El Niño–Southern Oscillation (ENSO) and the Gulf of Mexico (GoM) influence winter tornado variability and significant tornado (EF2+, where EF is the enhanced Fujita scale) environments. Increases occur in the probability of a significant tornado environment from the southern Great Plains to the Midwest during La Niña, and across the southern contiguous United States (CONUS) during El Niño. Winter significant tornado environments are absent across Florida, Georgia, and the coastal Carolinas during moderate-to-strong La Niña events. Jet stream modulation by ENSO contributes to higher tornado totals during El Niño in December and La Niña in January, especially when simultaneous with a warm GoM. ENSO-neutral phases yield fewer and weaker tornadoes, but proximity to warm GoM climate features can enhance the probability of a significant tornado environment. ENSO intensity matters; stronger ENSO phases generate increases in tornado frequency and the probability of a significant tornado environment, but are characterized by large variance, in which very strong El Niño and La Niña events can produce unfavorable tornado climatological states. This study suggests that it is a feasible undertaking to expand spring seasonal and subseasonal tornado prediction efforts to encompass the winter season, which is of importance given the notable threat posed by winter tornadoes. Significant tornadoes account for 95% of tornado fatalities and winter tornadoes are rated significant more frequently than during other seasons.

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Dinoflagellates of the genus Ceratium are predominantly found in marine environments, with a few species in inland waters. Over the last decades, the freshwater species Ceratium hirundinella and Ceratium furcoides have colonized and invaded several South American basins. The purpose of this study was to create a distribution model for the invasive dinoflagellate C. furcoides in South America in order to further investigate the basins at potential risk, as well as the environmental conditions that influence its expansion. This species is known to develop blooms due to its mobility, resistance to sedimentation, and optimized use of resources. Although nontoxic, blooms of the species cause many problems to both the natural ecosystems and water users. Potential distribution was predicted by using a maximum entropy algorithm (MaxEnt). Model was run with 101 occurrences obtained from the scientific literature, and climatic, hydrological and topographic variables. The developed model had a very good performance for the study area. The most susceptible areas identified were mainly concentrated in the basins between southeastern Brazil and northeastern Argentina. Besides already affected regions, new potentially suitable areas were identified in temperate regions of South America. The information generated here will be useful for authorities responsible for water and watershed management to monitor the spread of this species and address problems related to its establishment in new environments.

Different features of the Gulf of Mexico (GOM), such as the Loop Current and warm‐core rings, are found to influence monthly‐to‐seasonal severe weather occurrence in different regions of the United States (U.S.). The warmer (cooler) the GOM sea surface temperatures, the more (less) hail and tornadoes occur during March–May over the southern U.S. This pattern is reflected physically in boundary layer specific humidity and mixed‐layer convective available potential energy, two large‐scale atmospheric conditions favorable for severe weather occurrence. This relationship is complicated by interactions between the GOM and El Niño–Southern Oscillation (ENSO) but persists when analyzing ENSO neutral conditions. This suggests that the GOM can influence hail and tornado occurrence and provides another source of regional predictability for seasonal severe weather.

Abstract. Extreme weather events have been demonstrated to be increasing in frequency and intensity across the globe and are anticipated to increase further with projected changes in climate. Solar climate intervention strategies, specifically stratospheric aerosol injection (SAI), have the potential to minimize some of the impacts of a changing climate while more robust reductions in greenhouse gas emissions take effect. However, to date little attention has been paid to the possible responses of extreme weather and climate events under climate intervention scenarios. We present an analysis of 16 extreme surface temperature and precipitation indices, as well as associated vegetation responses, applied to the Geoengineering Large Ensemble (GLENS). GLENS is an ensemble of simulations performed with the Community Earth System Model (CESM1) wherein SAI is simulated to offset the warming produced by a high-emission scenario throughout the 21st century, maintaining surface temperatures at 2020 levels. GLENS is generally successful at maintaining global mean temperature near 2020 levels; however, it does not completely offset some of the projected warming in northern latitudes. Some regions are also projected to cool substantially in comparison to the present day, with the greatest decreases in daytime temperatures. The differential warming–cooling also translates to fewer very hot days but more very hot nights during the summer and fewer very cold days or nights compared to the current day. Extreme precipitation patterns, for the most part, are projected to reduce in intensity in areas that are wet in the current climate and increase in intensity in dry areas. We also find that the distribution of daily precipitation becomes more consistent with more days with light rain and fewer very intense events than currently occur. In many regions there is a reduction in the persistence of long dry and wet spells compared to present day. However, asymmetry in the night and day temperatures, together with changes in cloud cover and vegetative responses, could exacerbate drying in regions that are already sensitive to drought. Overall, our results suggest that while SAI may ameliorate some of the extreme weather hazards produced by global warming, it would also present some significant differences in the distribution of climate extremes compared to the present day.

Long‐term trends suggest shifts toward earlier tornado season peaks, and yet fail to examine the role of year‐to‐year climate variability. Here, El Niño–Southern Oscillation phase is demonstrated to influence annual cycle characteristics of United States tornadoes. Observations and favorable environments show substantial modification of the peak spatial distribution and the temporal onset of tornado occurrence. La Niña produces an earlier annual peak probability by 1.5–2 weeks, with a higher overall fraction of events in March and April. In contrast, El Niño leads to a week delay in the maximum probability and enhances a second peak in the fall months. Consequently, this suggests that climate change is not the sole driver of changes to seasonal onset and peak, and climate variability plays an important role in modulating the annual cycle.

Many summer fires in Valencia are enhanced by the abundance of maquis. Nevertheless, fire field studies on the soil temperature–time curves under summer conditions with controlled amount and structure of fuel are scarce. Experimental summer fires were conducted to analyse the influence of the fuel load and the fuel structure on the soil temperature-time profiles. The increase of fuel load from 2 to 4 kg m–2 increased the net radiant heat per unit area (5691 to 11263 kJ m–2), the total duration of heat (190 to 396 min) and the duration of temperatures greater than 100ºC (19.8 to 35.9 min) whereas the peak temperature increased 100ºC (from 416ºC to 516ºC). Variations of fuel height from 1.5 to 0.75 m and bulk density from 2 to 4 kg m–3 respectively, increased net radiant heat per unit area, Hp/a (6510 to 10 444 kJ m–2), ttotal (219 to 375 min), and t>100ºC (9.7 to 36. 1 min) whereas Tmax increased 40ºC (446 to 486ºC). At plot scale, fire intensity and severity will increase with the fuel load. At plant scale, more degradation will occur in the soil patches with higher bulk density, mainly because an increased duration of high temperatures in soil. Fuel amount and structure are then key factors in maquis fires since they will determine the post-fire patchiness of soil conditions and plant recovery.

Abstract. The potential for multiyear prediction of impactful Earth system change remains relatively underexplored compared to shorter (subseasonal to seasonal) and longer (decadal) timescales. In this study, we introduce a new initialized prediction system using the Community Earth System Model version 2 (CESM2) that is specifically designed to probe potential and actual prediction skill at lead times ranging from 1 month out to 2 years. The Seasonal-to-Multiyear Large Ensemble (SMYLE) consists of a collection of 2-year-long hindcast simulations, with four initializations per year from 1970 to 2019 and an ensemble size of 20. A full suite of output is available for exploring near-term predictability of all Earth system components represented in CESM2. We show that SMYLE skill for El Niño–Southern Oscillation is competitive with other prominent seasonal prediction systems, with correlations exceeding 0.5 beyond a lead time of 12 months. A broad overview of prediction skill reveals varying degrees of potential for useful multiyear predictions of seasonal anomalies in the atmosphere, ocean, land, and sea ice. The SMYLE dataset, experimental design, model, initial conditions, and associated analysis tools are all publicly available, providing a foundation for research on multiyear prediction of environmental change by the wider community.