127 research outputs found
Pole-to-pole validation of GOME WFDOAS total ozone with groundbased data
International audienceThis paper summarises the validation of GOME total ozone retrieved using the Weighting Function Differential Optical Absorption Spectroscopy (WFDOAS) algorithm Version 1.0. This algorithm has been described in detail in a companion paper by Coldewey-Egbers et al. (2005). Compared to the operational GDP (GOME Data Processor) V3, several improvements to the total ozone retrieval have been introduced that account for the varying ozone dependent contribution to rotational Raman scattering, includes a new cloud scheme, and uses the GOME measured effective albedo in the retrieval. In this paper the WFDOAS results have been compared with selected ground-based measurements from the WOUDC (World Ozone and UV Radiation Data Centre) that collects total ozone measurements from a global network of stations covering all seasons. From the global validation excellent agreement between WFDOAS and ground data was observed. The agreement lies within ±1%, and very little seasonal variations in the differences are found. In the polar regions and at high solar zenith angles, however, a positive bias varying between 5 and 8% is found near the polar night period. As a function of solar zenith angle as well as of the retrieved total ozone, the WFDOAS differences to ground polar data, however, show a much weaker dependence as compared to the operational GOME Data Processor Version 3 of GOME that represents a significant improvement. Very few stations carry out simultaneous measurements by Brewer and Dobson spectrometers over an extended period (three years or more). Simultaneous Brewer and Dobson measurements from Hradec Kralove, Czech Republic (50.2N, 15.8E) and Hohenpeissenberg, Germany (47.8N, 11.0E) covering the period 1996-1999 have been compared with our GOME results. Agreement with Brewers are generally better than with the simultaneous Dobson measurements and this may be explained by the neglect of stratospheric (ozone) temperature correction in the standard ozone retrieval from the ground
SCIAMACHY lunar occultation water vapor measurements : retrieval and validation results
SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) lunar occultation measurements have been used to derive vertical profiles of stratospheric water vapor for the Southern Hemisphere in the near infrared (NIR) spectral range of 1350–1420 nm. The focus of this study is to present the retrieval methodology including the sensitivity studies and optimizations for the implementation of the radiative transfer model on SCIAMACHY lunar occultation measurements. The study also includes the validation of the data product with the collocated measurements from two satellite occultation instruments and two instruments measuring in limb geometry. The SCIAMACHY lunar occultation water vapor measurement comparisons with the ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) instrument have shown an agreement of 5% on the average that is well within the reported biases of ACE in the stratosphere. The comparisons with HALOE (Halogen Occultation Experiment) have also shown good results where the agreement between the instruments is within 5 %. The validations of the lunar occultation water vapor measurements with MLS (Microwave Limb Sounder) instrument are exceptionally good, varying between 1.5 to around 4 %. The validations with MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) are in the range of 10 %. A validated dataset of water vapor vertical distributions from SCIAMACHY lunar occultation measurements is expected to facilitate the understanding of physical and chemical processes in the southern midlatitudes and the dynamical processes related to the polar vortex
Global carbon monoxide as retrieved from SCIAMACHY by WFM-DOAS
First results concerning the retrieval of tropospheric carbon monoxide (CO) from satellite solar backscatter radiance measurements in the near-infrared spectral region (~2.3µm) are presented. The Weighting Function Modified (WFM) DOAS retrieval algorithm has been used to retrieve vertical columns of CO from SCIAMACHY/ENVISAT nadir spectra. We present detailed results for three days from the time periode January to October 2003 selected to have good overlap with the daytime CO measurements of MOPITT onboard EOS Terra. Because the WFM-DOAS Version 0.4 CO columns presented in this paper are scaled by a constant factor of 0.5 to compensate for an obvious overestimation we focus on the variability of the retrieved columns rather than on their absolute values. It is shown that plumes of CO resulting from, e.g. biomass burning in Africa, are detectable with single overpass SCIAMACHY data. Globally, the SCIAMACHY CO columns are in reasonable agreement with the Version 3 CO column data product of MOPITT. For example, for measurements over land, where the quality of the data is typically better than over ocean due to higher surface reflectivity, the standard deviation of the difference with respect to MOPITT is in the range 0.4-0.6x10<sup>18</sup> molecules/cm<sup>2</sup> and the linear correlation coefficient is between 0.4 and 0.7. The level of agreement between the data of both sensors depends on time and location but is typically within 30% for most latitudes. In the southern hemisphere outside Antarctica SCIAMACHY tends to give systematically higher values than MOPITT. More studies are needed to find out what the reasons for the observed differences with respect to MOPITT are and how the algorithm can be modified to improve the quality of the CO columns as retrieved from SCIAMACHY
The semianalytical cloud retrieval algorithm for SCIAMACHY II. The application to MERIS and SCIAMACHY data
International audienceThe SemiAnalytical CloUd Retrieval Algorithm (SACURA) is applied to the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) data. In particular, we derive simultaneously cloud optical thickness (COT) and cloud top height (CTH), using SCIAMACHY measurements in the visible (442 nm, COT) and in the oxygen A-band (755?775 nm, CTH). Some of the results obtained are compared with those derived from the Medium Resolution Imaging Spectrometer (MERIS), which has better spatial resolution and observes almost the same scene as SCIAMACHY. The same cloud algorithm is applied to both MERIS and SCIAMACHY data. In addition, we perform the vicarious calibration of SCIAMACHY at the wavelength 442 nm, using MERIS measurements at the same wavelength. Differences in the retrieved COT for the same cloud field obtained using MERIS and SCIAMACHY measurements are discussed
Chemical ozone loss and ozone mini-hole event during the Arctic winter 2010/2011 as observed by SCIAMACHY and GOME-2
Corrigendum: Does a Combination of Virtual Reality, Neuromodulation and Neuroimaging Provide a Comprehensive Platform for Neurorehabilitation? - A Narrative Review of the Literature.
The FDR4ATMOS Project
The FDR4ATMOS project has two main tasks. The focus of task A is to update the SCIAMACHY processing chain for better Ozone total columns. After the full re-processing of the SCIAMACHY mission with processor versions 9 (Level 1) and version 7 (Level 2), the comparison with ground-based data showed that the total Ozone column showed a downward trend of nearly 2% from the
beginning of the time series to its end. This trend is an artefact and is likely caused by changes made to the calibration algorithms in the Level 1 processor (the DOAS retrieval algorithm for Ozone was not changed). The most likely reason are changes in the degradation correction that lead
to subtle changes in the spectral structures that in the retrieval are interpreted as an atmospheric signature. In task A we will update the Level 0-1 processor with the final aim of a mission re-processing.
The second task in the FDR4ATMOS project is to develop a cross-instrument Level 1 product for GOME-1 and SCIAMACHY for the UV, VIS and NIR spectral range with a focus on the spectral windows used for O3, SO2, NO2 total column retrieval and the determination of cloud properties.
Contrary to other projects, FDR4ATMOS does not aim to build a harmonised time series on Level 2 products but on Level 1 products, i.e. radiances and reflectances. The GOME-1 and SCIAMACHY instrument together span 17 years of spectrally highly resolved data. The goal of the FDR4ATMOS
project is to generate harmonised data sets that allow the user to use it directly in long term trend analysis, independent of the instrument. Since this was never done for highly resolved spectrometers, new methods have to be developed that e.g. take into account the different observation geometries and observation times of the instrument without impacting the spectral
structures that are used for the retrieval of the atmospheric species. The resulting algorithms and the processor should also be as generic as possible to be able to transfer the methodology easily to other instruments (e.g. GOME-2, Sentinel-5p) for a future extension of the time series.
The FDR4ATMOS started in October 2019 and is currently in phase 1. We will present the goals of the project and first results
An Ethical Façade? Medical Students' Miscomprehensions of Substituted Judgment
Background: We studied how well first-year medical students understand and apply the concept of substituted judgment, following a course on clinical ethics. Method: Students submitted essays on one of three ethically controversial scenarios presented in class. One scenario involved a patient who had lost decisional capacity. Through an iterative process of textual analysis, the essays were studied and coded for patterns in the ways students misunderstood or misapplied the principle of substituted judgment. Results: Students correctly articulated course principles regarding patient autonomy, substituted judgment, and nonimposition of physician values. However, students showed misunderstanding by giving doctors the responsibility of balancing the interests of the patient against the interests of the family, by stating doctors and surrogates should be guided primarily by a best-interest standard, and by suggesting that patient autonomy becomes the guiding principle only when patients can no longer express their wishes. Conclusion: Students did not appear to internalize or correctly apply the substituted judgment standard, even though they could describe it accurately. This suggests the substituted judgment standard may run counter to students ’ moral intuitions
UTLS water vapour from SCIAMACHY limb measurements V3.01 (2002-2012)
The SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) aboard the Envisat satellite provided measurements from August 2002 until April 2012. SCIAMACHY measured the scattered or direct sunlight using different observation geometries. The limb viewing geometry allows the retrieval of water vapour at about 10–25 km height from the near-infrared spectral range (1353–1410 nm). These data cover the upper troposphere and lower stratosphere (UTLS), a region in the atmosphere which is of special interest for a variety of dynamical and chemical processes as well as for the radiative forcing. Here, the latest data version of water vapour (V3.01) from SCIAMACHY limb measurements is presented and validated by comparisons with data sets from other satellite and in situ measurements. Considering retrieval tests and the results of these comparisons, the V3.01 data are reliable from about 11 to 23 km and the best results are found in the middle of the profiles between about 14 and 20 km. Above 20 km in the extra tropics V3.01 is drier than all other data sets. Additionally, for altitudes above about 19 km, the vertical resolution of the retrieved profile is not sufficient to resolve signals with a short vertical structure like the tape recorder. Below 14 km, SCIAMACHY water vapour V3.01 is wetter than most collocated data sets, but the high variability of water vapour in the troposphere complicates the comparison. For 14–20 km height, the expected errors from the retrieval and simulations and the mean differences to collocated data sets are usually smaller than 10% when the resolution of the SCIAMACHY data is taken into account. In general, the temporal changes agree well with collocated data sets except for the Northern Hemisphere extratropical stratosphere, where larger differences are observed. This indicates a possible drift in V3.01 most probably caused by the incomplete treatment of volcanic aerosols in the retrieval. In all other regions a good temporal stability is shown. In the tropical stratosphere an increase in water vapour is found between 2002 and 2012, which is in agreement with other satellite data sets for overlapping time periods
The SPARC water vapour assessment II: biases and drifts of water vapour satellite data records with respect to frost point hygrometer records
Satellite data records of stratospheric water vapour have been compared to
balloon-borne frost point hygrometer (FP) profiles that are coincident in space and
time. The satellite data records of 15 different instruments cover water vapour data available from
January 2000 through December 2016. The hygrometer data are from 27 stations
all over the world in the same period. For the comparison, real or constructed
averaging kernels have been applied to the
hygrometer profiles to adjust them to the measurement characteristics of
the satellite instruments. For bias evaluation, we have compared satellite
profiles averaged over the available temporal coverage to the means of coincident FP profiles for
individual stations. For drift determinations, we
analysed time series of relative differences between spatiotemporally coincident
satellite and hygrometer
profiles at individual stations. In a synopsis we have also calculated the mean
biases and drifts (and their respective uncertainties) for each satellite record
over all applicable hygrometer stations in three altitude ranges (10–30 hPa,
30–100 hPa, and 100 hPa to tropopause). Most of the satellite data have
biases <10 % and average drifts <1 % yr−1 in at least one of the respective
altitude ranges.
Virtually all biases are significant in the sense that their
uncertainty range in terms of twice the standard error of the mean does not include
zero. Statistically significant drifts (95 % confidence) are detected for 35 %
of the ≈ 1200 time series of relative differences between satellites and
hygrometers.</p
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