Reduced neutron widths in the nuclear data ensemble: Experiment and theory do not agree

I have analyzed reduced neutron widths ({\Gamma}_{n}^0) for the subset of 1245 resonances in the nuclear data ensemble (NDE) for which they have been reported. Random matrix theory (RMT) predicts for the Gaussian orthogonal ensemble (GOE) that these widths should follow a \c{hi}^2 distribution having one degree of freedom ({\nu}=1) - the Porter Thomas distribution (PTD). Careful analysis of the {\Gamma}_{n}^2 values in the NDE rejects the validity of the PTD with a statistical significance of at least 99.97% ({\nu}=0.801\pm0.052). This striking disagreement with the RMT prediction is most likely due to the inclusion of significant p-wave contamination to the supposedly pure s-wave NDE. When an energy dependent threshold is used to remove the p-wave contamination, the PTD is still rejected with a statistical significance of at least 98.17% ({\nu}=1.217\pm0.092). Furthermore, examination of the primary references for the NDE reveals that many resonances in most of the individual data sets were selected using methods derived from RMT. Therefore, using the full NDE data set to test RMT predictions seems highly questionable. These results cast very serious doubt on claims that the NDE represents a striking confirmation of RMT.Comment: Accepted for publication in Phys. Rev.

Effects of atmospheric sphericity on stratospheric chemistry and dynamics over Antarctica

Atmospheric sphericity is an important factor that must be considered in order to evaluate an accurate ozone loss rate in the polar stratosphere. The built-in plane-parallel radiative transfer scheme of a nudging chemical transport model (CTM) and an atmospheric general circulation model (AGCM) with coupled chemistry is modified by a pseudospherical approximation. The plane-parallel atmosphere radiative transfer version (PPA version) is compared with the pseudospherical atmosphere radiative transfer version (SA version) for both the nudging CTM and AGCM. The nudging CTM can isolate the chemical effects for a given dynamical field, while the interaction among the chemical, radiative, and dynamical processes can be studied with the AGCM. The present analysis focuses on Antarctica during an ozone hole period. In the ozone loss period over Antarctica, ozone starts to decrease earlier and minimum value of total ozone becomes lower in the SA versions of both the nudging CTM and the AGCM than in the corresponding PPA versions. The ozone mixing ratio decreases earlier in the SA version because of an earlier increase of ClO concentration initiated by the upward actinic flux at solar zenith angles greater than 90°. Dynamics plays an important role as well as the chemical processes. During the ozone recovery period, the ozone distribution becomes almost the same in the SA and PPA versions of the nudging CTM, while in the AGCM the ozone amount in the SA version remains at lower values compared to those of the PPA version. In the AGCM, a decrease of ozone over Antarctica enhances the latitudinal gradient of temperature and thus strengthens the polar vortex in the SA version. A resultant delay of the polar vortex breakup causes the delay of the ozone recovery. For the AGCM, ensemble runs are performed. The ensemble experiment exhibits large ozone variances after the middle of December, when the ozone recovery is dynamically controlled. Most ensemble members of the AGCM show a delay of the polar vortex breakup in the SA version, while a few members show opposite results. In the latter members, the polar vortex breakup is strongly affected by the enhanced EP flux from the troposphere around 100 hPa, which causes the variances in the ozone recovery period. Most members, however, do not show large statistical variances; that justifies the conclusions from the ensemble means

Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment

Increasing concentrations of greenhouse gases in the atmosphere are expected to modify the global water cycle with significant consequences for terrestrial hydrology. We assess the impact of climate change on hydrological droughts in a multimodel experiment including seven global impact models (GIMs) driven by biascorrected climate from five global climate models under four representative concentration pathways (RCPs). Drought severity is defined as the fraction of land under drought conditions. Results show a likely increase in the global severity of hydrological drought at the end of the 21st century, with systematically greater increases for RCPs describing stronger radiative forcings. Under RCP8.5, droughts exceeding 40% of analyzed land area are projected by nearly half of the simulations. This increase in drought severity has a strong signal-to-noise ratio at the global scale, and Southern Europe, the Middle East, the Southeast United States, Chile, and South West Australia are identified as possible hotspots for future water security issues. The uncertainty due to GIMs is greater than that from global climate models, particularly if including a GIM that accounts for the dynamic response of plants to CO2 and climate, as this model simulates little or no increase in drought frequency. Our study demonstrates that different representations of terrestrial water-cycle processes in GIMs are responsible for a much larger uncertainty in the response of hydrological drought to climate change than previously thought. When assessing the impact of climate change on hydrology, it is therefore critical to consider a diverse range of GIMs to better capture the uncertainty

The efficient global primitive equation climate model SPEEDO V2.0

The efficient primitive-equation coupled atmosphere-ocean model SPEEDO V2.0 is presented. The model includes an interactive sea-ice and land component. SPEEDO is a global earth system model of intermediate complexity. It has a horizontal resolution of T30 (triangular truncation at wave number 30) and 8 vertical layers in the atmosphere, and a horizontal resolution of 2 degrees and 20 levels in the ocean. The parameterisations in SPEEDO are developed in such a way that it is a fast model suitable for large ensembles or long runs (of O(104) years) on a typical current workstation. The model has no flux correction. We compare the mean state and inter-annual variability of the model with observational fields of the atmosphere and ocean. In particular the atmospheric circulation, the midlatitude patterns of variability and teleconnections from the tropics are well simulated. To show the capabilities of the model, we performed a long control run and an ensemble experiment with enhanced greenhouse gases. The long control run shows that the model is stable. CO2 doubling and future climate change scenario experiments show a climate sensitivity of 1.84KW-1m2, which is within the range of state-of-the-art climate models. The spatial response patterns are comparable to state-of-the-art, higher resolution models. However, for very high greenhouse gas concentrations the parameterisations are not valid. We conclude that the model is suitable for past, current and future climate simulations and for exploring wide parameter ranges and mechanisms of variability. However, as with any model, users should be careful when using the model beyond the range of physical realism of the parameterisations and model setup

Correlations in mesoscopic magnetic systems

The purpose of this proposal is to study the ferro/para phase transition in a mesoscopic Ising-like lattice and in particular demonstrate the existence of a negative magnetic susceptibility in the fixed magnetization ensemble. To this aim we will use the correlation = /N2 where N is the total number of spins for a single cluster, M the total magnetization of the cluster, and the equality holds if we choose r0<Dr<R where r0 is the linear size of a spin site and R is the linear size of a cluster

Future changes in tropical cyclone activity in the North Indian Ocean projected by high-resolution MRI-AGCMs

Open Access at publisher's web site: http://www.springerlink.com/content/b682734237171631