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The Colombian Andes (CA) are located over the northwestern corner of tropical South America (NW‐TropSA), where land and atmosphere interchange moisture and energy in a complex way owing to the orographic influence on the recycling of moisture over land. We aim to understand where and when water vapor evaporated from land turns into rainfall through moisture recycling, using the Water Accounting Model‐2layers (WAM‐2), an offline model to track atmospheric moisture forced with data from ERA‐5 at its native 0.25° resolution during 1980–2020. We define the spatiotemporal distribution of sources (high evaporation recycle ratios, ϵC) and receptors (high precipitation recycle ratios, ρC) of continental moisture at diverse timescales, including monthly, seasonal, annual and interannual (ENSO). Referring to the regional runs of WAM‐2 over NW‐TropSA (4°S–12°N/80°W–66°W), at elevations above 1,000 m.a.s.l., the CA has a mean annual ρC of 11% (ranging 6%–16%) and a mean annual ϵC of 35% (ranging 27%–40%). Moisture recycling in the CA exhibits a strong annual cycle over the region. The seasonal dynamic of moisture recycling shows two clear‐cut sources of moisture: the eastern foothills of the Eastern and Central ranges of the CA. Both foothills are also regions of high rainfall, although moisture recycling mechanisms differ. Sources of continental moisture grow spatially during September‐October‐November and March‐April‐May. The seasonal availability of moisture recycled coincides with regions where orography interacts with low level jets sourcing humidity. At interannual timescales, sources and receptors of continental moisture in the CA are modulated by the extreme phases of ENSO. Key Points: The orography of the Colombian Andes emerged as a critical factor shaping the interaction between land and atmospheric moisture fluxesFoothills and valleys of the Colombian Andes play a pivotal role in continental moisture recycling, in terms of convergence and divergenceENSO modulates both sources and receptors of continental moisture at interannual timescales [ABSTRACT FROM AUTHOR]

Currently there are several precipitation reconstructions for northern Mexico; however, there is a lack of temperature reconstructions to understand past climate change, the impact on ecosystems and societies, etc. The central region of Chihuahua is located in a transition zone between the Sierra Madre Occidental and the Great Northern Plain, characterized by extreme temperatures and marked seasonal variability. The objectives of this study were (1) to generate a climatic association between variables from reanalysis models and the earlywood series for the center of Chihuahua, (2) to generate a reconstruction of mean temperature, (3) to determine extreme events, and (4) to identify the influence of ocean–atmosphere phenomena. Chronologies were downloaded from the International Tree-Ring Data Bank and climate information from the NLDAS-2 and ClimateNA reanalysis models. The response function was performed using climate models and regional dendrochronological series. A reconstruction of mean temperature was generated, and extreme periods were identified. The representativeness of the reconstruction was evaluated through spatial correlation, and low-frequency events were determined through multitaper spectral analysis and wavelet analysis. The influence of ocean–atmosphere phenomena on temperature reconstruction was analyzed using Pearson correlation, and the influence of ENSO was examined through wavelet coherence analysis. Highly significant correlations were found for maximum, minimum, and mean temperature, as well as for precipitation and relative humidity, before and after the growth year. However, the seasonal period with the highest correlation was found from May to June for mean temperature, which was used to generate the reconstruction from 1775 to 2022. The most extreme periods were 1775, 1801, 1805, 1860, 1892–1894, 1951, 1953–1954, and 2011–2012. Spectral analysis showed significant frequencies of 56.53 and 2.09 years, and wavelet analysis from 0 to 2 years from 1970 to 1980, from 8 to 11 years from 1890 to 1910, and from 30 to 70 years from 1860 to 2022. A significant association was found with the Multivariate ENSO Index phenomenon (r = 0.40; p = 0.009) and Pacific Decadal Oscillation (r = −0.38; p = 0.000). Regarding the ENSO phenomenon, an antiphase association of r = −0.34; p = 0.000 was found, with significant periods of 1 to 4 years from 1770 to 1800, 1845 to 1850, and 1860 to 1900, with periods of 6 to 10 years from 1875 to 1920, and from 6 to 8 years from 1990 to 2000. This study allowed a reconstruction of mean temperature through reanalysis data, as well as a historical characterization of temperature for central Chihuahua beyond the observed records. [ABSTRACT FROM AUTHOR]

Paleoclimatological field reconstructions are valuable for understanding hydroclimatic variability. While being similarly impactful on societies as temperature variability, hydroclimatic variability has still remained less in focus. However, reconstructing globally complete fields of climate variables lacks adequate proxy data from tropical regions like South America, limiting our understanding of past hydroclimatic changes in these areas. This study addresses this gap using low resolution climate archives, including speleothems, previously omitted from reconstructions. Speleothems record climate variations on decadal to centennial time scales and provide a rich dataset for the otherwise proxy data scarce region of tropical South America. By employing a multi-time scale Paleoclimate Data Assimilation approach, we synthesize climate proxy records and climate model simulations, capable of simulating water isotopologues in the atmosphere, to reconstruct 2000 years of South American climate. This includes surface air temperature, precipitation amount, drought index, isotopic composition of precipitation amount, and the intensity of the South American Summer Monsoon. The reconstruction reveals anomalous climate periods: a wetter and colder phase during the Little Ice Age (1500–1850 CE) and a drier, warmer period corresponding to the early Medieval Climate Anomaly (600–900 CE). However, these patterns are not uniform across the continent, with exceptions in northeastern Brazil and the Southern Cone, indicating regional variability. The anomalies are more pronounced than in previous reconstructions, but align with local proxy record studies, thus highlighting the importance of including speleothem proxies. The multi-timescale approach is essential for reconstructing multi-decadal and centennial climate variability. Despite methodological uncertainties regarding climate model biases and proxy record interpretations, this study marks a crucial first step in incorporating speleothems into climate field reconstructions, potentially enhancing insights into past hydroclimatic variability and hydroclimate projections. [ABSTRACT FROM AUTHOR]

We show that ModE‐Sim, a global ensemble of atmospheric model simulations that uses observed ocean boundary conditions and radiative forcings providing 36 members with daily climate information can be used to in‐depth analyze the known spatial and temporal variability of heatwaves in the Northern Hemisphere and Australia during the past 160 years. It can also be used to study actual past extreme events like heatwaves during the El Nino 1877/1878. To analyze past heatwaves we use a novel approach of a transient baseline climatology and compare to different observational data sets. Furthermore, we analyze sea surface temperature anomalies during the most extreme heatwave summers in North America, Europe and Australia and identify the most prominent anomaly patterns over the Subpolar North Atlantic and in the Central Pacific. Using a large ensemble of forced simulations, like ModE‐Sim can consequently contribute to a better understanding of preindustrial heatwaves, their decadal variability and their driving mechanisms. Plain Language Summary: In this study we use an atmospheric model to look at historical heatwaves during the past 160 years. In several regions of the Northern Hemisphere and in Australia we can successfully reproduce heatwave variability that we see in observations with our model. One of the main reasons that we reproduce the evolution and distribution of past heatwaves with our model is that our simulations use observed Sea Surface Temperatures. We show that deviations from the mean Sea Surface Temperatures over the Central Pacific and the Subpolar North Atlantic are connected to more summer heatwaves over Europe and North America. We also look at the big El Nino event in 1877/1878 and show that there was global increase in heatwaves during this event, even though heatwaves in parts of Europe and in North America got less frequent. Overall, we show that this model is very useful to better understand extreme events like heatwaves during the preindustrial era where we only have very little or no climate observations. Key Points: Using a forced AGCM ensemble can largely reproduce heatwave variability of the past 160 years throughout the Northern Hemisphere and AustraliaSea surface temperature anomalies over the Central Pacific and Subpolar North Atlantic are connected to strong heatwave summers in North America and EuropeDuring the El Nino 1877/1878 there was a global increase in heatwave days, while heatwaves in North America and parts of Europe decreased [ABSTRACT FROM AUTHOR]

The availability of fresh water over land may become increasingly scarce under climate change, and natural and human-induced tree cover changes can further enhance or negate the water scarcity. Previous studies showed that global tree cover change can have large impacts on water availability under current climate conditions, but did not touch upon the implications of global tree cover change under climate change. Here, we study the hydrological impacts of large-scale tree cover change (climate-induced changes in combination with large-scale afforestation) in a future climate (SSP3-7.0) following an interdisciplinary approach. By combining data from five CMIP6 climate models with a future potential tree cover dataset, six Budyko models, and the UTrack moisture recycling dataset, we can disentangle the impacts of climate change and future tree cover change on evaporation, precipitation, and runoff. We quantify per grid cell and for five selected river basins (Yukon, Mississippi, Amazon, Danube, and Murray-Darling) if tree cover changes enhance or counteract the climate-driven changes in runoff due to their impact on evapotranspiration and moisture recycling. Globally averaged, the impacts of climate change and large-scale tree cover change on runoff are of similar magnitude with opposite signs. While climate change increases the global runoff, the changing tree cover reverses this effect which overall results in a limited net impact on runoff relative to the present climate and current tree cover. Nevertheless, locally the change in runoff due to tree cover change and climate change can be substantial with increases and decreases of more than 100 mmyear-1. We show that for approximately 16 % of the land surface, tree cover change can increase the water availability significantly. However, we also find that, for 14 % of the land surface, both tree cover change and climate change might decrease water availability with more than 5 mm year-1. For each of the selected catchments, the direction and magnitude of the impacts of climate change and tree cover change vary, with dominating climate change impacts in all basins except the Mississippi River basin. Our results show that ecosystem restoration projects targeting an altered tree cover should consider the corresponding hydrological impacts to limit unwanted (non-)local reductions in water availability. [ABSTRACT FROM AUTHOR]

El Niño‐Southern Oscillation (ENSO) flavors in the tropical Pacific are studied from a regime perspective. Five recurring spatial patterns or regimes characterizing the diversity of ENSO are established using a clustering approach applied to the HadISST sea surface temperature (SST) anomalies. Compared to previous studies, our approach gives a monthly characterization of the diversity of the warm and cold phases of ENSO established from observations but commonly applied to models and observations. Two warm (eastern and central El Niño), two cold (basin wide and central La Niña) and a neutral reference regimes are found. Simulated SST anomalies by the models from the latest Coupled Model Intercomparison Project Phase 6 are then matched to these reference regimes. This allows for a consistent assessment of the skill of the models in reproducing the reference regimes over the historical period and the change in these regimes under the high‐warming Shared Socio‐economic Pathway (SSP5.8.5) scenario. Results over the historical period show that models simulate well the reference regimes with some discrepancies. Models simulate more intense and spatially extended ENSO patterns and have issues in capturing the correct regime seasonality, persistence, and transition between regimes. Some models also have difficulty simulating the frequency of regimes, the eastern El Niño regime in particular. In the future, both El Niño and central La Niña regimes are expected to be more frequent accompanied with a less frequent neutral regime. The central Pacific El Niño and La Niña regimes are projected to increase in amplitude and variability. Plain Language Summary: A heuristic definition to characterize the diversity of sea surface temperature spatial patterns or regimes, typical of the El Niño‐Southern Oscillation (ENSO) and common to observation and climate model simulations, is established here. Using this approach, we found from the observations two warm (eastern and central El Niño), two cold (basin wide and central La Niña), and a neutral reference ENSO regimes. State‐of‐the‐art climate models are generally able to simulate the spatial patterns of these observed five ENSO regimes to some extent. Models simulate overly intense and spatially extended ENSO patterns and have issues in capturing the correct regime seasonality, persistence, and transition between regimes. Under the business as usual future scenario, the model projections indicate that eastern and central El Niño and central La Niña regimes are expected to be more frequent accompanied with a less frequent neutral regime. The central Pacific El Niño and La Niña regimes are projected to increase in amplitude and variability. Key Points: A clustering approach identifies two observed warm and cold El Niño‐Southern Oscillation (ENSO) regimes to which simulated regimes are matched and consistently evaluatedOver historical period, Coupled Model Intercomparison Project Phase 6 models well simulate ENSO patterns with discrepancies in terms of frequency, seasonality, and persistenceFuture evolution in terms of frequency, magnitude, and variability depends on type of cold or warm ENSO regime [ABSTRACT FROM AUTHOR]

Tropical forests such as the Amazonian rainforests play an important role for climate, are large carbon stores and are a treasure of biodiversity. Amazonian forests have been exposed to large-scale deforestation and degradation for many decades. Deforestation declined between 2005 and 2012 but more recently has again increased with similar rates as in 2007–2008. The resulting forest fragments are exposed to substantially elevated temperatures in an already warming world. These temperature and land cover changes are expected to affect the forests, and an important diagnostic of their health and sensitivity to climate variation is their carbon balance. In a recent study based on CO 2 atmospheric vertical profile observations between 2010 and 2018, and an air column budgeting technique used to estimate fluxes, we reported the Amazon region as a carbon source to the atmosphere, mainly due to fire emissions. Instead of an air column budgeting technique, we use an inverse of the global atmospheric transport model, TOMCAT, to assimilate CO 2 observations from Amazon vertical profiles and global flask measurements. We thus estimate inter- and intra-annual variability in the carbon fluxes, trends over time and controls for the period of 2010–2018. This is the longest period covered by a Bayesian inversion of these atmospheric CO 2 profile observations to date. Our analyses indicate that the Amazon is a small net source of carbon to the atmosphere (mean 2010–2018 = 0.13 ± 0.17 Pg C yr -1 , where 0.17 is the 1 σ uncertainty), with the majority of the emissions coming from the eastern region (77 % of total Amazon emissions). Fire is the primary driver of the Amazonian source (0.26 ± 0.13 Pg C yr -1), while forest carbon uptake removes around half of the fire emissions to the atmosphere (- 0.13 ± 0.20 Pg C yr -1). The largest net carbon sink was observed in the western-central Amazon region (72 % of the fire emissions). We find larger carbon emissions during the extreme drought years (such as 2010, 2015 and 2016), correlated with increases in temperature, cumulative water deficit and burned area. Despite the increase in total carbon emissions during drought years, we do not observe a significant trend over time in our carbon total, fire and net biome exchange estimates between 2010 and 2018. Our analysis thus cannot provide clear evidence for a weakening of the carbon uptake by Amazonian tropical forests. [ABSTRACT FROM AUTHOR]

Coastal convection is often organized into multiple mesoscale systems that propagate in either direction across the coastline (i.e., landward and oceanward). These systems interact non-trivially with synoptic and intraseasonal disturbances such as convectively coupled waves and the Madden–Julian oscillation. Despite numerous theoretical and observational efforts to understand coastal convection, global climate models still fail to represent it adequately, mainly because of limitations in spatial resolution and shortcomings in the underlying cumulus parameterization schemes. Here, we use a simplified climate model of intermediate complexity to simulate coastal convection under the influence of the diurnal cycle of solar heating. Convection is parameterized via a stochastic multicloud model (SMCM), which mimics the subgrid dynamics of organized convection due to interactions (through the environment) between the cloud types that characterize organized tropical convection. Numerical results demonstrate that the model is able to capture the key modes of coastal convection variability, such as the diurnal cycle of convection and the accompanying sea and land breeze reversals, the slowly propagating mesoscale convective systems that move from land to ocean and vice-versa, and numerous moisture-coupled gravity wave modes. The physical features of the simulated modes, such as their propagation speeds, the timing of rainfall peaks, the penetration of the sea and land breezes, and how they are affected by the latitudinal variation in the Coriolis force, are generally consistent with existing theoretical and observational studies. [ABSTRACT FROM AUTHOR]

Runoff from glacierised Andean river basins is essential for sustaining the livelihoods of millions of people. By running a high-resolution climate model over the two most glacierised regions of Peru we unravel past climatic trends in precipitation and temperature. Future changes are determined from an ensemble of statistically downscaled global climate models. Projections under the high emissions scenario suggest substantial increases in temperature of 3.6 °C and 4.1 °C in the two regions, accompanied by a 12% precipitation increase by the late 21st century. Crucially, significant increases in precipitation extremes (around 75% for total precipitation on very wet days) occur together with an intensification of meteorological droughts caused by increased evapotranspiration. Despite higher precipitation, glacier mass losses are enhanced under both the highest emission and stabilization emission scenarios. Our modelling provides a new projection of combined and contrasting risks, in a region already experiencing rapid environmental change. [ABSTRACT FROM AUTHOR]

Climate change may have significant impacts on water balance and may considerably influence flooding dynamics of river systems by increasing extreme precipitation. This study evaluates the potential effects of climate change on river discharge and inundation in the Magdalena River basin, the main river in Colombia, using the synergy between the MGB (Modelo de Grandes Bacias) hydrological–hydrodynamic model and downscaled Eta-regional climate model (RCM) projections based on four global climate models (GCMs): BESM (Brazilian Earth System Model), CanESM2 (Canadian Earth System Model), MIROC5 (Model for Interdisciplinary Research on Climate Version Five), and HadGEM2-ES (Hadley Centre Global Environment Model version 2). We used two different greenhouse gas scenarios (RCP4.5 and RCP8.5 (Representative Concentration Pathway)) for the "historical" (1986–2005) and "mid-term prospective" (2046–2065) periods. Model results for the "mid-term prospective" period under scenarios RCP4.5 and RCP8.5 indicate increase in mean river discharges in the east portion of the basin, decreased river discharges (mainly in the dry season) in the upper Magdalena basin, and increased inundation extent. By coupling hydrological–hydrodynamic and GCMs/RCMs models, modelling frameworks like the one used in this study provide an effective management tool for stakeholders interested in potential climate change impacts on tropical river basins. [ABSTRACT FROM AUTHOR]

Accurate rainfall fields are important for several hydrological and meteorological applications. In poorly instrumented basins, the lack of rain gauges heavily affects the spatial rainfall estimation, yet neither remote sensed nor climate model estimates are good enough for management applications. To tackle this problem, we investigate the impacts of combining both sources of information by varying the kernel bandwidth value of the double smoothing merging algorithm and analyzing the error of the rainfall fields. We explored the correlation between rain gauge density and bandwidth and compared the results against classical geostatistical interpolation methods based solely on in-situ measurements. Propagation of rainfall error into hydrological modelling is usual, and therefore we evaluated the influence of the bandwidth in streamflow simulations implementing two hydrological models. The hydrological evaluation considered the analysis of hydrological signatures rather than just performance metrics. We found that there is a clear correlation between kernel bandwidth and monitoring network density and that the bandwidth also affects hydrological performance. Simple bilinear downscaling did not produce a significant difference in meteorological or hydrological errors, and rain gauge network configuration also impacts the error of the field. We conclude that merging outperforms the results of classical interpolation methods, in some cases by 20% or 50%, suggesting the suitability of the method for being applied in data-scarce domains. Reliable rainfall fields are important for estimating water resource availability and other related applications. However, using just rain gauges can misrepresent the estimated spatial variability of the field. Around the world, the number of rainfall gauges has been decreasing, making this task more challenging. Satellite and reanalysis data can help to overcome these problems, but their direct use is also insufficient. Merging the two mentioned data sources (in-situ and reanalysis data) is the option the authors implemented in this work. The authors focused on evaluating the advantages and disadvantages of the merging by comparing both rainfall and streamflow observations with estimates simulated by a hydrological model. The authors chose the double smoothing algorithm because it is oriented to enhance rainfall estimates in areas with very sparse rain gauge data, yet we evaluate its behavior in two basins with different monitoring conditions. The authors conclude that the merging outperforms the results of classical interpolation methods, in some cases by 20% or 50%, suggesting the suitability of the method for being applied in data-scarce domains to improve hydrological modelling estimates and use their results in water resource management and planning, in climate classification, and in the study of droughts and floods, among others. [ABSTRACT FROM AUTHOR]

In this study, we assess the performance of the Regional Climate Model version 4 (RegCM4) in simulating the climatology of the cyclones near the west coast of South America. The synoptic evolution and seasonality of these systems are thoroughly investigated. The analyses are based on four simulations from the CORDEX-CORE Southern America (SA) domain, at 0.25° of horizontal resolution: one driven by ERA-Interim and three driven by different GCMs. The reference dataset is represented by ERA5. Cyclones were detected by an objective scheme in the period 1995–2005 and classified in three different classes: (i) Coastal Lows (CLs) and cyclones affecting the coast (CAC) (ii) crossing and (iii) not crossing the Andes. In general, RegCM4 is able to reproduce the climatology of cyclones affecting the western coast of SA. In particular: (i) CLs are shown to be more frequent in austral summer although their frequency is underestimated by the simulations in this season; (ii) CAC not crossing the Andes represent 76% of all CAC and are more frequent in winter, with simulation underestimating their frequency by ~ 22% due to the differences in the simulated upper-level jets, which tend to get weaker (by ~ 5–10 m s− 1) northwards of 30°S; (iii) the frequency of CAC crossing the Andes tends to be overestimated mainly in winter, which is associated with the combination of the stronger upper-level jets and weaker SLP in the simulations, especially southwards of 40°S. [ABSTRACT FROM AUTHOR]

The Patagonian Icefields (Northern and Southern Patagonian Icefield) are the largest ice masses in the Andes Cordillera. Despite its importance, little is known about the main mechanisms that underpin the interaction between these ice masses and climate. Furthermore, the nature of large-scale climatic control over the surface mass variations of the Patagonian Icefields still remains unclear. The main aim of this study is to understand the present-day climatic control of the surface mass balance (SMB) of the Patagonian Icefields at interannual timescales, especially considering large-scale processes. We modeled the present-day (1980–2015) glacioclimatic surface conditions for the southern Andes Cordillera by statistically downscaling the output from a regional climate model (RegCMv4) from a 10 km spatial resolution to a 450 m resolution grid and then using the downscaled fields as input for a simplified SMB model. Series of spatially averaged modeled fields over the Patagonian Icefields were used to derive regression and correlation maps against fields of climate variables from the ERA-Interim reanalysis. Years of relatively high SMB are associated with the establishment of an anomalous low-pressure center near the Drake Passage, the Drake low, that induces an anomalous cyclonic circulation accompanied with enhanced westerlies impinging on the Patagonian Icefields, which in turn leads to increases in the precipitation and the accumulation over the icefields. Also, the Drake low is thermodynamically maintained by a core of cold air that tends to reduce the ablation. Years of relatively low SMB are associated with the opposite conditions. We found low dependence of the SMB on main atmospheric modes of variability (El Niño–Southern Oscillation, Southern Annular Mode), revealing a poor ability of the associated indices to reproduce the interannual variability of the SMB. Instead, this study highlights the Drake Passage as a key region that has the potential to influence the SMB variability of the Patagonian Icefields. [ABSTRACT FROM AUTHOR]

The El Niño‐Southern Oscillation (ENSO) is one of Earth's main modes of climate variability, having huge impacts on weather, agriculture, and people worldwide. Although these impacts and teleconnections have been studied for decades, the role of atmospheric transport is not completely understood. We analyze the atmospheric transport outgoing from the Equatorial Pacific with the Lagrangian particle dispersion model FLEXPART driven by reanalysis data. Our results demonstrate the interocean‐basin exchange via the atmosphere: anomalously energetic air from the ENSO region mainly remains within the Tropics and Subtropics, while more air is transported toward the east during El Niño. Transport of anomalous moist air can directly be linked to several observed teleconnections, for example, droughts in the Amazon Basin and precipitation in Southeastern U.S. during El Niño. These results show that atmospheric transport plays a role in several ENSO teleconnections. Plain Language Summary: The El Niño Southern Oscillation (ENSO) is a climate variability that is associated with changes in the climate state every 2–7 years. It occurs due to changes in the sea surface temperature (SST) in the Equatorial Pacific (EP) and causes shifts in the atmospheric circulation. Influences on weather, agriculture and thus the lives of many people worldwide makes understanding the role of the atmosphere important. In order to uncover the role of the atmosphere, we model the atmospheric transport with specialized computer code. We find that the air from the EP Ocean, where the largest anomalies in SSTs occur, is relatively warm when arriving over the Atlantic Ocean and releases its heat into the Ocean. Over South Central America, northern South America, and West Africa warmer and drier air is arriving, which leads to droughts associated with the ENSO. Over Mexico, North America's Gulf Coast and along the Gulf Stream wetter air is arriving, thus favoring precipitation during El Niño. Our results show that the transport of temperature and moisture anomalies from the EP via the atmosphere plays an important role for the weather conditions in several regions. Key Points: Transported air from the Equatorial Pacific (EP) shows significant anomalies in moisture and heat compared to its environmentThe transport of anomalously dry or wet air can be linked to several observed atmospheric teleconnections associated with El Niño Southern OscillationDeposition of excess energy into the Atlantic Ocean can directly be linked to energetic air from the EP [ABSTRACT FROM AUTHOR]

The South American Summer Monsoon (SASM) is the main driver of regional hydroclimate variability across tropical and subtropical South America. It is best recorded on paleoclimatic timescales by stable oxygen isotope proxies, which are more spatially representative of regional hydroclimate than proxies for local precipitation alone. Network studies of proxies that can isolate regional influences lend particular insight into various environmental characteristics that modulate hydroclimate, such as atmospheric circulation variability and changes in the regional energy budget as well as understanding the climate system sensitivity to external forcings. We extract the coherent modes of variability of the SASM over the last millennium (LM) using a Monte Carlo empirical orthogonal function (MCEOF) decomposition of 14 δ18 O proxy records and compare them with modes decomposed from isotope-enabled climate model data. The two leading modes reflect the isotopic variability associated with (1) thermodynamic changes driving the upper-tropospheric monsoon circulation (Bolivian High–Nordeste Low waveguide) and (2) the latitudinal displacement of the South Atlantic Convergence Zone (SACZ). The spatial characteristics of these modes appear to be robust features of the LM hydroclimate over South America and are reproduced both in the proxy data and in isotope-enabled climate models, regardless of the nature of the model-imposed external forcing. The proxy data document that the SASM was characterized by considerable temporal variability throughout the LM, with significant departures from the mean state during both the Medieval Climate Anomaly (MCA) and the Little Ice Age (LIA). Model analyses during these periods suggest that the local isotopic composition of precipitation is primarily a reflection of upstream rainout processes associated with monsoon convection. Model and proxy data both point to an intensification of the monsoon during the LIA over the central and western parts of tropical South America and indicate a displacement of the South Atlantic Convergence Zone (SACZ) to the southwest. These centennial-scale changes in monsoon intensity over the LM are underestimated in climate models, complicating the attribution of changes on these timescales to specific forcings and pointing toward areas of important model development. [ABSTRACT FROM AUTHOR]

Climate hazards associated with compound events (CEs) have lately received increasing attention over South America (SA) due to their potential risks and amplification of impacts. This work addressed the evaluation of different temperature‐ and precipitation‐based CE in SA considering the CORDEX‐CORE ensemble of regional climate models (RCMs) and their driving earth system models (ESMs) in the reference period 1981–2010 and the late 21st century (2070–2099), for the Representative Concentration Pathways (RCPs) 2.6 and 8.5 scenarios. The assessment focused on model performance for the individual events—heatwaves (HWs), Extreme rainfall (ER) days, and dry‐spells (DSs)—and their compound occurrence in terms of climatological frequency and duration. The spatial patterns of individual events were adequately reproduced by the RCMs, evidencing general overestimations in extreme precipitation intensities. In terms of CE, the frequencies of coincident HWs and DSs (sequential DSs and ER) were remarkable over central‐eastern Brazil and southern SA (southeastern SA). The main features of CE were generally well‐simulated by the RCMs, although they presented regional differences such as an underestimation of the maximum frequencies of these two CE in northeastern Brazil and southeastern SA, respectively. The high‐resolution information was generally in line with the larger‐scale driving ESMs. The climate change signal analysis generally showed robust future increases in CE frequency and duration in different areas of SA, as for coincident HWs and DSs (sequential DSs and ER) over northern SA and southern Brazil (southeastern SA). This was mostly consistent among the RCMs ensemble and notably strengthened in the worst‐case scenario (RCP 8.5). Key Points: Coincident heatwaves and dry‐spells (DSs) and sequential DSs and extreme rainfall are remarkable compound events (CEs) over South AmericaRegional climate models can reproduce the frequency and duration of CEs, but with some regional differencesCEs are generally expected to be more frequent in the late 21st century, particularly in the Representative Concentration Pathway 8.5 scenario [ABSTRACT FROM AUTHOR]

Climate model precipitation is the foremost input for hydrological models in climate change risk assessment. However, some aspects of precipitation (e.g., frequency, seasonality, and extremes) are usually not well represented by climate models, especially at the regional scale and in the tropics. In this study, we use a set of well‐established metrics to evaluate the marginal, temporal, and spatial aspects of CMIP5 and CMIP6 precipitation in Southern Brazil. This region is in the transition between tropical and subtropical climates with diverse rainfall generation mechanisms and complex topography. We compare the multi‐model‐ensemble mean (MME) and a constrained ensemble (CE) of CMIP5 and CMIP6 against a high‐resolution precipitation data grid. The constrained ensemble is obtained using a weighting approach that minimizes the difference between the simulated and observed cumulative distribution functions. We find that CMIP6 outperforms CMIP5 for most metrics, especially in the simulation of the seasonal cycle and the spatial distribution of precipitation. Simulated precipitation is more seasonal and more spatially dependent than the observations, with a dry bias characterized by lower precipitation amounts and higher consecutive dry days. Our analysis suggests that the models are not able to reproduce the transition between tropical and subtropical climates in this region as well as the passage of frontal systems. Future studies using CMIP6 should focus on those regional mechanisms of precipitation variability. [ABSTRACT FROM AUTHOR]

A multi-experiment ensemble is performed using the WRF (Weather Research and Forecasting) model at high spatial resolution (1 km) over the Antisana glacier region (Ecuador), during the year 2005. Our goal is to identify the best model configurations to simulate atmospheric processes at diurnal and seasonal scales. The model is able to reproduce the complex zonal gradient of precipitation between the wet Amazon and the drier inter-Andean region. The main precipitation biases are (i) an overestimation in the afternoon (up to 6 mm/day) in the Antisana region related to local surface circulation patterns and (ii) a nighttime overestimation (up to 20 mm/day) in the Andes-Amazon transition zone associated with the regional circulation. Changing the microphysics scheme and/or the cumulus scheme primarily affect nighttime processes, while changing the topography forcing and activating slope radiation and shading options mostly affects afternoon processes. An adequate choice of the model configuration allows a correct representation of the diurnal cycle of precipitation, and in particular: (i) the mid-level easterly regional flow, (ii) the local moisture transport along and across the valleys, and (iii) the orographic mountain waves on the Antisana summit. For this specific area and year, the best configuration retained defined as "dSRTM_LRad" shows nighttime (daytime) precipitation biases smaller than 2 mm/day (3 mm/day); it is based on non-smoothed SRTM digital elevation model (dSRTM), Lin Purdue microphysics (L), and slope and shading radiation options (Rad). This 1-km resolution configuration requires the activation of the cumulus scheme, that improves the regional nighttime convection induced by the easterly regional flow on the Amazon-Andes transition region. It allows also a realistic strengthening of the daytime upward moisture transport. This study demonstrates that in the Antisana region, 1 km is a resolution still too coarse to deactivate cumulus schemes for a correct representation of cloud convection. [ABSTRACT FROM AUTHOR]

Moisture evaporated from the land contributing to precipitation in a given area is known as precipitation recycling and needs to be accurately represented in climate models. The Amazon and Congo basins are reported to have the highest precipitation recycling rates globally, but model representation has not yet been assessed over these regions. We evaluated recycling over the Amazon and Congo in 45 Coupled Model Intercomparison Project Phase 6 models. Regional annual means from models and reanalyzes agreed well over both basins. Models captured seasonal variation in recycling over the Congo but there was a large‐scale underestimation of recycling during the Amazon dry‐to‐wet transition season relative to ERA5, caused by models underestimating Amazon evapotranspiration and overestimating incoming wind speed and associated water vapor imports. Both regions show robust declines in precipitation recycling over the next century under future climate‐change scenarios. Our results suggest models may underestimate impacts of deforestation on regional precipitation in the Amazon. Plain Language Summary: In the Amazon and Congo basins, much of the rain that falls to Earth is transferred back to the atmosphere through evaporation over tropical forests, providing essential moisture for further rainfall events downwind. This process of rainfall recycling, which is vital for sustaining the rainforest, is disrupted when forest is cut down. For researchers to understand how deforestation in the Amazon and Congo might impact the climate it is vital that climate models accurately represent the fraction of rain coming from recycled moisture. Our study found that models represented rainfall recycling relatively well in the Congo, but underestimate recycling in the Amazon dry‐to‐wet transition season. This is important because it could mean these models underpredict the influence of deforestation on climate in the Amazon. Key Points: This study quantifies, for the first time, precipitation recycling ratios over the Amazon and Congo Basins in Coupled Model Intercomparison Project Phase 6 modelsSeasonal recycling is well represented in the Congo but there is a large‐scale underestimation in the Amazon dry‐to‐wet transition seasonThese findings have implications for model representation of land‐use change impacts in the Amazon [ABSTRACT FROM AUTHOR]

Climate variability, as an element of uncertainty in water management, affects community, sectoral, and individual decision‐making. Long‐range prediction models are tools that offer the potential for integration and joint analysis with the hydrological, hydrodynamic, and management response of the socio‐ecological systems to which they are linked. The main objective of this article is to present a seasonal climate prediction model, the open‐source algorithm SIE‐Climate, whose application consists of three phases (exploration, development, and evaluation), and to describe its application to the Lake Sochagota socio‐ecological system (Paipa, Boyacá, Colombia). The K‐nearest neighbours method is used when defining a target matrix that represents and integrates macro‐ and micro‐climatic phenomena (Oceanic Niño Index, local temperature, and local rainfall) to identify periods of similar climatic behaviour. Considering a 1‐year horizon and management purposes the tool is calibrated and validated in periods with and without climatic anomalies (2000–2018), giving reliable adjustment results (RSME:4.86; R2: 0.95; PBIAS: −8.89%; EFF: 0.85). SIE‐Climate can be adapted to various contexts, variables of interest, and temporal and spatial scales, with an appropriate technological and computational cost for regional water management. [ABSTRACT FROM AUTHOR]

Understanding the regional impact of future climate change is one of the major global challenges of this century. This study investigated possible effects of climate change on malaria in West Africa in the near future (2006–2035) and the far future (2036–2065) under two representative concentration pathway (RCP) scenarios (RCP4.5 and RCP8.5), compared to an observed evaluation period (1981–2010). Projected rainfall and temperature were obtained from the coordinated regional downscaling experiment (CORDEX) simulations of the Rossby Centre Regional Atmospheric regional climate model (RCA4). The malaria model used is the Liverpool malaria model (LMM), a dynamical malaria model driven by daily time series of rainfall and temperature obtained from the CORDEX data. Our results highlight the unimodal shape of the malaria prevalence distribution, and the seasonal malaria transmission contrast is closely linked to the latitudinal variation of the rainfall. Projections showed that the mean annual malaria prevalence would decrease in both climatological periods under both RCPs but with a larger magnitude of decreasing under the RCP8.5. We found that the mean malaria prevalence for the reference period is greater than the projected prevalence for 6 of the 8 downscaled GCMs. The study enhances understanding of how malaria is impacted under RCP4.5 and RCP8.5 emission scenarios. These results indicate that the southern area of West Africa is at most risk of epidemics, and the malaria control programs need extra effort and help to make the best use of available resources by stakeholders. [ABSTRACT FROM AUTHOR]

Climate variability, as an element of uncertainty in water management, affects community, sectoral, and individual decision-making. Long-range prediction models are tools that offer the potential for integration and joint analysis with the hydrological, hydrodynamic, and management response of the socio-ecological systems to which they are linked. The main objective of this article is to present a seasonal climate prediction model, the open-source algorithm SIE-Climate, whose application consists of three phases (exploration, development, and evaluation), and to describe its application to the Lake Sochagota socio-ecological system (Paipa, Boyaca, Colombia). The K-nearest neighbours method is used when defining a target matrix that represents and integrates macro-and micro-climatic phenomena (Oceanic Nino Index, local temperature, and local rainfall) to identify periods of similar climatic behaviour. Considering a 1-year horizon and management purposes the tool is calibrated and validated in periods with and without climatic anomalies (2000-2018), giving reliable adjustment results (RSME:4.86; R2: 0.95; PBIAS: -8.89%; EFF: 0.85). SIE-Climate can be adapted to various contexts, variables of interest, and temporal and spatial scales, with an appropriate technological and computational cost for regional water management. [ABSTRACT FROM AUTHOR]

In this study the simulated extreme and moderate El Niño events (e.g., frequency of occurrence and spatial variability) are characterized and the historical teleconnections on precipitation and temperature climate extremes in South America are analysed. Future projected changes in these teleconnections under a global warming context are also addressed. For this purpose a set of 10 Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCMs) simulations derived from three experiments (historical, RCP4.5 and RCP8.5) are considered. The study period is 1916–2100. As El Niño is seasonally phase‐locked, peaking in late austral spring and summer, the present analysis is carried out for these two seasons, as well as annually. Results indicate that extreme El Niño events are projected to double their occurrence considering RCP4.5 and RCP8.5, while a less pronounced increase is projected for moderate El Niño events. Most of these events show a similar pattern of sea surface temperature (SST) anomalies: a positive centre in the central equatorial Pacific that extends eastward to the coast of America. In a global warming context, the resemblance between these events may decrease. Overall, the spatial structure of the impacts of El Niño are expected to be similar between moderate and extreme events, although in some cases (regions and seasons), a higher intensity is observed considering the events characterized as extreme El Niños rather than moderate ones. As extreme El Niño events are expected to be more frequent in the future, the impacts on climate extremes as well as the associated socioeconomic impacts would also take place much more frequently too. [ABSTRACT FROM AUTHOR]

The Amazon forest enhances precipitation levels regionally as trees take up water from the soil and release it back into the atmosphere through transpiration. Therefore, land‐use changes in the Amazon affect precipitation patterns but to what extent remains unclear. Recent studies used hydrological and atmospheric models to estimate the contribution of tree transpiration to precipitation but assumed that precipitation decreases proportionally to the transpired portion of atmospheric moisture. Here, we relaxed this assumption by, first, relating observed hourly precipitation levels to atmospheric column water vapor in a relatively flat study area encompassing a large part of the Amazon. We found that the effect of column water vapor on hourly precipitation was strongly nonlinear, showing a steep increase in precipitation above a column water vapor content of around 60 mm. Next, we used published atmospheric trajectories of moisture from tree transpiration across the whole Amazon to estimate the transpiration component in column water vapor in our study area. Finally, we estimated precipitation reductions for column water vapor levels without this transpired moisture, given the nonlinear relationship we found. Although loss of tree transpiration from the Amazon causes a 13% drop in column water vapor, we found that it could result in a 55%–70% decrease in precipitation annually. Consequences of this nonlinearity might be twofold: although the effects of deforestation may be underestimated, it also implies that forest restoration may be more effective for precipitation enhancement than previously assumed. [ABSTRACT FROM AUTHOR]

Climate teleconnections are essential for the verification of valuable precipitation forecasts generated by global climate models (GCMs). This paper develops a novel approach to attributing correlation skill of dynamical GCM forecasts to statistical El Niño–Southern Oscillation (ENSO) teleconnection by using the coefficient of determination (R2). Specifically, observed precipitation is respectively regressed against GCM forecasts, Niño3.4 and both of them, and then the intersection operation is implemented to quantify the overlapping R2 for GCM forecasts and Niño3.4. The significance of overlapping R2 and the sign of ENSO teleconnection facilitate three cases of attribution, i.e., significantly positive anomaly correlation attributable to positive ENSO teleconnection, attributable to negative ENSO teleconnection and not attributable to ENSO teleconnection. A case study is devised for the Climate Forecast System version 2 (CFSv2) seasonal forecasts of global precipitation. For grid cells around the world, the ratio of significantly positive anomaly correlation attributable to positive (negative) ENSO teleconnection is respectively 10.8 % (11.7 %) in December–January–February (DJF), 7.1 % (7.3 %) in March–April–May (MAM), 6.3 % (7.4 %) in June–July–August (JJA) and 7.0 % (14.3 %) in September–October–November (SON). The results not only confirm the prominent contributions of ENSO teleconnection to GCM forecasts, but also present spatial plots of regions where significantly positive anomaly correlation is subject to positive ENSO teleconnection, negative ENSO teleconnection and teleconnections other than ENSO. Overall, the proposed attribution approach can serve as an effective tool to investigate the sources of predictability for GCM seasonal forecasts of global precipitation. [ABSTRACT FROM AUTHOR]

Convection observed in the OTREC field program in the tropical east Pacific and southwest Caribbean is simulated using a cloud‐resolving model employing the weak temperature gradient approximation. Simulations are made using reference profiles derived from three‐dimensional variational analyses of dropsonde data selected for different ranges of saturation fraction, a kind of column relative humidity. For each of these humidity ranges, two simulations are performed, one with ventilation of the model domain by the ambient wind (a new model feature) and one without this ventilation. The model results using ventilation are much closer to observation than those without ventilation, especially for drier environments. These results have strong implications for the distribution of ITCZ convection in the east Pacific and for the construction of cumulus parameterizations. Plain Language Summary: Weak temperature gradient (WTG) modeling of deep atmospheric convection enables the realistic interaction of the modeled convection with the surrounding environment in the Tropics. A new model is presented here which takes into account the flow of surrounding environmental air through the convective domain in a more realistic fashion than in previous WTG models. We show that such "ventilation" is needed for these models to reproduce the observed characteristics of real convection in the tropical east Pacific and the southwest Caribbean. Global weather and climate models would likely benefit from incorporating such ventilation in their idealized treatments of convection. Key Points: A new weak temperature gradient (WTG) convective model includes shear‐induced ventilation by dry environmental airWTG modeling of convection produces better agreement with observations when ventilation is turned onIncluding the effects of ventilation on convection may be needed in weather and climate models [ABSTRACT FROM AUTHOR]

The effects of climate change projected for 2050 to 2079 relative to the 1968–2014 reference period were evaluated using 39 CMIP5 models under the RCP8.5 emissions scenario in the Guayas River basin. The monthly normalized precipitation index (SPI) was used in this study to assess the impact of climate change for wet events and droughts from a meteorological perspective. The GR2M model was used to project changes in the streamflow of the Daule River. The climate projection was based on the four rigorously selected models to represent the climate of the study area. On average, an increase in temperature (~2 °C) and precipitation (~6%) is expected. A 7% increase in precipitation would result in a 10% increase in streamflow for flood periods, while an 8% decrease in precipitation could result in approximately a 60% reduction in flow for dry periods. The analysis of droughts shows that they will be more frequent and prolonged in the highlands (Andes) and the middle part of the basin. In the future, wet periods will be less frequent but of greater duration and intensity on the Ecuadorian coast. These results point to future problems such as water deficit in the dry season but also increased streamflow for floods during the wet season. This information should be taken into account in designing strategies for adaptation to climate change. [ABSTRACT FROM AUTHOR]

This study analyzes the variability of the Choco jet (CJ) and Caribbean low-level jet (CLLJ) with consideration of the simultaneous Pacific interdecadal oscillation (PDO) and Atlantic multidecadal oscillation (AMO) low-frequency mean states and their effects on the atmospheric circulation and rainfall in northwestern South America and Central America for the 1900–2015 period, during the seasons with the highest intensities of the CJ (September–November (SON)) and the CLLJ (June–August). Variations in the sea surface temperature (SST) anomaly positioning in the eastern Pacific, tropical North Atlantic (TNA)/Caribbean Sea during different mean states restrict the anomalous circulation, and, consequently, the intensity of the CJ and CLLJ. During the warm AMO (WAMO)/cold PDO (CPDO), the SST gradient from the tropical Pacific into the TNA, accompanied by a cyclonic circulation near the east coast of the Americas, intensifies the west–east circulation in the region, strengthening the CJ and weakening the CLLJ during SON such that rainfall increases over Colombia, Central America and in adjacent oceans. During the cold AMO (CAMO)/warm PDO (WPDO) phase, a relative east/west SST gradient occurs in TNA, consistent with a cyclonic circulation in western TNA, establishing an anomalous southwest–northwestward circulation from the eastern Pacific into the Caribbean basin, forming a well-configured CJ, increasing precipitation over Central America and its adjacent oceans. For the CLLJ, during CAMO phases, the anticyclonic circulations extended over most of the TNA favor its intensification from 30° W to the Caribbean Sea. In contrast, during WAMO, the cyclonic circulation near the east coast of the United States restricts its intensification to the Caribbean Sea region. To the best of our knowledge, the results presented here are new and might be useful in atmospheric modeling and extreme event studies. [ABSTRACT FROM AUTHOR]

This paper examines the relative role of the Indian Ocean basin-wide (IOBW) mode and El Niño–Southern Oscillation (ENSO) in the atmospheric circulation and rainfall interannual variations over South America (SA) during southern summer of the 1951‒2016 period. The effects of the warm IOBW and El Niño (EN) events, and of the cold IOBW and La Niña (LN) events are examined using partial correlations. The ENSO and IOBW modes, through the associated large-scale and regional anomalous circulation patterns, induce contrasting effects on the rainfall in northeastern SA. The EN without the warm IOBW effect induces anomalously dry conditions over eastern Amazon and part of northeastern Brazil (NEB) through anomalous sinking motions of the EN-related anomalous Walker and Hadley cells and strong moisture divergence associated with a vigorous anticyclone over tropical South Atlantic (TSA) and SA. The warm IOBW without the EN effect induces anomalously wet conditions in NEB, which is marginally related to the anomalous Walker and Hadley cells but is modulated by an anticyclone over SA between the equator and 20° S, and a cyclone in the southwestern Atlantic between 20° S and 40° S. The results here might be relevant for climate monitoring and modeling studies. [ABSTRACT FROM AUTHOR]