ABOUT THE PORTAL
Context
A world that is +2°C above pre-industrial levels poses significant risks, pushing Earth systems toward tipping points like ice-sheet collapse and coral die-off. The Paris Agreement aims to keep global temperatures well below +2°C, ideally limiting them to +1.5°C relative to pre-industrial levels (1850-1900) to avoid severe climate risks to ecosystems and societies.
Currently, global average temperatures have risen about +1.2°C, resulting in severe impacts such as droughts and floods. In 2024, temperatures exceeded +1.5°C for the first time, highlighting our proximity to a critical threshold. Immediate action through emission cuts and investment in resilience is crucial to prevent irreversible changes.
Brasil is among the countries most affected by these impacts, facing increasingly severe climate extremes each year. The country has endured devastating floods in Rio Grande do Sul, historic droughts in the Amazon and Pantanal, and extreme heatwaves that have strained public health, agriculture, and energy systems.
This reality shows that Brasil has reached its own turning point. Confronted with the climate crisis and biodiversity loss, it is urgent to accelerate the transition toward a more productive, resilient, and nature-positive economy.
About the project
With this purpose, Instituto Itaúsa and Lobelia Earth developed the open-data platform “Brasil in a +2°C World”, giving businesses, citizens, scientists, and decision-makers access to valuable information on current climate challenges and the essential role of nature.
The platform compares a +2°C climate scenario with the historical baseline for Brasil, revealing climate exposure risks across key sectors - such as infrastructure, agriculture, and urban areas - at national, state, and municipal levels.
Additionally, it provides insightful contextual layers, including flood extent, deforestation, forest degradation, and specific exposure indicators that identify and emphasize critical and urgent hotspots based on observed data.
The platform is designed and flexible to evolve, allowing the integration of new datasets, insights and sectors as Brasil advances toward a data-driven transition for resilience.
Suggestions can be sent to: brasil2c@lobelia.earth
Economic Sectors covered
The platform provides a national overview of climate and nature-related threats across key economic sectors. Its initial focus is on critical infrastructure (roads and energy), agriculture, and urban areas - the backbone of Brasil’s economy - since disruptions in these systems create cascading operational, financial, and logistical effects. The goal is to show where climate threats converge, where nature can help buffer their impacts, and how to prioritize adaptation actions.
About the data
All data has been processed by © Lobelia Earth.
Datasets are divided between physical climate exposure layers and contextual layers.
Physical Climate Exposure Layers:
These layers show how specific assets - such as roads, power lines, or hydropower plants - are exposed to climate hazards like extreme temperatures, floods, or landslides. Each asset segment is classified by risk level (Low, Medium, High, or Extreme) under two timeframes:
- Baseline (1986-2005) - represents baseline climate conditions.
- +2 °C Scenario - illustrates expected changes if global warming reaches +2 °C.
Physical Climate Exposure Layers:
These are raster datasets covering the entire country. They include both the raw climatic indicators (e.g., rainfall intensity, temperature extremes) and nature-related datasets such as deforestation, vegetation loss, and forest degradation.
Contextual layers help users understand the broader environmental context, showing how climate and nature interact - how degraded areas may worsen flood risk, for instance, or how vegetation cover helps buffer heat and water extremes.ROADS
PHYSICAL CLIMATE EXPOSURE LAYERS
River Flooding Risk
Roads exposed to at least 0.5 m of water during a 100-year river flood
This layer shows the river flooding risk along Brasil’s national road network for both the baseline period and a +2°C global warming scenario.
It consists of 1 km OpenStreetMap trunk and primary road segments, each assigned the highest risk value within a 250 m buffer. Flooding risk is based on the JRC Global River Flood Hazard Maps, which simulate 100-year return period flood depths using LISFLOOD hydrological and LISFLOOD-FP hydraulic models. Future risk incorporates the climate change signal from WRI Aqueduct Floods Hazard Maps applied at the river basin scale. Risk indicates exposure to at least 0.5 m of water depth. In four risk levels: Low, Medium, High, and Extreme, in a +2ºC scenario and in the historical scenario (baseline) at the state and municipality levels.
Landslide Risk
Roads exposure to landslides at national, state and municipality levels
This layer shows the landslide risk along Brasil’s national road network for the historical period and a +2°C global warming scenario.
It consists of 1 km OpenStreetMap trunk and primary road segments, each assigned the highest risk value within a 250 m buffer. Landslide risk combines the IBGE landslide susceptibility map, derived from underlying terrain characteristics, with rainfall-triggered potential estimated from the annual 5-day maximum precipitation (RX5day) derived from the satellite-based CHIRPS v3 product for the historical baseline and bias-adjusted CORDEX climate projections for the future period. The integration of terrain susceptibility and rainfall potential produces four risk levels: Low, Medium, High, and Extreme, in a +2ºC scenario and in the historical scenario (baseline) at the national, state and municipality levels.
Extreme Precipitation Risk
Roads exposure to extreme precipitation in at national, state and municipality levels
This layer shows the extreme precipitation risk along Brasil's national road network for both the historical period and a +2°C global warming scenario.
It consists of 1 km OpenStreetMap trunk and primary road segments, each assigned the highest risk value within a 250 m buffer. Extreme precipitation is represented by the annual maximum one-day rainfall (RX1day) associated with a 10-year return period event. Thresholds based on observed impacts of past events, including the 2023 El Niño, and define four risk classes: Low (<50 mm), Medium (50-80 mm), High (80-120 mm), and Extreme (≥120 mm). Historical baseline is derived from the satellite-based CHIRPS v3 product and bias-adjusted CORDEX climate projections for the future period. Extreme precipitation risk is displayed in a +2ºC scenario and in the historical scenario (baseline) at the national, state and municipality levels.
Wildfire Risk
Roads exposure to wildfires. Integrated Fire Weather Index (FWI) and vegetation presence
This layer shows the wildfire risk along Brasil’s national road network for both the historical period and a +2°C global warming scenario.
It consists of 1 km OpenStreetMap trunk and primary road segments, each assigned the highest risk value within a 250 m buffer. Wildfire risk is derived from the 90th annual percentile of the Fire Weather Index (FWI) which accounts for fire prone weather conditions.The satellite based ESA CCI Burned Area product across the different Brasilian biomes was used to set empirical FWI thresholds for assessing risk levels in Amazon, Cerrado, and Caatinga: Low, Medium, High, and Extreme. Historical baseline is derived from CHIRPS, CHIRTS and ERA5 observational products and future conditions are based on bias-adjusted CORDEX projections. It covers a +2ºC scenario and in the historical scenario (baseline) at the national, state and municipality levels.
Extreme Temperature Risk
Roads exposure to extreme temperatures
This layer shows the extreme temperature risk along Brasil’s national road network for both the historical period and a +2°C global warming scenario.
It consists of 1 km OpenStreetMap trunk and primary road segments, each assigned the highest risk value within a 250 m buffer. Extreme temperature is represented by the annual maximum daily maximum temperature (TXx) associated with a 5-year return period event. Risk thresholds, based on the relationship between air temperature, pavement temperature, and maintenance costs, are Low (<35°C), Medium (35–38°C), High (38–41°C), and Extreme (≥41°C). Historical baseline is derived from the satellite-based CHIRPS product and future conditions are based on bias-adjustedCORDEX projections. In four risk levels: Low, Medium, High, and Extreme, in a +2ºC scenario and in the historical scenario (baseline) at the national, state and municipality levels.
CONTEXTUAL LAYERS
Flood extent map
River flooding ≥0.5 m of water for a 100-year event
This layer shows river flood hazard across Brasil, derived from the JRC Global River Flood Hazard Maps at 100 m resolution. It represents the maximum water depth expected during a 100-year return period flood, equivalent to a 1% annual probability. Historical flood hazard is based on LISFLOOD and LISFLOOD-FP hydrological and hydraulic simulations. Future flood hazard under a +2°C scenario is estimated by applying the climate change signal from WRI Aqueduct Floods Hazard Maps at the river basin scale to the historical JRC maps.
This layer provides essential information for assessing flood exposure and infrastructure vulnerability.
Deforestation 2017-2023
Accumulated deforestation from 2017 to 2023
This layer shows the total deforested area across Brasil between 2017 and 2023, based on annual land cover change detection. The data are derived from MapBiomas Collection 9, with a spatial resolution of 30 meters. Deforestation is calculated from Class 4 (Loss of Primary Vegetation), defined as areas changing from Primary Vegetation to Anthropic land use in the year of analysis. This category includes pixels that were persistently classified as Primary Vegetation for at least two consecutive years, followed by a persistent classification as Anthropic in the input dataset for three, five, or seven years, including the year of analysis. Area calculations are performed using the EPSG:3857 coordinate reference system, by counting all pixels within the area of interest and multiplying them by their reference value in square meters (m²), calculated previously. It is important to note that statistics may differ from those reported by early-warning deforestation systems, as these operate with higher temporal and spatial resolution.
This layer allows users to visualize the cumulative extent of primary vegetation loss and major deforestation hotspots, as well as to identify infrastructure segments exposed to compounded environmental pressures, where vegetation loss may increase vulnerability to flooding.
Forest degradation 2017-2013
Accumulated degradation between 2017 and 2023
This layer shows the total area of secondary vegetation loss across Brasil between 2017 and 2023, based on annual land cover change detection. The data are derived from MapBiomas Collection 9, with a spatial resolution of 30 meters.
The loss of secondary vegetation is calculated from Class 6 (Loss of Secondary Vegetation), defined as areas changing from Secondary Vegetation to Anthropic land use in the year of analysis. This category includes pixels persistently classified as Secondary Vegetation for at least two consecutive years, followed by a persistent classification as Anthropic in the input dataset for three, five, or seven years, including the year of analysis.
Area calculations are performed using the EPSG:3857 coordinate reference system, by counting all pixels within the area of interest and multiplying them by their reference value in square meters (m²), calculated previously.
This layer allows users to visualize the cumulative extent of secondary vegetation loss and major degradation hotspots, as well as to identify infrastructure segments exposed to compounded environmental pressures, where vegetation degradation may increase vulnerability to flooding.
Landslide risk map
Combination of landslide susceptibility and extreme precipitation risk
This layer shows landslide risk for the historical period and a +2°C global warming scenario. It is provided as a continuous 1 × 1 km spatial grid, with each cell showing the combined landslide risk for that location. Landslide risk integrates the IBGE susceptibility map, derived from terrain characteristics, with rainfall-triggered potential estimated from the annual maximum of consecutive 5-day rainfall. Historical rainfall comes from satellite-based CHIRPS v3 product, while future conditions use a composite of bias-adjusted CORDEX climate projections.
The scaled combination produces four risk classes: Low, Medium, High, and Extreme.
Maximum 5-day precipitation (Rx5day)
Extreme precipitation map
This layer shows the intensity of multi-day extreme precipitation events across Brasil, represented by the annual maximum rainfall accumulated over five consecutive days (RX5day) associated with a 50-year return period extreme event, equivalent to a 2% annual probability. It is provided as a continuous spatial grid for both the historical period and a +2°C global warming scenario. Historical baseline is derived from satellite-based CHIRPS v3 product, while future conditions use a set of bias-adjusted CORDEX climate projections.
This indicator highlights persistent, high-intensity rainfall episodes that can trigger landslides and soil instability.
Fire Weather Index (90th percentile)
Integrated Fire Weather Index (FWI) and vegetation presence
This layer shows the Fire Weather Index (FWI) across Brasil, represented by its 90th percentile. It is provided as a continuous 0.25° spatial grid for both the historical period and a +2°C global warming scenario. Historical baseline is derived from CHIRTS, CHIRPS v3, and ERA5 observational products while future conditions use a set of bias-adjusted CORDEX climate projections. The 90th percentile highlights the most fire-prone 10% of days, capturing persistent or recurrent extreme fire weather.
This indicator identifies areas with high climatic potential for wildfire ignition and spread under current and projected conditions.
Primary forest in 2024
Presence of primary forest cover in 2024
This layer maps the presence of primary forest cover in 2024, based on the Land Use and Land Cover (LULC) Map – MapBiomas Brasil Collection 9, with a spatial resolution of 30 meters. The dataset provides land use and land cover information for Brasil, where the Forest class includes Forest Formation, Savanna Formation, Mangrove, Floodable Forest, and Wooded Sandbank Vegetation (Primary Forest) (MapBiomas, 2025b).
Primary forests, characterized by their high biomass and structural complexity, represent significant potential fuel loads in the event of fire. This layer highlights areas where infrastructure intersects with primary forests, identifying segments exposed to compounded environmental risks—particularly where the presence of dense vegetation could intensify wildfire behavior or propagation.
Maximum daily temperature (TXx)
Maximum value of the daily maximum temperature in a year (TXx)
This layer shows the annual maximum daily maximum temperature (TXx) across Brasil, represented by the highest daily temperature associated with a 5-year return period extreme event, equivalent to a 20% annual probability. It is provided as a continuous 0.25° spatial grid for both the historical period and a +2°C global warming scenario. Historical baseline is derived from the satellite-based CHIRTS product while future conditions use a set of bias-adjusted CORDEX climate projections.
This indicator captures short-duration extreme heat events that can impact infrastructure, ecosystems, and fire risk under current and projected climate conditions.
Maximum 1-day precipitation (Rx1day)
Maximum value of the daily maximum precipitation in a year (mm)
This layer shows the intensity of extreme daily precipitation events (RX1day) across Brasil, associated with a 10-year return period, equivalent to a 10% annual probability. It is provided as a continuous spatial grid for both the historical period and a +2°C global warming scenario. Historical baseline is derived from the satellite-based CHIRPS v3 product while future conditions use a set of bias-adjusted CORDEX climate projections.
This indicator captures short-duration, high-intensity rainfall events that can lead to flooding, providing essential information for extreme rainfall risk assessment and flood management under current and projected climate conditions.
Disclaimer
The maps, metrics, and analyses provided by Brasil in a +2°C World are informational and do not replace on-site assessments, technical reports, environmental impact studies, or legal and administrative evaluations performed by competent authorities. The platform does not issue judgments regarding the legality, compliance, or effectiveness of adaptation, conservation, or restoration measures associated with the areas displayed. All information results from automated processing and interpretation of long-term climate data, satellite imagery, and public datasets. These results are therefore subject to technical limitations and uncertainties inherent to the data sources and methods used.
The platform is under continuous improvement to detect and resolve these cases in future releases. Suggestions for new data sources can be sent to: brasil2c@lobelia.earth
Limitations and Responsible Use
- Data limitations: differences in spatial resolution, update frequency, and classification accuracy may affect local precision. The results should be interpreted as screening-level insights, not as asset/site-specific diagnostics.
- Informational nature: the platform does not replace technical, legal, or administrative assessments.
- Temporal coverage: datasets span multiple years and sources; temporal inconsistencies may exist.
- User responsibility: decisions or interpretations based on these data should be complemented with local validation.
How to credit this work
We ask that you attribute our work as “Source: Lobelia Earth, Brasil in a +2ºC World, accessed on [insert date]” with a link, if possible, to https://portal.brasil2c.com/
If you use or reference “Lobelia Earth, Brasil in a +2ºC World” in publicly-available work, please share it with our team:brasil2c@lobelia.earth