The diurnal nature of future extreme precipitation intensification

Short‐duration, high‐impact precipitation events in the extratropics are invariably convective in nature, typically occur during the summer, and are projected to intensify under climate change. The occurrence of convective precipitation is strongly regulated by the diurnal convective cycle, peaking in the late afternoon. Here we perform very high resolution (convection‐permitting) regional climate model simulations to study the scaling of extreme precipitation under climate change across the diurnal cycle. We show that the future intensification of extreme precipitation has a strong diurnal signal and that intraday scaling far in excess of overall scaling, and indeed thermodynamic expectations, is possible. We additionally show that, under a strong climate change scenario, the probability maximum for the occurrence of heavy to extreme precipitation may shift from late afternoon to the overnight/morning period. We further identify the thermodynamic and dynamic mechanisms which modify future extreme environments, explaining both the future scaling's diurnal signal and departure from thermodynamic expectations

Evidence for charge orbital and spin stripe order in an overdoped manganite

We present diffraction data on a single-layered manganite La(0.42)Sr(1.58)MnO4 with hole doping (x>0.5). Overdoped La(0.42)Sr(1.58)MnO4 exhibits a complex ordering of charges, orbitals and spins. Single crystal neutron diffraction experiments reveal three incommensurate and one commensurate order parameters to be tightly coupled. The position and the shape of the distinct superstructure scattering points to a stripe arrangement in which ferromagnetic zigzag chains are disrupted by additional Mn4+ stripes

A classification algorithm for selective dynamical downscaling of precipitation extremes

High-resolution climate data O(1km) at the catchment scale can be of great value to both hydrological modellers and end users, in particular for the study of extreme precipitation. While dynamical downscaling with convection-permitting models is a valuable approach for producing quality high-resolution O(1km) data, its added value can often not be realized due to the prohibitive computational expense. Here we present a novel and flexible classification algorithm for discriminating between days with an elevated potential for extreme precipitation over a catchment and days without, so that dynamical downscaling to convection-permitting resolution can be selectively performed on high-risk days only, drastically reducing total computational expense compared to continuous simulations; the classification method can be applied to climate model data or reanalyses. Using observed precipitation and the corresponding synoptic-scale circulation patterns from reanalysis, characteristic extremal circulation patterns are identified for the catchment via a clustering algorithm. These extremal patterns serve as references against which days can be classified as potentially extreme, subject to additional tests of relevant meteorological predictors in the vicinity of the catchment. Applying the classification algorithm to reanalysis, the set of potential extreme days (PEDs) contains well below 10% of all days, though it includes essentially all extreme days; applying the algorithm to reanalysis-driven regional climate simulations over Europe (12km resolution) shows similar performance, and the subsequently dynamically downscaled simulations (2km resolution) well reproduce the observed precipitation statistics of the PEDs from the training period. Additional tests on continuous 12km resolution historical and future (RCP8.5) climate simulations, downscaled in 2km resolution time slices, show the algorithm again reducing the number of days to simulate by over 90% and performing consistently across climate regimes. The downscaling framework we propose represents a computationally inexpensive means of producing high-resolution climate data, focused on extreme precipitation, at the catchment scale, while still retaining the advantages of convection-permitting dynamical downscaling

Cell tracking of convective rainfall: sensitivity of climate-change signal to tracking algorithm and cell definition (Cell-TAO v1.0)

Lagrangian analysis of convective precipitation involves identifying convective cells (“objects”) and tracking them through space and time. The Lagrangian approach helps to gain insight into the physical properties and impacts of convective cells and, in particular, how these may respond to climate change. Lagrangian analysis requires both a fixed definition of what constitutes a convective object and a reliable tracking algorithm. Whether the climate-change signals of various object properties are sensitive to the choice of tracking algorithm or to how a convective object is defined has received little attention. Here we perform ensemble pseudo-global-warming experiments at a convection-permitting resolution to test this question. Using two conceptually different tracking algorithms, Lagrangian analysis is systematically repeated with different thresholds for defining a convective object, namely minimum values for object area, intensity and lifetime. It is found that the threshold criteria for identifying a convective object can have a strong and statistically significant impact on the magnitude of the climate-change signal, for all analysed object properties. The tracking method, meanwhile, has no impact on the climate-change signal as long as the precipitation data have a sufficiently high temporal resolution: in general, the lower the minimum permitted object size is, the higher the precipitation data's temporal resolution must be. For the case considered in our study, these insights reveal that irrespective of the tracking method, projected changes in the characteristics of convective rainfall vary considerably between cells of differing intensity, area and lifetime

Subhourly rainfall in a convection-permitting model

Convection-permitting models (CPMs)—the newest generation of high-resolution climate models—have been shown to greatly improve the representation of subdaily and hourly precipitation, in particular for extreme rainfall. Intense precipitation events, however, often occur on subhourly timescales. The distribution of subhourly precipitation, extreme or otherwise, during a rain event can furthermore have important knock-on effects on hydrological processes. Little is known about how well CPMs represent precipitation at the subhourly timescale, compared to the hourly. Here we perform multi-decadal CPM simulations centred over Catalonia and, comparing with a high temporal-resolution gauge network, find that the CPM simulates subhourly precipitation at least as well as hourly precipitation is simulated. While the CPM inherits a dry bias found in its parent model, across a range of diagnostics and aggregation times (5, 15, 30 and 60 min) we find no consistent evidence that the CPM precipitation bias worsens with shortening temporal aggregation. We furthermore show that the CPM excels in its representation of subhourly extremes, extending previous findings at the hourly timescale. Our findings support the use of CPMs for modelling subhourly rainfall and add confidence to CPM-based climate projections of future changes in subhourly precipitation, particularly for extremes

Preface: Understanding dynamics and current developments of climate extremes in the Mediterranean region

There is an increasing interest of scientists on climate extremes. A progressively larger number of papers dealing with climate issues have been produced in the past 15 yr, and those dealing with extremes have increased at an even faster pace. The number of papers on extremes in the Mediterranean follows this overall trend and confirms how extremes are perceived to be important by the scientific community and by society. This special issue (which is mainly related to activities of the MedCLIVAR (Mediterranean CLImate VARiability and Predictability) and CIRCE (Climate Change and Impact Research: the Mediterranean Environment) projects), contains thirteen papers that are representative of current research on extremes in the Mediterranean region. Five have precipitation as its main target, four temperature (one paper addresses both variables), and two droughts; the remaining papers consider sea level, winds and impacts on society. Results are quite clear concerning climate evolution toward progressively hotter temperature extremes, but more controversial for precipitation, though in the published literature there are indications for a future increasing intensity of hydrological extremes (intense precipitation events and droughts). Scenario simulations suggest an attenuation of extreme storms, winds, waves and surges, but more results are requested for confirming this future change

Theory of Optical Orientation in n-Type Semiconductors

Time resolved measurements of magnetization in n-GaAs have revealed a rich array of spin decoherence processes, and have shown that fairly long lifetimes (\sim 100 ns) can be achieved under certain circumstances. In time-resolved Faraday rotation and time-resolved Kerr rotation the evolution of the magnetization can be followed as a function of temperature, applied field, doping level and excitation level. We present a theory for the spin relaxation in n-GaAs based on a set of rate equations for two interacting thermalized subsystems of spins: localized states on donor sites and itinerant states in the conduction band. The conduction band spins relax by scattering from defects or phonons through the D'yakonov-Perel' mechanism, while the localized spins relax by interacting with phonons (when in an applied field) or through the Dzyaloshinskii-Moriya interaction. In this model, numerous features of the data, including puzzling temperature and doping dependences of the relaxation time, find an explanation.Comment: 4 pages, 2 figures; revised version has a more complete discussion of the Elliott-Yafet and spin-phonon decay mechanism

The nonlinear association between grandiose and vulnerable narcissism: An individual data meta‐analysis

Objective: Narcissism can manifest in grandiose and vulnerable patterns of experience and behavior. While largely unrelated in the general population, individuals with clinically relevant narcissism are thought to display both. Our previous studies showed that trait measures of grandiosity and vulnerability were unrelated at low-to-moderate levels of grandiose narcissism, but related at high levels. Method: We replicate and extend these findings in a preregistered individual data meta-analysis ("mega-analysis") using data from the Narcissistic Personality Inventory (NPI)/Hypersensitive Narcissism Scale (HSNS; N = 10,519, k = 28) and the Five-Factor Narcissism Inventory (FFNI; N = 7,738, k = 17). Results: There was strong evidence for the hypothesis in the FFNI (βGrandiose 1 SD = .36, βGrandiose > 2 SD = .53), and weaker evidence in the NPI/HSNS (βGrandiose 1 SD = .12, βGrandiose > 2 SD = .32). Nonlinearity increased with age but was invariant across other moderators. Higher vulnerability was predicted by elevated antagonistic and low agentic narcissism at subfactor level. Conclusion: Narcissistic vulnerability increases at high levels of grandiosity. Interpreted along Whole Trait Theory, the effects are thought to reflect state changes echoing in trait measures and can help to link personality and clinical models

Present and future diurnal hourly precipitation in 0.11° EURO-CORDEX models and at convection-permitting resolution

The diurnal cycle of precipitation (DCP) is a core mode of precipitation variability in regions and seasons where the dominant precipitation type is convective. The occurrence of extreme precipitation is often closely linked to the DCP. Future changes in extreme precipitation may furthermore, in certain regions, exhibit a strong diurnal signal. Here we investigate the present and future diurnal cycle of hourly precipitation in the state-of-the-art 0.11°C EURO-CORDEX (EC-11) ensemble and in a convection-permitting model (CPM), with a focus on extremes. For the present climate, long-standing timing and frequency biases in the DCP found in lower-resolution models persist in the EC-11 ensemble. In the CPM, however, these biases are largely absent, particularly the diurnal distribution of extremes, which the EC-11 ensemble misrepresents. For future changes to hourly precipitation, we find clear diurnal signals in the CPM and in EC-11 models, with high regional and intra-ensemble variability. The diurnal signal typically peaks in the morning. Interestingly, the EC-11 ensemble mean shows reasonable agreement with the CPM on the diurnal signal's timing, showing that this feature is representable by models with parametrized convection. Comparison with the CPM suggests that EC-11 models greatly underestimate the amplitude of this diurnal signal. Our study highlights the advantages of CPMs for investigating future precipitation change at the diurnal scale, while also showing the EC-11 ensemble capable of detecting a diurnal signal in future precipitation change