In tropical regions, particularly in Central and South America (CSA), the projections of climate seasonality under climate change are still uncertain. This is especially true for ecologically‐relevant variables such as precipitation and temperature. However, assessments of model‐based projections of seasonal climate for this region are scarce. We analyzed the simulation of seasonal precipitation and air surface temperature in CSA and six sub‐regions within from 49 models included in the Coupled Intercomparison Project Phase 5 (CMIP5) and 33 models from CMIP6. In general, continental patterns and seasonality of both variables are moderately well resembled, while most models show systematic biases over the oceans, producing unrealistic spatial patterns. To quantify how well CMIP5/CMIP6 models simulate these variables, we used Taylor diagrams with respect to TRMM for precipitation and ERA5 for temperature. Precipitation shows the largest spread among models. Conversely, temperature shows a better simulation. CMIP5/CMIP6 models exhibit a better performance simulating both variables during December–January–February and March–April–May than during the other seasons. This is partly due to the reduced model biases in representing the Intertropical Convergence Zone during these two seasons. In general, biases are reduced in the CMIP6 models with respect to CMIP5. Regarding regional evaluations, precipitation patterns for Mesoamerica, Cerrado and Chaco regions are better reproduced compared to TRMM, while the annual cycles for the Andes hotspot, Central Chile and Guianas are not well simulated, mainly during their wet seasons. However, these biases are reduced in CMIP6 models. In regard to precipitation projections, models only agree over most of the regions with decreasing precipitation. Conversely, temperature exhibits a general consensus on persistent warming even during the historical period, with an average increase of 6°C by the end of the century, according to the CMIP6 models.

This paper provides an updated review of the most relevant scientific literature related to the hydroclimate of the Andes. The Andes, the longest cordillera in the world, faces major challenges regarding climate variability and climate change, which impose several threats to sustainable development, including water supply and the sustainability of ecosystem services. This review focuses on hydroclimate variability of the Andes at a sub-continental scale. The annual water cycle and long-term water balance along the Andes are addressed first, followed by the examination of the effects of orography on convective and frontal precipitation through the study of precipitation gradients in the tropical, subtropical and extratropical Andes. In addition, a review is presented of the current scientific literature on the climate variability in the Andes at different timescales. Finally, open research questions are presented in the last section of this article.

Since 2019, Central South America (CSA) has been reeling under drought conditions, with the last 4 months of 2022 receiving only 44% of the average total precipitation. Simultaneously to the drought, a series of record-breaking heat waves has affected the region. The rainfall deficit during October–November-December (OND) is highly correlated with the Niño3.4 index, indicating that the OND 2022 rainfall deficit is partly driven by La Niña, as observed in previous droughts in this region. To identify whether human-induced climate change was also a driver of the OND 2022 rainfall deficit, we analysed precipitation over the most impacted region. Our findings revealed a pattern of decreased rainfall over the past 40 years, although we cannot definitively conclude whether this trend exceeds what would be expected from natural variations. To clarify if this trend can be attributed to climate change, we looked at 1-in-20-year low rainfall events over the same region in climate models. The models show that the severity of low rainfall events decreases (i.e. they become wetter, the opposite of the trend observed in most weather records), although this trend is again not significant and is compatible with natural variability. Therefore, we cannot attribute the low rainfall to climate change. Moreover, our analysis of effective precipitation potential (evapotranspiration minus rainfall) shows that, in climate models, the increase in temperature does partly compensate for the increase in rainfall but only to offset the wetting, and does not lead to a significant climate change signal in effective precipitation. However, higher temperatures in the region, which have been attributed to climate change, decreased water availability in the models in late 2022, indicating that climate change probably reduced water availability over this period also in the observations, increasing agricultural drought, although this study did not quantify this effect. This means that even though the reduced rainfall is within the natural variability, the consequences of drought are becoming more severe due to the strong increase in extreme heat. The case of the OND 2022 rainfall deficit and the ongoing drought in CSA is a clear example of the interplay between climate variability and human-induced climate change. This shows the importance of considering not only those aspects associated with climate change but also climate variability in order to understand and attribute particular events or trends at the regional level.