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\begin{document}

\title{Human influence on the increasing drought risk over Southeast Asian
monsoon region}



\author[1]{Lixia Zhang}%
\author[2]{Ziming Chen}%
\author[3]{Tianjun Zhou}%
\affil[1]{LASG, Institute of Atmospheric Physics Chinese Academy of Sciences}%
\affil[2]{LASG, Institute of Atmospheric Physics, Chinese Academy of Sciences}%
\affil[3]{IAP}%


\vspace{-1em}



  
  \date{May 22, 2024}


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\selectlanguage{english}
\begin{abstract}
Southeast Asian monsoon region is regularly stricken by drought, but
less attention is paid due to its slow-onset and less visual impact.
This study investigated the observed drought changes over Southeast
Asian monsoon region and impacts of anthropogenic forcing using the
Coupled Model Intercomparison Project phase 6 (CMIP6) models. We
revealed an increasing drought risk for 1951-2018 due to more frequent
and wide-spread droughts. The influence of anthropogenic forcing is
successfully detected, which has increased the likelihood of the extreme
droughts in historical simulation by reducing precipitation and
enhancing evapotranspiration. The time of emergence of anthropogenic
forcing in extreme drought occurrence and affected area occurs around
the 1960s. The future projected severe and extreme drought risks are
still beyond natural only forced changes under all scenarios. Our
findings demonstrate a robust impact of anthropogenic forcing on drought
risk over Southeast Asia, and highlight the importance of future pathway
choice.%
\end{abstract}%



\sloppy


\textbf{Table S1} CMIP6 models and the years of their piControl
simulation used in this study\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\textbf{Model} & \textbf{Institute/Country} & \textbf{Lat x Lon} &
\textbf{piControl} & \textbf{Reference}\tabularnewline
\midrule
\endhead
BCC-CSM2-MR & BCC-CMA/China & 160 x 320 & 600 & Wu et al.
(2019)\tabularnewline
CNRM-CM6-1 & CNRM-CERFACS/France & 128 x 256 & 500 & Voldoire et al.
(2019).\tabularnewline
CNRM-ESM2-1 & CNRM-CERFACS/France & 128 x 256 & 500 & S\selectlanguage{ngerman}éférian et al.
(2019)\tabularnewline
CanESM5 & CCCMA/Canada & 64 x 128 & 1000 & Swart et al.
(2019)\tabularnewline
EC-Earth3 & EC-Earth-Consortium/Europe & 256 x 512 & 501 & Haarsma et
al. (2020)\tabularnewline
FGOALS-g3 & LASG-IAP/China & 90x180 & 700 & Li et al.
(2020)\tabularnewline
GFDL-ESM4 & NOAA-GFDL/USA & 180 x 360 & 500 & Dunne et al.
(2020)\tabularnewline
INM-CM4-8 & INM/Russia & 120X180 & 531 & Volodin, et al.
(2018)\tabularnewline
IPSL-CM6A-LR & IPSL/France & 143 x 144 & 1200 & Boucher et al.
(2019)\tabularnewline
MIROC6 & MIROC/Japan & 128 x 256 & 800 & Tatebe et al.
(2019)\tabularnewline
MPI-ESM1-2-HR & MPI-M/Germany & 192 x 384 & 500 & M\selectlanguage{ngerman}üller et al.
(2018)\tabularnewline
MPI-ESM1-2-LR & MPI-M/Germany & 96 x 192 & 1000 & Mauritsen et al.
(2019)\tabularnewline
MRI-ESM2-0 & MRI/Japan & 96 x 192 & 701 & Yakimoto et al.
(2019)\tabularnewline
UKESM1-0-LL & MOHC/UK & 144 x 192 & 1100 & Sellar et al.
(2019)\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table S2 Number of realizations for the historical and future
projection}\selectlanguage{english}
\begin{longtable}[]{@{}llllll@{}}
\toprule
\textbf{Model} & \textbf{Historical} & \textbf{SSP1-2.6} &
\textbf{SSP2-4.5} & \textbf{SSP3-7.0} & \textbf{SSP5-8.5}\tabularnewline
\midrule
\endhead
BCC-CSM2-MR & 3 & 1 & 1 & 1 & 1\tabularnewline
CNRM-CM6-1 & 10 & 6 & 6 & 6 & 6\tabularnewline
CNRM-ESM2-1 & 5 & 5 & 5 & 5 & 5\tabularnewline
CanESM5 & 25 & 14 & 10 & 10 & 10\tabularnewline
EC-Earth3 & 1 & 1 & 1 & 1 & 1\tabularnewline
FGOALS-g3 & 1 & 1 & 1 & 1 & 1\tabularnewline
GFDL-ESM4 & 1 & 1 & 1 & 1 & 1\tabularnewline
INM-CM4-8 & 1 & 1 & 1 & 1 & 1\tabularnewline
IPSL-CM6A-LR & 9 & 5 & 5 & 5 & 5\tabularnewline
MIROC6 & 10 & 10 & 3 & 3 & 10\tabularnewline
MPI-ESM1-2-HR & 1 & 1 & 1 & 1 & 1\tabularnewline
MPI-ESM1-2-LR & 1 & 1 & 1 & 1 & 1\tabularnewline
MRI-ESM2-0 & 1 & 1 & 1 & 1 & 1\tabularnewline
UKESM1-0-LL & 1 & 1 & 1 & 1 & 1\tabularnewline
\bottomrule
\end{longtable}

\textbf{Table S3} TOE (unit: year) of precipitation (P),
evapotranspiration (ET) and P minus ET (PmE) area-averaged over the
Southeast Asian monsoon region firstly occurs in Hist (first row). The
numbers for SSP1-2.6, SSP2-4.5, SSP3.0 and SSP5-8.5 are the years when
the external forced changes fall in the range of internal variability in
the future projection. The ranges in the parenthesis denote the \selectlanguage{ngerman}±1
standard deviation. ``---'' means the external forced changes never
return to natural variability in the future.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{Scenarios} & \textbf{P} & \textbf{ET} &
\textbf{PmE}\tabularnewline
\midrule
\endhead
\textbf{Hist} & 1980 (1973\textasciitilde{}1987) & 1999(1968-2030) &
1981 (1973\textasciitilde{}1989)\tabularnewline
SSP1-2.6 & 2030 (2025\textasciitilde{}2035) & --- & 2049
(2041\textasciitilde{}2057)\tabularnewline
SSP2-4.5 & 2037 (2031\textasciitilde{}2043) & --- & ---\tabularnewline
SSP3-7.0 & 2059 (2054\textasciitilde{}2064) & --- & ---\tabularnewline
SSP5-8.5 & 2039 (2032\textasciitilde{}2046) & --- & 2078
(2061\textasciitilde{}2095)\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Fig.S1} The temporal changes of drought intensity for different
drought categories averaged over Southeast Asian land monsoon region
(10-30\selectlanguage{ngerman}°N, 90-120°E) based on (a) SPEI, and (b) sc-PDSI. The yellow,
orange, brown and red lines represent abnormally dry (SPEI\selectlanguage{english}[?]-0.5,
sc-PDSI\selectlanguage{english}[?]-1.0), moderate drought (SPEI\selectlanguage{english}[?]-1.0, sc-PDSI\selectlanguage{english}[?]-2.0), severe
drought (SPEI\selectlanguage{english}[?]-1.5, sc-PDSI\selectlanguage{english}[?]-3.0), and extreme drought (SPEI\selectlanguage{english}[?]-2.0,
sc-PDSI\selectlanguage{english}[?]-4.0), respectively.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Fig.S2} Same as Fig.1, but for the results based on sc-PDSI.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Fig. S3} The linear trend of (a) surface soil moisture (0-10cm
soil moisture content, unit: kg
m\textsuperscript{-2}68yr\textsuperscript{-1}), (b) severe drought
occurrence (unit: mon 68yr\textsuperscript{-1}), (c) extreme drought
occurrence (unit: mon 68yr\textsuperscript{-1}) for 1951-2014 derived
from GLDAS dataset. To minimize the geophysical discrepancy of soil
moisture, we standardized the surface soil moisture anomalies and then
use the standardized results to characterize drought. A severe and
extreme drought event is a month with the surface soil moisture less
than -1.5 and -2.0 standard deviation, respectively. This approach
adopted here is similar to Sohrabi et al. (2015), but only employs
surface soil moisture.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

\textbf{Fig.A4} (a)-(b), same as Fig.1a-b, bur for the results derived
from SPEI\_PRE. (c) The ratio of the linear trend of SPEI\_PRE to that
of SPEI\_All. (d) the ratio of the linear trend of extreme drought
occurrence derived from SPEI\_PRE to that derived from SPEI\_All. The
original SPEI with both changes in precipitation and ET is referred as
SPEI\_All. SPEI\_PRE is similar to SPEI\_All, but calculated from the
detrended ET for 1901-2018 and the original precipitation (Cook et al.
2014). When the ratio in (c)-(d) is higher than 0.5, it indicates the
contribution of precipitation changes is higher than that of ET.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image7/image7}

\end{center}
\end{figure}

\textbf{Fig. S5} The standard deviation of (a) extreme drought
occurrence (unit: mon per year) and (b) area fraction (unit: \%) from
1950 to 2014 from the observation (dash lines) and the historical run of
the 14 CMIP6 models (bar) for 1951-2014. The blue bars denote the
multi-model ensemble mean (MME). The 20-yr running mean has been carried
out before calculating the standard deviation. (c) and (d) are same as
(a) and (b) but for the severe drought.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image8/image8}

\end{center}
\end{figure}

\textbf{Fig. S6} (a) The spatial distribution of TOE for extreme drought
occurrence firstly appeared in Hist and (b) the anomalies of extreme
drought frequency (unit: mon year\textsuperscript{-1}) averaged over the
20-yr around TOE relative to piControl. The white areas denote that the
TOE does not exist.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image9/image9}

\end{center}
\end{figure}

\textbf{Fig.S7} (a)-(b) are the same as Fig.S6, but for precipitation.
(c)-(f) are the years when changes in precipitation return to the ranges
of internal variability. The stippling denotes that precipitation
decreases exceed the range of internal variability in the TOE.

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