Total ozone time series analysis: a neural network model approach

International audienceThis work is focused on the application of neural network based models to the analysis of total ozone (TO) time series. Processes that affect total ozone are extremely non linear, especially at the considered European mid-latitudes. Artificial neural networks (ANNs) are intrinsically non-linear systems, hence they are expected to cope with TO series better than classical statistics do. Moreover, neural networks do not assume the stationarity of the data series so they are also able to follow time-changing situations among the implicated variables. These two features turn NNs into a promising tool to catch the interactions between atmospheric variables, and therefore to extract as much information as possible from the available data in order to make, for example, time series reconstructions or future predictions. Models based on NNs have also proved to be very suitable for the treatment of missing values within the data series. In this paper we present several models based on neural networks to fill the missing periods of data within a total ozone time series, and models able to reconstruct the data series. The results released by the ANNs have been compared with those obtained by using classical statistics methods, and better accuracy has been achieved with the non linear ANNs techniques. Different network structures and training strategies have been tested depending on the specific task to be accomplished

The middle atmospheric meridional circulation for 2002–2012 derived from MIPAS observations

Measurements of long-lived trace gases (SF6, CFC-11, CFC-12, HCFC-22, CCl4, N2O, CH4, H2O, and CO) performed with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) have been used to infer the stratospheric and mesospheric meridional circulation. The MIPAS data set covers the time period from July 2002 to April 2012. The method used for this purpose was the direct inversion of the two-dimensional continuity equation for the concentrations of trace gases and air density. This inversion predicts an “effective velocity” that gives the best fit for the evolution of the concentrations on the assumption that an explicit treatment of Fickian diffusion can be neglected. These effective velocity fields are used to characterize the mean meridional circulation. Multiannual monthly mean effective velocity fields are presented, along with their variabilities. According to this measure, the stratospheric circulation is found to be highly variable over the year, with a quite robust annual cycle. The new method allows us to track the evolution of various circulation patterns over the year in more detail than before. According to the effective velocity characterization of the circulation, the deep branch of the Brewer–Dobson circulation and the mesospheric overturning pole-to-pole circulation are not separate but intertwined phenomena. The latitude of stratospheric uplift in the middle and upper stratosphere is found to be quite variable and is not always found at equatorial latitudes. The usual schematic of stratospheric circulation with the deep and the shallow branch of the Brewer–Dobson circulation and the mesospheric overturning circulation is an idealization which best describes the observed atmosphere around equinox. Sudden stratospheric warmings and the quasi-biennial oscillation cause a pronounced year-to-year variability of the meridional circulation.</p

Artificial Neural Network to predict mean monthly total ozone in Arosa, Switzerland

Present study deals with the mean monthly total ozone time series over Arosa, Switzerland. The study period is 1932-1971. First of all, the total ozone time series has been identified as a complex system and then Artificial Neural Networks models in the form of Multilayer Perceptron with back propagation learning have been developed. The models are Single-hidden-layer and Two-hidden-layer Perceptrons with sigmoid activation function. After sequential learning with learning rate 0.9 the peak total ozone period (February-May) concentrations of mean monthly total ozone have been predicted by the two neural net models. After training and validation, both of the models are found skillful. But, Two-hidden-layer Perceptron is found to be more adroit in predicting the mean monthly total ozone concentrations over the aforesaid period.Comment: 22 pages, 14 figure

Summary and Highlights of the SPARC-Reanalysis Intercomparison Project

The climate research community uses global atmospheric reanalysis data sets to understand a wide range of processes and variability in the atmosphere; they are a particularly powerful tool for studying phenomena that cannot be directly observed. Different reanalyses may give very different results for the same diagnostics. The Stratosphere troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP) is a coordinated activity to compare key diagnostics that are important for stratospheric processes and their tropospheric connections among available reanalyses. S-RIP has been identifying differences among reanalyses and their underlying causes, providing guidance on appropriate usage of reanalysis products in scientific studies (particularly those of relevance to SPARC), and contributing to future improvements in the reanalysis products by establishing collaborative links between reanalysis centres and data users. S-RIP emphasizes diagnostics of the upper troposphere, stratosphere, and lower mesosphere. The draft S-RIP final report is expected to be completed in 2018. This poster gives a summary of the S-RIP project and presents highlights including results on the Brewer-Dobson circulation, stratosphere/troposphere dynamical coupling, the extra-tropical upper troposphere / lower stratosphere, the tropical tropopause layer, the quasi-biennial oscillation, lower stratospheric polar processing, and the upper stratosphere/lower mesosphere

SEAS5: the new ECMWF seasonal forecast system

In this paper we describe SEAS5, ECMWF's fifth generation seasonal forecast system, which became operational in November 2017. Compared to its predecessor, System 4, SEAS5 is a substantially changed forecast system. It includes upgraded versions of the atmosphere and ocean models at higher resolutions, and adds a prognostic sea-ice model. Here, we describe the configuration of SEAS5 and summarise the most noticeable results from a set of diagnostics including biases, variability, teleconnections and forecast skill. An important improvement in SEAS5 is the reduction of the equatorial Pacific cold tongue bias, which is accompanied by a more realistic El Niño amplitude and an improvement in El Niño prediction skill over the central-west Pacific. Improvements in 2&thinsp;m temperature skill are also clear over the tropical Pacific. Sea-surface temperature (SST) biases in the northern extratropics change due to increased ocean resolution, especially in regions associated with western boundary currents. The increased ocean resolution exposes a new problem in the northwest Atlantic, where SEAS5 fails to capture decadal variability of the North Atlantic subpolar gyre, resulting in a degradation of DJF 2&thinsp;m temperature prediction skill in this region. The prognostic sea-ice model improves seasonal predictions of sea-ice cover, although some regions and seasons suffer from biases introduced by employing a fully dynamical model rather than the simple, empirical scheme used in System 4. There are also improvements in 2&thinsp;m temperature skill in the vicinity of the Arctic sea-ice edge. Cold temperature biases in the troposphere improve, but increase at the tropopause. Biases in the extratropical jets are larger than in System 4: extratropical jets are too strong, and displaced northwards in JJA. In summary, development and added complexity since System 4 has ensured that SEAS5 is a state-of-the-art seasonal forecast system which continues to display a particular strength in the El Niño Southern Oscillation (ENSO) prediction.</p

Observed and simulated time evolution of HCl, ClONO2, and HF total column abundances

Time series of total column abundances of hydrogen chloride (HCl), chlorine nitrate (ClONO2), and hydrogen fluoride (HF) were determined from ground-based Fourier transform infrared (FTIR) spectra recorded at 17 sites belonging to the Network for the Detection of Atmospheric Composition Change (NDACC) and located between 80.05°N and 77.82°S. By providing such a near-global overview on ground-based measurements of the two major stratospheric chlorine reservoir species, HCl and ClONO2, the present study is able to confirm the decrease of the atmospheric inorganic chlorine abundance during the last few years. This decrease is expected following the 1987 Montreal Protocol and its amendments and adjustments, where restrictions and a subsequent phase-out of the prominent anthropogenic chlorine source gases (solvents, chlorofluorocarbons) were agreed upon to enable a stabilisation and recovery of the stratospheric ozone layer. The atmospheric fluorine content is expected to be influenced by the Montreal Protocol, too, because most of the banned anthropogenic gases also represent important fluorine sources. But many of the substitutes to the banned gases also contain fluorine so that the HF total column abundance is expected to have continued to increase during the last few years. The measurements are compared with calculations from five different models: the two-dimensional Bremen model, the two chemistry-transport models KASIMA and SLIMCAT, and the two chemistry-climate models EMAC and SOCOL. Thereby, the ability of the models to reproduce the absolute total column amounts, the seasonal cycles, and the temporal evolution found in the FTIR measurements is investigated and inter-compared. This is especially interesting because the models have different architectures. The overall agreement between the measurements and models for the total column abundances and the seasonal cycles is good. Linear trends of HCl, ClONO2, and HF are calculated from both measurement and model time series data, with a focus on the time range 2000–2009. This period is chosen because from most of the measurement sites taking part in this study, data are available during these years. The precision of the trends is estimated with the bootstrap resampling method. The sensitivity of the trend results with respect to the fitting function, the time of year chosen and time series length is investigated, as well as a bias due to the irregular sampling of the measurements. The measurements and model results investigated here agree qualitatively on a decrease of the chlorine species by around 1%yr-1. The models simulate an increase of HF of around 1%yr-1. This also agrees well with most of the measurements, but some of the FTIR series in the Northern Hemisphere show a stabilisation or even a decrease in the last few years. In general, for all three gases, the measured trends vary more strongly with latitude and hemisphere than the modelled trends. Relative to the FTIR measurements, the models tend to underestimate the decreasing chlorine trends and to overestimate the fluorine increase in the Northern Hemisphere. At most sites, the models simulate a stronger decrease of ClONO2 than of HCl. In the FTIR measurements, this difference between the trends of HCl and ClONO2 depends strongly on latitude, especially in the Northern Hemisphere.Peer reviewe

Microbiological testing of adults hospitalised with community-acquired pneumonia: An international study

This study aimed to describe real-life microbiological testing of adults hospitalised with community-acquired pneumonia (CAP) and to assess concordance with the 2007 Infectious Diseases Society of America (IDSA)/American Thoracic Society (ATS) and 2011 European Respiratory Society (ERS) CAP guidelines. This was a cohort study based on the Global Initiative for Methicillin-resistant Staphylococcus aureus Pneumonia (GLIMP) database, which contains point-prevalence data on adults hospitalised with CAP across 54 countries during 2015. In total, 3702 patients were included. Testing was performed in 3217 patients, and included blood culture (71.1%), sputum culture (61.8%), Legionella urinary antigen test (30.1%), pneumococcal urinary antigen test (30.0%), viral testing (14.9%), acute-phase serology (8.8%), bronchoalveolar lavage culture (8.4%) and pleural fluid culture (3.2%). A pathogen was detected in 1173 (36.5%) patients. Testing attitudes varied significantly according to geography and disease severity. Testing was concordant with IDSA/ATS and ERS guidelines in 16.7% and 23.9% of patients, respectively. IDSA/ATS concordance was higher in Europe than in North America (21.5% versus 9.8%; p&lt;0.01), while ERS concordance was higher in North America than in Europe (33.5% versus 19.5%; p&lt;0.01). Testing practices of adults hospitalised with CAP varied significantly by geography and disease severity. There was a wide discordance between real-life testing practices and IDSA/ATS/ERS guideline recommendations

Prevalence and etiology of community-acquired pneumonia in immunocompromised patients

Background. The correct management of immunocompromised patients with pneumonia is debated. We evaluated the prevalence, risk factors, and characteristics of immunocompromised patients coming from the community with pneumonia. Methods. We conducted a secondary analysis of an international, multicenter study enrolling adult patients coming from the community with pneumonia and hospitalized in 222 hospitals in 54 countries worldwide. Risk factors for immunocompromise included AIDS, aplastic anemia, asplenia, hematological cancer, chemotherapy, neutropenia, biological drug use, lung transplantation, chronic steroid use, and solid tumor. Results. At least 1 risk factor for immunocompromise was recorded in 18% of the 3702 patients enrolled. The prevalences of risk factors significantly differed across continents and countries, with chronic steroid use (45%), hematological cancer (25%), and chemotherapy (22%) the most common. Among immunocompromised patients, community-acquired pneumonia (CAP) pathogens were the most frequently identified, and prevalences did not differ from those in immunocompetent patients. Risk factors for immunocompromise were independently associated with neither Pseudomonas aeruginosa nor non\u2013community-acquired bacteria. Specific risk factors were independently associated with fungal infections (odds ratio for AIDS and hematological cancer, 15.10 and 4.65, respectively; both P = .001), mycobacterial infections (AIDS; P = .006), and viral infections other than influenza (hematological cancer, 5.49; P < .001). Conclusions. Our findings could be considered by clinicians in prescribing empiric antibiotic therapy for CAP in immunocompromised patients. Patients with AIDS and hematological cancer admitted with CAP may have higher prevalences of fungi, mycobacteria, and noninfluenza viruses

Burden and risk factors for Pseudomonas aeruginosa community-acquired pneumonia:a Multinational Point Prevalence Study of Hospitalised Patients

Pseudornonas aeruginosa is a challenging bacterium to treat due to its intrinsic resistance to the antibiotics used most frequently in patients with community-acquired pneumonia (CAP). Data about the global burden and risk factors associated with P. aeruginosa-CAP are limited. We assessed the multinational burden and specific risk factors associated with P. aeruginosa-CAP. We enrolled 3193 patients in 54 countries with confirmed diagnosis of CAP who underwent microbiological testing at admission. Prevalence was calculated according to the identification of P. aeruginosa. Logistic regression analysis was used to identify risk factors for antibiotic-susceptible and antibiotic-resistant P. aeruginosa-CAP. The prevalence of P. aeruginosa and antibiotic-resistant P. aeruginosa-CAP was 4.2% and 2.0%, respectively. The rate of P. aeruginosa CAP in patients with prior infection/colonisation due to P. aeruginosa and at least one of the three independently associated chronic lung diseases (i.e. tracheostomy, bronchiectasis and/or very severe chronic obstructive pulmonary disease) was 67%. In contrast, the rate of P. aeruginosa-CAP was 2% in patients without prior P. aeruginosa infection/colonisation and none of the selected chronic lung diseases. The multinational prevalence of P. aeruginosa-CAP is low. The risk factors identified in this study may guide healthcare professionals in deciding empirical antibiotic coverage for CAP patients