The role of dynamics in total ozone deviations from their long-term mean over the Northern Hemisphere

International audienceTotal ozone anomalies (deviation from the long-term mean) are created by anomalous circulation patterns. The dynamically produced ozone anomalies can be estimated from known circulation parameters in the layer between the tropopause and the middle stratosphere by means of statistics. Satellite observations of ozone anomalies can be compared with those expected from dynamics. Residual negative anomalies may be due to chemical ozone destruction. The statistics are derived from a 14 year data set of TOMS (Total Ozone Mapping Spectrometer January 1979-Dec. 1992) and corresponding 300 hPa geopotential (for the tropopause height) together with 30 hPa temperature (for stratospheric waves) at 60°N. The correlation coefficient for the linear multiple regression between total ozone (dependent variable) and the dynamical parameters (independent variables) is 0.88 for the zonal deviations in the winter of the Northern Hemisphere. Zonal means are also significantly dependent on circulation parameters, besides showing the known negative trend function of total ozone observed by TOMS. The significant linear trend for 60°N is \sim3 DU/year in the winter months taking into account the dependence on the dynamics between the tropopause region and the mid-stratosphere. The highest correlation coefficient for the monthly mean total ozone anomalies is reached in November with 0.94

Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)

Results of ecological models differ, to some extent, more from measured data than from empirical knowledge. Existing techniques for validation based on quantitative assessments sometimes cause an underestimation of the performance of models due to time shifts, accelerations and delays or systematic differences between measurement and simulation. However, for the application of such models it is often more important to reproduce essential patterns instead of seemingly exact numerical values. This paper presents techniques to identify patterns and numerical methods to measure the consistency of patterns between observations and model results. An orthogonal set of deviance measures for absolute, relative and ordinal scale was compiled to provide informations about the type of difference. Furthermore, two different approaches accounting for time shifts were presented. The first one transforms the time to take time delays and speed differences into account. The second one describes known qualitative criteria dividing time series into interval units in accordance to their main features. The methods differ in their basic concepts and in the form of the resulting criteria. Both approaches and the deviance measures discussed are implemented in an R package. All methods are demonstrated by means of water quality measurements and simulation data. The proposed quality criteria allow to recognize systematic differences and time shifts between time series and to conclude about the quantitative and qualitative similarity of patterns.

Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)

Results of ecological models differ, to some extent, more from measured data than from empirical knowledge. Existing techniques for validation based on quantitative assessments sometimes cause an underestimation of the performance of models due to time shifts, accelerations and delays or systematic differences between measurement and simulation. However, for the application of such models it is often more important to reproduce essential patterns instead of seemingly exact numerical values. This paper presents techniques to identify patterns and numerical methods to measure the consistency of patterns between observations and model results. An orthogonal set of deviance measures for absolute, relative and ordinal scale was compiled to provide informations about the type of difference. Furthermore, two different approaches accounting for time shifts were presented. The first one transforms the time to take time delays and speed differences into account. The second one describes known qualitative criteria dividing time series into interval units in accordance to their main features. The methods differ in their basic concepts and in the form of the resulting criteria. Both approaches and the deviance measures discussed are implemented in an R package. All methods are demonstrated by means of water quality measurements and simulation data. The proposed quality criteria allow to recognize systematic differences and time shifts between time series and to conclude about the quantitative and qualitative similarity of patterns

Testing isotropy of the universe using the Ramsey resonance technique on ultracold neutron spins

Physics at the Planck scale could be revealed by looking for tiny violations of fundamental symmetries in low energy experiments. In 2008, a sensitive test of the isotropy of the Universe using has been performed with stored ultracold neutrons (UCN), this is the first clock-comparison experiment performed with free neutrons. During several days we monitored the Larmor frequency of neutron spins in a weak magnetic field using the Ramsey resonance technique. An non-zero cosmic axial field, violating rotational symmetry, would induce a daily variation of the precession frequency. Our null result constitutes one of the most stringent tests of Lorentz invariance to date.Comment: proceedings of the PNCMI2010 conferenc

Diffuse reflection of ultracold neutrons from low-roughness surfaces

We report a measurement of the reflection of ultracold neutrons from flat, large-area plates of different Fermi potential materials with low surface roughness. The results were used to test two diffuse reflection models, the well-known Lambert model and the micro-roughness model which is based on wave scattering. The Lambert model fails to reproduce the diffuse reflection data. The surface roughness b and correlation length w , obtained by fitting the micro-roughness model to the data are in the range 1$\le$ b $\le$3 nm and 10$\le$ w $\le$120 nm, in qualitative agreement with independent measurements using atomic force microscop