Instituto Franco-Argentino sobre Estudios de Clima y sus Impactos

The Cyanobacteria Prochlorococcus and Synechococcus account for a substantial fraction of marine primary production. Here, we present quantitative niche models for these lineages that assess present and future global abundances and distributions. These niche models are the result of neural network, nonparametric, and parametric analyses, and they rely on >35,000 discrete observations from all major ocean regions. The models assess cell abundance based on temperature and photosynthetically active radiation, but the individual responses to these environmental variables differ for each lineage. The models estimate global biogeographic patterns and seasonal variability of cell abundance, with maxima in the warm oligotrophic gyres of the Indian and the western Pacific Oceans and minima at higher latitudes. The annual mean global abundances of Prochlorococcus and Synechococcus are 2.9 ± 0.1 × 10(27) and 7.0 ± 0.3 × 10(26) cells, respectively. Using projections of sea surface temperature as a result of increased concentration of greenhouse gases at the end of the 21st century, our niche models projected increases in cell numbers of 29% and 14% for Prochlorococcus and Synechococcus, respectively. The changes are geographically uneven but include an increase in area. Thus, our global niche models suggest that oceanic microbial communities will experience complex changes as a result of projected future climate conditions. Because of the high abundances and contributions to primary production of Prochlorococcus and Synechococcus, these changes may have large impacts on ocean ecosystems and biogeochemical cycles.

Increased concentrations of atmospheric greenhouse gases have led to a global mean surface temperature 1.0°C higher than during the pre-industrial period. We expand on the recent IPCC Special Report on global warming of 1.5°C and review the additional risks associated with higher levels of warming, each having major implications for multiple geographies, climates, and ecosystems. Limiting warming to 1.5°C rather than 2.0°C would be required to maintain substantial proportions of ecosystems and would have clear benefits for human health and economies. These conclusions are relevant for people everywhere, particularly in low- and middle-income countries, where the escalation of climate-related risks may prevent the achievement of the United Nations Sustainable Development Goals.

Abstract. Several sets of reference regions have been used in the literature for the regional synthesis of observed and modelled climate and climate change information. A popular example is the series of reference regions used in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Adaptation (SREX). The SREX regions were slightly modified for the Fifth Assessment Report of the IPCC and used for reporting subcontinental observed and projected changes over a reduced number (33) of climatologically consistent regions encompassing a representative number of grid boxes. These regions are intended to allow analysis of atmospheric data over broad land or ocean regions and have been used as the basis for several popular spatially aggregated datasets, such as the Seasonal Mean Temperature and Precipitation in IPCC Regions for CMIP5 dataset. We present an updated version of the reference regions for the analysis of new observed and simulated datasets (including CMIP6) which offer an opportunity for refinement due to the higher atmospheric model resolution. As a result, the number of land and ocean regions is increased to 46 and 15, respectively, better representing consistent regional climate features. The paper describes the rationale for the definition of the new regions and analyses their homogeneity. The regions are defined as polygons and are provided as coordinates and a shapefile together with companion R and Python notebooks to illustrate their use in practical problems (e.g. calculating regional averages). We also describe the generation of a new dataset with monthly temperature and precipitation, spatially aggregated in the new regions, currently for CMIP5 and CMIP6, to be extended to other datasets in the future (including observations). The use of these reference regions, dataset and code is illustrated through a worked example using scatter plots to offer guidance on the likely range of future climate change at the scale of the reference regions. The regions, datasets and code (R and Python notebooks) are freely available at the ATLAS GitHub repository: https://github.com/SantanderMetGroup/ATLAS (last access: 24 August 2020), https://doi.org/10.5281/zenodo.3998463 (Iturbide et al., 2020).

Abstract The evolution of ocean temperature measurement systems is presented with a focus on the development and accuracy of two critical devices in use today (expendable bathythermographs and conductivity‐temperature‐depth instruments used on Argo floats). A detailed discussion of the accuracy of these devices and a projection of the future of ocean temperature measurements are provided. The accuracy of ocean temperature measurements is discussed in detail in the context of ocean heat content, Earth's energy imbalance, and thermosteric sea level rise. Up‐to‐date estimates are provided for these three important quantities. The total energy imbalance at the top of atmosphere is best assessed by taking an inventory of changes in energy storage. The main storage is in the ocean, the latest values of which are presented. Furthermore, despite differences in measurement methods and analysis techniques, multiple studies show that there has been a multidecadal increase in the heat content of both the upper and deep ocean regions, which reflects the impact of anthropogenic warming. With respect to sea level rise, mutually reinforcing information from tide gauges and radar altimetry shows that presently, sea level is rising at approximately 3 mm yr −1 with contributions from both thermal expansion and mass accumulation from ice melt. The latest data for thermal expansion sea level rise are included here and analyzed.

The carbon balance of peatlands is predicted to shift from a sink to a source this century. However, peatland ecosystems are still omitted from the main Earth system models that are used for future climate change projections, and they are not considered in integrated assessment models that are used in impact and mitigation studies. By using evidence synthesized from the literature and an expert elicitation, we define and quantify the leading drivers of change that have impacted peatland carbon stocks during the Holocene and predict their effect during this century and in the far future. We also identify uncertainties and knowledge gaps in the scientific community and provide insight towards better integration of peatlands into modelling frameworks. Given the importance of the contribution by peatlands to the global carbon cycle, this study shows that peatland science is a critical research area and that we still have a long way to go to fully understand the peatland–carbon–climate nexus. Peatlands are impacted by climate and land-use changes, with feedback to warming by acting as either sources or sinks of carbon. Expert elicitation combined with literature review reveals key drivers of change that alter peatland carbon dynamics, with implications for improving models.

Abstract Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of $$\sim $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>∼</mml:mo> </mml:math> 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution ( $$\sim $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mo>∼</mml:mo> </mml:math> 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from $$\sim \,$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>∼</mml:mo> <mml:mspace/> </mml:mrow> </mml:math> −40% at 12 km to $$\sim \,$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>∼</mml:mo> <mml:mspace/> </mml:mrow> </mml:math> −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.

Abstract Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

The Atlantic Meridional Overturning Circulation (AMOC) extends from the Southern Ocean to the northern North Atlantic, transporting heat northwards throughout the South and North Atlantic, and sinking carbon and nutrients into the deep ocean. Climate models indicate that changes to the AMOC both herald and drive climate shifts. Intensive trans-basin AMOC observational systems have been put in place to continuously monitor meridional volume transport variability, and in some cases, heat, freshwater and carbon transport. These observational programs have been used to diagnose the magnitude and origins of transport variability, and to investigate impacts of variability on essential climate variables such as sea surface temperature, ocean heat content and coastal sea level. AMOC observing approaches vary between the different systems, ranging from trans-basin arrays (OSNAP, RAPID 26 N, 11 S, SAMBA 34.5 S) to arrays concentrating on western boundaries (e.g., RAPID WAVE, MOVE 16 N). In this paper, we outline the different approaches (aims, strengths and limitations) and summarize the key results to date. We also discuss alternate approaches for capturing AMOC variability including direct estimates (e.g., using sea level, bottom pressure, and Frajka-Williams et al.

Abstract We evaluate the performance of a large ensemble of Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over South America for a recent past reference period and examine their projections of twenty-first century precipitation and temperature changes. The future changes are computed for two time slices (2040–2059 and 2080–2099) relative to the reference period (1995–2014) under four Shared Socioeconomic Pathways (SSPs, SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5). The CMIP6 GCMs successfully capture the main climate characteristics across South America. However, they exhibit varying skill in the spatiotemporal distribution of precipitation and temperature at the sub-regional scale, particularly over high latitudes and altitudes. Future precipitation exhibits a decrease over the east of the northern Andes in tropical South America and the southern Andes in Chile and Amazonia, and an increase over southeastern South America and the northern Andes—a result generally consistent with earlier CMIP (3 and 5) projections. However, most of these changes remain within the range of variability of the reference period. In contrast, temperature increases are robust in terms of magnitude even under the SSP1–2.6. Future changes mostly progress monotonically from the weakest to the strongest forcing scenario, and from the mid-century to late-century projection period. There is an increase in the seasonality of the intra-annual precipitation distribution, as the wetter part of the year contributes relatively more to the annual total. Furthermore, an increasingly heavy-tailed precipitation distribution and a rightward shifted temperature distribution provide strong indications of a more intense hydrological cycle as greenhouse gas emissions increase. The relative distance of an individual GCM from the ensemble mean does not substantially vary across different scenarios. We found no clear systematic linkage between model spread about the mean in the reference period and the magnitude of simulated sub-regional climate change in the future period. Overall, these results could be useful for regional climate change impact assessments across South America.

Abstract Despite notable scientific and medical advances, broader political, socioeconomic and behavioural factors continue to undercut the response to the COVID-19 pandemic 1,2 . Here we convened, as part of this Delphi study, a diverse, multidisciplinary panel of 386 academic, health, non-governmental organization, government and other experts in COVID-19 response from 112 countries and territories to recommend specific actions to end this persistent global threat to public health. The panel developed a set of 41 consensus statements and 57 recommendations to governments, health systems, industry and other key stakeholders across six domains: communication; health systems; vaccination; prevention; treatment and care; and inequities. In the wake of nearly three years of fragmented global and national responses, it is instructive to note that three of the highest-ranked recommendations call for the adoption of whole-of-society and whole-of-government approaches 1 , while maintaining proven prevention measures using a vaccines-plus approach 2 that employs a range of public health and financial support measures to complement vaccination. Other recommendations with at least 99% combined agreement advise governments and other stakeholders to improve communication, rebuild public trust and engage communities 3 in the management of pandemic responses. The findings of the study, which have been further endorsed by 184 organizations globally, include points of unanimous agreement, as well as six recommendations with &gt;5% disagreement, that provide health and social policy actions to address inadequacies in the pandemic response and help to bring this public health threat to an end.

To predict the ecological consequences of biodiversity loss, researchers have spent much time and effort quantifying how biological variation affects the magnitude and stability of ecological processes that underlie the functioning of ecosystems. Here we add to this work by looking at how biodiversity jointly impacts two aspects of ecosystem functioning at once: (1) the production of biomass at any single point in time (biomass/area or biomass/ volume), and (2) the stability of biomass production through time (the CV of changes in total community biomass through time). While it is often assumed that biodiversity simultaneously enhances both of these aspects of ecosystem functioning, the joint distribution of data describing how species richness regulates productivity and stability has yet to be quantified. Furthermore, analyses have yet to examine how diversity effects on production covary with diversity effects on stability. To overcome these two gaps, we reanalyzed the data from 34 experiments that have manipulated the richness of terrestrial plants or aquatic algae and measured how this aspect of biodiversity affects community biomass at multiple time points. Our reanalysis confirms that biodiversity does indeed simultaneously enhance both the production and stability of biomass in experimental systems, and this is broadly true for terrestrial and aquatic primary producers. However, the strength of diversity effects on biomass production is independent of diversity effects on temporal stability. The independence of effect sizes leads to two important conclusions. First, while it may be generally true that biodiversity enhances both productivity and stability, it is also true that the highest levels of productivity in a diverse community are not associated with the highest levels of stability. Thus, on average, diversity does not maximize the various aspects of ecosystem functioning we might wish to achieve in conservation and management. Second, knowing how biodiversity affects productivity gives no information about how diversity affects stability (or vice versa). Therefore, to predict the ecological changes that occur in ecosystems after extinction, we will need to develop separate mechanistic models for each independent aspect of ecosystem functioning.

). They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and aerosol-removal rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend that is consistent with airborne infection and enable recommendations to minimize transmission risk. Transmission in typical prepandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, influenza, and tuberculosis were also assessed. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at higher risk parameter values. Because both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on masking, ventilation and aerosol-removal rates, number of occupants, and duration of exposure, to investigate airborne transmission.

Abstract The emergence of clear semantics for causal claims and of a sound logic for causal reasoning is relatively recent, with the consolidation over the past decades of a coherent theoretical corpus of definitions, concepts, and methods of general applicability that is anchored into counterfactuals. The latter corpus has proved to be of high practical interest in numerous applied fields (e.g., epidemiology, economics, and social science). In spite of their rather consensual nature and proven efficacy, these definitions and methods are to a large extent not used in detection and attribution (D&amp;A). This article gives a brief overview of the main concepts underpinning the causal theory and proposes some methodological extensions for the causal attribution of weather and climate-related events that are rooted into the latter. Implications for the formulation of causal claims and their uncertainty are finally discussed.

Abstract. The ozone profile records of a large number of limb and occultation satellite instruments are widely used to address several key questions in ozone research. Further progress in some domains depends on a more detailed understanding of these data sets, especially of their long-term stability and their mutual consistency. To this end, we made a systematic assessment of 14 limb and occultation sounders that, together, provide more than three decades of global ozone profile measurements. In particular, we considered the latest operational Level-2 records by SAGE II, SAGE III, HALOE, UARS MLS, Aura MLS, POAM II, POAM III, OSIRIS, SMR, GOMOS, MIPAS, SCIAMACHY, ACE-FTS and MAESTRO. Central to our work is a consistent and robust analysis of the comparisons against the ground-based ozonesonde and stratospheric ozone lidar networks. It allowed us to investigate, from the troposphere up to the stratopause, the following main aspects of satellite data quality: long-term stability, overall bias and short-term variability, together with their dependence on geophysical parameters and profile representation. In addition, it permitted us to quantify the overall consistency between the ozone profilers. Generally, we found that between 20 and 40 km the satellite ozone measurement biases are smaller than ±5 %, the short-term variabilities are less than 5–12 % and the drifts are at most ±5 % decade−1 (or even ±3 % decade−1 for a few records). The agreement with ground-based data degrades somewhat towards the stratopause and especially towards the tropopause where natural variability and low ozone abundances impede a more precise analysis. In part of the stratosphere a few records deviate from the preceding general conclusions; we identified biases of 10 % and more (POAM II and SCIAMACHY), markedly higher single-profile variability (SMR and SCIAMACHY) and significant long-term drifts (SCIAMACHY, OSIRIS, HALOE and possibly GOMOS and SMR as well). Furthermore, we reflected on the repercussions of our findings for the construction, analysis and interpretation of merged data records. Most notably, the discrepancies between several recent ozone profile trend assessments can be mostly explained by instrumental drift. This clearly demonstrates the need for systematic comprehensive multi-instrument comparison analyses.

The Andes is the most biodiverse region across the globe. In addition, some of the largest urban areas in South America are located within this region. Therefore, ecosystems and human population are affected by hydroclimate changes reported at global, regional and local scales. This paper summarizes progress of knowledge about long-term trends observed during the last two millennia over the entire Andes, with more detail for the period since the second half of the 20th century, and presents a synthesis of climate change projections by the end of the 21st century. In particular, this paper focuses on temperature, precipitation and surface runoff in the Andes. Changes in the Andean cryosphere is not reviewed here since this particular topic is assessed by Masiokas et al. (2019) in a paper presented in this same special issue. While previous works have reviewed the hydroclimate of South America and particular sectors (i.e. Amazon and La Plata basins, the Altiplano, northern South America, etc) this review includes for the first time the entire Andes region, considering all latitudinal ranges: tropical (north of 27°S), subtropical (27°S-37°S) and extratropical (south of 37°S). This paper provides a comprehensive view of past and recent changes, as well as available climate change projections, over the entire Andean range. From this review, the main knowledge gaps are highlighted as well as urgent research necessities in order to provide more mechanistic understanding of hydroclimate changes in the Andes and more confident projections of its possible changes in association with global climate change.

We present an interdisciplinary review of the observed and projected variations in atmospheric and oceanic circulation within the southwestern South Atlantic focused on basin-scale processes driven by climate change, and their potential impact on the regional fisheries. The observed patterns of atmospheric circulation anomalies are consistent with anthropogenic climate change. There is strong scientific evidence suggesting that the Brazil Current is intensifying and shifting southwards during the past decades in response to changes in near-surface wind patterns, leading to intense ocean warming along the path of the Brazil Current, the South Brazil Bight, and in the Río de la Plata. These changes are presumably responsible for the poleward shift of commercially important pelagic species in the region and the long-term shift from cold-water to warm-water species in industrial fisheries of Uruguay. Scientific and traditional knowledge shows that climate change is also affecting small-scale fisheries. Long-term records suggest that mass mortalities decimated harvested clam populations along coastal ecosystems of the region, leading to prolonged shellfishery closures. More frequent and intense harmful algal blooms together with unfavorable environmental conditions driven by climate change stressors affect coastal shellfisheries, impact economic revenues, and damage the livelihood of local communities. We identify future modelling needs to reduce uncertainty in the expected effects of climate change on marine fisheries. However, the paucity of fisheries data prevents a more effective assessment of the impact of climate change on fisheries and hampers the ability of governments and communities to adapt to these changes.

ABSTRACT The purpose of this study is to evaluate the ability of two sets of global climate models (GCMs) derived from the Coupled Model Intercomparison Projects Phase 3 ( CMIP3 ) and Phase 5 ( CMIP5 ) to represent the summer, winter, and annual precipitation mean patterns in South America south of the equator and in three particular sub‐regions, between years 1960 and 1999. Different metrics (relative bias, spatial correlation, RMSE , and relative errors) were calculated and compared between both projects to determine if there has been improvement from CMIP3 to CMIP5 models in the representation of regional rainfall. Results from this analysis indicate that for the analysed seasons, precipitation simulated by both CMIP3 and CMIP5 models' ensembles exhibited some differences. In DJF , the relative bias over Amazonia, central South America, eastern Argentina, and Uruguay is reduced in CMIP5 compared with CMIP3 . In JJA , the same occurs in some areas of Amazonia. Annual precipitation is also better represented by the CMIP5 than CMIP3 GCMs as they underestimate precipitation to a lesser extent, although in NE Brazil the overestimation values are much larger in CMIP5 than in CMIP3 analysis. In line with previous studies, the multi‐model ensembles show the best representation of the observed patterns in most seasons and regions. Only in some cases, single GCMs [ MIROC3 .2(hires) – CMIP3 – and MIROC4h – CMIP5 ] presented better results than the ensemble. The high horizontal resolution of these models suggests that this could be a relevant issue for a more adequate estimation of rainfall at least in the analysed regions.

Abstract This study aims to compare simulated soil moisture anomalies derived from different versions of the Global Land Data Assimilation System (GLDAS), the standardized precipitation index (SPI), and a new multisatellite surface soil moisture product over southern South America. The main motivation is the need for assessing the reliability of GLDAS variables to be used in the characterization of soil state and its variability at the regional scale. The focus is on the southeastern part of South America (SESA), which is part of the La Plata basin, one of the largest basins of the world, where agriculture is the main source of income. The results show that GLDAS data capture soil moisture anomalies and their variability, taking into account regional and seasonal dependencies and showing correspondence with other proxies used to characterize soil states. Over large portions of the domain, and particularly over SESA, the correlation with the SPI is very high, with the second version of GLDAS, version 2 (GLDAS-2 v2), exhibiting the highest values regardless of the season. Similar results were obtained by comparing the surface soil moisture anomalies from the GLDAS land surface model (LSM) against the satellite estimations for a shorter period of time. This work documents that the precipitation dataset used to force each LSM and the choice of the LSM are of major relevance for representing soil conditions in an adequate manner. The results are considered to support the use of GLDAS as an indicator of soil moisture states and for developing new soil moisture–monitoring indices that can be applied, for example, in the context of agricultural production management.

Abstract This article provides an overview of the experimental design, execution, education and public outreach, data collection, and initial scientific results from the Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign. RELAMPAGO was a major field campaign conducted in the Córdoba and Mendoza provinces in Argentina and western Rio Grande do Sul State in Brazil in 2018–19 that involved more than 200 scientists and students from the United States, Argentina, and Brazil. This campaign was motivated by the physical processes and societal impacts of deep convection that frequently initiates in this region, often along the complex terrain of the Sierras de Córdoba and Andes, and often grows rapidly upscale into dangerous storms that impact society. Observed storms during the experiment produced copious hail, intense flash flooding, extreme lightning flash rates, and other unusual lightning phenomena, but few tornadoes. The five distinct scientific foci of RELAMPAGO—convection initiation, severe weather, upscale growth, hydrometeorology, and lightning and electrification—are described, as are the deployment strategies to observe physical processes relevant to these foci. The campaign’s international cooperation, forecasting efforts, and mission planning strategies enabled a successful data collection effort. In addition, the legacy of RELAMPAGO in South America, including extensive multinational education, public outreach, and social media data gathering associated with the campaign, is summarized.

Abstract Aim Climate change is expected to impact mountain biodiversity by shifting species ranges and the biomes they shape. The extent and regional variation in these impacts are still poorly understood, particularly in the highly biodiverse Andes. Regional syntheses of climate change impacts on vegetation are pivotal to identify and guide research priorities. Here we review current data, knowledge and uncertainties in past, present and future climate change impacts on vegetation in the Andes. Location: Andes. Taxon: Plants. Methods We (i) conducted a literature review on Andean vegetation responses to past and contemporary climatic change, (ii) analysed future climate projections for different elevations and slope orientations at 19 Andean locations using an ensemble of model outputs from the Coupled Model Intercomparison Project 5, and (iii) calculated changes in the suitable climate envelope area of Andean biomes and compared these results to studies that used species distribution models. Results Future climatic changes (2040–2070) are projected to be stronger at high‐elevation areas in the tropical Andes (up to 4°C under RCP 8.5), while in the temperate Andes temperature increases are projected to be up to 2°C. Under this worst‐case scenario, temperate deciduous forests and the grasslands/steppes from the Central and Southern Andes are predicted to show the greatest losses of suitable climatic space (30% and 17%–23%, respectively). The high vulnerability of these biomes contrasts with the low attention from researchers modelling Andean species distributions. Critical knowledge gaps include a lack of an Andean wide plant checklist, insufficient density of weather stations at high‐elevation areas, a lack of high‐resolution climatologies that accommodates the Andes' complex topography and climatic processes, insufficient data to model demographic and ecological processes, and low use of palaeo data for distribution modelling. Main conclusions Climate change is likely to profoundly affect the extent and composition of Andean biomes. Temperate Andean biomes in particular are susceptible to substantial area contractions. There are, however, considerable challenges and uncertainties in modelling species and biome responses and a pressing need for a region‐wide approach to address knowledge gaps and improve understanding and monitoring of climate change impacts in these globally important biomes.