Datasets for the publication " Climate mitigation and adaptation in long-term energy planning: implications for Brazil's energy transition"

This dataset contains the Calliope model outputs supporting the study of climate change impacts and adaptation strategies in Brazil’s net-zero energy transition. The simulations use a spatially explicit, sector-coupled energy system model representing electricity generation, bioenergy, hydrogen, synthetic fuels, transport, industry, storage and energy infrastructure.

The dataset comprises six core scenarios formed by combining two land-availability regimes with three climate conditions:

1. Technical potential (baseline): infrastructure expansion is constrained by the common legal, environmental and physical land exclusions adopted in the study.

2. Conservation (conservation): applies the technical-potential exclusions and additionally excludes priority areas for biodiversity conservation.

Each land regime is evaluated under:

• No climate change (noclimate): reference renewable-resource conditions;

• SSP2–4.5 (ssp245): an intermediate climate-change pathway;

• SSP5–8.5 (ssp585): a high-emissions climate-change pathway.

Climate-related changes are applied to hydropower, onshore wind, solar generation and electricity demand. Hydropower projections are based on an ensemble combining ten global climate models and three hydrological models. Changes in wind and solar resources are represented using climate-change factors derived from CMIP6 projections.

The files included in this deposit are:

• out_scenario_noclimate_baseline_2013.nc

• out_scenario_noclimate_conservation_2013.nc

• out_scenario_ssp245_baseline_2013.nc

• out_scenario_ssp245_conservation_2013.nc

• out_scenario_ssp585_baseline_2013.nc

• out_scenario_ssp585_conservation_2013_spores10.nc

The suffix 2013 identifies the meteorological year used to represent the system’s hourly renewable-resource and demand profiles; it does not represent the energy-system planning year. The model uses projected 2050 energy-service demands and techno-economic assumptions.

The NetCDF files preserve the original Calliope model results, including installed and newly built capacities, energy production, technology operation, storage behaviour, resource availability, transmission and fuel flows, system costs and other model variables. They can be opened using Calliope 0.6.10 or inspected directly with software supporting NetCDF, such as Python’s xarray package.

The SSP5–8.5 Conservation file additionally contains ten near-optimal system configurations generated using SPORES. These alternatives are constrained to remain within 10% of the minimum system cost and are used to investigate technological and spatial flexibility beyond a single least-cost solution.

Together, the scenarios allow users to examine how climate-induced changes in renewable resources interact with land conservation constraints and how Brazil’s energy system can adapt through technology substitution, additional infrastructure, storage deployment and spatial reallocation of renewable capacity.

The model configuration, input structure and related analysis code are available in the associated GitHub repository.

Users of this dataset should cite both the associated scientific article and the Zenodo record.