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Accurate information about uncertainties is required in nearly all data analyses, e.g., inter-comparisons, data assimilation, combined use. Validation of precision estimates (viz., the random component of estimated uncertainty) is important for remote sensing measurements, which provide the information about atmospheric parameters by solving an inverse problem. For the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument, this is a real challenge, due to the dependence of the signal-to-noise ratio (and thus precision estimates) on stellar properties, small number of self-collocated measurements, and growing noise as a function of time due to instrument aging. The estimated ozone uncertainties are small in the stratosphere for bright star occultations, which complicates validation of precision values, given the natural ozone variability. In this paper, we discuss different methods for geophysical validation of precision estimates and their applicability to GOMOS data. We propose a simple method for validation of GOMOS precision estimates for ozone in the stratosphere. This method is based on comparisons of differences in sample variance with differences in uncertainty estimates for measurements from different stars selected in a region of small natural variability. For GOMOS, the difference in sample variances for different stars at tangent altitudes 25-45 km is well explained by the difference in squared precisions, if the stars are not dim. Since this is observed for several stars, and since normalized X2 is close to 1 for these occultations in the stratosphere, we conclude that the GOMOS precision estimates are realistic in occultations of sufficiently bright stars. For dim stars, errors are overestimated due to improper accounting of the dark charge correction uncertainty in the error budget. The proposed method can also be applied to stratospheric ozone data from other instruments, including multi-instrument analyses. [ABSTRACT FROM AUTHOR]

Accurate information about uncertainties is required in nearly all data analyses (intercomparisons, data assimilation, combined use, etc.). Validation of precision estimates (viz., the random component of estimated uncertainty) is important for remote sensing measurements, which provide the information about atmospheric parameters via solving an inverse problem. For the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument, it is of a real challenge, due to dependence of signal-to-noise ratio (and thus precision estimates) on stellar properties, small number of self-collocated measurements, and uncertainty estimates growing with time due to instrument ageing. Estimated uncertainties of ozone retrievals are small in the stratosphere for bright stars, which results in additional complexity of detecting them on the background of natural ozone variability. In this paper, we discuss different methods for geophysical validation of precision estimates and their applicability to GOMOS data. We propose a simple method for validation of GOMOS precision estimates for ozone in the stratosphere. This method is based on comparisons of difference in sample variance with the difference in uncertainty estimates for measurements from different stars selected in a region of small natural variability. For GOMOS, the difference in sample variances for different stars at altitudes 25- 45 km is well explained by the difference in squared precisions, if stars are not dim. Since it is observed for several stars, and since normalized χ2 is close to 1 in these occultations in the stratosphere, we can conclude that GOMOS precision estimates are realistic in occultations of sufficiently bright stars. For dim stars, errors are overestimated due to improper accounting for the dark charge correction uncertainty in the error budget. The proposed method can also be applied to stratospheric ozone data from other instruments, including multi-instrument analyses. [ABSTRACT FROM AUTHOR]

The article presents a study that compares two unique satellite-borne data sets of nitrogen trioxide (NO3) vertical profiles. The two data sets compared are the Global Ozone Monitoring by the Occultation of Stars (GOMOS) and the Stratospheric Aerosol and Gas Experiment (SAGE III) nitrogen trioxide (NO3). The study suggests that the median difference between the two data sets is within 25 percent.

The article presents a study which compares Global Ozone Monitoring by the Occultation of Stars (GOMOS) stellar occultations and Strato-5 spheric Aerosols and Gas Experiment (SAGE) lunar occultations III radical nitrate (NO3) vertical profiles. The study discovers an agreement between satellite-borne data sets of NO3 vertical and zonal median profiles. Through direct comparison with these observations, it verifies accuracies of the NO3 quantification.

Centrifugal pumps are often used in operating conditions where they can be susceptible to premature failure. The cavitation phenomenon can be considered as a typical cause of pump failure as it erodes the internal parts of the pump and deteriorates the pump performance. The cavitation phenomenon can be detected by means of external measurements, for instance by monitoring the pump vibration. However, the use of additional sensors results in additional costs, which favours the use of sensorless methods in the field of condition monitoring. In this article, a novel method for detecting cavitation in a centrifugal pump with a frequency converter is proposed. The method is based on the frequency converter's estimates for the rotational speed and shaft torque of the pump. The method has been tested in the laboratory with two different pumping systems and the obtained results are presented. Test results show that high flow cavitation can be detected by the proposed method. [ABSTRACT FROM AUTHOR]

GOMOS (Global Ozone Monitoring by Occultation of Stars) on board Envisat measures O3, NO2, NO3, neutral density, aerosols, H2O, and O2, in the stratosphere and mesosphere by detecting absorption of starlight in ultraviolet, visible and near-infrared wavelengths. During bright limb conditions GOMOS will also observe scattered solar radiation. GOMOS will deliver ozone concentration profiles at altitudes 15–100 km with a vertical sampling better than 1.7 km and with a global coverage. As a self-calibrating method stellar occultation measurements provide a basis for a long-term global monitoring of ozone profiles. We will present here the status of the GOMOS instrument and show samples of first results obtained in 2002. [Copyright &y& Elsevier]

We have created a daytime ozone profile data set from the measurements of the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the Envisat satellite. This so-called GOMOS bright limb (GBL) data set contains ∼ 358 000 stratospheric daytime ozone profiles measured by GOMOS in 2002-2012. The GBL data set complements the widely used GOMOS nighttime data based on stellar occultation measurements. The GBL data set is based on the GOMOS daytime occultations but instead of the transmitted star light we use limb-scattered solar light. The ozone profiles retrieved from these radiance spectra cover the 18-60 km altitude range and have approximately 2-3 km vertical resolution. We show that these profiles are generally in better than 10% agreement with the NDACC (Network for the Detection of Atmospheric Composition Change) ozonesonde profiles and with the GOMOS nighttime, MLS (Microwave Limb Sounder), and OSIRIS (Optical Spectrograph and InfraRed Imager System) satellite measurements. However, there is a 10-13% negative bias at 40 km altitude and a 10-50% positive bias at 50 km for solar zenith angles > 75°. These biases are most likely caused by stray light which is difficult to characterize and to remove entirely from the measured spectra. Nevertheless, the GBL data set approximately doubles the amount of useful GOMOS ozone profiles and improves coverage of the summer pole. [ABSTRACT FROM AUTHOR]

We have created a daytime ozone profile data set from the measurements of the Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the Envisat satellite. This so-called GOMOS bright limb (GBL) data set contains ~ 358 000 strato- spheric daytime ozone profiles measured by GOMOS in 2002-2012. The GBL data set complements the widely used GOMOS night-time data based on stellar occultation measurements. The GBL data set is based on the GOMOS daytime occultations but instead of the transmitted star light, we use limb scattered solar light. The ozone profiles retrieved from these radiance spectra cover 18-60km tangent height range and have approximately 2-3 km vertical resolution. We show that these profiles are generally in better than 10% agreement with the NDACC (Network for the Detection of Atmospheric Composition Change) ozone sounding profiles and with the GOMOS night-time, MLS (Microwave Limb Sounder), and OSIRIS (Optical Spectrograph, and InfraRed Imaging System) satellite measurements. However, there is a 10-13% negative bias at 40 km tangent height and a 10-50% positive bias at 50 km when the solar zenith angle > 75°. These biases are most likely caused by stray light which is difficult to characterize and remove entirely from the measured spectra. Nevertheless, the GBL data set approximately doubles the amount of useful GOMOS ozone profiles and improves coverage of the summer pole. [ABSTRACT FROM AUTHOR]

We study uncertainty quantification in remote sensing of aerosols in the atmosphere with top of the atmosphere reflectance measurements from the nadir-viewing Ozone Monitoring Instrument (OMI). Focus is on the uncertainty in aerosol model selection of pre-calculated aerosol models and on the statistical modelling of the model inadequacies. The aim is to apply statistical methodologies that improve the uncertainty estimates of the aerosol optical thickness (AOT) retrieval by propagating model selection and model error related uncertainties more realistically. We utilise Bayesian model selection and model averaging methods for the model selection problem and use Gaussian processes to model the smooth systematic discrepancies from the modelled to observed reflectance. The systematic model error is learned from an ensemble of operational retrievals. The operational OMI multi-wavelength aerosol retrieval algorithm OMAERO is used for cloud free, over land pixels of the OMI instrument with the additional Bayesian model selection and model discrepancy techniques. The method is demonstrated with four examples with different aerosol properties: weakly absorbing aerosols, forest fires over Greece and Russia, and Sahara dessert dust. The presented statistical methodology is general; it is not restricted to this particular satellite retrieval application. [ABSTRACT FROM AUTHOR]

In this paper, we present a HARMonized dataset of OZone profiles (HARMOZ) based on limb and occultation measurements from Envisat (GOMOS, MIPAS and SCIAMACHY), Odin (OSIRIS, SMR) and SCISAT (ACE-FTS) satellite instruments. These measurements provide high-vertical-resolution ozone profiles covering the altitude range from the upper troposphere up to the mesosphere in years 2001-2012. HARMOZ has been created in the framework of the European Space Agency Climate Change Initiative project. The harmonized dataset consists of original retrieved ozone profiles from each instrument, which are screened for invalid data by the instrument teams. While the original ozone profiles are presented in different units and on different vertical grids, the harmonized dataset is given on a common pressure grid in netCDF (network common data form)-4 format. The pressure grid corresponds to vertical sampling of ~ 1 km below 20 km and 2-3 km above 20 km. The vertical range of the ozone profiles is specific for each instrument, thus all information contained in the original data is preserved. Provided altitude and temperature profiles allow the representation of ozone profiles in number density or mixing ratio on a pressure or altitude vertical grid. Geolocation, uncertainty estimates and vertical resolution are provided for each profile. For each instrument, optional parameters, which are related to the data quality, are also included. For convenience of users, tables of biases between each pair of instruments for each month, as well as bias uncertainties, are provided. These tables characterize the data consistency and can be used in various bias and drift analyses, which are needed, for instance, for combining several datasets to obtain a long-term climate dataset. This user-friendly dataset can be interesting and useful for various analyses and applications, such as data merging, data validation, assimilation and scientific research. [ABSTRACT FROM AUTHOR]

Abstract: With the successful launch of the European Space Agency’s Envisat satellite new possibilities for global night-time measurements of middle atmospheric ozone have emerged. The GOMOS and MIPAS instruments on board Envisat are able to measure ozone in both day and night conditions, which is especially important in the mesosphere where the diurnal variations of ozone are substantial. In this paper, we present a comparison of MIPAS and GOMOS night-time measurements. We show individual measurement profiles as well as statistical average profiles of stratospheric and mesospheric ozone from both instruments. Our conclusion is that the two instruments are generally in a good agreement throughout the middle atmosphere. [Copyright &y& Elsevier]

Single crystal X-ray structures (monoclinic space group P21) for methyl 3-oxo-5β-cholan-24-oate and methyl 3,12-dioxo-5β-cholan-24-oate have been solved and compared with HF/6-31G* optimised structures. In the crystalline packings the side chains are connected with weak OC(sp3)H⋯O-type of interactions between C25–H and C24–O–C25 and the keto ends with weak C(sp3)H⋯O...C-type of interactions between C4–Hand O...C3. The orientations of the side chains, which steric configurations are of great importance to the biological activity of the molecules, are compared with the experimental structure of methyl 3α-hydroxy-5β-cholan-24-oate. Probable reasons for the observed differences are discussed. In addition, 13C and 17O NMR chemical shifts of methyl 3-oxo-5β-cholan-24-oate and methyl 3,12-dioxo-5β-cholan-24-oate as well as the epimeric methyl 3α-hydroxy-5β-cholan-24-oate and methyl 3β-hydroxy-5β-cholan-24-oate have been calculated (DFT/B3LYP/6-311G*) and compared with the experimental values by linear regression analyses. In general, the correspondence between the theoretical and experimental parameters is good or excellent. [Copyright &y& Elsevier]

The three Global Ozone Monitoring Experiment- 2 instruments will provide unique and long data sets for atmospheric research and applications. The complete time period will be 2007-2022, including the period of ozone depletion as well as the beginning of ozone layer recovery. Besides ozone chemistry, the GOME-2 (Global Ozone Monitoring Experiment-2) products are important e.g. for air quality studies, climate modelling, policy monitoring and hazard warnings. The heritage for GOME-2 is in the ERS/GOME and Envisat/SCIAMACHY instruments. The current Level 2 (L2) data cover a wide range of products such as ozone and minor trace gas columns (NO2, BrO, HCHO, H2O, SO2), vertical ozone profiles in high and low spatial resolution, absorbing aerosol indices, surface Lambertian-equivalent reflectivity database, clear-sky and cloud-corrected UV indices and surface UV fields with different weightings and photolysis rates. The Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M SAF) processes and disseminates data 24/7. Data quality is guaranteed by the detailed review processes for the algorithms, validation of the products as well as by a continuous quality monitoring of the products and processing. This paper provides an overview of the O3M SAF project background, current status and future plans for the utilisation of the GOME-2 data. An important focus is the provision of summaries of the GOME-2 products including product principles and validation examples together with sample images. Furthermore, this paper collects references to the detailed product algorithm and validation papers. [ABSTRACT FROM AUTHOR]

This paper presents a comparison of vertical ozone profiles retrieved by the Ozone ProfilE Retrieval Algorithm (OPERA) (versions 1.14-1.24) from the Global Ozone Monitoring Experiment-2 (GOME-2) measurements on board the Meteorological operational Metop-A satellite with spaceborne high-vertical-resolution ozone profiles by Global Ozone Monitoring by Occultation of Stars (GOMOS), Optical Spectrograph and Infrared Imager System (OSIRIS) and Microwave Limb Sounder (MLS). The comparison, with global coverage, focuses on the stratosphere and the lower mesosphere and covers the period from March 2008 until the end of 2011. The comparison shows an agreement of GOME-2 ozone profiles with those of GOMOS, OSIRIS and MLS within ±15 % in the altitude range from 15 km up to ~ 35-40 km depending on latitude. The GOME-2 bias with respect to the reference instruments depends on season, with the strongest dependence observed at high latitudes. The GOME-2 ozone profiles retrieved from non-degradation corrected radiances have a tendency to a systematic negative bias with respect to the reference data above ~ 30 km. We have studied the influence of solar zenith angle and the effect of instrumental degradation correction. In addition, we have studied GOME-2 performance in Arctic ozone depletion case and demonstrated that GOME-2 data provide valuable information about ozone profiles. [ABSTRACT FROM AUTHOR]

This paper presents a comparison of vertical ozone profiles retrieved by the Ozone ProfilE Retrieval Algorithm (OPERA) (versions 1.14-1.24) from the Global Ozone Monitoring Experiment-2 (GOME-2) measurements on board the Meteorological operational Metop-A satellite with spaceborne high-vertical-resolution ozone profiles by Global Ozone Monitoring by Occultation of Stars (GOMOS), Optical Spectrograph and Infrared Imager System (OSIRIS) and Microwave Limb Sounder (MLS). The comparison, with global coverage, focuses on the stratosphere and the lower mesosphere and covers the period from March 2008 until the end of 2011. The comparison shows an agreement of GOME-2 ozone profiles with those of GOMOS, OSIRIS and MLS within ±15% in the altitude range from 15 km up to ~ 35-40 km depending on latitude. The GOME-2 bias with respect to the reference instruments depends on season, with the strongest dependence observed at high latitudes. The GOME-2 ozone profiles retrieved from non-degradation corrected radiances have a tendency to a systematic negative bias with respect to the reference data above ~ 30 km. We have studied the influence of solar zenith angle and the effect of instrumental degradation correction. In addition, we have studied GOME-2 performance in Arctic ozone depletion case and demonstrated that GOME-2 data provide valuable information about ozone profiles. [ABSTRACT FROM AUTHOR]

This paper shows the results of the comparison of satellite SO2 observations from OMI (Ozone Monitoring Instrument) and OMPS (Ozone Mapping Profiler Suite) with ground-based measurements during the Icelandic Holuhraun fissure eruption in September 2014. The volcanic plume reached Finland on several days during the month of September. The SO2 total columns from the Brewer direct sun (DS) measurements in Sodankylä (67.42° N, 26.59° E), northern Finland, are compared to the satellite data. The operational satellite SO2 products are evaluated for high latitude conditions (e.g. large solar zenith angle, SZA). The results show that the best agreement can be found for lowest SZAs, close-to-nadir satellite pixels, cloud fraction below 0.3 and small distance between the station and the centre of the pixel. Under good retrieval conditions, the difference between satellite data and Brewer measurements remains mostly below the uncertainty on the satellite SO2 retrievals (up to about 2DU at high latitudes). The satellite products assuming a priori profile with SO2 predominantly in the planetary boundary layer give total column values with the best agreement with the ground-based data. The analysis of the SO2 surface concentrations at four air quality stations in northern Finland shows that the volcanic plume coming from Iceland was located very close to the surface. This is connected to the fact that this was a fissure eruption and most of the SO2 was emitted into the troposphere. This is an exceptional case because the SO2 volcanic emissions directly affect the air quality levels at surface in an otherwise pristine environment like northern Finland. The time evolution of the SO2 concentrations peaks during the same days when large SO2 total column values are measured by the Brewer in Sodankylä and enhanced SO2 signal is visible over northern Finland from the satellite maps. Thus, the satellite retrievals were able to detect the spatiotemporal evolution of the volcanic plume as compared to the surface observations. Furthermore, direct-broadcast SO2 satellite data (from both OMI and OMPS instruments) are compared for the first time against ground-based observations. [ABSTRACT FROM AUTHOR]

We consider an inverse boundary value problem for the heat equation ∂tu = div (γ∇xu) in (0,T) × Ω,u = fon (0,T) × ∂Ω,u|t=0 = u0, in a bounded domain Ω ⊂ ℝn,n ≥ 2, where the heat conductivity γ(t,x) is piecewise constant and the surface of discontinuity depends on time: γ(t,x) = k2 (x ∈ D(t)), γ(t,x) = 1 (x ∈ Ω∖D(t)). Fix a directione* ∈ 𝕊n−1arbitrarily. Assuming that ∂D(t) is strictly convex for 0 ≤ t ≤ T, we show thatkand sup {e*·x;x ∈ D(t)} (0 ≤ t ≤ T), in particularD(t) itself, are determined from the Dirichlet-to-Neumann map :f → ∂νu(t,x)|(0, T)×∂Ω. The knowledge of the initial datau0is not used in the proof. If we know min0≤t≤T(supx∈D(t)x·e*), we have the same conclusion from the local Dirichlet-to-Neumann map. Numerical examples of stationary and moving circles inside the unit disk are shown. The results have applications to nondestructive testing. Consider a physical body consisting of homogeneous material with constant heat conductivity except for a moving inclusion with different conductivity. Then the location and shape of the inclusion can be monitored from temperature and heat flux measurements performed at the boundary of the body. Such a situation appears for example in blast furnaces used in ironmaking. [ABSTRACT FROM PUBLISHER]

As part of ESA's climate change initiative high vertical resolution ozone profiles from three instruments all aboard ESA's Envisat (GOMOS, MIPAS, SCIAMACHY) in combination with ESA's third party missions (OSIRIS, SMR, ACE-FTS) are to be combined in order to create an essential climate variable data record for the last decade. A prerequisite before combining data is the examination of differences and drifts between the datasets. In this paper, we present a detailed analysis of ozone profile differences based on pairwise collocated measuerements, including the evolution of the differences with time. Such a diagnosis is helpful to identify strengths and weaknesses of each data set that may vary in time and introduce uncertainties in long-term trend estimates. Main results of this paper indicate that the 6 instruments perform well in the stratosphere particularly between 20 and 40 km with a mean relative difference of ±5% (middle latitudes) to ±10% (tropics). Larger differences and variability in the differences are found in the upper troposphere lower stratosphere region and in the mesosphere. The analysis reveals that the relative drift between the sensors is not statistically significant for most pairs of instruments. [ABSTRACT FROM AUTHOR]

This paper shows the validation results of the satellite SO2 observations from OMI (Ozone Monitoring Instrument) and OMPS (Ozone Mapping Profiler Suite) during the Icelandic Holuhraun fissure eruption in September 2014. The volcanic plume reached Finland on several days during the month of September. The SO2 total columns from the Brewer direct sun (DS) measurements in Sodankylä (67.4° N, 26.59° E), northern Finland, are compared to the satellite data. Challenging retrieval conditions at high latitudes (like large solar zenith angle, SZA) are considered in the comparison. The results show that the best agreement can be found for small SZAs, close-to-nadir satellite pixels, cloud fraction below 0.3 and small distance between the station and the centre of the pixel. Under good retrieval conditions, the difference between satellite data and Brewer measurements remains mostly below the uncertainty on the satellite SO2 retrievals (up to about 2DU at high latitudes). The satellite products assuming a priori profile with SO2 predominantly in the plan15 etary boundary layer give total column values close to the ground-based data, suggesting that the volcanic SO2 plume was located at particularly low altitudes. This is connected to the fact that this was a fissure eruption and most of the SO2 was emitted into the troposphere. The analysis of the SO2 surface concentrations at four air quality stations in north ern Finland supports the hypothesis that the volcanic plume coming from Iceland was located very close to the surface. The time evolution of the SO2 concentrations peaks during the same days when large SO2 total column values are measured by the Brewer in Sodankylä and enhanced SO2 signal is visible over northern Finland from the satellite maps. This is an exceptional case because the SO2 volcanic emission directly affect the air quality levels at surface in an otherwise pristine environment like northern Finland. OMI and OMPS SO2 retrievals from direct-broadcast measurements are validated for the first time in this paper. [ABSTRACT FROM AUTHOR]

Total column water vapour product from the Global Ozone Monitoring Experiment-2 on board Metop-A and Metop-B satellites (GOME-2/Metop-A and GOME-2/Metop-B) produced by the Satellite Application Facility on Ozone and Atmospheric Chemistry Monitoring (O3M SAF) is compared with co-located radiosonde and Global Positioning System (GPS) observations. The comparisons are performed using recently reprocessed data by the GOME Data Processor (GDP) version 4.7. The comparisons are performed for the period of January 2007-July 2013 (GOME- 2A) and from December 2012 to July 2013 (GOME-2B). Radiosonde data are from the Integrated Global Radiosonde Archive (IGRA) maintained by National Climatic Data Center (NCDC) and screened for soundings with incomplete tropospheric column. Ground-based GPS observations from COSMIC/SuomiNet network are used as the second independent data source. Good general agreement between GOME-2 and the ground-based observations is found. The median relative difference of GOME-2 to radiosonde observations is -2.7% for GOME-2A and -0.3% for GOME-2B. Against GPS observations, the median relative differences are 4.9 and 3.2% for GOME-2A and B, respectively. For water vapour total columns below 10 kgm-2, large wet biases are observed, especially against GPS observations. Conversely, at values above 50 kgm-2, GOME-2 generally underestimates both ground-based observations. [ABSTRACT FROM AUTHOR]

The Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the European platform ENVISAT (ENVironment SATellite) was dedicated to the study of the of Earth's atmosphere using the stellar occultation technique. The spectral range of the GOMOS spectrometer extends from the UV (ultra violet) to the near infrared, allowing for the retrieval of species such as O3, NO2, NO3, H2O, O2, air density, aerosol extinction and OClO. Nevertheless, OClO cannot be retrieved using a single GOMOS measurement because of the weak signal-to-noise ratio and the small optical thickness associated with this molecule. We present here the method used to detect this molecule by using several GOMOS measurements. It is based on a two-step approach. First, several co-located measurements are combined in a statistical way to build an averaged measurement with a higher signal-to-noise ratio; then, a differential optical absorption spectroscopy (DOAS) method is applied to retrieve OClO slant column densities (SCD). The statistics of the sets of GOMOS measurements used to build the averaged measurement and the spectral window selection are analyzed. The obtained retrievals are compared to results from two balloon-borne instruments. It appears that the inter-comparisons of OClO are generally satisfying (relative differences are about 15-60 %). Two nighttime climatologies of OClO based on GOMOS averaged measurements are presented. The first depicts annual global pictures of OClO from 2003 to 2011. From this climatology, the presence of an OClO SCD peak in the equatorial region at about 35 km is confirmed and strong OClO SCD in both polar regions are observed (more than 1016 cm-2 in the Antarctic region and slightly less in the Arctic region), a sign of chlorine activation. The second climatology is a monthly time series. It clearly shows the chlorine activation of the lower stratosphere during winter. Moreover the equatorial OClO SCD peak is observed during all years without any significant variations. This very promising method, applied on GOMOS measurements, allowed us to build the first nighttime climatology of OClO using limb-viewing instruments. [ABSTRACT FROM AUTHOR]

The discrimination of cloudy from cloud-free pixels is required in almost any estimate of a parameter retrieved from satellite data in the ultraviolet (UV), visible (VIS) or infrared (IR) parts of the electromagnetic spectrum. In this paper we report on the development of a neural network (NN) algorithm to estimate cloud fractions using radiances measured at the top of the atmosphere with the NASA-Aura Ozone Monitoring Instrument (OMI). We present and discuss the results obtained from the application of two different types of neural networks, i.e., extreme learning machine (ELM) and back propagation (BP). The NNs were trained with an OMI data sets existing of six orbits, tested with three other orbits and validated with another two orbits. The results were evaluated by comparison with cloud fractions available from the MODerate Resolution Imaging Spectrometer (MODIS) flying on Aqua in the same constellation as OMI, i.e., with minimal time difference between the OMI and MODIS observations. The results from the ELM and BP NNs are compared. They both deliver cloud fraction estimates in a fast and automated way, and they both performs generally well in the validation. However, over highly reflective surfaces, such as desert, or in the presence of dust layers in the atmosphere, the cloud fractions are not well predicted by the neural network. Over ocean the two NNs work equally well, but over land ELM performs better. [ABSTRACT FROM AUTHOR]

We consider an inverse boundary value problem for the heat equation on the interval (0, 1), where the heat conductivity γ(t, x) is piecewise constant and the point of discontinuity depends on time: γ(t, x) = k² (0 < x < s(t)), γ(t, x) = 1 (s(t) < x < 1). First, we show that k and s(t) on the time interval [0,T] are determined from a partial Dirichlet-to-Neumann map: u(t, 1) → ∂xu(t, 1), 0 < t < T, u(t, x) being the solution to the heat equation such that u(t, 0) = 0, independently of the initial data u(0, x). Second, we show that another partial Dirichlet-to-Neumann map: u(t, 0) → ∂xu(t, 1), 0 < t < T, u(t, x) being the solution to the heat equation such that u(t, 1) = 0, restricts the pair (k, s(t)) to, at most, two cases on the time interval [0,T], independently of the initial data u(0, x). [ABSTRACT FROM AUTHOR]

The Global Ozone Monitoring by Occultation of Stars (GOMOS) instrument on board the European platform ENVISAT was dedicated to the study of the atmosphere of the Earth using the stellar occultation technique. The spectral range of the GOMOS spectrometer extends from the UV to the near infrared, allowing for the retrieval of species such as O3, NO2, NO3, H2O, O2, air density, aerosol extinction and OCIO. Nevertheless, OCIO can not be retrieved using a single GOMOS measurement because of the weak signal-to-noise ratio and the small optical thickness associated with this molecule. We present here the method used to detect this molecule by using several GOMOS measurements. It is based on a two-step approach. First, several co-located measurements are combined in a statistical way to build an averaged measurement with a higher signal-to-noise ratio. Then, a Differential Optical Absorption Spectroscopy (DOAS) method is applied to retrieve OCIO slant column densities. The statistics of the sets of GOMOS measurements used to build the averaged measurement and the spectral window selection are analyzed. The obtained retrievals are compared to results from two balloon-borne instruments. It appears that the inter-comparisons of OCIO are generally satisfying. Then, two nighttime climatologies of OCIO slant column densities based on GOMOS averaged measurements are presented. The first depicts annual global pictures of OCIO from 2003 to 2011. From this climatology, the presence of an OCIO layer in the equatorial region at about 35km is confirmed and strong concentrations of OCIO in both polar regions are observed, a sign of chlorine activation. The second climatology is a monthly time series. It clearly shows the chlorine activation of the lower stratosphere during winter. Moreover the equatorial OCIO layer is observed during all the years without any significant variations. Finally, the anti-correlation between OCIO and NO2 is highlighted. This very promising method, applied on GOMOS measurements, allowed us to build the first nighttime climatology of OCIO [ABSTRACT FROM AUTHOR]

The discrimination of cloudy pixels is required in almost any estimate of a parameter retrieved from a satellite image in the ultraviolet (UV), visual (VIS) or infra-red (IR) parts of the electromagnetic spectrum. Also, the distincion of clouds within satellite imagery and the distribution of their micro-physical properties is essential to the understanding of radiative transfer through the atmosphere. This paper reports the development of neural network algorithms for cloud detection for the NASA-Aura Ozone Monitoring Instrument (OMI). We present and discuss the results obtained by training mathematical neural networks with simultaneous application to OMI and Aqua-MODerate Resolution Imaging Spectrometer (MODIS) data. The neural network delivers cloud fraction estimates in a fast and automated way. The developed neural network approach performs generally well in the training. Highly reflective surfaces, such as ice, snow, sun glint and desert, or atmospheric dust mislead the neural network to a wrong predicted cloud fraction. [ABSTRACT FROM AUTHOR]

Abstract: In the summer 2010 extensive wildfires in the western parts of Russia emitted massive amounts of smoke and aerosols into the atmosphere. These smoke plumes also drifted to Finland over 1000 km away from the fires. The smoke plumes were detected in Kuopio (Eastern Finland) with a wide range of instruments on two specific days: July 29 and August 8. The plumes were studied with several spaceborne instruments: MODIS, OMI, AIRS and CALIOP. Furthermore, a ground-based remote sensing instrument (Cimel) was also used in the analysis. Our results show that ground-based and spaceborne instruments were in good agreement on the Aerosol optical depth (AOD550) values during the episode (July–mid August). The correlation coefficient between MODIS and AERONET measurements done in Kuopio was 0.98 and the mean difference was 0.005 (AERONET AOD being larger). Spaceborne measurements of carbon monoxide provided a clear indicator for biomass burning aerosols. Particle mass (PM2.5) and AERONET AOD550 measurements were also in good agreement with a correlation coefficient of 0.87. Single scattering albedo (SSA675) values derived from AERONET measurements and calculated from in-situ absorption and scattering measurements had similar values close 0.9. On average, the daily in-situ SSA values were 0.02 smaller than the corresponding AERONET values. CALIOP provided vertical profiles of the smoke plumes for the two most polluted days in Kuopio. In July the plume was located close to the surface (mainly below 2 km) while in August the plume had two elevated layers: one between 1 and 2 km and the other between 2.5 and 4 km. [Copyright &y& Elsevier]

The possibility of a bearing damage caused by inverter-induced bearing currents in modern variable-speed drive systems is well recognised at present. In this study a non-intrusive method to detect and monitor the frequency of occurrence of these currents is presented. A technique of this kind makes it possible to analyse a certain drive system with respect to the appearance of inverter-induced bearing currents and to estimate the risk they might pose to the bearings. The proposed method is based on measurement of the radio frequency signal emitted by the discharge and transmitted by the machine itself. The theory behind the technique and its realisation is discussed. Exemplary measurements are presented to demonstrate the feasibility of the theory by studying the relationship between the motor shaft speed and the bearing current discharge activity for a 15 kW induction motor. [ABSTRACT FROM AUTHOR]

Abstract: GOMOS (Global Ozone Monitoring by Occultation of Stars) and MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) are remote sensing instruments on board the European Space Agency’s Envisat satellite. GOMOS and MIPAS have been designed for observations of stratospheric and mesospheric constituents, including ozone and nitrogen dioxide. Both instruments have a good global coverage of observations and can provide data also from the polar regions. In this paper, we compare night-time data from GOMOS with those from MIPAS. We present statistics of selected sets of data spanning from the year 2003 to 2006. The results for low-to-mid latitudes show that the two instruments are in a good agreement in the middle stratosphere, the differences being typically less than 5%. In the upper stratosphere, GOMOS observations generally show 15% higher values than those from MIPAS. The bias is in virtually all cases smaller than the combined systematic error of the measurements, giving great confidence in the GOMOS and MIPAS data quality. The result for high mesospheric mixing ratios observed in the polar regions during winter times indicate a good agreement between GOMOS and MIPAS. In the mesosphere, the difference is less than 35% and smaller than the systematic error. Due to the high mesospheric signal, MIPAS sensitivity decreases in the stratosphere which results in larger differences between the two instruments. [Copyright &y& Elsevier]

Abstract: We present first results of the analysis of fine details present in GOMOS co-added transmittances. In particular, mesospheric sodium (around 589nm) and the oxygen green line (at 557nm) have been unambiguously identified and the Na concentration profile can be obtained by standard inversion techniques. Two other unusual spectral signatures have been observed, both exhibiting a strong altitude dependence, in absorption (511.7nm) and in emission (601.2nm), the first one perhaps being related to a transition involving an excited state of molecular oxygen. The general usefulness of averaging limb transmittances data is discussed. [Copyright &y& Elsevier]

Abstract: GOMOS is a stellar occultation instrument onboard ENVISAT. It has already measured several hundreds of thousands occultations since March 2002. In some circumstances, the obliqueness of the star setting causes the remote sounding of possible horizontal turbulence that cannot be adequately corrected by using the fast photometer signals, leading to the presence of residual scintillation in the atmospheric transmittance. We investigate the mechanism that produces this spurious signal that may cause the retrieval of wavy constituent profiles. A special algorithm of vertical autoregressive smoothing (VAS) is proposed that takes into account the physical correlation between adjacent measurements at different tangent altitudes. A regularization parameter of the method may be optimized on basis of the minimal correlation between the residuals as prescribed by the Durbin–Watson statistics. The improvements obtained in the retrieval of both O3 and NO2 number density profiles is presented and discussed with respect to the results of the official data processing model. [Copyright &y& Elsevier]

Abstract: The GOMOS experiment onboard ENVISAT is a UV–Vis spectrometer designed to obtain constituent density and aerosol extinction profiles by the measurement of transmitted light through the atmosphere during a stellar occultation. Although the aerosol amount in the stratosphere is presently at the lowest level since decades, the optical extinction is measurable. Starting from GOMOS transmittance spectra, we calculated local gas concentration and aerosol extinction profiles, using a global retrieval scheme: spectral and spatial inversion are performed at the same time, in one step. In the inversion model, the aerosol extinction spectrum is described as a quadratic polynomial. We subsequently compared individual aerosol extinction profiles with coincident results from SAGE II and POAM III. A good agreement is found. [Copyright &y& Elsevier]

Global ozone monitoring by occultation of stars (GOMOS) on ENVISAT is the first space instrument dedicated to the study of the atmosphere of the Earth by the technique of stellar occultations (global ozone monitoring by occultation of stars). From a polar orbit, it allows to have a good latitude coverage. Because it is self-calibrated, it is particularly well adapted to the long time trend monitoring of stratospheric species. With four spectrometers the wavelength coverage of 245–942 nm allows to monitor ozone, H2O, NO2, NO3, air, aerosols, O2 and the temperature profiles. Two additional fast photometers (1 kHz sampling rate) allow for the correction of scintillations, as well as a study of the turbulence regime. A high vertical resolution profile of the temperature may also be obtained from the time shift between the red and the blue photometer. The first results of GOMOS are presented and ozone measurements compared to other sources. [Copyright &y& Elsevier]

In an epidemiological multi-centre study, parents filled in the Rutter Parent Questionnaire (RA2) and teachers filled in the Rutter Teacher Questionnaire (RB2) for almost 6000 children. The children filled in the Children's Depression Inventory (CDI). The subjects well represented the entire population of 8-9-year-old children in Finland. The material and design of the study as well as the basic demographic characteristics are presented. [ABSTRACT FROM AUTHOR]