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\title{Supplementary material for \\
"How will global change scenarios affect solar energy resources in diversified Brazilian climate regions?"}

%\author[]{Paula Conde Santos Borba \footnote{Corresponding author: paula.borba@ga.ita.br} \orcidlink{0000-0002-4714-5659} \ Wilson C. Sousa Junior\orcidlink{0000-0001-6176-2410} \ Stefan Pfenninger \orcidlink{0000-0002-8420-9498}}


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%\title{Supplementary material for "How will global change scenarios affect solar energy resources in diversified Brazilian climate regions?"}

\begin{center}
{\centering\textbf{\Large{Supplementary Material for "Reducing uncertainties of climate projections on solar energy resources in Brazil"}}} 
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{\centering {Francisco José Lopes de Lima$^{1,3}$} \orcidlink{0000-0002-8503-233X}
André Rodrigues Gonçalves$^{1}$\orcidlink{0000-0002-9430-1685}
Rodrigo Santos Costa$^{1}$ \orcidlink{0000-0002--9544-4610}
Marcelo Pizzuti Pes$^{1,3}$ \orcidlink{0000-0002-3930-4031}
%Ana Paula Paes dos Santos$^1$ \orcidlink{0000-0002-7736-7818}
Jose Antonio Marengo Orsini$^2$ \orcidlink{0000-0001-8578-7639}
Enio Bueno Pereira$^{1}$ \orcidlink{0000-0002-5095-0085}
Fernando Ramos Martins$^{3}$ \orcidlink{0000-0002-7618-4462}} %\Envelope}


\end{center}

\begin{center}
\scriptsize{1. Division of Impacts, Adaptation and Vulnerabilities, National Institute for Space Research, São José dos Campos, SP, Brazil. \\
2. National Center for Monitoring and Early Warning of Natural Disasters, São José dos Campos, Brazil. \\
3. Institute of Marine Sciences, Federal University of São Paulo - \textit{campus} Baixada Santista, Santos, SP, Brazil.}\\
%\Envelope - fernando.martins@unifesp.br}
\end{center} 

\vspace{1cm}

This manuscript includes supplementary tables and figures to complement the information and results presented in the submitted paper %(\url{ doi xxx}).
. Results, additional datasets, and codes used in data analysis are deposited at available for public access at \url{10.6084/m9.figshare.25396612} and \url{10.6084/m9.figshare.25396210}. 

%This supplementary material includes methods and results of the published paper "\textit{X}" (\url{ doi xxx}). The model has been deposited to Zenodo \url{XX}. Results and additional data are available on: \url{XXX}.

\vspace{1cm}

\tableofcontents
\newpage

\section{BIAS CORRECTION OF ERA5 DATASET}
Fig. \ref{fig:SSR_targets} shows the downward surface solar irradiance \((SSR\)) climatology obtained from the bias-adjusted reanalysis (\(ERA5_{QM}\)) for the 1980-2014 period, overlayed to three target regions. It is the reference dataset used to evaluate CMIP6 models’ deviations. \\

\begin{figure}[h]
  \centering
  \includegraphics[scale=0.44]{Sup_figs/FiguraS01.jpg}
  \captionsetup{justification=justified}
  \caption{Surface solar irradiance reference map based on the \(ERA5_{QM}\). The rectangles indicate the target regions used in the performance evaluation of CMIP6 models: area A1 (red) in the Brazilian Northeast, A2 (blue) in the South, and A3 (black) in the Central of Brazil.}
  \label{fig:SSR_targets}
\end{figure}

Fig. \ref{fig:maps_biascorrection}(a and b) shows the \(SSR\) mapping in the Brazilian territory using the BSR and ERA5 datasets. Both datasets present a similar geographical pattern, but Fig. \ref{fig:maps_biascorrection}(c) demonstrates that the original ERA5 dataset has a moderate bias (up to 20 \(W/m^2\)) concerning the reference data (BSR). Besides that, the ERA5 dataset overestimates \(SSR\) variability in northern Brazil, as indicated in Fig. \ref{fig:maps_biascorrection}(e). 

After applying the Quantile Mapping approach, the \(ERA5_{QM}\) dataset has the bias reduced to values lower than 5 \(W/m^2\) (Fig. \ref{fig:maps_biascorrection}(d)). The maximum monthly standard deviation differences were also reduced from 30 to 10 \(W/m^2\), as shown in Fig. \ref{fig:maps_biascorrection}(f). In summary, the bias-corrected ERA5 database \(ERA5_{QM}\) provides \(SSR\) data with very high confidence for 34 years (from 1980 to 2014), matching the required features to be a reference dataset for the performance evaluation of the CMIP6 climate models. \\

\begin{figure}[H]
  \centering
  \includegraphics[width=0.82\textwidth]{Sup_figs/FiguraS02.jpg}
  \captionsetup{justification=justified}
  \caption{Annual mean of \(SSR\) map prepared using BSR (a) and ERA5 (b) datasets; b) deviation map of annual mean \(SSR\) from ERA5 dataset (c) and \(ERA5_{QM}\) (d) concerning the BSR dataset; the standard deviation map from \(SSR\) from ERA5 (e) and \(ERA5_{QM}\) (f).}
  \label{fig:maps_biascorrection}
\end{figure}

\newpage
\section{SPATIAL CORRELATION}

\begin{longtblr}[ 
caption = {Results from spatial correlation analysis between \(SSR\) in \(ERA_{QM}\) and CMIP6 climate models and the ensemble (ENS). The symbol (***) represents a significant correlation (p < 0.05) in all target areas. The “0” means no-significant correlation in the sequence of target areas A1, A2, and A3. Models highlighted in orange were removed from the next method step},
label = {tab:spatial_corr},  ]
{
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  hlines,
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\textbf{ID.} & \textbf{JAN} & \textbf{FEB} & \textbf{MAR} & \textbf{APR} & \textbf{MAY} & \textbf{JUN} & \textbf{JUL} & \textbf{AUG} & \textbf{SEP} & \textbf{OCT} & \textbf{NOV} & \textbf{DEC} \\
\textbf{M01}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & ***          & ***          \\
\textbf{M02}       & ***          & **0          & **0          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & **0          & **0          \\
\textbf{M03}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M04}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & ***          & ***          \\
\textbf{M05}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M06}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & ***          & ***          \\
\textbf{M07}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & ***          & ***          \\
\textbf{M08}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M09}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M10}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M11}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M12}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M13}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M14}       & ***          & ***          & 0**          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M15}       & ***          & ***          & 0**          & **0          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M16}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M17}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M18}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M19}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M20}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & ***          & **0          \\
\textbf{M21}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M22}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M23}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M24}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & 0**          & ***          \\
\textbf{M25}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M26}       & 0**          & 0**          & 0**          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M27}       & ***          & ***          & ***          & **0          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M28}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M29}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & ***          & ***          \\
\textbf{M30}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & ***          & ***          \\
\textbf{M31}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & **0          & ***          \\
\textbf{M32}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M33}       & 0**          & ***          & 0**          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & 0**          \\
\textbf{M34}       & 0**          & 0**          & 0**          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & ***          & 0**          \\
\textbf{M35}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M36}       & ***          & ***          & 0**          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M37}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & **0          & ***          & ***          \\
\textbf{M38}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M39}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{M40}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          \\
\textbf{ENS}       & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          & ***          

\end{longtblr}

\newpage
\section{ANNUAL CYCLE OF SURFACE SOLAR RADIATION (SSR)}

Fig. \ref{fig:plot_SSRsazonal} displays the annual cycle of \(SSR\) in the three target areas, as determined by \(SME\) and the \(ERA5_{QM}\) dataset. The \(SSR\) deviations are generally below 20\(W/m^2\), except for September through November in area A1 (red lines). The high correlation coefficients (greater than 0.80) indicate that \(SME\) accurately represents the annual cycle of \(SSR\) for the three target areas.

\begin{figure}[ht]
  \centering
  \includegraphics[scale=0.45]{Sup_figs/FiguraS03.jpg}
  \captionsetup{justification=justified}
  \caption{Annual cycle of \(SSR\) in the three target areas used in performance assessment of CMIP6 models. The line plot presents the \(SME\) outcomes (dotted lines) and the reference ERA5.QM dataset ( solid lines) for the historical period.}
  \label{fig:plot_SSRsazonal}
\end{figure}


\section{STATISTICAL METRICS ACHIEVED BY CMIP6 MODELS}

Table \ref{tab:22CMIP_metrics} lists the statistical metrics achieved by the twenty-two CMIP6 models with significant spatial correlation according to Table \ref{tab:spatial_corr}. The 40-models' ensemble \(ENS\) is in the penultimate line. The statistical parameters are referred to the average value of the three target areas. Based on the performance evaluation results, a Smart Ensemble Model (\(SME\)) using the ten models with \(TSS\) higher than 0.9 was executed to predict \(SSR\) data in future climate scenarios.

\definecolor{Gray}{rgb}{0.501,0.501,0.501}
\begin{table} [htbp]
\centering
\captionsetup{justification=justified}
\caption{Statistical metrics achieved by the CMIP6 models with significant spatial correlation. The 40-models ensemble \(ENS\) is in last line. The models with TSS < 0.9 are highlighted in gray.}
\begin{tblr}{
  %width = \linewidth,
  %colspec = {Q[154]Q[160]Q[229]Q[271]Q[96]},
  row{2} = {fg=blue},
  row{3} = {fg=blue},
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  %hlines,
  hline{1,26} = {-}{0.1em},
  hline{2,12,24} = {-}{0.06em},
}
\textbf{Models} & {\textbf{uRMSD}\\\textbf{$(W.m^{-2})$}} & {\textbf{Time}\\\textbf{Correlation}} & {\textbf{Std Deviation}\\\textbf{$(W.m^{-2})$}} & {\textbf{TSS}} \\
M25             & 6.55                              & 0.98                                  & 32.02                                     & 0.98                                              \\
M40             & 8.20                              & 0.97                                  & 34.41                                     & 0.96                                              \\
M19             & 7.85                              & 0.97                                  & 28.92                                     & 0.95                                              \\
M03             & 8.18                              & 0.96                                  & 30.48                                     & 0.95                                              \\
M35             & 8.65                              & 0.96                                  & 32.77                                     & 0.95                                              \\
M28             & 8.81                              & 0.96                                  & 31.71                                     & 0.94                                              \\
M38             & 9.30                              & 0.95                                  & 28.63                                     & 0.92                                              \\
M17             & 10.19                             & 0.94                                  & 29.07                                     & 0.91                                              \\
M08             & 9.91                              & 0.97                                  & 23.35                                     & 0.90                                              \\
M16             & 10.82                             & 0.94                                  & 29.46                                     & 0.90                                              \\
M11             & 11.07                             & 0.93                                  & 26.75                                     & 0.88                                              \\
M23             & 12.39                             & 0.92                                  & 30.22                                     & 0.86                                              \\
M21             & 13.01                             & 0.91                                  & 26.23                                     & 0.82                                              \\
M22             & 13.73                             & 0.89                                  & 26.79                                     & 0.81                                              \\
M13             & 13.65                             & 0.90                                  & 25.06                                     & 0.80                                              \\
M05             & 13.71                             & 0.90                                  & 25.33                                     & 0.80                                              \\
M12             & 14.82                             & 0.88                                  & 24.77                                     & 0.76                                              \\
M18             & 17.21                             & 0.83                                  & 24.42                                     & 0.68                                              \\
M32             & 17.55                             & 0.83                                  & 20.90                                     & 0.63                                              \\
M39             & 18.02                             & 0.82                                  & 20.60                                     & 0.61                                              \\
M10             & 18.92                             & 0.80                                  & 20.89                                     & 0.57                                              \\
M09             & 21.27                             & 0.72                                  & 23.45                                     & 0.52                                              \\
ENS             & 10.24                             & 0.94                                  & 27.62                                     & 0.90                                              \\
SME             & 7.79                              & 0.97                                  & 29.90                                     & 0.96                                              
\end{tblr}
\label{tab:22CMIP_metrics}
\end{table}

\newpage
\section{SEASONAL VARIABILITY OF CLIMATE CHANGE FACTOR (CCF)}
Figs. \ref{fig:plot_CCRsazonal_A1},  \ref{fig:plot_CCRsazonal_A2} and \ref{fig:plot_CCRsazonal_A3} compare the climate change factor (\(CCF\)) obtained from \(SME\) predictions for the future climate scenarios in timeslices - near-future and end-of-century.

The seasonal \(CCF\) variation for the Northeastern (area A1) and Central regions of Brazil (area A3) presents positive values all year long for the near future, denoting an increase in \(SSR\) between 1\% and 2.5\%.   The highest \(CCFs\) in the Central region occur during the rainy season (from November to February) (3-5\% in SSP5-8.5 and 2-3\% in SSP2-4.5) at the 2071-2100 timeslice, as indicated in Fig. \ref{fig:plot_CCRsazonal_A3}. The predicted seasonal variability is small in the Northeastern region except for the end-of-century when \(CCF\) rise is discernible from September to November. The \(SME\) outcomes indicate small changes in \(SSR\) for the first two months of the year in area A1 for the 2070-2100 period. These results align with previous studies evaluating the climate change impact on precipitation \cite{Dantas2022, Almazroui2021}.

The opposite seasonal pattern occurs in area A2 (Fig. \ref{fig:plot_CCRsazonal_A2}), where \(CCF\) gets negative values most of the year except for January and February when CCF is around 0.5-1.0\% in both scenarios and timeslices. The \(SSR\) decreases during the April-August months, achieving \(CCF\) around -4.5\%(-2\%) in SSP5-8.5 (SSP2-4.5) at the end-of-century.


\begin{figure}[h]
  \centering
  \includegraphics[scale=0.40]{Sup_figs/FiguraS04.jpg}
  \captionsetup{justification=justified}
  \caption{Seasonal variation of climate change factor (CCF) and surface solar irradiance (SSR) based on the outcomes from SME for SSP2-4.5 and SSP5-8.5 pathways regarding the target area A1 in the Brazilian Northeastern region.}
  \label{fig:plot_CCRsazonal_A1}
\end{figure}

\begin{figure}[H]
  \centering
  \includegraphics[scale=0.40]{Sup_figs/FiguraS05.jpg}
  \captionsetup{justification=justified}
  \caption{Seasonal variation of climate change factor (CCF) and surface solar irradiance (SSR) based on the outcomes from SME for SSP2-4.5 and SSP5-8.5 pathways regarding the target area A2 in the Brazilian Southern region.}
  \label{fig:plot_CCRsazonal_A2}
\end{figure}

\begin{figure}[H]
  \centering
  \includegraphics[scale=0.40]{Sup_figs/FiguraS06.jpg}
  \captionsetup{justification=justified}
  \caption{Seasonal variation of climate change factor (CCF) and surface solar irradiance (SSR) based on the outcomes from SME for SSP2-4.5 and SSP5-8.5 pathways regarding the target area A3 in the Brazilian Central region.}
  \label{fig:plot_CCRsazonal_A3}
\end{figure}


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