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Abstract. This paper presents validation results of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System MACC (Monitoring Atmospheric Composition and Climate) re-analysis aerosol optical depth (AOD) for the period [2003][2004][2005][2006]. We evaluate the MACC AOD at a UV wavelength (340 nm) and at mid-visible (500 and 550 nm) by comparing against ground-based AERONET measurements at 12 sites. The AERONET sites cover various parts of the globe and are categorized in three groups: urban/anthropogenic, biomass burning and dust, depending on the typically dominating aerosol type. This is the first time a global model such as the ECMWF has been evaluated for the performance of AOD at a UV wavelength. The results show that the MACC system generally provides a good representation of the AOD on a monthly basis, showing a realistic seasonal cycle. The model is mostly able to capture major dust load events and also the peak months of biomass burning correctly. For Kanpur and Solar Village, however, the model overestimates the AOD during the monsoon period when the aerosol load is generally low. When comparing hourly AOD values, the modelmeasurement agreement is better for biomass burning and dust sites than for urban sites, with an average correlation coefficient around 0.90 for biomass burning sites, around 0.77 for dust sites, and below 0.70 for urban sites. The AOD at 500 nm averaged over all sites shows only a small systematic difference between modeled and measured values, with a relative mean bias of 0.02. However, for the AOD at 340 nm the relative mean bias is −0.2. All sites included in the study show a relative mean bias at 340 nm smaller (or more negative) than that at 500 nm, indicating a strong wavelength dependence in the performance of the AOD in the MACC system. A comparison against fine and coarse mode AOD of the AERONET indicates that this has to do with the size distribution of the model: generally, the ECMWF model overestimates the contribution by coarse mode particles.

Despite advances in the treatment of patients with human immunodeficiency virus (HIV), HIV-associated neurocognitive disorder occurs in 15-50% of HIV-infected individuals, and may become more apparent as ageing advances. In the present study we investigated regional cerebral blood flow (rCBF) and regional cerebral metabolic rate of glucose uptake (rCMRglc) in medically and psychiatrically stable HIV-1-infected participants in two age-groups. Positron emission tomography (PET) and magnetic resonance imaging (MRI)-based arterial spin labeling (ASL) were used to measure rCMRglc and rCBF, respectively, in 35 HIV-infected participants and 37 HIV-negative matched controls. All participants were currently asymptomatic with undetectable HIV-1 viral loads, without medical or psychiatric comorbidity, alcohol or substance misuse, stable on medication for at least 6 months before enrolment in the study. We found significant age effects on both ASL and PET with reduced rCBF and rCMRglc in related frontal brain regions, and consistent, although small, reductions in rCBF and rCMRglc in the anterior cingulate cortex (ACC) in HIV, a finding of potential clinical significance. There was no significant interaction between HIV status and the ageing process, and no significant HIV-related changes elsewhere in the brain on PET or ASL. This is the first paper to combine evidence from ASL and PET method in HIV participants. These finding provide evidence of crossvalidity between the two techniques, both in ageing and a clinical condition (HIV).

There are very few case series of patients with acute psychogenic memory loss (also known as dissociative/functional amnesia), and still fewer studies of outcome, or comparisons with neurological memory-disordered patients. Consequently, the literature on psychogenic amnesia is somewhat fragmented and offers little prognostic value for individual patients. In the present study, we reviewed the case records and neuropsychological findings in 53 psychogenic amnesia cases (ratio of 3:1, males:females), in comparison with 21 consecutively recruited neurological memory-disordered patients and 14 healthy control subjects. In particular, we examined the pattern of retrograde amnesia on an assessment of autobiographical memory (the Autobiographical Memory Interview). We found that our patients with psychogenic memory loss fell into four distinct groups, which we categorized as: (i) fugue state; (ii) fugue-to-focal retrograde amnesia; (iii) psychogenic focal retrograde amnesia following a minor neurological episode; and (iv) patients with gaps in their memories. While neurological cases were characterized by relevant neurological symptoms, a history of a past head injury was actually more common in our psychogenic cases (P = 0.012), perhaps reflecting a 'learning episode' predisposing to later psychological amnesia. As anticipated, loss of the sense of personal identity was confined to the psychogenic group. However, clinical depression, family/relationship problems, financial/employment problems, and failure to recognize the family were also statistically more common in that group. The pattern of autobiographical memory loss differed between the psychogenic groups: fugue cases showed a severe and uniform loss of memories for both facts and events across all time periods, whereas the two focal retrograde amnesia groups showed a 'reversed' temporal gradient with relative sparing of recent memories. After 3-6 months, the fugue patients had improved to normal scores for facts and near-normal scores for events. By contrast, the two focal retrograde amnesia groups showed less improvement and continued to show a reversed temporal gradient. In conclusion, the outcome in psychogenic amnesia, particularly those characterized by fugue, is better than generally supposed. Findings are interpreted in terms of Markowitsch's and Kopelman's models of psychogenic amnesia, and with respect to Anderson's neuroimaging findings in memory inhibition.

Publications in atmospheric sciences typically neglect biases caused by regression dilution (bias of the ordinary least squares line fitting) and regression to the mean (RTM) in comparisons of uncertain data. We use synthetic observations mimicking real atmospheric data to demonstrate how the biases arise from random data uncertainties of measurements, model output, or satellite retrieval products. Further, we provide examples of typical methods of data comparisons that have a tendency to pronounce the biases. The results show, that data uncertainties can significantly bias data comparisons due to regression dilution and RTM, a fact that is known in statistics but disregarded in atmospheric sciences. Thus, we argue that often these biases are widely regarded as measurement or modeling errors, for instance, while they in fact are artificial. It is essential that atmospheric and geoscience communities become aware of and consider these features in research.

Abstract. Spectral solar UV radiation measurements are performed in France using three spectroradiometers located at very different sites. One is installed in Villeneuve d'Ascq, in the north of France (VDA). It is an urban site in a topographically flat region. Another instrument is installed in Observatoire de Haute-Provence, located in the southern French Alps (OHP). It is a rural mountainous site. The third instrument is installed in Saint-Denis, Réunion Island (SDR). It is a coastal urban site on a small mountainous island in the southern tropics. The three instruments are affiliated with the Network for the Detection of Atmospheric Composition Change (NDACC) and carry out routine measurements to monitor the spectral solar UV radiation and enable derivation of UV index (UVI). The ground-based UVI values observed at solar noon are compared to similar quantities derived from the Ozone Monitoring Instrument (OMI, onboard the Aura satellite) and the second Global Ozone Monitoring Experiment (GOME-2, onboard the Metop-A satellite) measurements for validation of these satellite-based products. The present study concerns the period 2009-September 2012, date of the implementation of a new OMI processing tool. The new version (v1.3) introduces a correction for absorbing aerosols that were not considered in the old version (v1.2).Both versions of the OMI UVI products were available before September 2012 and are used to assess the improvement of the new processing tool. On average, estimates from satellite instruments always overestimate surface UVI at solar noon. Under cloudless conditions, the satellite-derived estimates of UVI compare satisfactorily with ground-based data: the median relative bias is less than 8 % at VDA and 4 % at SDR for both OMI v1.3 and GOME-2, and about 6 % for OMI v1.3 and 2 % for GOME-2 at OHP. The correlation between satellite-based and ground-based data is better at VDA and OHP (about 0.99) than at SDR (0.96) for both space-borne instruments. For all sky conditions, the median relative biases are much larger, with large dispersion for both instruments at all sites (VDA: about 12 %; OHP: 9 %; SDR: 11 %). Correlation between satellite-based and ground-based data is still better at VDA and OHP (about 0.95) than at SDR (about 0.73) for both satellite instruments. These results are explained considering the time of overpass of the two satellites, which is far from solar noon, preventing a good estimation of the cloud cover necessary for a good modelling of the UVI. Site topography and environment are shown to have a non-significant influence. At VDA and OHP, OMI Published by Copernicus Publications on behalf of the European Geosciences Union.

Abstract. We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different wavelengths (0.47, 0.55, 0.64, and 2.1 µm). The accuracy of the new algorithm is evaluated by comparing the AOD retrievals to Aerosol Robotic Network (AERONET) AOD. The results show that the BAR significantly improves the accuracy of AOD retrievals over the operational Dark Target (DT) algorithm. A reduction of about 29 % in the AOD root mean square error and decrease of about 80 % in the median bias of AOD were found globally when the BAR was used instead of the DT algorithm. Furthermore, the fraction of AOD retrievals inside the ±(0.05+15%) expected error envelope increased from 55 to 76 %. In addition to retrieving the values of AOD, FMF, and surface reflectance, the BAR also gives pixel-level posterior uncertainty estimates for the retrieved parameters. The BAR algorithm always results in physical, non-negative AOD values, and the average computation time for a single granule was less than a minute on a modern personal computer.