Australia’s Tinderbox Drought: An extreme natural event likely worsened by human-caused climate change
Data files
Feb 15, 2024 version files 28.54 GB
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README.md
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Tinderbox_Drought_data.zip
Abstract
We examine the characteristics and causes of southeast Australia’s Tinderbox Drought (2017–2019) that preceded the Black Summer fire disaster. The Tinderbox Drought was characterised by cool season rainfall deficits of around –50% in three consecutive years, which was exceptionally unlikely in the context of natural variability alone. The precipitation deficits were initiated and sustained by an anomalous atmospheric circulation that diverted oceanic moisture away from the region, despite traditional indicators of drought risk in southeast Australia generally being in neutral states. Moisture deficits were intensified by unusually high temperatures, high vapour pressure deficits and sustained reductions in terrestrial water availability. Anthropogenic forcing intensified the rainfall deficits of the Tinderbox Drought by around 18% with an interquartile range of 34.9% to –13.3% highlighting the considerable uncertainty in attributing droughts of this kind to human activity. Skillful predictability of this drought was possible by incorporating multiple remote and local predictors through machine learning, providing prospects for improving forecasting of multi-year droughts.
README: Australia’s Tinderbox Drought: an extreme natural event likely worsened by human-caused climate change
https://doi.org/10.5061/dryad.12jm63z4q
Description of the data and file structure
Tinderbox_Drought_data.zip is an archive that contains the listed folders.
Contents of each folder:
agricultural_impacts: Processed data of historical anomalies in agricultural yield, production and area harvested of major crops.
drought_break_probability
GLM_results_.nc: contains the estimated parameters of the GLM models and the drought breaking probabilities predicted using the models.
probability_contributions/GLM_base_probability_.nc: contains the base GLM probabilities corresponding to zero values of the climate indices, and the probabilities after including the climate predictors one by one.drought_focus_region
The shapefile of the drought focus region identified based on percentile thresholds of rainfall & soil moisture, as well as standardised indices.drought_occurrence_probability
100 realisations of area-mean rainfall over the 2017-2019 drought area, with one value per year for 117 years. Values are anomalies from the 1900-2016 mean, with a three-month running mean applied prior to calculation of the annual or seasonal means. ‘AMJJAS’ = April to September inclusive; ‘DJF’ = December to February inclusive; ‘ann’ = January to December inclusive. Each column is one realisation; the final column is an arbitrary year column. Linear Inverse Models were calculated using Australian rainfall data from AGCD, and global sea surface temperature data from COBE or ERSST.land_atmopshere_feedbacks
directory 'drght_2017_2019_bl_pbl2_mp4_sf_sfclay2_climatology_2018':
CLIM simulation during Dec 2018 ~ Jan 2019 initialised by 1970-1999 climatological soil and aquifer moisture on 30 Nov.
directory 'drght_2017_2019_bl_pbl2_mp4_sf_sfclay2_climatology_2019':
CLIM simulation during Dec 2019 ~ Jan 2020 initialised by 1970-1999 climatological soil and aquifer moisture on 30 Nov.
directory 'drght_2017_2019_bl_pbl2_mp4_sf_sfclay2_20181201':
DROUGHT simulation during Dec 2018 ~ Jan 2019 initialised by equilibrated land conditions from the offline simulation on 30 Nov 2018
directory 'drght_2017_2019_bl_pbl2_mp4_sf_sfclay2_20191201':
DROUGHT simulation during Dec 2019 ~ Jan 2020 initialised by equilibrated land conditions from the offline simulation on 30 Nov 2019machine_learning_prediction
The drought impacts are collated based on information from the sources listed in Supplementary Table S4.
In the file ML_Database_All_AWRA_MOf_and_3MPrecip.csv, the first few columns is the drought database and the remaining columns are the coinciding climate conditions.moisture_sources
Directory fig_6_finished contains two subdirectories fig_6_a_b_c, and fig_6_d_e_f.
Subdirectory fig_6_a_b_c contains netcdf files of:
2017 (oceanic_apr_jul_2017_fw.nc),
2018 (oceanic_apr_jul_2018_fw.nc), and
2019 (oceanic_apr_jul_2019_fw.nc) oceanic moisture contribution (E-P<0; in mm/day) determined in a forward experiment.
These files are used to calculate anomalies for:
2017 (oceanic_anomaly_apr_jul_2017_respect_to_clim_apr_jul_1980_2016_fw.nc)
2018 (oceanic_anomaly_apr_jul_2018_respect_to_clim_apr_jul_1980_2016_fw.nc), and
2019 (oceanic_anomaly_apr_jul_2019 _respect_to_clim_apr_jul_1980_2016_fw.nc)
relative to climatology Apr-Jul 1980–2016 (oceanic_apr_jul_1980_2016_fw_clim.nc).Subdirectory fig_6_d_e_f contains netcdf files of
2017 (terrestrial_apr_jul_2017_fw.nc),
2018 (terrestrial_apr_jul_2018_fw.nc), and
2019 (terrestrial_apr_jul_2019_fw.nc) terrestrial moisture contribution (E-P<0; in mm/day) determined in a forward experiment.
These files are used to calculate anomalies for:
2017 (terrestrial_anomaly_apr_jul_2017_respect_to_clim_apr_jul_1980_2016_fw.nc)
2018 (terrestrial_anomaly_apr_jul_2018_respect_to_clim_apr_jul_1980_2016_fw.nc), and
2019 (terrestrial_anomaly_apr_jul_2019_respect_to_clim_apr_jul_1980_2016_fw.nc)
relative to climatology Apr-Jul 1980–2016 (terrestrial_apr_jul_1980_2016_fw_clim.nc).Directory fig_s7_finished contains netcdf files to plot climatological moisture sources (E-P>0) with optimal integration time for the Tinderbox Drought region obtained from the backward experiment from 1980 to 2016.
April 1980-2016 (apr_1980_2016_bw_6_days.nc),
May 1980-2016 (may_1980_2016_bw_7_days.nc)
June 1980-2016 (jun_1980_2016_bw_8_days.nc)
July 1980-2016 (jul_1980_2016_bw_8_days.nc)
August 1980-2016 (aug_1980_2016_bw_8_days.nc)
September 1980-2016 (sep_1980_2016_bw_9_days.nc)Directory fig_s8_finished
Contains netcdf files of:
2017 (apr_jul_2017_bw.nc), 2018 (apr_jul_2018_bw.nc), and 2019 (apr_jul_2019_bw.nc) moisture sources (E-P>0; in mm/day) determined in a bacward experiment.
These files are used to calculate anomalies of moisture sources for:
2017 (anomaly_apr_jul_2017_respect_to_clim_apr_jul_1980_2016_bw.nc),
2018 (anomaly_apr_jul_2018_respect_to_clim_apr_jul_1980_2016_bw.nc), and
2019 (anomaly_apr_jul_2019_respect_to_clim_apr_jul_1980_2016_bw)
relative to climatology Apr-Jul 1980–2016 (apr_jul_1980_2016_bw.nc).Directory fig_s9_finished contains two subdirectories fig_ss9_a_b, and fig_s9_c_d_e_f.
Subdirectory fig_s9_a_b contains netcdf files of:
2017 (apr_sep_2017_bw.nc), and 2018 (apr_sep_2018_bw.nc) moisture sources (E-P>0; in mm/day) determined in a bacward experiment.
These files are used to calculate anomalies of moisture sources for:
2017 (apr_sep_2017_anomaly_respect_to_clim_apr_sep_1980_2016_bw.nc) and
2018 (apr_sep_2018_anomaly_respect_to_clim_apr_sep_1980_2016_bw.nc)
relative to climatology Apr-Sep 1980–2016 (apr_sep_1980_2016_bw.nc).Subdirectory fig_s9_c_d_e_f contains netcdf files of:
2017 (oceanic_apr_sep_2017_fw.nc), 2018 (oceanic_apr_sep_2018_fw.nc) oceanic moisture contribution and
2017 (terrestrial_apr_sep_2017_fw.nc), 2018 (terrestrial_apr_sep_2018_fw.nc) terrestrial moisture contribution (E-P<0; in mm/day) determined in a forward experiment.
These files are used to calculate anomalies of oceanic and terrestrial contribution for:
2017 (oceanic_anomaly_apr_sep_2017_respect_to_clim_apr_sep_1980_2016_fw.nc), and
2018 (oceanic_anomaly_apr_sep_2018_respect_to_clim_apr_sep_1980_2016_fw.nc)
relative to climatology Apr-Sep 1980–2016 (oceanic_apr_sep_1980_2016_fw_clim.nc) and
2017 (terrestrial_anomaly_apr_sep_2017_respect_to_clim_apr_sep_1980_2016_fw.nc), and
2018 (terrestrial_anomaly_apr_sep_2018_respect_to_clim_apr_sep_1980_2016_fw.nc)
relative to climatology Apr-Sep 1980–2016 (terrestrial_apr_sep_1980_2016_fw_clim.nc).
synoptic_analysis
Daily_rainfall_area_1980_2016.nc & Daily_rainfall_area_2015_2020.nc: Processed daily rainfall files for the Tinderbox Drought region. These are used to calculated the anomalous rainfall proportions decsribed in the synoptics section.
precip_attr_JJA_HREs_Tinderbox.nc: precipitation attributed to weather systems for JJA heavy rainfall events over the Tinderbox region in the period 1980-2019.
Code/Software
Tinderbox_Drought_code.zip
The zip archive contains the code used for analyses archived from https://github.com/anjanadevanand/Tinderbox_drought