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Abstract In wildfire-prone coastal Santa Barbara, California, downslope winds observed on the southern slopes of the east-west oriented Santa Ynez Mountains are known as Sundowner winds (or Sundowners). One important feature of Sundowners is the remarkable spatial and temporal variability in lee slope jet characteristics. Besides the intensity of the flow approaching the mountain range, the acceleration of the lee slope jet can be influenced by reflected gravity waves associated with one or more of the following mechanisms: a self-induced critical level, an inversion close to mountaintop, and the presence of a mean-state critical level (MSCL). The relative contribution of these mechanisms to the enhancement of Sundowners is yet unknown. This study uses 32-yr simulations (hourly, 1-km grid spacing) complemented with observations collected during the Sundowner Winds Experiment (SWEX) to better quantify the relative contribution of these mechanisms and to quantify the importance of MSCLs. We show that when an MSCL is present below 5 km, less atmospheric forcing is necessary to attain similar lee-slope jet strengths compared to when MSCLs are absent or above 5 km. This was evidenced from simulations and verified with observations. Although MSCLs during Sundowners occur year-round, their relative frequency increases in summer, when temperatures are high and fuels are dry, enhancing wildfire risk. Properly identifying these processes contributes to improved understanding and predictability of Sundowners and many other hazardous downslope windstorms in coastal environments. 

Abstract The hydrological cycle in South America during austral summer, including extreme precipitation and floods, is significantly influenced by northerly low-level jets (LLJs) along the eastern Andes. These synoptic weather events have been associated with three different types of LLJs (Central, Northern, and Andes) and are sensitive to remote large-scale forcings. This study investigates how tropical forcings related to El Niño/Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) regulate the duration and frequency of each LLJ type and their impacts on extreme precipitation. Our analysis reveals that ENSO and PDO are important in driving the variability of LLJs over the past 65 years. Specifically, the Central LLJ type is more prevalent during El Niño and Warm/Neutral PDO phases, leading to heightened extreme precipitation in southern South America. Conversely, La Niña years during Cold PDO phases tend to favor the Northern and Andes LLJs, which are associated with increased precipitation extremes in the western Amazon and southeastern South America. Central and Andes LLJs tend to persist longer during these favored conditions, causing more pronounced precipitation events in the areas under their influence. This study enhances our understanding of the influence of large-scale atmospheric forcings on the regional precipitation dynamics in South America. 

Abstract Forest fire frequency, extent, and severity have rapidly increased in recent decades across the western United States (US) due to climate change and suppression‐oriented wildfire management. Fuels reduction treatments are an increasingly popular management tool, as evidenced by California's plan to treat 1 million acres annually by 2050. However, the aggregate efficacy of fuels treatments in dry forests at regional and multi‐decadal scales is unknown. We develop a novel fuels treatment module within a coupled dynamic vegetation and fire model to study the effects of dead biomass removal from forests in the Sierra Nevada region of California. We ask how annual treatment extent, stand‐level treatment intensiveness, and spatial treatment placement alter fire severity and live carbon loss. We find that a ∼30% reduction in stand‐replacing fire was achieved under our baseline treatment scenario of 1,000 km² year⁻¹after a 100‐year treatment period. Prioritizing the most fuel‐heavy stands based on precise fuel distributions yielded cumulative reductions in pyrogenic stand‐replacement of up to 50%. Both removing constraints on treatment location due to remoteness, topography, and management jurisdiction and prioritizing the most fuel‐heavy stands yielded the highest stand‐replacement rate reduction of ∼90%. Even treatments that succeeded in lowering aggregate fire severity often took multiple decades to yield measurable effects, and avoided live carbon loss remained negligible across scenarios. Our results suggest that strategically placed fuels treatments are a promising tool for controlling forest fire severity at regional, multi‐decadal scales, but may be less effective for mitigating live carbon losses. 

Abstract The presence of an aerosol layer in the upper troposphere/lower stratosphere (UT/LS) in South America was identified with the Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2). This layer, which we shall refer to as the South American tropopause aerosol layer (SATAL), was identified over the Amazon basin at altitudes between 11 and 14 km. It exhibits a seasonal behavior similar to the Asian tropopause aerosol layer (ATAL) and the North American tropopause aerosol layer (NATAL). The SATAL is observed from October to March, coinciding with the presence of the South American monsoon. It forms first in the eastern Amazon basin in October, then moves to the southern Amazon, where it weakens in December–January and finally dissipates in February–March. We hypothesize that two main factors influence the SATAL formation in the UT/LS: 1) the source of aerosols from Africa and 2) the updraft mass flux from deep convective systems during the active phase of the South American monsoon system that transports aerosols to the UT/LS. Further satellite observations of aerosols and field campaigns are needed to provide useful information to find the origin and composition of the aerosols in the UT/LS during the South American monsoon. 

Abstract Northerly low-level jets (LLJ) along the eastern Andes are important conduits of moisture transport and play central roles in modulating precipitation in South America. This study further investigates the variability of the LLJ during extended austral summers. A new method characterizes the spatial extent of the LLJ and finds four distinct types: Central, Northern, Andes and Peru. We show the existence of specific evolutions such that the LLJ may initiate in the central region, expands along the Andes and terminates in the northern region. Conversely, the LLJ may propagate from north-to-south. The spatiotemporal evolution of the LLJ is remotely forced by Rossby wave trains propagating from the Pacific Ocean towards South America, and the different phases of the wave trains favor the occurrences of Central, Northern or Andes types. Occurrences of Central and Northern types are more frequent in El Niño and La Niña years, respectively. The persistence of precipitation is shown to be directly related to the persistence of the LLJ. Lastly, the Madden-Julian Oscillation plays an important role in generating wave trains modulating the frequency of LLJ, especially the Central type. 

Surface winds over California can compound fire risk during autumn, yet their long-term trends in the face of decadal warming are less clear compared to other climate variables like temperature, drought, and snowmelt. To determine where and how surface winds are changing most, this article uses multiple reanalyses and Remote Automated Weather Stations (RAWS) to calculate autumn 10 m wind speed trends during 1979–2020. Reanalysis trends show statistically significant increases in autumn night-time easterlies on the western slopes of the Sierra Nevada. Although downslope windstorms are frequent to this region, trends instead appear to result from elevated gradients in warming between California and the interior continent. The result is a sharper horizontal temperature gradient over the Sierra crest and adjacent free atmosphere above the foothills, strengthening the climatological nocturnal katabatic wind. While RAWS records show broad agreement, their trend is likely influenced by year-to-year changes in the number of observations. 

The Brazilian Amazon provides important hydrological cycle functions, including precipitation regimes that bring water to the people and environment and are critical to moisture recycling and transport, and represents an important variable for climate models to simulate accurately. This paper evaluates the performance of 13 Coupled Model Intercomparison Project Phase 6 (CMIP6) models. This is done by discussing results from spatial pattern mapping, Taylor diagram analysis and Taylor skill score, annual climatology comparison, cumulative distribution analysis, and empirical orthogonal function (EOF) analysis. Precipitation analysis shows: (1) This region displays higher rainfall in the north-northwest and drier conditions in the south. Models tend to underestimate northern values or overestimate the central to northwest averages. (2) The southern Amazon has a more defined dry season (June, July, and August) and wet season (December, January, and February) and models simulate this well. The northern Amazon dry season tends to occur in August, September, and October and the wet season occurs in March, April, and May, and models are not able to capture the climatology as well. Models tend to produce too much rainfall at the start of the wet season and tend to either over- or under-estimate the dry season, although ensemble means typically display the overall pattern more precisely. (3) Models struggle to capture extreme values of precipitation except when precipitation values are close to 0. (4) EOF analysis shows that models capture the dominant mode of variability, which was the annual cycle or South American Monsoon System. (5) When all evaluation metrics are considered, the models that perform best are CESM2, MIROC6, MRIESM20, SAM0UNICON, and the ensemble mean. This paper supports research in determining the most up-to-date CMIP6 model performance of precipitation regime for 1981–2014 for the Brazilian Amazon. Results will aid in understanding future projections of precipitation for the selected subset of global climate models and allow scientists to construct reliable model ensembles, as precipitation plays a role in many sectors of the economy, including the ecosystem, agriculture, energy, and water security. 

Rainfall in the Amazon is influenced by atmospheric circulation dynamics on multiple spatiotemporal scales. Anthropogenic influences such as deforestation, land-use changes, and global climate change are also critical factors in determining rainfall in South America. Modeling studies have projected a drier climate with the ongoing deforestation in the Amazon, but observational evaluation of the variability of rainfall and deforestation patterns has been limited. This study analyzes spatiotemporal trends in rainfall between 1981 and 2020 and relationships with deforestation age in the Brazilian Legal Amazon (BLA). An improved rainfall dataset is derived by calibrating the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data with observations from a rain gauge network in the BLA. Trend analysis is employed to identify significant changes in precipitation over the BLA. Satellite-based land cover data Mapbiomas and ET datasets are used to evaluate similar trends. While large spatial variability is observed, the results show coherent relationships between negative dry-season rainfall trends and old-age deforested areas. Deforestation aged up to a decade enhanced rainfall and older deforested regions have reduced rainfall during the dry season. These results suggest substantial changes in the hydroclimate of the BLA and increased vulnerability to future land cover change.