استكشف المجموعة الواسعة من العناوين المتاحة.

Novel high-resolution convection-permitting regional climate simulations over the US employing the pseudo-global warming approach are used to investigate changes in the convective population and thermodynamic environments in a future climate. Two continuous 13-year simulations were conducted using (1) ERA-Interim reanalysis and (2) ERA-Interim reanalysis plus a climate perturbation for the RCP8.5 scenario. The simulations adequately reproduce the observed precipitation diurnal cycle, indicating that they capture organized and propagating convection that most climate models cannot adequately represent. This study shows that weak to moderate convection will decrease and strong convection will increase in frequency in a future climate. Analysis of the thermodynamic environments supporting convection shows that both convective available potential energy (CAPE) and convective inhibition (CIN) increase downstream of the Rockies in a future climate. Previous studies suggest that CAPE will increase in a warming climate, however a corresponding increase in CIN acts as a balancing force to shift the convective population by suppressing weak to moderate convection and provides an environment where CAPE can build to extreme levels that may result in more frequent severe convection. An idealized investigation of fundamental changes in the thermodynamic environment was conducted by shifting a standard atmospheric profile by ± 5 °C. When temperature is increased, both CAPE and CIN increase in magnitude, while the opposite is true for decreased temperatures. Thus, even in the absence of synoptic and mesoscale variations, a warmer climate will provide more CAPE and CIN that will shift the convective population, likely impacting water and energy budgets on Earth.

Effective locomotion in nature happens by transitioning across multiple modes (e.g., walk, run, climb). Despite this, far more mechanistic understanding of terrestrial locomotion has been on how to generate and stabilize around near–steady-state movement in a single mode. We still know little about how locomotor transitions emerge from physical interaction with complex terrain. Consequently, robots largely rely on geometric maps to avoid obstacles, not traverse them. Recent studies revealed that locomotor transitions in complex three-dimensional (3D) terrain occur probabilistically via multiple pathways. Here, we show that an energy landscape approach elucidates the underlying physical principles. We discovered that locomotor transitions of animals and robots self-propelled through complex 3D terrain correspond to barrier-crossing transitions on a potential energy landscape. Locomotor modes are attracted to landscape basins separated by potential energy barriers. Kinetic energy fluctuation from oscillatory self-propulsion helps the system stochastically escape from one basin and reach another to make transitions. Escape is more likely toward lower barrier direction. These principles are surprisingly similar to those of near-equilibrium, microscopic systems. Analogous to free-energy landscapes for multipathway protein folding transitions, our energy landscape approach from first principles is the beginning of a statistical physics theory of multipathway locomotor transitions in complex terrain. This will not only help understand how the organization of animal behavior emerges from multiscale interactions between their neural and mechanical systems and the physical environment, but also guide robot design, control, and planning over the large, intractable locomotor-terrain parameter space to generate robust locomotor transitions through the real world.

Mesoscale convective systems (MCSs) are frequently observed over the U.S. Great Plains during boreal spring and summer. Here, four types of synoptically favorable environments for spring MCSs and two types each of synoptically favorable and unfavorable environments for summer MCSs are identified using selforganizing maps (SOMs) with inputs from observational data. During spring, frontal systems providing a lifting mechanism and an enhanced Great Plains low-level jet (GPLLJ) providing anomalous moisture are important features identified by SOM analysis for creating favorable dynamical and thermodynamic environments for MCS development. During summer, the composite MCS environment shows small positive convective available potential energy (CAPE) and convective inhibition (CIN) anomalies, which are in stark contrast with the large positive CAPE and negative CIN anomalies in spring. This contrast suggests that summer convection may occur even with weak large-scale dynamical and thermodynamic perturbations so MCSs may be inherently less predictable in summer. The two synoptically favorable environments identified in summer have frontal characteristics and an enhanced GPLLJ, but both shift north compared to spring. The two synoptically unfavorable environments feature enhanced upper-level ridges, but differ in the strength of the GPLLJ. In both seasons, MCS precipitation amount, area, and rate are much larger in the frontal-related MCSs than in nonfrontal MCSs. Alarge-scale index constructed using pattern correlation between large-scale environments and the synoptically favorable SOM types is found to be skillful for estimating MCS number, precipitation rate, and area in spring, but its explanatory power decreases significantly in summer. The low predictability of summer MCSs deserves further investigation in the future.

Abstract Studies exploring long-term energy system transitions rely on resource cost-supply curves derived from estimates of renewable energy (RE) potentials to generate wind and solar power projections. However, estimates of RE potentials are characterized by large uncertainties stemming from methodological assumptions that vary across studies, including factors such as the suitability of land and the performance and configuration of technology. Based on a synthesis of modeling approaches and parameter values used in prior studies, we explore the implications of these uncertain assumptions for onshore wind and solar photovoltaic electricity generation projections globally using the Global Change Analysis Model. We show that variability in parametric assumptions related to land use (e.g. land suitability) are responsible for the most substantial uncertainty in both wind and solar generation projections. Additionally, assumptions about the average turbine installation density and turbine technology are responsible for substantial uncertainty in wind generation projections. Under scenarios that account for climate impacts on wind and solar energy, we find that these parametric uncertainties are far more significant than those emerging from differences in climate models and scenarios in a global assessment, but uncertainty surrounding climate impacts (across models and scenarios) have significant effects regionally, especially for wind. Our analysis suggests the need for studies focusing on long-term energy system transitions to account for this uncertainty.

Atmospheric convective available potential energy (CAPE) is expected to increase under greenhouse gas–induced global warming, but a recent regional study also suggests enhanced convective inhibition (CIN) over land although its cause is not well understood. In this study, a global climate model is first evaluated by comparing its CAPE and CIN with reanalysis data, and then their future changes and the underlying causes are examined. The climate model reasonably captures the present-day CAPE and CIN patterns seen in the reanalysis, and projects increased CAPE almost everywhere and stronger CIN over most land under global warming. Over land, the cases or times with medium to strong CAPE or CIN would increase while cases with weak CAPE or CIN would decrease, leading to an overall strengthening in their mean values. These projected changes are confirmed by convection-permitting 4-km model simulations over the United States. The CAPE increase results mainly from increased low-level specific humidity, which leads to more latent heating and buoyancy for a lifted parcel above the level of free convection (LFC) and also a higher level of neutral buoyancy. The enhanced CIN over most land results mainly from reduced low-level relative humidity (RH), which leads to a higher lifting condensation level and a higher LFC and thus more negative buoyancy. Over tropical oceans, the near-surface RH increases slightly, leading to slight weakening of CIN. Over the subtropical eastern Pacific and Atlantic Ocean, the impact of reduced low-level atmospheric lapse rates overshadows the effect of increased specific humidity, leading to decreased CAPE.

Lightning is an indicator and a driver of climate change. Here, using satellite observations of lightning flash rate and ERA5 reanalysis, we find that the spatial pattern of summer lightning over northern circumpolar regions exhibits a strong positive relationship with the product of convective available potential energy (CAPE) and precipitation. Applying this relationship to Climate Model Intercomparison Project Phase 5 climate projections for a high-emissions scenario (RCP8.5) shows an increase in CAPE (86 ± 22%) and precipitation (17 ± 2%) in areas underlain by permafrost, causing summer lightning to increase by 112 ± 38% by the end of the century (2081–2100). Future flash rates at the northern treeline are comparable to current levels 480 km to the south in boreal forests. We hypothesize that lightning increases may induce a fire–vegetation feedback whereby more burning in Arctic tundra expedites the northward migration of boreal trees, with the potential to accelerate the positive feedback associated with permafrost soil carbon release. Changes in lightning activity are uncertain under climate change. The authors project that summer lightning in the Arctic is likely to more than double by the end of the century, with implications for lightning-strike tundra wildfires and associated carbon release from permafrost.

Abstract Observed proximity soundings from Europe are used to highlight how well environmental parameters discriminate different kind of severe thunderstorm hazards. In addition, the skill of parameters in predicting lightning and waterspouts is also tested. The research area concentrates on central and western European countries and the years 2009–15. In total, 45 677 soundings are analyzed including 169 associated with extremely severe thunderstorms, 1754 with severe thunderstorms, 8361 with nonsevere thunderstorms, and 35 393 cases with nonzero convective available potential energy (CAPE) that had no thunderstorms. Results indicate that the occurrence of lightning is mainly a function of CAPE and is more likely when the temperature of the equilibrium level drops below −10°C. The probability for large hail is maximized with high values of boundary layer moisture, steep mid- and low-level lapse rates, and high lifting condensation level. The size of hail is mainly dependent on the deep layer shear (DLS) in a moderate to high CAPE environment. The likelihood of tornadoes increases along with increasing CAPE, DLS, and 0–1-km storm-relative helicity. Severe wind events are the most common in high vertical wind shear and steep low-level lapse rates. The probability for waterspouts is maximized in weak vertical wind shear and steep low-level lapse rates. Wind shear in the 0–3-km layer is the best at distinguishing between severe and extremely severe thunderstorms producing tornadoes and convective wind gusts. A parameter WMAXSHEAR multiplying square root of 2 times CAPE (WMAX) and DLS turned out to be the best in distinguishing between nonsevere and severe thunderstorms, and for assessing the severity of convective phenomena.

Abstract Lasting updrafts are necessary to produce severe hail; conventional wisdom suggests that extremely large hailstones require updrafts of commensurate strength. Because updraft strength is largely controlled by convective available potential energy (CAPE), one would expect environments with larger CAPE to be conducive to storms producing larger hail. By systematically varying CAPE in a horizontally homogeneous initial environment, we simulate hail production in high-shear, high-instability supercell storms using Cloud Model 1 and a detailed 3D hail growth trajectory model. Our results suggest that CAPE modulates the updraft’s strength, width, and horizontal wind field, as well as the liquid water content along hailstones’ trajectories, all of which have a significant impact on final hail sizes. In particular, hail sizes are maximized for intermediate CAPE values in the range we examined. Results show a non-monotonic relationship between the hailstones’ residence time and CAPE due to changes to the updraft wind field. The ratio of updraft area to southerly wind speed within the updraft serves as a proxy for residence time. Storms in environments with large CAPE may produce smaller hail because the in-updraft horizontal wind speeds become too great, and hailstones are prematurely ejected out of the optimal growth region. Liquid water content (LWC) along favorable hailstone pathways also exhibits peak values for intermediate CAPE values, owing to the horizontal displacement across the midlevel updraft of moist inflow air from differing source levels. In other words, larger CAPE does not equal larger hail, and storm-structural nuances must be examined.

Severe local storm (SLS) activity is known to occur within specific thermodynamic and kinematic environments. These environments are commonly associated with key synoptic-scale features—including southerly Great Plains low-level jets, drylines, elevated mixed layers, and extratropical cyclones—that link the large-scale climate to SLS environments. This work analyzes spatiotemporal distributions of both extreme values of SLS environmental parameters and synoptic-scale features in the ERA5 reanalysis and in the Community Atmosphere Model, version 6 (CAM6), historical simulation during 1980–2014 over North America. Compared to radiosondes, ERA5 successfully reproduces SLS environments, with strong spatio-temporal correlations and low biases, especially over the Great Plains. Both ERA5 and CAM6 reproduce the climatology of SLS environments over the central United States as well as its strong seasonal and diurnal cycles. ERA5 and CAM6also reproduce the climatological occurrence of the synoptic-scale features, with the distribution pattern similar to that of SLS environments. Compared to ERA5, CAM6 exhibits a high bias in convective available potential energy over the eastern United States primarily due to a high bias in surface moisture and, to a lesser extent, storm-relative helicity due to enhanced low-level winds. Composite analysis indicates consistent synoptic anomaly patterns favorable for significant SLS environments over much of the eastern half of the United States in both ERA5 and CAM6, though the pattern differs for the southeastern United States. Overall, our results indicate that both ERA5 and CAM6 are capable of reproducing SLS environments as well as the synoptic-scale features and transient events that generate them.

Colombia is a country that is characterized by having potential in many renewable and sustainable energy sources such as solar, wind, hydroelectric, biomass, etc., in this country the growth value of renewable energy (ER) has not yet reached a benchmark, this due to the existence of several barriers or limitations that have hindered the path of research and implementation. It is difficult to identify and prioritize the impact of these barriers that mostly hinder growth or improvement in the quality of life of a specific population. For this research, a systematic structure has been developed to identify and prioritize the barriers and manage to find a solution path to the aforementioned. This study aims to recognize and classify the barriers according to their impact on the development of renewable energy technologies, as well as demonstrate the non-relationship that may exist between a territory rich in energy potential and the good quality of life of its inhabitants, the study consists of four phases; (1) A study area was taken for its characterization in renewable energy potential and compared with the current quality of its inhabitants, (2) The barriers were recognized from the available literature studies, project reports and interactions with 6 experts from academia and industries, (3) for the final selection, the FAHP decision method was used, then, 24 were selected and classified into five groups: social and economic barriers, political and, administrative and market barriers and geographical and environmental barriers and (4) the FAHP method was used to obtain the priority weight and the hierarchy between these barriers. The results showed first that there is no relationship indicating that a potential area in renewable energy source has a positive impact on people's quality of life, also that politics and political barriers occupies the first place among the main barriers, besides that corruption and nepotism is the most relevant sub-criterion according to the experts’ results. Sensitivity analysis is used to confirm the stability of all prioritized barriers.