object.

Requirements

Requires:

• Python 3.9+ environment (best to use conda for CLIMADA repository)
• CLIMADA repository version 3.3.3+: https://github.com/CLIMADA-project/climada_python

ETH cluster

Computationally demanding calculations were run on the Euler cluster of ETH Zurich.

Documentation:

Publication: submitted to Nature Communications

Documentation for CLIMADA is available on Read the Docs:

• online (recommended)
• PDF file

If script fails, revert CLIMADA version to release v3.3.3:

• from GitHub

History

Created on 25 June 2024

www.wcr.ethz.ch