DOI: 10.5061/dryad.12jm63z4q
title: Australia’s Tinderbox Drought: An extreme natural event likely worsened by human-caused climate change

description: 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.
description: # Australia’s Tinderbox Drought: an extreme natural event likely worsened
 by human-caused climate change
 ## 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 2019 *
 **machine_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&lt;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&lt;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&gt;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&gt;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&gt;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&lt;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