Search for: All records

Enabling elliptically polarized high-order harmonics overcomes a historical limitation in the generation of this highly nonlinear process in atomic, molecular and optical physics with applications in other branches. Here, we shed new light on a controversy between experimental observations and theoretical predictions on the possibility to generate harmonics with large ellipticity using two bichromatic laser pulses which are linearly polarized in orthogonal directions. Results of numerical calculations confirm the previous experimental data that in short laser pulses even harmonics with large ellipticity can be obtained for the interaction of such cross-polarized laser pulses with atoms initially in as- orp-state, while odd harmonics have low ellipticity. The amount of the ellipticity can be controlled via the relative carrier-envelope phase of the pulses, their intensity ratio and the duration of the pulses.

 

Mesoscale convective systems (MCSs) are a substantial source of precipitation in the eastern U.S. and may be sensitive to regional climatic change. We use a suite of convection-permitting climate simulations to examine possible changes in MCS precipitation. Specifically, annual and regional totals of MCS and non-MCS precipitation generated during a retrospective simulation are compared to end-of-21st-century simulations based on intermediate and extreme climate change scenarios. Both scenarios produce more MCS precipitation and less non-MCS precipitation, thus significantly increasing the proportion of precipitation associated with MCSs across the U.S.

 

The conformational state of DNA fine-tunes the transcriptional rate and abundance of RNA. Here, we report that G-quadruplex DNA (G4-DNA) accumulates in neurons, in an experience-dependent manner, and that this is required for the transient silencing and activation of genes that are critically involved in learning and memory in male C57/BL6 mice. In addition, site-specific resolution of G4-DNA by dCas9-mediated deposition of the helicase DHX36 impairs fear extinction memory. Dynamic DNA structure states therefore represent a key molecular mechanism underlying memory consolidation.

One-Sentence Summary:G4-DNA is a molecular switch that enables the temporal regulation of the gene expression underlying the formation of fear extinction memory.

 

Elevated mixed layers (EMLs) influence the severe convective storm climatology in the contiguous United States (CONUS), playing an important role in the initiation, sustenance, and suppression of storms. This study creates a high-resolution climatology of the EML to analyze variability and potential changes in EML frequency and characteristics for the first time. An objective algorithm is applied to ERA5 to detect EMLs, defined in part as layers of steep lapse rates (≥8.0°C km⁻¹) at least 200 hPa thick, in the CONUS and northern Mexico from 1979 to 2021. EMLs are most frequent over the Great Plains in spring and summer, with a standard deviation of 4–10 EML days per year highlighting sizable interannual variability. Mean convective inhibition associated with the EML’s capping inversion suggests many EMLs prohibit convection, although—like nearly all EML characteristics—there is considerable spread and notable seasonal variability. In the High Plains, statistically significant increases in EML days (4–5 more days per decade) coincide with warmer EML bases and steeper EML lapse rates, driven by warming and drying in the low levels of the western CONUS during the study period. Additionally, increases in EML base temperatures result in significantly more EML-related convective inhibition over the Great Plains, which may continue to have implications for convective storm frequency, intensity, severe perils, and precipitation if this trend persists.

Elevated mixed layers (EMLs) play a role in the spatiotemporal frequency of severe convective storms and precipitation across the contiguous United States and northern Mexico. This research creates a detailed EML climatology from a modern reanalysis dataset to uncover patterns and potential changes in EML frequency and associated meteorological characteristics. EMLs are most common over the Great Plains in spring and summer, but show significant variability year-to-year. Robust increases in the number of days with EMLs have occurred since 1979 across the High Plains. Lapse rates associated with EMLs have trended steeper, in part due to warmer EML base temperatures. This has resulted in increasing EML convective inhibition, which has important implications for regional climate.

 

A supercell is a distinct type of intense, long-lived thunderstorm that is defined by its quasi-steady, rotating updraft. Supercells are responsible for most damaging hail and deadly tornadoes, causing billions of dollars in losses and hundreds of casualties annually. This research uses high-resolution, convection-permitting climate simulations across 15-yr epochs that span the twenty-first century to assess how supercells may change across the United States. Specifically, the study explores how late-twentieth-century supercell populations compare with their late-twenty-first-century counterparts for two—intermediate and pessimistic—anthropogenic climate change trajectories. An algorithm identifies, segments, and tracks supercells in the simulation output using updraft helicity, which measures the magnitude of corkscrew flow through a storm’s updraft and is a common proxy for supercells. Results reveal that supercells will be more frequent and intense in future climates, with robust spatiotemporal shifts in their populations. Supercells are projected to become more numerous in regions of the eastern United States, while decreasing in frequency in portions of the Great Plains. Supercell risk is expected to escalate outside of the traditional severe storm season, with supercells and their perils likely to increase in late winter and early spring months under both emissions scenarios. Conversely, the latter part of the severe storm season may be curtailed, with supercells expected to decrease midsummer through early fall. These results suggest the potential for more significant tornadoes, hail, and extreme rainfall that, when combined with an increasingly vulnerable society, may produce disastrous consequences. 

Explicit representation of finer‐scale processes can affect the sign and magnitude of the precipitation response to climate change between convection‐permitting and convection‐parameterizing models. We compare precipitation across two 15‐year epochs, a historical (HIST) and an end‐of‐21st‐century (EoC85), between a set of dynamically downscaled regional climate simulations at 3.75 km grid spacing (WRF) and bias‐corrected Community Earth System Model (CESM) output used to initialize and force the lateral boundaries of the downscaled simulations. In the historical climate, the downscaled simulations demonstrate less overall error than CESM when compared to observations for most portions of the conterminous United States. Both sets of simulations overestimate the incidence of environments with moderate to high precipitable water while CESM generally simulates rainfall that is too frequent but less intense. Within both sets of simulations, EoC85 rainfall amounts decrease in low‐moisture environments due to reduced rainfall frequency and intensity while rainfall amounts increase in high‐moisture environments as they occur more often. Overall, reductions in rainfall are stronger in WRF than in CESM, particularly during the warm season. This reduced drying in CESM is attributed to relatively higher rainfall frequency in environments with high concentrations of precipitable water and weak vertical motion. As a result, an increase in the occurrence of high moisture environments in EoC85 naturally favors more rainfall in CESM than WRF. Our results present an in‐depth examination of the characteristics of changes in overall accumulated precipitation and highlight an extra dimension of uncertainty when comparing convection‐permitting models against convection‐parameterizing models.

 

Human activity along our coasts and throughout our oceans has been increasing over the past few decades. In 2017, the output of the global Blue Economy was estimated at €1.3 trillion, and that value is expected to more than double by 2030. Offshore wind and tourism are major sectors in the blue economy, and they have the potential to function jointly through multi-use, thereby creating added benefits for both sectors as well as society overall. To contribute to the assessment of multi-use’s viability, this project has evaluated existing areas where offshore wind and tourism are successfully infused together and globally identified additional areas where they are likely to work together. Taking advantage of multi-use is becoming increasingly beneficial. By having industries function jointly in the same space, instead of parceling out ocean space by industry, the blue economy can remain sustainable and competitive. Early identification of these areas viable for offshore wind and tourism multi-use is important not only to businesses and coastal communities, but to the sustainable future of our oceans. The areas that are likely to benefit the most from this form of multi-use can be identified using GIS to analyze ocean space. First, datasets including ship density, wind speed, light at night, and tourism arrivals were used to understand both environmental and social factors indicative of supporting this form of multi-use. Then, these factors were spatially quantified and aggregated together in ArcGIS to identify locations best suited to combining offshore wind and tourism. Results indicate a higher potential for multi-use success in higher populated and more developed regions. Low population limits the potential for this type of multi-use in many areas, but a smaller-scale, regional analysis would provide more detailed insight into specific regions.