| 1. |
- Dunn, R. J. H., et al.
(författare)
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GLOBAL CLIMATE : State of the Climate in 2020
- 2021
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Ingår i: Bulletin of the American Meteorological Society. - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 102:8
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Ades, M., et al.
(författare)
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Global Climate : in State of the climate in 2019
- 2020
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Ingår i: Bulletin of The American Meteorological Society - (BAMS). - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 101:8, s. S17-S127
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Tidskriftsartikel (refereegranskat)
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| 3. |
- Ades, M., et al.
(författare)
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GLOBAL CLIMATE
- 2020
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Ingår i: BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY. - 0003-0007 .- 1520-0477. ; 101:8
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Tidskriftsartikel (refereegranskat)
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| 4. |
- Wendisch, M., et al.
(författare)
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Atmospheric and Surface Processes, and Feedback Mechanisms Determining Arctic Amplification: A Review of First Results and Prospects of the (AC)(3) Project
- 2023
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Ingår i: Bulletin of the American Meteorological Society. - : American Meteorological Society. - 0003-0007 .- 1520-0477. ; 104:1
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Tidskriftsartikel (refereegranskat)abstract
- Mechanisms behind the phenomenon of Arctic amplification are widely discussed. To contribute to this debate, the (AC)(3) project was established in 2016 (www.ac3-tr.de/). It comprises modeling and data analysis efforts as well as observational elements. The project has assembled a wealth of ground-based, airborne, shipborne, and satellite data of physical, chemical, and meteorological properties of the Arctic atmosphere, cryosphere, and upper ocean that are available for the Arctic climate research community. Short-term changes and indications of long-term trends in Arctic climate parameters have been detected using existing and new data. For example, a distinct atmospheric moistening, an increase of regional storm activities, an amplified winter warming in the Svalbard and North Pole regions, and a decrease of sea ice thickness in the Fram Strait and of snow depth on sea ice have been identified. A positive trend of tropospheric bromine monoxide (BrO) column densities during polar spring was verified. Local marine/biogenic sources for cloud condensation nuclei and ice nucleating particles were found. Atmospheric-ocean and radiative transfer models were advanced by applying new parameterizations of surface albedo, cloud droplet activation, convective plumes and related processes over leads, and turbulent transfer coefficients for stable surface layers. Four modes of the surface radiative energy budget were explored and reproduced by simulations. To advance the future synthesis of the results, cross-cutting activities are being developed aiming to answer key questions in four focus areas: lapse rate feedback, surface processes, Arctic mixed-phase clouds, and airmass transport and transformation.
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| 5. |
- Docherty, Anna R, et al.
(författare)
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GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.
- 2023
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Ingår i: The American journal of psychiatry. - : American Psychiatric Association Publishing. - 1535-7228 .- 0002-953X. ; 180:10, s. 723-738
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Tidskriftsartikel (refereegranskat)abstract
- Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures.This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses.Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors.This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.
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| 6. |
- Mullins, Niamh, et al.
(författare)
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Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors
- 2022
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Ingår i: Biological Psychiatry. - : Elsevier. - 0006-3223 .- 1873-2402. ; 91:3, s. 313-327
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders.METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.
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| 9. |
- Hegglin, Michaela I., et al.
(författare)
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Overview and update of the SPARC Data Initiative: comparison of stratospheric composition measurements from satellite limb sounders
- 2021
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Ingår i: Earth System Science Data. - : Copernicus GmbH. - 1866-3516 .- 1866-3508. ; 13:5, s. 1855-1903
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Forskningsöversikt (refereegranskat)abstract
- The Stratosphere-troposphere Processes and their Role in Climate (SPARC) Data Initiative (SPARC, 2017) performed the first comprehensive assessment of currently available stratospheric composition measurements obtained from an international suite of space-based limb sounders. The initiative's main objectives were (1) to assess the state of data availability, (2) to compile time series of vertically resolved, zonal monthly mean trace gas and aerosol fields, and (3) to perform a detailed intercomparison of these time series, summarizing useful information and highlighting differences among datasets. The datasets extend over the region from the upper troposphere to the lower mesosphere (300-0.1 hPa) and are provided on a common latitude-pressure grid. They cover 26 different atmospheric constituents including the stratospheric trace gases of primary interest, ozone (O-3) and water vapor (H2O), major long-lived trace gases (SF6, N2O, HF, CCl3F, CCl2F2, NO y), trace gases with intermediate lifetimes (HCl, CH4, CO, HNO3), and shorter-lived trace gases important to stratospheric chemistry including nitrogen-containing species (NO, NO2, NOx, N2O5, HNO4), halogens (BrO, ClO, ClONO2, HOCl), and other minor species (OH, HO2, CH2O, CH3CN), and aerosol. This overview of the SPARC Data Initiative introduces the updated versions of the SPARC Data Initiative time series for the extended time period 1979-2018 and provides information on the satellite instruments included in the assessment: LIMS, SAGE I/II/III, HALOE, UARS-MLS, POAM II/III, OSIRIS, SMR, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACEMAESTRO, Aura-MLS, HIRDLS, SMILES, and OMPS-LP. It describes the Data Initiative's top-down climatological validation approach to compare stratospheric composition measurements based on zonal monthly mean fields, which provides upper bounds to relative inter-instrument biases and an assessment of how well the instruments are able to capture geophysical features of the stratosphere. An update to previously published evaluations of O-3 and H2O monthly mean time series is provided. In addition, example trace gas evaluations of methane (CH4), carbon monoxide (CO), a set of nitrogen species (NO, NO2, and HNO3), the reactive nitrogen family (NOy), and hydroperoxyl (HO2) are presented. The results highlight the quality, strengths and weaknesses, and representativeness of the different datasets. As a summary, the current state of our knowledge of stratospheric composition and variability is provided based on the overall consistency between the datasets. As such, the SPARC Data Initiative datasets and evaluations can serve as an atlas or reference of stratospheric composition and variability during the "golden age" of atmospheric limb sounding. The updated SPARC Data Initiative zonal monthly mean time series for each instrument are publicly available and accessible via the Zenodo data archive (Hegglin et al., 2020).
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| 10. |
- von Clarmann, Thomas, et al.
(författare)
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Overview: Estimating and reporting uncertainties in remotely sensed atmospheric composition and temperature
- 2020
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Ingår i: Atmospheric Measurement Techniques. - : Copernicus GmbH. - 1867-1381 .- 1867-8548. ; 13:8, s. 4393-4436
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Tidskriftsartikel (refereegranskat)abstract
- Remote sensing of atmospheric state variables typically relies on the inverse solution of the radiative transfer equation. An adequately characterized retrieval provides information on the uncertainties of the estimated state variables as well as on how any constraint or a priori assumption affects the estimate. Reported characterization data should be intercomparable between different instruments, empirically validatable, grid-independent, usable without detailed knowledge of the instrument or retrieval technique, traceable and still have reasonable data volume. The latter may force one to work with representative rather than individual characterization data. Many errors derive from approximations and simplifications used in real-world retrieval schemes, which are reviewed in this paper, along with related error estimation schemes. The main sources of uncertainty are measurement noise, calibration errors, simplifications and idealizations in the radiative transfer model and retrieval scheme, auxiliary data errors, and uncertainties in atmospheric or instrumental parameters. Some of these errors affect the result in a random way, while others chiefly cause a bias or are of mixed character. Beyond this, it is of utmost importance to know the influence of any constraint and prior information on the solution. While different instruments or retrieval schemes may require different error estimation schemes, we provide a list of recommendations which should help to unify retrieval error reporting.
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