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  • 1
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 17, No. 21 ( 2017-11-07), p. 13139-13150
    Abstract: Abstract. To simulate the impacts of volcanic eruptions on the stratosphere, chemistry–climate models that do not include an online aerosol module require temporally and spatially resolved aerosol size parameters for heterogeneous chemistry and aerosol radiative properties as a function of wavelength. For phase 1 of the Chemistry-Climate Model Initiative (CCMI-1) and, later, for phase 6 of the Coupled Model Intercomparison Project (CMIP6) two such stratospheric aerosol data sets were compiled, whose functional capability and representativeness are compared here. For CCMI-1, the SAGE-4λ data set was compiled, which hinges on the measurements at four wavelengths of the SAGE (Stratospheric Aerosol and Gas Experiment) II satellite instrument and uses ground-based lidar measurements for gap-filling immediately after the 1991 Mt Pinatubo eruption, when the stratosphere was too optically opaque for SAGE II. For CMIP6, the new SAGE-3λ data set was compiled, which excludes the least reliable SAGE II wavelength and uses measurements from CLAES (Cryogenic Limb Array Etalon Spectrometer) on UARS, the Upper Atmosphere Research Satellite, for gap-filling following the Mt Pinatubo eruption instead of ground-based lidars. Here, we performed SOCOLv3 (Solar Climate Ozone Links version 3) chemistry–climate model simulations of the recent past (1986–2005) to investigate the impact of the Mt Pinatubo eruption in 1991 on stratospheric temperature and ozone and how this response differs depending on which aerosol data set is applied. The use of SAGE-4λ results in heating and ozone loss being overestimated in the tropical lower stratosphere compared to observations in the post-eruption period by approximately 3 K and 0.2 ppmv, respectively. However, less heating occurs in the model simulations based on SAGE-3λ, because the improved gap-filling procedures after the eruption lead to less aerosol loading in the tropical lower stratosphere. As a result, simulated tropical temperature anomalies in the model simulations based on SAGE-3λ for CMIP6 are in excellent agreement with MERRA and ERA-Interim reanalyses in the post-eruption period. Less heating in the simulations with SAGE-3λ means that the rate of tropical upwelling does not strengthen as much as it does in the simulations with SAGE-4λ, which limits dynamical uplift of ozone and therefore provides more time for ozone to accumulate in tropical mid-stratospheric air. Ozone loss following the Mt Pinatubo eruption is overestimated by up to 0.1 ppmv in the model simulations based on SAGE-3λ, which is a better agreement with observations than in the simulations based on SAGE-4λ. Overall, the CMIP6 stratospheric aerosol data set, SAGE-3λ, allows SOCOLv3 to more accurately simulate the post-Pinatubo eruption period.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2017
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  • 2
    Online Resource
    Online Resource
    Copernicus GmbH ; 2017
    In:  Geoscientific Model Development Vol. 10, No. 12 ( 2017-12-15), p. 4563-4575
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 10, No. 12 ( 2017-12-15), p. 4563-4575
    Abstract: Abstract. A method, based on climate pattern scaling, has been developed to expand a small number of projections of fields of a selected climate variable (X) into an ensemble that encapsulates a wide range of indicative model structural uncertainties. The method described in this paper is referred to as the Ensemble Projections Incorporating Climate model uncertainty (EPIC) method. Each ensemble member is constructed by adding contributions from (1) a climatology derived from observations that represents the time-invariant part of the signal; (2) a contribution from forced changes in X, where those changes can be statistically related to changes in global mean surface temperature (Tglobal); and (3) a contribution from unforced variability that is generated by a stochastic weather generator. The patterns of unforced variability are also allowed to respond to changes in Tglobal. The statistical relationships between changes in X (and its patterns of variability) and Tglobal are obtained in a training phase. Then, in an implementation phase, 190 simulations of Tglobal are generated using a simple climate model tuned to emulate 19 different global climate models (GCMs) and 10 different carbon cycle models. Using the generated Tglobal time series and the correlation between the forced changes in X and Tglobal, obtained in the training phase, the forced change in the X field can be generated many times using Monte Carlo analysis. A stochastic weather generator is used to generate realistic representations of weather which include spatial coherence. Because GCMs and regional climate models (RCMs) are less likely to correctly represent unforced variability compared to observations, the stochastic weather generator takes as input measures of variability derived from observations, but also responds to forced changes in climate in a way that is consistent with the RCM projections. This approach to generating a large ensemble of projections is many orders of magnitude more computationally efficient than running multiple GCM or RCM simulations. Such a large ensemble of projections permits a description of a probability density function (PDF) of future climate states rather than a small number of individual story lines within that PDF, which may not be representative of the PDF as a whole; the EPIC method largely corrects for such potential sampling biases. The method is useful for providing projections of changes in climate to users wishing to investigate the impacts and implications of climate change in a probabilistic way. A web-based tool, using the EPIC method to provide probabilistic projections of changes in daily maximum and minimum temperatures for New Zealand, has been developed and is described in this paper.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2017
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  • 3
    Online Resource
    Online Resource
    Copernicus GmbH ; 2018
    In:  Atmospheric Measurement Techniques Vol. 11, No. 5 ( 2018-05-24), p. 3021-3029
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 11, No. 5 ( 2018-05-24), p. 3021-3029
    Abstract: Abstract. Upper-air measurements of essential climate variables (ECVs), such as temperature, are crucial for climate monitoring and climate change detection. Because of the internal variability of the climate system, many decades of measurements are typically required to robustly detect any trend in the climate data record. It is imperative for the records to be temporally homogeneous over many decades to confidently estimate any trend. Historically, records of upper-air measurements were primarily made for short-term weather forecasts and as such are seldom suitable for studying long-term climate change as they lack the required continuity and homogeneity. Recognizing this, the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) has been established to provide reference-quality measurements of climate variables, such as temperature, pressure, and humidity, together with well-characterized and traceable estimates of the measurement uncertainty. To ensure that GRUAN data products are suitable to detect climate change, a scientifically robust instrument replacement strategy must always be adopted whenever there is a change in instrumentation. By fully characterizing any systematic differences between the old and new measurement system a temporally homogeneous data series can be created. One strategy is to operate both the old and new instruments in tandem for some overlap period to characterize any inter-instrument biases. However, this strategy can be prohibitively expensive at measurement sites operated by national weather services or research institutes. An alternative strategy that has been proposed is to alternate between the old and new instruments, so-called interlacing, and then statistically derive the systematic biases between the two instruments. Here we investigate the feasibility of such an approach specifically for radiosondes, i.e. flying the old and new instruments on alternating days. Synthetic data sets are used to explore the applicability of this statistical approach to radiosonde change management.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2018
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  • 4
    In: Atmospheric Measurement Techniques, Copernicus GmbH, Vol. 12, No. 4 ( 2019-04-08), p. 2129-2138
    Abstract: Abstract. When computing climatological averages of atmospheric trace-gas mixing ratios obtained from satellite-based measurements, sampling biases arise if data coverage is not uniform in space and time. Homogeneous spatiotemporal coverage is essentially impossible to achieve. Solar occultation measurements, by virtue of satellite orbit and the requirement of direct observation of the sun through the atmosphere, result in particularly sparse spatial coverage. In this proof-of-concept study, a method is presented to adjust for such sampling biases when calculating climatological means. The method is demonstrated using carbonyl sulfide (OCS) measurements at 16 km altitude from the ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer). At this altitude, OCS mixing ratios show a steep gradient between the poles and Equator. ACE-FTS measurements, which are provided as vertically resolved profiles, and integrated stratospheric OCS columns are used in this study. The bias adjustment procedure requires no additional information other than the satellite data product itself. In particular, the method does not rely on atmospheric models with potentially unreliable transport or chemistry parameterizations, and the results can be used uncompromised to test and validate such models. It is expected to be generally applicable when constructing climatologies of long-lived tracers from sparsely and heterogeneously sampled satellite measurements. In the first step of the adjustment procedure, a regression model is used to fit a 2-D surface to all available ACE-FTS OCS measurements as a function of day-of-year and latitude. The regression model fit is used to calculate an adjustment factor that is then used to adjust each measurement individually. The mean of the adjusted measurement points of a chosen latitude range and season is then used as the bias-free climatological value. When applying the adjustment factor to seasonal averages in 30∘ zones, the maximum spatiotemporal sampling bias adjustment was 11 % for OCS mixing ratios at 16 km and 5 % for the stratospheric OCS column. The adjustments were validated against the much denser and more homogeneous OCS data product from the limb-sounding MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) instrument, and both the direction and magnitude of the adjustments were in agreement with the adjustment of the ACE-FTS data.
    Type of Medium: Online Resource
    ISSN: 1867-8548
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2019
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  • 5
    In: Journal of Neuroimaging, Wiley, Vol. 30, No. 1 ( 2020-01), p. 104-109
    Abstract: To identify and evaluate diagnostic magnetic resonance imaging (MRI) features in patients with suspicion of discoligamentous cervical injury after hyperextension trauma of the cervical spine. METHODS MR images with a standard protocol (1.5 T, including sagittal T2‐weighted images and short tau inversion recovery [STIR]) in 21 patients without any sign of fracture or instability on multidetector computed tomography of the cervical spine were assessed. Among other structures we evaluated the following: prevertebral hematoma, anterior longitudinal ligament (ALL), intervertebral disc, and spinal cord. Presence and the anatomic level of injury were identified and recorded. Results were then compared with intraoperative findings as a reference standard. Simple descriptive statistical analysis, agreement coefficients (given by calculating the percent agreement), and the determination of Gwet's AC1 coefficient were used to analyze our results. RESULTS The overall percent agreement between STIR and intraoperative findings was 90.9% (AC1 = .881) and for T2 69.7% (AC1 = .498). For the ALL, the overall agreement was 87.9% (AC1 = .808) and for the intervertebral disc 78.8% (AC1 = .673), in which STIR always showed a higher agreement. Prevertebral hematoma was found in 20 of 21 patients with the maximum thickness at the same anatomic level as the intraoperatively proven lesion in 12 of 18 patients (67%). Edema and/or hemorrhage of the spinal cord was shown in 16 of 21 being at the same anatomic level as the intraoperatively confirmed pathology in 16 of 16 patients (100%). CONCLUSIONS MRI is a reliable tool for the evaluation of discoligamentous injuries in the cervical spine, with ancillary features proven as helpful information.
    Type of Medium: Online Resource
    ISSN: 1051-2284 , 1552-6569
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2020
    detail.hit.zdb_id: 2035400-9
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  • 6
    In: Reviews of Geophysics, American Geophysical Union (AGU), Vol. 54, No. 2 ( 2016-06), p. 278-335
    Type of Medium: Online Resource
    ISSN: 8755-1209
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2016
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    SSG: 16,13
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  • 7
    Online Resource
    Online Resource
    American Geophysical Union (AGU) ; 2015
    In:  Geophysical Research Letters Vol. 42, No. 21 ( 2015-11-16), p. 9473-9480
    In: Geophysical Research Letters, American Geophysical Union (AGU), Vol. 42, No. 21 ( 2015-11-16), p. 9473-9480
    Abstract: First observed positive trend in OCS in the Southern Hemisphere Observed trends indicate imbalanced OCS budget Temporal structure of trend is similar across middle‐ and high‐latitude sites
    Type of Medium: Online Resource
    ISSN: 0094-8276 , 1944-8007
    URL: Issue
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2015
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    SSG: 16,13
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  • 8
    In: American Journal of Hematology, Wiley, Vol. 98, No. 6 ( 2023-06), p. 890-899
    Abstract: Anemia of inflammation (AI) is frequently present in subjects with inflammatory disorders, primarily caused by inflammation‐driven iron retention in macrophages. So far, only limited data on qualitative and quantitative estimates of tissue iron retention in AI patients exist. We performed a prospective cohort study analyzing splenic, hepatic, pancreatic, and cardiac iron content with MRI‐based R2*‐relaxometry in AI patients, including subjects with concomitant true iron deficiency (AI+IDA) hospitalized between 05/2020–01/2022. Control groups were individuals without inflammation. Spleen R2* values in AI patients with ferritin ≤200 μg/L (AI+IDA) were comparable with those found in controls. In AI patients with ferritin 〉 200 μg/L, spleen (47.6 s −1 vs. 19.3 s −1 , p   〈  .001) and pancreatic R2* values (32.5 s −1 vs. 24.9 s −1 , p  = .011) were significantly higher compared with controls, while liver and heart R2*‐values did not differ. Higher spleen R2* values were associated with higher ferritin, hepcidin, CRP, and IL‐6 concentrations. Spleen R2* values normalized in AI patients after recovery (23.6 s −1 vs. 47.6 s −1 , p  = .008), while no changes were found in patients with baseline AI+IDA. This is the first study investigating tissue iron distribution in patients with inflammatory anemia and AI with concomitant true iron deficiency. The results support the findings in animal models demonstrating iron retention in macrophages, which are primarily accumulating in the spleen under inflammatory conditions. MRI‐related iron measurement may help to better characterize actual iron needs and to define better biomarker thresholds in the diagnosis of true ID in patients with AI. It may qualify as a useful diagnostic method to estimate the need for iron supplementation and to guide therapy.
    Type of Medium: Online Resource
    ISSN: 0361-8609 , 1096-8652
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2023
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  • 9
    Online Resource
    Online Resource
    Copernicus GmbH ; 2009
    In:  Atmospheric Chemistry and Physics Vol. 9, No. 8 ( 2009-04-23), p. 2679-2694
    In: Atmospheric Chemistry and Physics, Copernicus GmbH, Vol. 9, No. 8 ( 2009-04-23), p. 2679-2694
    Abstract: Abstract. In this study backward trajectories from the tropical lower stratosphere were calculated for the Northern Hemisphere (NH) winters 1995–1996, 1997–1998 (El Niño) and 1998–1999 (La Niña) and summers 1996, 1997 and 1999 using both ERA-40 reanalysis data of the European Centre for Medium-Range Weather Forecast (ECMWF) and coupled Chemistry-Climate Model (CCM) data. The calculated trajectories were analysed to determine the distribution of points where individual air masses encounter the minimum temperature and thus minimum water vapour mixing ratio during their ascent through the tropical tropopause layer (TTL) into the stratosphere. The geographical distribution of these dehydration points and the local conditions there determine the overall water vapour entry into the stratosphere. Results of two CCMs are presented: the ECHAM4.L39(DLR)/CHEM (hereafter: E39/C) from the German Aerospace Center (DLR) and the Freie Universität Berlin Climate Middle Atmosphere Model with interactive chemistry (hereafter: FUB-CMAM-CHEM). In the FUB-CMAM-CHEM model the minimum temperatures are overestimated by about 9 K in NH winter and about 3 K in NH summer, resulting in too high water vapour entry values compared to ERA-40. However, the geographical distribution of dehydration points is fairly similar to ERA-40 for NH winter 1995–1996 and 1998–1999. The distribution of dehydration points in the boreal summer 1996 suggests an influence of the Indian monsoon upon the water vapour transport. The E39/C model displays a temperature bias of about +5 K. Hence, the minimum water vapour mixing ratios are higher relative to ERA-40. The geographical distribution of dehydration points is fairly well in NH winter 1995–1996 and 1997–1998 with respect to ERA-40. The distribution is not reproduced for the NH winter 1998–1999 (La Niña event) compared to ERA-40. There is an excessive water vapour flux through warm regions e.g. Africa in the NH winter and summer. The possible influence of the Indian monsoon on the transport is not seen in the boreal summer 1996. Further, the residence times of air parcels in the TTL were derived from the trajectory calculations. The analysis of the residence times reveals that in both CCMs residence times in the TTL are lower compared to ERA-40 and the seasonal variation is hardly present.
    Type of Medium: Online Resource
    ISSN: 1680-7324
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2009
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  • 10
    Online Resource
    Online Resource
    Copernicus GmbH ; 2020
    In:  Earth System Science Data Vol. 12, No. 2 ( 2020-06-23), p. 1419-1435
    In: Earth System Science Data, Copernicus GmbH, Vol. 12, No. 2 ( 2020-06-23), p. 1419-1435
    Abstract: Abstract. High-quality satellite-based measurements are crucial to the assessment of global stratospheric composition change. The Stratospheric Aerosol and Gas Experiment II (SAGE II) provides the longest, continuous data set of vertically resolved ozone and aerosol extinction coefficients to date and therefore remains a cornerstone of understanding and detecting long-term ozone variability and trends in the stratosphere. Despite its stability, SAGE II measurements must be screened for outliers that are a result of excessive aerosol emitted into the atmosphere and that degrade inferences of change. Current methods for SAGE II ozone measurement quality assurance consist of multiple ad hoc and sometimes conflicting rules, leading to too much valuable data being removed or outliers being missed. In this work, the SAGE II ozone data set version 7.00 is used to develop and present a new set of screening recommendations and to compare the output to the screening recommendations currently used. Applying current recommendations to SAGE II ozone leads to unexpected features, such as removing ozone values around zero if the relative error is used as a screening criterion, leading to biases in monthly mean zonal mean ozone concentrations. Most of these current recommendations were developed based on “visual inspection”, leading to inconsistent rules that might not be applicable at every altitude and latitude. Here, a set of new screening recommendations is presented that take into account the knowledge of how the measurements were made. The number of screening recommendations is reduced to three, which mainly remove ozone values that are affected by high aerosol loading and are therefore not reliable measurements. More data remain when applying these new recommendations compared to the rules that are currently being used, leading to more data being available for scientific studies. The SAGE II ozone data set used here is publicly available at https://doi.org/10.5281/zenodo.3710518 (Kremser et al., 2020). The complete SAGE II version 7.00 data set, which includes other variables in addition to ozone, is available at https://eosweb.larc.nasa.gov/project/sage2/sage2_v7_table (last access: December 2019), https://doi.org/10.5067/ERBS/SAGEII/SOLAR_BINARY_L2-V7.0 (SAGE II Science Team, 2012; Damadeo et al., 2013).
    Type of Medium: Online Resource
    ISSN: 1866-3516
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2020
    detail.hit.zdb_id: 2475469-9
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