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  • 1
    Online Resource
    Online Resource
    The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution
    American Geophysical Union (AGU) ; 2019
    In:  Journal of Advances in Modeling Earth Systems Vol. 11, No. 7 ( 2019-07), p. 2089-2129
    Details
    In: Journal of Advances in Modeling Earth Systems, American Geophysical Union (AGU), Vol. 11, No. 7 ( 2019-07), p. 2089-2129
    Abstract: This work documents E3SMv1, the first version of the U.S. DOE Energy Exascale Earth System Model The performance of E3SMv1 is documented with a set of standard CMIP6 DECK and historical simulations comprising nearly 3,000 years E3SMv1 has a high equilibrium climate sensitivity (5.3 K) and strong aerosol‐related effective radiative forcing (‐1.65 W/m 2 )
    Type of Medium: Online Resource
    ISSN: 1942-2466 , 1942-2466
    URL: Article
    DOI: 10.1029/2018MS001603
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2019
    detail.hit.zdb_id: 2462132-8
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  • 2
    Online Resource
    Online Resource
    Robust Anthropogenic Signal Identified in the Seasonal Cycle of Tropospheric Temperature
    American Meteorological Society ; 2022
    In:  Journal of Climate Vol. 35, No. 18 ( 2022-09-15), p. 6075-6100
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 35, No. 18 ( 2022-09-15), p. 6075-6100
    Abstract: Previous work identified an anthropogenic fingerprint pattern in T AC ( x , t ), the amplitude of the seasonal cycle of mid- to upper-tropospheric temperature (TMT), but did not explicitly consider whether fingerprint identification in satellite T AC ( x , t ) data could have been influenced by real-world multidecadal internal variability (MIV). We address this question here using large ensembles (LEs) performed with five climate models. LEs provide many different sequences of internal variability noise superimposed on an underlying forced signal. Despite differences in historical external forcings, climate sensitivity, and MIV properties of the five models, their T AC ( x , t ) fingerprints are similar and statistically identifiable in 239 of the 240 LE realizations of historical climate change. Comparing simulated and observed variability spectra reveals that consistent fingerprint identification is unlikely to be biased by model underestimates of observed MIV. Even in the presence of large (factor of 3–4) intermodel and inter-realization differences in the amplitude of MIV, the anthropogenic fingerprints of seasonal cycle changes are robustly identifiable in models and satellite data. This is primarily due to the fact that the distinctive, global-scale fingerprint patterns are spatially dissimilar to the smaller-scale patterns of internal T AC ( x , t ) variability associated with the Atlantic multidecadal oscillation and El Niño–Southern Oscillation. The robustness of the seasonal cycle detection and attribution results shown here, taken together with the evidence from idealized aquaplanet simulations, suggest that basic physical processes are dictating a common pattern of forced T AC ( x , t ) changes in observations and in the five LEs. The key processes involved include GHG-induced expansion of the tropics, lapse-rate changes, land surface drying, and sea ice decrease.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-21-0766.1
    DOI: 10.1175/JCLI-D-21-0766.s1
    RVK:
    UA 4548
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2022
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 3
    Online Resource
    Online Resource
    Better calibration of cloud parameterizations and subgrid effects increases the fidelity of the E3SM Atmosphere Model version 1
    Copernicus GmbH ; 2022
    In:  Geoscientific Model Development Vol. 15, No. 7 ( 2022-04-07), p. 2881-2916
    Details
    In: Geoscientific Model Development, Copernicus GmbH, Vol. 15, No. 7 ( 2022-04-07), p. 2881-2916
    Abstract: Abstract. Realistic simulation of the Earth's mean-state climate remains a major challenge, and yet it is crucial for predicting the climate system in transition. Deficiencies in models' process representations, propagation of errors from one process to another, and associated compensating errors can often confound the interpretation and improvement of model simulations. These errors and biases can also lead to unrealistic climate projections and incorrect attribution of the physical mechanisms governing past and future climate change. Here we show that a significantly improved global atmospheric simulation can be achieved by focusing on the realism of process assumptions in cloud calibration and subgrid effects using the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1). The calibration of clouds and subgrid effects informed by our understanding of physical mechanisms leads to significant improvements in clouds and precipitation climatology, reducing common and long-standing biases across cloud regimes in the model. The improved cloud fidelity in turn reduces biases in other aspects of the system. Furthermore, even though the recalibration does not change the global mean aerosol and total anthropogenic effective radiative forcings (ERFs), the sensitivity of clouds, precipitation, and surface temperature to aerosol perturbations is significantly reduced. This suggests that it is possible to achieve improvements to the historical evolution of surface temperature over EAMv1 and that precise knowledge of global mean ERFs is not enough to constrain historical or future climate change. Cloud feedbacks are also significantly reduced in the recalibrated model, suggesting that there would be a lower climate sensitivity when it is run as part of the fully coupled E3SM. This study also compares results from incremental changes to cloud microphysics, turbulent mixing, deep convection, and subgrid effects to understand how assumptions in the representation of these processes affect different aspects of the simulated atmosphere as well as its response to forcings. We conclude that the spectral composition and geographical distribution of the ERFs and cloud feedback, as well as the fidelity of the simulated base climate state, are important for constraining the climate in the past and future.
    Type of Medium: Online Resource
    ISSN: 1991-9603
    URL: Article
    DOI: 10.5194/gmd-15-2881-2022
    Language: English
    Publisher: Copernicus GmbH
    Publication Date: 2022
    detail.hit.zdb_id: 2456725-5
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  • 4
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    Contributions of Different Cloud Types to Feedbacks and Rapid Adjustments in CMIP5*
    American Meteorological Society ; 2013
    In:  Journal of Climate Vol. 26, No. 14 ( 2013-07-15), p. 5007-5027
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 26, No. 14 ( 2013-07-15), p. 5007-5027
    Abstract: Using five climate model simulations of the response to an abrupt quadrupling of CO2, the authors perform the first simultaneous model intercomparison of cloud feedbacks and rapid radiative adjustments with cloud masking effects removed, partitioned among changes in cloud types and gross cloud properties. Upon CO2 quadrupling, clouds exhibit a rapid reduction in fractional coverage, cloud-top pressure, and optical depth, with each contributing equally to a 1.1 W m−2 net cloud radiative adjustment, primarily from shortwave radiation. Rapid reductions in midlevel clouds and optically thick clouds are important in reducing planetary albedo in every model. As the planet warms, clouds become fewer, higher, and thicker, and global mean net cloud feedback is positive in all but one model and results primarily from increased trapping of longwave radiation. As was true for earlier models, high cloud changes are the largest contributor to intermodel spread in longwave and shortwave cloud feedbacks, but low cloud changes are the largest contributor to the mean and spread in net cloud feedback. The importance of the negative optical depth feedback relative to the amount feedback at high latitudes is even more marked than in earlier models. The authors show that the negative longwave cloud adjustment inferred in previous studies is primarily caused by a 1.3 W m−2 cloud masking of CO2 forcing. Properly accounting for cloud masking increases net cloud feedback by 0.3 W m−2 K−1, whereas accounting for rapid adjustments reduces by 0.14 W m−2 K−1 the ensemble mean net cloud feedback through a combination of smaller positive cloud amount and altitude feedbacks and larger negative optical depth feedbacks.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-12-00555.1
    DOI: 10.1175/JCLI-D-12-00555.s1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2013
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 5
    Online Resource
    Online Resource
    Clearing clouds of uncertainty
    Springer Science and Business Media LLC ; 2017
    In:  Nature Climate Change Vol. 7, No. 10 ( 2017-10), p. 674-678
    Details
    In: Nature Climate Change, Springer Science and Business Media LLC, Vol. 7, No. 10 ( 2017-10), p. 674-678
    Type of Medium: Online Resource
    ISSN: 1758-678X , 1758-6798
    URL: Article
    DOI: 10.1038/nclimate3402
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 2603450-5
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  • 6
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    Online Resource
    Sources of Intermodel Spread in the Lapse Rate and Water Vapor Feedbacks
    American Meteorological Society ; 2018
    In:  Journal of Climate Vol. 31, No. 8 ( 2018-04-15), p. 3187-3206
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 31, No. 8 ( 2018-04-15), p. 3187-3206
    Abstract: Sources of intermodel differences in the global lapse rate (LR) and water vapor (WV) feedbacks are assessed using CO2 forcing simulations from 28 general circulation models. Tropical surface warming leads to significant warming and moistening in the tropical and extratropical upper troposphere, signifying a nonlocal, tropical influence on extratropical radiation and feedbacks. Model spread in the locally defined LR and WV feedbacks is pronounced in the Southern Ocean because of large-scale ocean upwelling, which reduces surface warming and decouples the surface from the tropospheric response. The magnitude of local extratropical feedbacks across models and over time is well characterized using the ratio of tropical to extratropical surface warming. It is shown that model differences in locally defined LR and WV feedbacks, particularly over the southern extratropics, drive model variability in the global feedbacks. The cross-model correlation between the global LR and WV feedbacks therefore does not arise from their covariation in the tropics, but rather from the pattern of warming exerting a common control on extratropical feedback responses. Because local feedbacks over the Southern Hemisphere are an important contributor to the global feedback, the partitioning of surface warming between the tropics and the southern extratropics is a key determinant of the spread in the global LR and WV feedbacks. It is also shown that model Antarctic sea ice climatology influences sea ice area changes and southern extratropical surface warming. As a result, model discrepancies in climatological Antarctic sea ice area have a significant impact on the intermodel spread of the global LR and WV feedbacks.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    DOI: 10.1175/JCLI-D-17-0674.1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2018
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 7
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    Competing Influences of Anthropogenic Warming, ENSO, and Plant Physiology on Future Terrestrial Aridity
    American Meteorological Society ; 2017
    In:  Journal of Climate Vol. 30, No. 17 ( 2017-09), p. 6883-6904
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 30, No. 17 ( 2017-09), p. 6883-6904
    Abstract: The 2011–16 California drought illustrates that drought-prone areas do not always experience relief once a favorable phase of El Niño–Southern Oscillation (ENSO) returns. In the twenty-first century, such an expectation is unrealistic in regions where global warming induces an increase in terrestrial aridity larger than the changes in aridity driven by ENSO variability. This premise is also flawed in areas where precipitation supply cannot offset the global warming–induced increase in evaporative demand. Here, atmosphere-only experiments are analyzed to identify land regions where aridity is currently sensitive to ENSO and where projected future changes in mean aridity exceed the range caused by ENSO variability. Insights into the drivers of these changes in aridity are obtained using simulations with the incremental addition of three different factors to the current climate: ocean warming, vegetation response to elevated CO 2 levels, and intensified CO 2 radiative forcing. The effect of ocean warming overwhelms the range of ENSO-driven temperature variability worldwide, increasing potential evapotranspiration (PET) in most ENSO-sensitive regions. Additionally, about 39% of the regions currently sensitive to ENSO will likely receive less precipitation in the future, independent of the ENSO phase. Consequently aridity increases in 67%–72% of the ENSO-sensitive area. When both radiative and physiological effects are considered, the area affected by arid conditions rises to 75%–79% when using PET-derived measures of aridity, but declines to 41% when an aridity indicator for total soil moisture is employed. This reduction mainly occurs because plant stomatal resistance increases under enhanced CO 2 concentrations, resulting in improved plant water-use efficiency, and hence reduced evapotranspiration and soil desiccation. Imposing CO 2 -invariant stomatal resistance may overestimate future drying in PET-derived indices.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-17-0005.1
    DOI: 10.1175/JCLI-D-17-0005.s1
    RVK:
    UA 4548
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2017
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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  • 8
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    Online Resource
    Statistical significance of climate sensitivity predictors obtained by data mining
    American Geophysical Union (AGU) ; 2014
    In:  Geophysical Research Letters Vol. 41, No. 5 ( 2014-03-16), p. 1803-1808
    Details
    In: Geophysical Research Letters, American Geophysical Union (AGU), Vol. 41, No. 5 ( 2014-03-16), p. 1803-1808
    Abstract: Correlation magnitude is not sufficient proof of predictive skill Significance testing is complicated by model nonindependence in ensembles The best predictors of climate change are related to the Southern Ocean
    Type of Medium: Online Resource
    ISSN: 0094-8276 , 1944-8007
    URL: Issue
    URL: Article
    DOI: 10.1002/grl.v41.5
    DOI: 10.1002/2014GL059205
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2014
    detail.hit.zdb_id: 2021599-X
    detail.hit.zdb_id: 7403-2
    SSG: 16,13
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  • 9
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    Volcanic contribution to decadal changes in tropospheric temperature
    Springer Science and Business Media LLC ; 2014
    In:  Nature Geoscience Vol. 7, No. 3 ( 2014-3), p. 185-189
    Details
    In: Nature Geoscience, Springer Science and Business Media LLC, Vol. 7, No. 3 ( 2014-3), p. 185-189
    Type of Medium: Online Resource
    ISSN: 1752-0894 , 1752-0908
    URL: Article
    DOI: 10.1038/ngeo2098
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2014
    detail.hit.zdb_id: 2396648-8
    detail.hit.zdb_id: 2405323-5
    SSG: 16,13
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  • 10
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    Using Climate Model Simulations to Constrain Observations
    American Meteorological Society ; 2021
    In:  Journal of Climate Vol. 34, No. 15 ( 2021-08), p. 6281-6301
    Details
    In: Journal of Climate, American Meteorological Society, Vol. 34, No. 15 ( 2021-08), p. 6281-6301
    Abstract: We compare atmospheric temperature changes in satellite data and in model ensembles performed under phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). In the lower stratosphere, multidecadal stratospheric cooling during the period of strong ozone depletion is smaller in newer CMIP6 simulations than in CMIP5 or satellite data. In the troposphere, however, despite forcing and climate sensitivity differences between the two CMIP ensembles, their ensemble-average global warming over 1979–2019 is very similar. We also examine four properties of tropical behavior governed by basic physical processes. The first three are ratios between trends in water vapor (WV) and trends in sea surface temperature (SST), lower-tropospheric temperature (TLT), and mid- to upper-tropospheric temperature (TMT). The fourth property is the ratio between TMT and SST trends. All four ratios are tightly constrained in CMIP simulations but diverge markedly in observations. Model trend ratios between WV and temperature are closest to observed ratios when the latter are calculated with datasets exhibiting larger tropical warming of the ocean surface and troposphere. For the TMT/SST ratio, model–data consistency depends on the combination of observations used to estimate TMT and SST trends. If model expectations of these four covariance relationships are realistic, our findings reflect either a systematic low bias in satellite tropospheric temperature trends or an overestimate of the observed atmospheric moistening signal. It is currently difficult to determine which interpretation is more credible. Nevertheless, our analysis reveals anomalous covariance behavior in several observational datasets and illustrates the diagnostic power of simultaneously considering multiple complementary variables.
    Type of Medium: Online Resource
    ISSN: 0894-8755 , 1520-0442
    URL: Article
    URL: Article
    DOI: 10.1175/JCLI-D-20-0768.1
    DOI: 10.1175/JCLI-D-20-0768.s1
    RVK:
    UA 4548
    Language: Unknown
    Publisher: American Meteorological Society
    Publication Date: 2021
    detail.hit.zdb_id: 246750-1
    detail.hit.zdb_id: 2021723-7
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