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  • 1
    Online Resource
    Online Resource
    Human effect on global climate?
    Springer Science and Business Media LLC ; 1996
    In:  Nature Vol. 384, No. 6609 ( 1996-12-12), p. 524-524
    Details
    In: Nature, Springer Science and Business Media LLC, Vol. 384, No. 6609 ( 1996-12-12), p. 524-524
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
    URL: Article
    DOI: 10.1038/384524a0
    RVK:
    TA 1000
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    WA 15000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 1996
    detail.hit.zdb_id: 120714-3
    detail.hit.zdb_id: 1413423-8
    SSG: 11
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  • 2
    Online Resource
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    Human-Induced Changes in the Hydrology of the Western United States
    American Association for the Advancement of Science (AAAS) ; 2008
    In:  Science Vol. 319, No. 5866 ( 2008-02-22), p. 1080-1083
    Details
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 319, No. 5866 ( 2008-02-22), p. 1080-1083
    Abstract: Observations have shown that the hydrological cycle of the western United States changed significantly over the last half of the 20th century. We present a regional, multivariable climate change detection and attribution study, using a high-resolution hydrologic model forced by global climate models, focusing on the changes that have already affected this primarily arid region with a large and growing population. The results show that up to 60% of the climate-related trends of river flow, winter air temperature, and snow pack between 1950 and 1999 are human-induced. These results are robust to perturbation of study variates and methods. They portend, in conjunction with previous work, a coming crisis in water supply for the western United States.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    URL: Article
    DOI: 10.1126/science.1152538
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2008
    detail.hit.zdb_id: 128410-1
    detail.hit.zdb_id: 2066996-3
    detail.hit.zdb_id: 2060783-0
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  • 3
    Online Resource
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    Human influence on the seasonal cycle of tropospheric temperature
    American Association for the Advancement of Science (AAAS) ; 2018
    In:  Science Vol. 361, No. 6399 ( 2018-07-20)
    Details
    In: Science, American Association for the Advancement of Science (AAAS), Vol. 361, No. 6399 ( 2018-07-20)
    Abstract: We provide scientific evidence that a human-caused signal in the seasonal cycle of tropospheric temperature has emerged from the background noise of natural variability. Satellite data and the anthropogenic “fingerprint” predicted by climate models show common large-scale changes in geographical patterns of seasonal cycle amplitude. These common features include increases in amplitude at mid-latitudes in both hemispheres, amplitude decreases at high latitudes in the Southern Hemisphere, and small changes in the tropics. Simple physical mechanisms explain these features. The model fingerprint of seasonal cycle changes is identifiable with high statistical confidence in five out of six satellite temperature datasets. Our results suggest that attribution studies with the changing seasonal cycle provide powerful evidence for a significant human effect on Earth’s climate.
    Type of Medium: Online Resource
    ISSN: 0036-8075 , 1095-9203
    URL: Article
    DOI: 10.1126/science.aas8806
    RVK:
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    Language: English
    Publisher: American Association for the Advancement of Science (AAAS)
    Publication Date: 2018
    detail.hit.zdb_id: 128410-1
    detail.hit.zdb_id: 2066996-3
    detail.hit.zdb_id: 2060783-0
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  • 4
    Online Resource
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    Quantifying stochastic uncertainty in detection time of human-caused climate signals
    Proceedings of the National Academy of Sciences ; 2019
    In:  Proceedings of the National Academy of Sciences Vol. 116, No. 40 ( 2019-10), p. 19821-19827
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 116, No. 40 ( 2019-10), p. 19821-19827
    Abstract: Large initial condition ensembles of a climate model simulation provide many different realizations of internal variability noise superimposed on an externally forced signal. They have been used to estimate signal emergence time at individual grid points, but are rarely employed to identify global fingerprints of human influence. Here we analyze 50- and 40-member ensembles performed with 2 climate models; each was run with combined human and natural forcings. We apply a pattern-based method to determine signal detection time t d in individual ensemble members. Distributions of t d are characterized by the median t d { m } and range t d { r } , computed for tropospheric and stratospheric temperatures over 1979 to 2018. Lower stratospheric cooling—primarily caused by ozone depletion—yields t d { m } values between 1994 and 1996, depending on model ensemble, domain (global or hemispheric), and type of noise data. For greenhouse-gas–driven tropospheric warming, larger noise and slower recovery from the 1991 Pinatubo eruption lead to later signal detection (between 1997 and 2003). The stochastic uncertainty t d { r } is greater for tropospheric warming (8 to 15 y) than for stratospheric cooling (1 to 3 y). In the ensemble generated by a high climate sensitivity model with low anthropogenic aerosol forcing, simulated tropospheric warming is larger than observed; detection times for tropospheric warming signals in satellite data are within t d { r } ranges in 60% of all cases. The corresponding number is 88% for the second ensemble, which was produced by a model with even higher climate sensitivity but with large aerosol-induced cooling. Whether the latter result is physically plausible will require concerted efforts to reduce significant uncertainties in aerosol forcing.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1904586116
    RVK:
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2019
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 5
    Online Resource
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    Natural variability contributes to model–satellite differences in tropical tropospheric warming
    Proceedings of the National Academy of Sciences ; 2021
    In:  Proceedings of the National Academy of Sciences Vol. 118, No. 13 ( 2021-03-30)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 118, No. 13 ( 2021-03-30)
    Abstract: A long-standing discrepancy exists between general circulation models (GCMs) and satellite observations: The multimodel mean temperature of the midtroposphere (TMT) in the tropics warms at approximately twice the rate of observations. Using a large ensemble of simulations from a single climate model, we find that tropical TMT trends (1979–2018) vary widely and that a subset of realizations are within the range of satellite observations. Realizations with relatively small tropical TMT trends are accompanied by subdued sea-surface warming in the tropical central and eastern Pacific. Observed changes in sea-surface temperature have a similar pattern, implying that the observed tropical TMT trend has been reduced by multidecadal variability. We also assess the latest generation of GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6). CMIP6 simulations with muted warming over the central and eastern Pacific also show reduced tropical tropospheric warming. We find that 13% of the model realizations have tropical TMT trends within the observed trend range. These simulations are from models with both small and large climate sensitivity values, illustrating that the magnitude of tropical tropospheric warming is not solely a function of climate sensitivity. For global averages, one-quarter of model simulations exhibit TMT trends in accord with observations. Our results indicate that even on 40-y timescales, natural climate variability is important to consider when comparing observed and simulated tropospheric warming and is sufficiently large to explain TMT trend differences between models and satellite data.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2020962118
    RVK:
    TA 1000
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    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2021
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
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  • 6
    Online Resource
    Online Resource
    Climate constraint reflects forced signal
    Springer Science and Business Media LLC ; 2018
    In:  Nature Vol. 563, No. 7729 ( 2018-11), p. E6-E9
    Details
    In: Nature, Springer Science and Business Media LLC, Vol. 563, No. 7729 ( 2018-11), p. E6-E9
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
    URL: Article
    DOI: 10.1038/s41586-018-0640-y
    RVK:
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2018
    detail.hit.zdb_id: 120714-3
    detail.hit.zdb_id: 1413423-8
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  • 7
    Online Resource
    Online Resource
    Ocean response to greenhouse warming
    Springer Science and Business Media LLC ; 1990
    In:  Nature Vol. 345, No. 6276 ( 1990-6), p. 589-593
    Details
    In: Nature, Springer Science and Business Media LLC, Vol. 345, No. 6276 ( 1990-6), p. 589-593
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
    URL: Article
    DOI: 10.1038/345589a0
    RVK:
    TA 1000
    RVK:
    UA 1000
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    WA 15000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 1990
    detail.hit.zdb_id: 120714-3
    detail.hit.zdb_id: 1413423-8
    SSG: 11
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  • 8
    Online Resource
    Online Resource
    Stratospheric cooling and the troposphere
    Springer Science and Business Media LLC ; 2004
    In:  Nature Vol. 432, No. 7017 ( 2004-12), p. 1-1
    Details
    In: Nature, Springer Science and Business Media LLC, Vol. 432, No. 7017 ( 2004-12), p. 1-1
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
    URL: Article
    DOI: 10.1038/nature03209
    RVK:
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    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2004
    detail.hit.zdb_id: 120714-3
    detail.hit.zdb_id: 1413423-8
    SSG: 11
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  • 9
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    Online Resource
    Selecting global climate models for regional climate change studies
    Proceedings of the National Academy of Sciences ; 2009
    In:  Proceedings of the National Academy of Sciences Vol. 106, No. 21 ( 2009-05-26), p. 8441-8446
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 106, No. 21 ( 2009-05-26), p. 8441-8446
    Abstract: Regional or local climate change modeling studies currently require starting with a global climate model, then downscaling to the region of interest. How should global models be chosen for such studies, and what effect do such choices have? This question is addressed in the context of a regional climate detection and attribution (D & A) study of January-February-March (JFM) temperature over the western U.S. Models are often selected for a regional D & A analysis based on the quality of the simulated regional climate. Accordingly, 42 performance metrics based on seasonal temperature and precipitation, the El Nino/Southern Oscillation (ENSO), and the Pacific Decadal Oscillation are constructed and applied to 21 global models. However, no strong relationship is found between the score of the models on the metrics and results of the D & A analysis. Instead, the importance of having ensembles of runs with enough realizations to reduce the effects of natural internal climate variability is emphasized. Also, the superiority of the multimodel ensemble average ( MM ) to any 1 individual model, already found in global studies examining the mean climate, is true in this regional study that includes measures of variability as well. Evidence is shown that this superiority is largely caused by the cancellation of offsetting errors in the individual global models. Results with both the MM and models picked randomly confirm the original D & A results of anthropogenically forced JFM temperature changes in the western U.S. Future projections of temperature do not depend on model performance until the 2080s, after which the better performing models show warmer temperatures.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.0900094106
    RVK:
    TA 1000
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2009
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
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  • 10
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    Online Resource
    Significant impact of forcing uncertainty in a large ensemble of climate model simulations
    Proceedings of the National Academy of Sciences ; 2021
    In:  Proceedings of the National Academy of Sciences Vol. 118, No. 23 ( 2021-06-08)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 118, No. 23 ( 2021-06-08)
    Abstract: Forcing due to solar and volcanic variability, on the natural side, and greenhouse gas and aerosol emissions, on the anthropogenic side, are the main inputs to climate models. Reliable climate model simulations of past and future climate change depend crucially upon them. Here we analyze large ensembles of simulations using a comprehensive Earth System Model to quantify uncertainties in global climate change attributable to differences in prescribed forcings. The different forcings considered here are those used in the two most recent phases of the Coupled Model Intercomparison Project (CMIP), namely CMIP5 and CMIP6. We show significant differences in simulated global surface air temperature due to volcanic aerosol forcing in the second half of the 19th century and in the early 21st century. The latter arise from small-to-moderate eruptions incorporated in CMIP6 simulations but not in CMIP5 simulations. We also find significant differences in global surface air temperature and Arctic sea ice area due to anthropogenic aerosol forcing in the second half of the 20th century and early 21st century. These differences are as large as those obtained in different versions of an Earth System Model employing identical forcings. In simulations from 2015 to 2100, we find significant differences in the rates of projected global warming arising from CMIP5 and CMIP6 concentration pathways that differ slightly but are equivalent in terms of their nominal radiative forcing levels in 2100. Our results highlight the influence of assumptions about natural and anthropogenic aerosol loadings on carbon budgets, the likelihood of meeting Paris targets, and the equivalence of future forcing scenarios.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.2016549118
    RVK:
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    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2021
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
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