69 research outputs found

    An Evaluation of the Large‐Scale Atmospheric Circulation and Its Variability in CESM2 and Other CMIP Models

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    The Community Earth System Model 2 (CESM2) is the latest Earth System Model developed by the National Center for Atmospheric Research in collaboration with the university community and is significantly advanced in most components compared to its predecessor (CESM1). Here, CESM2's representation of the large‐scale atmospheric circulation and its variability is assessed. Further context is providedthrough comparison to the CESM1 large ensemble and other models from the Coupled Model Intercomparison Project (CMIP5 and CMIP6). This includes an assessment of the representation of jet streams and storm tracks, stationary waves, the global divergent circulation, the annular modes, the North Atlantic Oscillation, and blocking. Compared to CESM1, CESM2 is substantially improved in the representation of the storm tracks, Northern Hemisphere (NH) stationary waves, NH winter blocking and the global divergent circulation. It ranks within the top 10% of CMIP class models in many of these features. Some features of the Southern Hemisphere (SH) circulation have degraded, such as the SH jet strength, stationary waves, and blocking, although the SH jet stream is placed at approximately the correct location. This analysis also highlights systematic deficiencies in these features across the new CMIP6 archive, such as the continued tendency for the SH jet stream to be placed too far equatorward, the North Atlantic westerlies to be too strong over Europe, the storm tracks as measured by low‐level meridional wind variance to be too weak and a lack of blocking in the North Atlantic sector

    Radiative and chemical response to interactive stratospheric sulfate aerosols in fully coupled CESM1(WACCM)

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    We present new insights into the evolution and interactions of stratospheric aerosol using an updated version of the Whole Atmosphere Community Climate Model (WACCM). Improved horizontal resolution, dynamics, and chemistry now produce an internally generated quasi-biennial oscillation and significant improvements to stratospheric temperatures and ozone compared to observations. We present a validation of WACCM column ozone and climate calculations against observations. The prognostic treatment of stratospheric sulfate aerosols accurately represents the evolution of stratospheric aerosol optical depth and perturbations to solar and longwave radiation following the June 1991 eruption of Mount Pinatubo. We confirm the inclusion of interactive OH chemistry as an important factor in the formation and initial distribution of aerosol following large inputs of sulfur dioxide (SO2) to the stratosphere. We calculate that depletion of OH levels within the dense SO2 cloud in the first weeks following the Pinatubo eruption significantly prolonged the average initial e-folding decay time for SO2 oxidation to 47 days. Previous observational and model studies showing a 30 day decay time have not accounted for the large (30–55%) losses of SO2 on ash and ice within 7–9 days posteruption and have not correctly accounted for OH depletion. We examine the variability of aerosol evolution in free-running climate simulations due to meteorology, with comparison to simulations nudged with specified dynamics. We assess calculated impacts of volcanic aerosols on ozone loss with comparisons to observations. The completeness of the chemistry, dynamics, and aerosol microphysics in WACCM qualify it for studies of stratospheric sulfate aerosol geoengineering

    Experimental Observation of Quantum Chaos in a Beam of Light

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    The manner in which unpredictable chaotic dynamics manifests itself in quantum mechanics is a key question in the field of quantum chaos. Indeed, very distinct quantum features can appear due to underlying classical nonlinear dynamics. Here we observe signatures of quantum nonlinear dynamics through the direct measurement of the time-evolved Wigner function of the quantum-kicked harmonic oscillator, implemented in the spatial degrees of freedom of light. Our setup is decoherence-free and we can continuously tune the semiclassical and chaos parameters, so as to explore the transition from regular to essentially chaotic dynamics. Owing to its robustness and versatility, our scheme can be used to experimentally investigate a variety of nonlinear quantum phenomena. As an example, we couple this system to a quantum bit and experimentally investigate the decoherence produced by regular or chaotic dynamics.Comment: 7 pages, 5 figure

    Evolution under Fluctuating Environments Explains Observed Robustness in Metabolic Networks

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    A high level of robustness against gene deletion is observed in many organisms. However, it is still not clear which biochemical features underline this robustness and how these are acquired during evolution. One hypothesis, specific to metabolic networks, is that robustness emerges as a byproduct of selection for biomass production in different environments. To test this hypothesis we performed evolutionary simulations of metabolic networks under stable and fluctuating environments. We find that networks evolved under the latter scenario can better tolerate single gene deletion in specific environments. Such robustness is underlined by an increased number of independent fluxes and multifunctional enzymes in the evolved networks. Observed robustness in networks evolved under fluctuating environments was “apparent,” in the sense that it decreased significantly as we tested effects of gene deletions under all environments experienced during evolution. Furthermore, when we continued evolution of these networks under a stable environment, we found that any robustness they had acquired was completely lost. These findings provide evidence that evolution under fluctuating environments can account for the observed robustness in metabolic networks. Further, they suggest that organisms living under stable environments should display lower robustness in their metabolic networks, and that robustness should decrease upon switching to more stable environments

    Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

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    Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified
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