Real-time forecasting of inflation and output growth with autoregressive models in the presence of data revisions

We examine how the accuracy of real-time forecasts from models that include autoregressive terms can be improved by estimating the models on ‘lightly revised’ data instead of using data from the latest-available vintage. The benefits of estimating autoregressive models on lightly revised data are related to the nature of the data revision process and the underlying process for the true values. Empirically, we find improvements in root mean square forecasting error of 2–4% when forecasting output growth and inflation with univariate models, and of 8% with multivariate models. We show that multiple-vintage models, which explicitly model data revisions, require large estimation samples to deliver competitive forecasts. Copyright © 2012 John Wiley & Sons, Ltd.

Representing the Arctic in global surface temperature time series of recent climate change

The Arctic is an important region in the study of climate change, but monitoring surface temperatures in this region is challenging, particularly in areas covered by sea ice. Here in situ, satellite and reanalysis data were utilised to investigate whether global warming over recent decades could be better estimated by changing the way the Arctic is treated in calculating global mean temperature. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice were investigated using reanalysis data as a testbed. Techniques which interpolated anomalies were found to result in smaller errors than non-interpolating techniques. Kriging techniques provided the smallest errors in anomaly estimates. Similar accuracies were found for anomalies estimated from in situ meteorological station SAT records using a kriging technique. Whether additional data sources, which are not currently utilised in temperature anomaly datasets, would improve estimates of Arctic surface air temperature anomalies was investigated within the reanalysis testbed and using in situ data. For the reanalysis study, the additional input anomalies were reanalysis data sampled at certain supplementary data source locations over Arctic land and sea ice areas. For the in situ data study, the additional input anomalies over sea ice were surface temperature anomalies derived from the Advanced Very High Resolution Radiometer satellite instruments. The use of additional data sources, particularly those located in the Arctic Ocean over sea ice or on islands in sparsely observed regions, can lead to substantial improvements in the accuracy of estimated anomalies. Decreases in Root Mean Square Error can be up to 0.2K for Arctic-average anomalies and more than 1K for spatially resolved anomalies. Further improvements in accuracy may be accomplished through the use of other data sources.

A systematic method of parameterisation estimation using data assimilation

In numerical weather prediction, parameterisations are used to simulate missing physics in the model. These can be due to a lack of scientific understanding or a lack of computing power available to address all the known physical processes. Parameterisations are sources of large uncertainty in a model as parameter values used in these parameterisations cannot be measured directly and hence are often not well known; and the parameterisations themselves are also approximations of the processes present in the true atmosphere. Whilst there are many efficient and effective methods for combined state/parameter estimation in data assimilation (DA), such as state augmentation, these are not effective at estimating the structure of parameterisations. A new method of parameterisation estimation is proposed that uses sequential DA methods to estimate errors in the numerical models at each space-time point for each model equation. These errors are then fitted to pre-determined functional forms of missing physics or parameterisations that are based upon prior information. We applied the method to a one-dimensional advection model with additive model error, and it is shown that the method can accurately estimate parameterisations, with consistent error estimates. Furthermore, it is shown how the method depends on the quality of the DA results. The results indicate that this new method is a powerful tool in systematic model improvement.

Small- and waiting-time behaviour of the thin-film-equation

We consider the small-time behavior of interfaces of zero contact angle solutions to the thin-film equation. For a certain class of initial data, through asymptotic analyses, we deduce a wide variety of behavior for the free boundary point. These are supported by extensive numerical simulations. © 2007 Society for Industrial and Applied Mathematics

Quantifying time scales of pedogenic calcrete formation using U-series disequilibria

Time scales of pedogenic calcrete development are quantified by subsampling carbonate from within a mature (stage V) pedogenic calcrete profile from southeast Spain and dating the material by U-series disequilibria. The location of the earliest and latest cements can be estimated by comparing previous studies of calcrete morphological development with micromorphological analysis of the study profile. Carbonate was sampled and dated from three locations within the profile: (1) below the lower surface of clasts within the hardpan (representing the earliest cement present-207 +/- 11 ka), (2) from the centre of cement filled pores within the hardpan (reflecting the final plugging of the calcrete hardpan-155 +/- 9 ka) and (3) from the laminar calcrete overlying the hardpan (representing the latest cement-112 +/- 15 ka). These results show that the hardpan took between 73 and 31 ka to form, whilst the mature stage V profile took between 121 and 69 ka to form. This is the first time that rates of mature calcrete development have been established by direct radiometric dating of the authigenic carbonate. The technique is appropriate for dating mature calcretes in dryland regions worldwide and offers the opportunity of increasing our understanding of the spatial and temporal variability in rates of pedogenic calcrete development. (C) 2004 Elsevier B.V. All rights reserved.

Uncertainties in annual riverine phosphorus load estimation: Impact of load estimation methodology, sampling frequency, baseflow index and catchment population density

Models developed to identify the rates and origins of nutrient export from land to stream require an accurate assessment of the nutrient load present in the water body in order to calibrate model parameters and structure. These data are rarely available at a representative scale and in an appropriate chemical form except in research catchments. Observational errors associated with nutrient load estimates based on these data lead to a high degree of uncertainty in modelling and nutrient budgeting studies. Here, daily paired instantaneous P and flow data for 17 UK research catchments covering a total of 39 water years (WY) have been used to explore the nature and extent of the observational error associated with nutrient flux estimates based on partial fractions and infrequent sampling. The daily records were artificially decimated to create 7 stratified sampling records, 7 weekly records, and 30 monthly records from each WY and catchment. These were used to evaluate the impact of sampling frequency on load estimate uncertainty. The analysis underlines the high uncertainty of load estimates based on monthly data and individual P fractions rather than total P. Catchments with a high baseflow index and/or low population density were found to return a lower RMSE on load estimates when sampled infrequently than those with a tow baseflow index and high population density. Catchment size was not shown to be important, though a limitation of this study is that daily records may fail to capture the full range of P export behaviour in smaller catchments with flashy hydrographs, leading to an underestimate of uncertainty in Load estimates for such catchments. Further analysis of sub-daily records is needed to investigate this fully. Here, recommendations are given on load estimation methodologies for different catchment types sampled at different frequencies, and the ways in which this analysis can be used to identify observational error and uncertainty for model calibration and nutrient budgeting studies. (c) 2006 Elsevier B.V. All rights reserved.

Time course of gag protein assembly in HIV-1-infected cells: a study by immunoelectron microscopy

Recent biochemical studies have identified high molecular complexes of the HIV Gag precursor in the cytosol of infected cells. Using immunoelectron microscopy we studied the time course of the synthesis and assembly of a HIV Gag precursor protein (pr55gag) in Sf9 cells infected with recombinant baculovirus expressing the HIV gag gene. We also immunolabeled for pr55gag human T4 cells acutely or chronically infected with HIV-1. In Sf9 cells, the time course study showed that the first Gag protein appeared in the cytoplasm at 28-30 h p.i. and that budding started 6-8 h later. Colloidal gold particles, used to visualize the Gag protein, were first scattered randomly throughout the cytoplasm, but soon clusters representing 100 to 1000 copies of pr55gag were also observed. By contrast, in cells with budding or released virus-like particles the cytoplasm was virtually free of gold particles while the released virus-like particles were heavily labeled. Statistical analysis showed that between 80 and 90% of the gold particles in the cytoplasm were seen as singles, as doublets, or in small groups of up to five particles probably representing small oligomers. Clusters of gold particles were also observed in acutely infected lymphocytes as well as in multinuclear cells of chronically infected cultures of T4 cells. In a few cases small aggregates of gold particles were found in the nuclei of T4 lymphocytes. These observations suggest that the Gag polyprotein forms small oligomers in the cytoplasm of expressing cells but that assembly into multimeric complexes takes place predominantly at the plasma membrane. Large accumulations of Gag protein in the cytoplasm may represent misfolded molecules destined for degradation.

Time course of oculomotor inhibition revealed by saccade trajectory modulation

Selecting a stimulus as the target for a goal-directed movement involves inhibiting other competing possible responses. Both target and distractor stimuli activate populations of neurons in topographic oculomotor maps such as the superior colliculus. Local inhibitory interconnections between these populations ensure only one saccade target is selected. Suppressing saccades to distractors may additionally involve inhibiting corresponding map regions to bias the local competition. Behavioral evidence of these inhibitory processes comes from the effects of distractors on oculomotor and manual trajectories. Individual saccades may initially deviate either toward or away from a distractor, but the source of this variability has not been investigated. Here we investigate the relation between distractor-related deviation of trajectory and saccade latency. Targets were presented with, or without, distractors, and the deviation of saccade trajectories arising from the presence of distractors was measured. A fixation gap paradigm was used to manipulate latency independently of the influence of competing distractors. Shorter- latency saccades deviated toward distractors and longer-latency saccades deviated away from distractors. The transition between deviation toward or away from distractors occurred at a saccade latency of around 200 ms. This shows that the time course of the inhibitory process involved in distractor related suppression is relatively slow.

An analysis of real time implementation of Fourier transform-based frequency recognition algorithms

Frequency recognition is an important task in many engineering fields such as audio signal processing and telecommunications engineering, for example in applications like Dual-Tone Multi-Frequency (DTMF) detection or the recognition of the carrier frequency of a Global Positioning, System (GPS) signal. This paper will present results of investigations on several common Fourier Transform-based frequency recognition algorithms implemented in real time on a Texas Instruments (TI) TMS320C6713 Digital Signal Processor (DSP) core. In addition, suitable metrics are going to be evaluated in order to ascertain which of these selected algorithms is appropriate for audio signal processing(1).