South America is highly vulnerable to storms and extreme precipitation. Mesoscale convective systems (MCSs), a prevalent storm type in tropical and subtropical South America, can be particularly damaging due to the organized, deep convection that fuels heavy precipitation over wide areas. Here, we track mature-stage MCSs in multiyear convection-permitting regional climate model simulations over South America [the South America Convection-Permitting Regional Climate Model (SA-CPRCM) simulations; Halladay et al. 2023] run by the Met Office to assess the representation of simulated present-day MCSs compared with satellite observations using a cloud-tracking algorithm [Tracking Object-Based Analysis of Clouds (tobac)]. The simulations perform well at capturing the observed MCS climatology, cluding spatial distribution pattern and diurnal and seasonal cycles. However, the simulations overestimate MCS frequency over the Amazon basin by a factor of 1.5 and, with a smaller bias, underestimate MCS frequency over the La Plata basin, likely due to weaker simulated moisture flux from the Amazon to the subtropics by the low-level jet. In general, regional variations in MCS characteristics are correctly simulated, but precipitation-related characteristics show larger model-observed differences. Simulated MCSs overestimate precipitation intensity by a factor of 1.5-2 and underestimate precipitation area by a factor of 2-2.5. This results in an underestimation of the MCS contribution to total rainfall of 20%-30% the model, particularly in subtropical South America. The results from this work highlight the benefits and limitations using the Met Office kilometer-scale climate simulations over South America to simulate MCSs and contribute to broader understanding of modeling challenges in this region. SIGNIFICANCE STATEMENT: The purpose of this study is to assess the representation of large-scale organized convection (specifically mesoscale convective systems) in convection-permitting climate simulations over South America. This is important because these storms frequently generate high-impact weather events such as flooding, hail, and high wind speeds yet are poorly represented in global climate models. Our results provide an evaluation of mesoscale convective system representation over South America in Met Office kilometer-scale simulations and contribute to broader understanding of modeling challenges in the region.

The third version of the Regional Atmosphere and Land (RAL3) science configuration is documented. Developed through international partnerships, RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator (JULES) when applied across timescales with kilometre and sub-kilometre-scale model grids. The RAL3 configuration represents a major advance compared to previous versions by delivering a common science definition suitable for application to tropical and mid-latitude regions. Developments within RAL3 include the introduction of a double-moment microphysics scheme and a bimodal cloud scheme, replacing use of a single-moment scheme and different cloud schemes for mid-latitudes and tropics in previous versions. Updates have been implemented to the boundary layer scheme and a consolidation of land model settings to be more consistent with global atmosphere and land (GAL) science configurations. Physics developments aimed to address priorities for model performance improvement identified by users. This paper documents the RAL3 science configuration, including a series of iterative revisions delivered since its first release, and their characteristics. Evidence is provided from the variety of assessments of RAL3, relative to the previous version (RAL2). Collaborative development and evaluation across organizations have enabled evaluation across a range of domains, grid spacing and timescales. The analysis indicates more realistic precipitation distributions, improved representation of clouds and of visibility, a continued trend to more realistic representation of convection, and reduced near-surface wind speeds but a persistent cold-temperature bias. Overall the convective-scale verification scores and climatological model distributions relative to observations improve for the majority of variables. Ensemble results show improvements to the spread-error relationship. User feedback from subjective assessment activities has also been positive. Differences between RAL3 revisions and RAL2 are further illustrated through a process-based analysis of a convective system over the UK. The latest RAL3 configuration (RAL3.3) is therefore recommended for research, operational numerical weather prediction, and climate production at kilometre and sub-kilometre scales.

The projected delay in the onset of the South American monsoon over central-east Brazil under global warming is explored in a pair of convection-permitting regional climate model (CPRCM) simulations performed at the Met Office, corresponding to the present day and an RCP8.5 scenario. We also examine the corresponding driving general circulation model (GCM) simulations to understand the impact of explicitly resolving convection within the CPRCM. The transition to the rainy season is associated with the buildup of lower-tropospheric moist static energy and moisture, the demands for which are enhanced in the RCP8.5 scenario. However, significant reductions in evapotranspiration and the absence of moisture flux convergence enhancement in September and October render unfavorable conditions for the onset of the rains in the future climate. The reduced evapotranspiration is irrespective of an increase in column soil moisture in the RCP8.5 scenario. A stomatal response to altered environmental conditions in the future climate contributes to this decline in evapotranspiration. These changes lead to a delayed and more abrupt onset in the RCP8.5 scenario. The direction of change in the onset is similar in both the CPRCM and the driving GCM, although the CPRCM is drier than the GCM during the onset phase. The findings from this study highlight the role of plant physiology in modulating climate projections and the necessity to improve their representation in climate models.

Unprecedented rainfall extremes resulting from global warming are becoming more frequent each year, including over South America. In this region, tropical-extratropical (TE) cloud bands in the South Atlantic convergence zone (SACZ) produce most of the rainy season precipitation. In this study, we diagnose the impacts of warming on the frequency and intensification of SACZ TE cloud bands. The cloud bands are identified using a feature-detection algorithm applied to a suite of convection-permitting simulations produced by the UK Met Office. Intensely raining clusters embedded within these large-scale cloud bands are diagnosed in order to identify the most intense events. Although the total number of cloud-band days will see a 20%–30% decrease in their frequency under high-emission global warming, the present day 1-in-5 most intense cloud-band days will happen every 3-in-5 cloud-band days in the future. Therefore, despite fewer cloud-band days occurring in a given year, when they form they will frequently be more intense than is typical in the current climate. This increase is primarily due to warming-driven intensification of rain rates within the heavily raining clusters embedded in these weather systems. These results highlight the growing risk of intense SACZ rainfall over South America under warming, increasing the likelihood of flash floods, landslides, and unprecedented catchment-scale fluvial flooding.

South America is highly vulnerable to storms and extreme precipitation. Mesoscale Convective Systems (MCSs), a prevalent storm type in tropical and subtropical South America, can be particularly damaging due to the organised, deep convection that fuels heavy precipitation over wide areas. Future warming will likely bring changes to MCS characteristics and precipitation extremes across the region. However, the relatively coarse spatial resolution of current regional climate models fails to explicitly resolve convective processes, making future changes to MCSs uncertain. Here, the representation of modelled MCSs is investigated in decade-long convection-permitting climate simulations over South America run by the UK Met Office. Changes to MCSs under global warming are then assessed using a future climate simulation. Simulated MCSs are tracked using a cloud tracking algorithm (tobac) and compared with those in satellite observations for seasonality, storm characteristics and regional differences. The simulations perform well at capturing the observed MCS climatology, including spatial frequency and seasonal cycle. However, the simulations overestimate MCS frequency over the Amazon Basin by a factor of 2 and underestimate MCS frequency over the La Plata Basin, likely due to a weak bias in the simulated South American Low-Level Jet. In general, regional variations in MCS characteristics are also well simulated, but precipitation-related characteristics show larger model-observed differences. Simulated MCSs overestimate precipitation intensity and underestimate precipitation area. This results in an underestimation of the MCS contribution to total rainfall of 20-30% in the model, particularly in subtropical South America. The results from this work suggest that MCSs are generally well-captured by the CPM and have been used to inform results for future changes to MCSs over South America under climate change.

Rainfall intensification due to planetary warming is increasingly impacting nearly all regions of the globe. South America is no exception with unprecedented landslides (São Sebastião, February 2023) and river catchment-scale flooding (Rio Grande do Sul, September 2023 and May 2024) being observed more frequently. Over South America, tropical-extratropical cloud bands in the South Atlantic Convergence Zone (SACZ) produce most of the rainy season precipitation. Droughts can occur in years with fewer SACZ events while intensely raining clusters within the cloud bands can trigger flash floods and landslides. Here, we diagnose the impacts of future precipitation intensification on the frequency and intensity of SACZ tropical-extratropical cloud bands using the first-of-its-kind continental-scale convection-permitting climate simulation. While cloud bands will see a future 20-30\% decrease in their frequency, intense events with a likelihood of 1-in-5 in the present day will become more frequent in the future, with 3-in-5 likelihood, increasing the risk of heavily raining clusters. This tripling in intense cloud band frequency results from intensified mesoscale rainfall structures within the continental-scale cloud bands, a risk better captured by convection-permitting models. Geographically, the intensification of mesoscale rainfall structures is most prevalent in the highly populated coastal regions of Southeastern and Southern Brazil, areas already highly exposed to extreme weather events, floods, and landslides. This increased risk significantly exceeds the projections from traditional climate models with convection parametrizations and highlights the growing risk of intense cloud-band rainfall over South America under warming.

Increasing spatial resolution to kilometre scales allows the deactivation of deep convection parameterisation schemes. As a result of various global initiatives for the next generation of climate studies, continental convection-permitting model (CPM) simulations are now accessible. Nonstationary local extremes, like heatwaves and intense precipitation, are probabilistically linked to regional circulation through scaling relationships. However, these relationships have not been extensively explored in the new simulations available in the early 2020s. Hourly time series data were extracted from the UK Climate Science for Service Partnership (CSSP) and the US South America Affinity Group (SAAG) CPM simulations to compare extreme characteristics of precipitation and temperature for 39 stations in a region of São Paulo, Brazil. Compared to reanalysis and satellite data, which exhibit lower variance in hourly time series, these two sets of CPM simulations have precipitation that is more similar to station observations than the ERA5 data and the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) data. The cross-correlation structures of the time series are investigated to quantify temporal dependence and reveal patterns between temperature and precipitation at an hourly timescale. Within a higher-dimensional probability space for joint risk, the cross-correlation structures between temperature and precipitation at different lags demonstrate the "memory" of these variables, indicating the influence of past values on future behaviour across multiple time points. Their forecasting power for these two variable based on each other is also explored to offer insights into the physical processes within the evolving simulated dynamic system. Overall, the results underscore the added value of convection-permitting models in providing more realistic simulations of local dynamics of extremes. The identified cross-correlation structures from the CPMs are valuable for exploring opportunities to design AI engines based on weather generator algorithms that use stochastic differential equations. Using CPM simulations, these weather generators can be employed to develop AI approaches for rapid decision support tools aimed at stakeholders facing extreme weather events related to compound risks of temperature and precipitation.

We investigated positive temperature (warm) and negative precipitation (dry) biases in convection-permitting model (CPM) simulations for Europe (2.2 km grid spacing) that were considerably larger than in equivalent regional climate model (RCM) simulations (12 km grid spacing). We found that improvements in dry biases could be made by (1) using a more complex runoff scheme which takes into account topography and groundwater, (2) delaying the onset of water stress in vegetation to enhance transpiration, (3) changing the microphysics scheme to CASIM (Cloud AeroSol Interacting Microphysics) which also decreases heavy rainfall and increases light rainfall. Increasing soil moisture to the critical point can remove dry precipitation biases in southern Europe but not in northern areas, indicating that soil moisture limitation is a key contributor to precipitation biases in the south only. Instead, in the north, changing the cloud scheme of the model has more impact on precipitation biases. We found that the more intense and intermittent nature of rainfall in the CPM, which is more realistic leads to different canopy interception compared to the RCM. This can impact canopy evaporation, evapotranspiration and feed back on precipitation. Increasing rainfall storage in the canopy only leads to small improvements in warm biases, since it still fills rapidly with intense CPM rainfall, suggesting the need for an additional moisture store via improved groundwater modelling or surface pooling. Overall, this work highlights the challenge of correctly capturing land surface feedbacks in CPMs, which play an important role in future climate projections in some regions.

Understanding precipitation properties at regional scales and generating reliable future projections is crucial in providing actionable information for decision-makers, especially in regions with high vulnerability to climate change, where future changes impact ecosystem resilience, biodiversity, agriculture, water resources and human health. The South America Convection-Permitting Regional Climate Model experiment (SA-CPRCM) examines climate change effects in convection-permitting simulations at 4.5 km resolution, on climate time scales (10 year present-day and 10-year future RCP8.5 around 2100), over a domain covering most of South America, using the Met Office Unified Model (UM) convection-permitting RCM.Under the RCP8.5 scenario, precipitation in the CPRCM decreases, becomes less frequent and more seasonal over the Eastern Amazon region. Dry spells lengthen, increasing the risk of drought. In the Western Amazon, precipitation increases in the wetter austral autumn (Apr. – Jun.) and decreases in the drier austral winter and spring (July – Oct.), leading to a more distinct dry season and imposing a greater risk of contraction of the tropical forest. Over South-eastern Brazil, future precipitation increases and becomes more frequent and more intense, increasing the risk of floods and landslides. A future increase in the intensity of precipitation and extremes is evident over all these regions, regardless of whether the mean precipitation is increasing or decreasing. The CPRCM and its driving GCM respond in a similar way to the future forcing. The models produce broadly similar large-scale spatial patterns of mean precipitation and comparable changes to frequency, intensity, and extremes, although the magnitude of change varies by region and season.

The South America Affinity Group (SAAG) was established in early 2019 by the National Center for Atmospheric Research (NCAR) Water Systems Program as a community effort focused on improving hydroclimate science over South America. SAAG supports large research efforts such as the ANDEX Regional Hydroclimate Program (Espinoza et al. 2020) as well as individual research groups. The group started with a dozen members and quickly grew to over 100 participants from more than 10 countries. For the past four years, the SAAG has been meeting online every two weeks and has organized sessions at international conferences such as the American Geophysical Union Fall Meeting and the Convection-Permitting Climate Workshop (Prein et al. 2022). At the core of the SAAG effort are two multidecadal convection-permitting (CP) model simulations with 4-km grid spacing for historical and future climates over the South American continent. Additionally, a major observational data collection effort has been undertaken, including in situ station data from South American meteorological and water services, gridded products, satellite-based observations, and field campaign data (NCAR 2023a). This article discusses the research needs and scientific goals that drive this community of scientists with diverse backgrounds and interests.

Climate science has long explored whether higher resolution regional climate models (RCMs) provide improved simulation of regional climates over global climate models (GCMs). The advent of convective-permitting RCMs (CPRCMs), where sufficiently fine-scale grids allow explicitly resolving rather than parametrising convection, has created a clear distinction between RCM and GCM formulations. This study investigates the simulation of tropical-extratropical (TE) cloud bands in a suite of pan-South America convective-permitting Met Office Unified Model (UM) and Weather Research and Forecasting (WRF) climate simulations. All simulations produce annual cycles in TE cloud band frequency within 10-30% of observed climatology. However, too few cloud band days are simulated during the early summer (Nov-Dec) and too many during the core summer (Jan-Feb). Compared with their parent forcing, CPRCMs simulate more dry days but systematically higher daily rainfall rates, keeping the total rain biases low. During cloud band systems, the CPRCMs correctly reproduced the observed changes in tropical rain rates and their importance to climatology. Circulation analysis suggests that simulated lower subtropical rain rates during cloud bands systems, in contrast to the higher rates in the tropics, are associated with weaker northwesterly moisture flux from the Amazon towards southeast South America, more evident in the CPRCMs. Taken together, the results suggest that CPRCMs tend to be more effective at producing heavy daily rainfall rates than parametrised simulations for a given level of near-surface moist energy. The extent to which this improves or degrades biases present in the parent simulations is strongly region-dependent.

We present the first convection-permitting regional climate model (CPRCM) simulations at 4.5 km horizontal resolution for South America at near-continental scale, including full details of the experimental setup and results from the reanalysis-driven hindcast and climate model-driven present-day simulations. We use a range of satellite and ground-based observations to evaluate the CPRCM simulations covering the period 1998–2007 comparing the CPRCM output with lower resolution regional and global climate model configurations for key regions of Brazil. We find that using the convection-permitting model at high resolution leads to large improvements in the representation of precipitation, specifically in simulating its diurnal cycle, frequency, and sub-daily intensity distribution (i.e. the proportion of heavy and light precipitation). We tentatively conclude that there are also improvements in the spatial structure of precipitation. We see higher precipitation intensity and extremes over Amazonia in the CPRCMs compared with observations, though more sub-daily observational data from meteorological stations are required to conclusively determine whether the CPRCMs add value in this regard. For annual mean precipitation and mean, maximum and minimum near surface temperatures, it is not clear that the CPRCMs add value compared with coarser-resolution models with parameterised convection. We also find large changes in the contribution to evapotranspiration from canopy evaporation compared to soil evaporation and transpiration compared with the RCM. This is likely to be related to the shift in precipitation intensity distribution of the CPRCMs compared to the RCM and its impact on the hydrological requires further investigation.

The Amazon rainforest holds more than 40% of all remaining tropical rainforest and is a key component of the climate system. The scale of deforestation in the Amazon significantly impacts both local and global climates. Under a business-as-usual scenario as much as 40% of the Brazilian Amazon rainforest will be lost by 2050. Despite the magnitude of these changes and its importance, the overall effects of deforestation on rainfall remain uncertain. Land-use change influences rainfall through a variety of mechanisms acting at local to continental scales. As such, previous research indicates conflicting responses to rainfall depending on the scales studied. In reality, rainfall processes interact across these scales, but until recently have been impossible to capture within a single model due to computational expense. Consequently we are unable to rely on these simulations as future estimations of rainfall for such a sensitive and anthropogenically impacted region as the Amazon. In this study, we overcome these limitations by running convection permitting simulations (horizontal resolution 4.5km) over a large domain (6000km covering the majority of South America) using a Tropical configuration of the UK Met Office Unified Model. The high-resolution and continental-scale of these simulations present an opportunity to reduce the uncertainty in Amazonian rainfall estimates within a single model and ensures rainfall processes and interactions across scales are captured. To investigate the impacts of deforestation we will include a series of land-use sensitivity runs making use of a range of socioeconomic scenarios to 2050. Here we present initial results from our simulations, indicating how localised storms, mesoscale convective systems and large-scale circulations respond to land-use change.

Increasingly, we are using high-resolution convection-permitting models for climate projections but these models are less well understood in terms of the interaction between soil moisture, precipitation and evapotranspiration. The work was motivated by the discovery of warm, dry biases in summer in the 2.2 km convection-permitting model over France and eastern Europe compared to the 12 km convection-parametrised model that were associated with drier soils. We analyse several 12 km and 2.2 km versions of the Met Office Unified Model including sensitivity tests relating to soil hydraulics, land cover type and runoff model. We conduct similar tests using the land surface only to compare results between online and offline versions as the absence of some feedbacks can also produce differences.

This article reviews recent scientific progress, relating to four major systems that could exhibit threshold behaviour: ice sheets, the Atlantic meridional overturning circulation (AMOC), tropical forests and ecosystem responses to ocean acidification. The focus is on advances since the Intergovernmental Panel on Climate Change Fifth Assessment Report (IPCC AR5). The most significant developments in each component are identified by synthesizing input from multiple experts from each field. For ice sheets, some degree of irreversible loss (timescales of millennia) of part of the West Antarctic Ice Sheet (WAIS) may have already begun, but the rate and eventual magnitude of this irreversible loss is uncertain. The observed AMOC overturning has decreased from 2004–2014, but it is unclear at this stage whether this is forced or is internal variability. New evidence from experimental and natural droughts has given greater confidence that tropical forests are adversely affected by drought. The ecological and socio-economic impacts of ocean acidification are expected to greatly increase over the range from today’s annual value of around 400, up to 650 ppm CO2 in the atmosphere (reached around 2070 under RCP8.5), with the rapid development of aragonite undersaturation at high latitudes affecting calcifying organisms. Tropical coral reefs are vulnerable to the interaction of ocean acidification and temperature rise, and the rapidity of those changes, with severe losses and risks to survival at 2 °C warming above pre-industrial levels. Across the four systems studied, however, quantitative evidence for a difference in risk between 1.5 and 2 °C warming above pre-industrial levels is limited.

Peter Good , Jonathan Bamber , Kate Halladay , Anna Harper , Laura Jackson , Gillian 5 Kay, Bart Kruijt, Jason Lowe , Oliver Phillips, Jeff Ridley, Meric Srokosz , Carol 6 Turley, Phillip Williamson 7 8 Met Office Hadley Centre, Exeter, United Kingdom. 9 School of Geographical Sciences, University of Bristol, UK 10 College of Engineering, Mathematics, and Physical Sciences, University of Exeter, UK 11 ALTERRA, Wageningen UR, PO box 47, 6700 AA Wageningen, Netherlands 12 School of Geography, University of Leeds, Leeds, UK 13 National Oceanography Centre, University of Southampton Waterfront Campus, 14 Southampton, UK 15 Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth PL1 3DH, UK 16 School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, UK and 17 Natural Environment Research Council, UK 18 19 20 21

In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a “special report in 2018 on the impacts of global warming of 1.5 C above pre-industrial levels and related global greenhouse gas emission pathways”. In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5 C, including a potential overshoot and longterm impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the lowemissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity).

This paper shows recent progress in our understanding of climate variability and trends in the Amazon region, and how these interact with land use change. The review includes an overview of up-to-date information on climate and hydrological variability, and on warming trends in Amazonia, which reached 0.6-0.7 °C over the last 40 years, with 2016 as the warmest year since at least 1950 (0.9 °C +0.3°C). We focus on local and remote drivers of climate variability and change. We review the impacts of these drivers on the length of dry season, the role of the forest in climate and carbon cycles, the resilience of the forest, the risk of fires and biomass burning, and the potential “die back” of the Amazon forests if surpassing a “tipping point”. The role of the Amazon in moisture recycling and transport is also investigated, and a review of model development for climate change projections in the region is included. In sum, future sustainability of the Amazonian forests and its many services requires management strategies that consider the likelihood of multi-year droughts superimposed on a continued warming trend. Science has assembled enough knowledge to underline the global and regional importance of an intact Amazon region that can support policymaking and to keep this sensitive ecosystem functioning. This major challenge requires substantial resources and strategic cross-national planning, and a unique blend of expertise and capacities established in Amazon countries and from international collaboration. This also highlights the role of deforestation control in in support of policy for mitigation options as established in the Paris Agreement of 2015.

In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a special report in 2018 on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways. In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5 °C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity).