Cavity-enhanced absorption: detection of nitrogen dioxide and iodine monoxide using a violet laser diode

We present an application of cavity-enhanced absorption spectroscopy with an off-axis alignment of the cavity formed by two spherical mirrors and with time integration of the cavity-output intensity for detection of nitrogen dioxide (NO2) and iodine monoxide (IO) radicals using a violet laser diode at lambda = 404.278 nm. A noise-equivalent (1sigma = root-mean-square variation of the signal) fractional absorption for one optical pass of 4.5x10(-8) was demonstrated with a mirror reflectivity of similar to0.99925, a cavity length of 0.22 m and a lock-in-amplifier time constant of 3 s. Noise-equivalent detection sensitivities towards nitrogen dioxide of 1.8x10(10) molecule cm(-3) and towards the IO radical of 3.3x10(9) molecule cm(-3) were achieved in flow tubes with an inner diameter of 4 cm for a lock-in-amplifier time constant of 3 s. Alkyl peroxy radicals were detected using chemical titration with excess nitric oxide (RO2 + NO --> RO + NO2). Measurement of oxygen-atom concentrations was accomplished by determining the depletion of NO2 in the reaction NO2 + O --> NO + O-2. Noise-equivalent concentrations of alkyl peroxy radicals and oxygen atoms were 3x10(10) molecule cm(-3) in the discharge-flow-tube experiments.

The climatology of the middle atmosphere in a vertically extended version of the Met Office's climate model. Part I: mean state

The climatology of a stratosphere-resolving version of the Met Office’s climate model is studied and validated against ECMWF reanalysis data. Ensemble integrations are carried out at two different horizontal resolutions. Along with a realistic climatology and annual cycle in zonal mean zonal wind and temperature, several physical effects are noted in the model. The time of final warming of the winter polar vortex is found to descend monotonically in the Southern Hemisphere, as would be expected for purely radiative forcing. In the Northern Hemisphere, however, the time of final warming is driven largely by dynamical effects in the lower stratosphere and radiative effects in the upper stratosphere, leading to the earliest transition to westward winds being seen in the midstratosphere. A realistic annual cycle in stratospheric water vapor concentrations—the tropical “tape recorder”—is captured. Tropical variability in the zonal mean zonal wind is found to be in better agreement with the reanalysis for the model run at higher horizontal resolution because the simulated quasi-biennial oscillation has a more realistic amplitude. Unexpectedly, variability in the extratropics becomes less realistic under increased resolution because of reduced resolved wave drag and increased orographic gravity wave drag. Overall, the differences in climatology between the simulations at high and moderate horizontal resolution are found to be small.

Mean-tracking clustering algorithm for radial basis function centre selection

Radial basis functions can be combined into a network structure that has several advantages over conventional neural network solutions. However, to operate effectively the number and positions of the basis function centres must be carefully selected. Although no rigorous algorithm exists for this purpose, several heuristic methods have been suggested. In this paper a new method is proposed in which radial basis function centres are selected by the mean-tracking clustering algorithm. The mean-tracking algorithm is compared with k means clustering and it is shown that it achieves significantly better results in terms of radial basis function performance. As well as being computationally simpler, the mean-tracking algorithm in general selects better centre positions, thus providing the radial basis functions with better modelling accuracy

Adaptive least mean square CDMA detection with Gram–Schmidt pre-processing

The Gram-Schmidt (GS) orthogonalisation procedure has been used to improve the convergence speed of least mean square (LMS) adaptive code-division multiple-access (CDMA) detectors. However, this algorithm updates two sets of parameters, namely the GS transform coefficients and the tap weights, simultaneously. Because of the additional adaptation noise introduced by the former, it is impossible to achieve the same performance as the ideal orthogonalised LMS filter, unlike the result implied in an earlier paper. The authors provide a lower bound on the minimum achievable mean squared error (MSE) as a function of the forgetting factor λ used in finding the GS transform coefficients, and propose a variable-λ algorithm to balance the conflicting requirements of good tracking and low misadjustment.

Atmospheric blocking and mean biases in climate models

Models often underestimate blocking in the Atlantic and Pacific basins and this can lead to errors in both weather and climate predictions. Horizontal resolution is often cited as the main culprit for blocking errors due to poorly resolved small-scale variability, the upscale effects of which help to maintain blocks. Although these processes are important for blocking, the authors show that much of the blocking error diagnosed using common methods of analysis and current climate models is directly attributable to the climatological bias of the model. This explains a large proportion of diagnosed blocking error in models used in the recent Intergovernmental Panel for Climate Change report. Furthermore, greatly improved statistics are obtained by diagnosing blocking using climate model data corrected to account for mean model biases. To the extent that mean biases may be corrected in low-resolution models, this suggests that such models may be able to generate greatly improved levels of atmospheric blocking.

Air flow influences on local climate: observed and simulated mean relationships for the United Kingdom

Synoptic-scale air flow variability over the United Kingdom is measured on a daily time scale by following previous work to define 3 indices: geostrophic flow strength, vorticity and direction. Comparing the observed distribution of air flow index values with those determined from a simulation with the Hadley Centre’s global climate model (HadCM2) identifies some minor systematic biases in the model’s synoptic circulation but demonstrates that the major features are well simulated. The relationship between temperature and precipitation from parts of the United Kingdom and these air flow indices (either singly or in pairs) is found to be very similar in both the observations and model output; indeed the simulated and observed precipitation relationships are found to be almost interchangeable in a quantitative sense. These encouraging results imply that some reliability can be assumed for single grid-box and regional output from this climate model; this applies only to those grid boxes evaluated here (which do not have high or complex orography), only to the portion of variability that is controlled by synoptic air flow variations, and only to those surface variables considered here (temperature and precipitation).

On merging gradient estimation with mean-tracking techniques for cluster identification

This paper discusses how numerical gradient estimation methods may be used in order to reduce the computational demands on a class of multidimensional clustering algorithms. The study is motivated by the recognition that several current point-density based cluster identification algorithms could benefit from a reduction of computational demand if approximate a-priori estimates of the cluster centres present in a given data set could be supplied as starting conditions for these algorithms. In this particular presentation, the algorithm shown to benefit from the technique is the Mean-Tracking (M-T) cluster algorithm, but the results obtained from the gradient estimation approach may also be applied to other clustering algorithms and their related disciplines.