The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate

Bentsen, Mats; Bethke, Ingo; Debernard, Jens Boldingh; Iversen, Trond; Kirkevåg, Alf; Seland, Øyvind; Drange, Helge; Roelandt, C.; Seierstad, Ivar A.; Hoose, Corinna; Kristjánsson, Jón Egill

doi:10.5194/gmd-6-687-2013

Cited by 836 publications

(602 citation statements)

References 162 publications

(223 reference statements)

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“…The rank that the observational estimates would have as a member of each ensemble of simulations [Hamill, 2001;Annan and Hargreaves, 2010] shows a slight tendency for observational estimates to fall with a higher frequency in the vicinity of the lower simulations for the CMIP5 (Figure 1c). This behavior is not present in the MPI-ESM large ensemble (Figure 1d) and is most likely caused by estimates in the period of 1999-2014.…”

Section: Internal Variability In Tropical Tropospheric Temperaturesmentioning

confidence: 99%

“…For simulations, we use historical and RCP4.5 runs from 44 different GCMs from the CMIP5 archive [Taylor et al, 2012;Bi et al, 2013;Xin et al, 2013;Ji et al, 2014;von Salzen et al, 2013;Meehl et al, 2012;Hurrell et al, 2012;Scoccimarro et al, 2011;Voldoire et al, 2013;Rotstayn et al, 2010;Hazeleger et al, 2010;Li et al, 2013;Delworth et al, 2006;Donner et al, 2011;Schmidt et al, 2014;Smith et al, 2010;Collins et al, 2011;Jones et al, 2011;Volodin et al, 2010;Dufresne et al, 2013;Hourdin et al, 2013;Sakamoto et al, 2012;Watanabe et al, 2010Watanabe et al, , 2011Giorgetta et al, 2013;Yukimoto et al, 2012;Bentsen et al, 2013], and from the 100 realization single-model large ensemble of the MPI-ESM [Giorgetta et al, 2013]. The large ensemble uses the model version MPI-ESM1.1 in low resolution (LR) configuration, with resolution T63 and 47 vertical levels in the atmosphere and 1.5 ∘ resolution and 40 vertical levels in the ocean.…”

Section: Datamentioning

confidence: 99%

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Internal variability in simulated and observed tropical tropospheric temperature trends

Suárez-Gutiérrez

Thorne

et al. 2017

Geophysical Research Letters

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We explore the extent to which internal variability can reconcile discrepancies between observed and simulated warming in the upper tropical troposphere. We compare all extant radiosonde‐based estimates for the period 1958–2014 to simulations from the Coupled Model Intercomparison Project phase 5 multimodel ensemble and the 100 realization Max Planck Institute large ensemble. We consider annual mean temperatures and all available 30‐and 15‐year trends. Most observed trends fall within the ensemble spread for most of the record, and trends calculated over 15‐year periods show better agreement than 30‐year trends, with generally larger discrepancies for the older observational products. The simulated amplification of surface warming aloft in the troposphere is consistent with observations, and the linear correlation between surface and simultaneous tropospheric warming trends decreases with trend length. We conclude that trend differences between observations and simulations of tropical tropospheric temperatures are dominated by observational uncertainty and chaotic internal variability rather than by systematic errors in model performance.

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Section: Internal Variability In Tropical Tropospheric Temperaturesmentioning

confidence: 99%

Section: Datamentioning

confidence: 99%

Internal variability in simulated and observed tropical tropospheric temperature trends

Suárez-Gutiérrez

Thorne

et al. 2017

Geophysical Research Letters

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“…The estimates were grouped into four submodels: GFDL-ESM2M [57], IPSL-CM5A-LR [58], MIROC-ESM-CHEM [59], and NorESM1-M [60], at two extremes of the concentrations of GHGs, representative concentration pathway (RCP) 2.6 and RCP 8.5, which cover the daily average temperature and precipitation data at a resolution of 0.5 • for the period 1950-2099 (the present research considered only the 2015-2099 subset). Given the greater uncertainty in estimating values from a single set, the average of the four climate models was used.…”

Section: Meteorological Drought Indexmentioning

confidence: 99%

Stock Volume Dependency of Forest Drought Responses in Yunnan, China

Luo

Zhou

et al. 2018

Forests

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Abstract:Revealing forest drought response characteristics and the potential impact factors is quite an important scientific issue against the background of global climate change, which is the foundation to reliably evaluate and predict the effects of future drought. Due to the high spatial heterogeneity of forest properties such as biomass, forest age, and height, and the distinct differences in drought stress in terms of frequency, intensity, and duration, current studies still contain many uncertainties. In this research, we used the forests in Yunnan Province in Southwest China as an example and aimed to reveal the potential impacts of forest properties (i.e., stock volume) on drought response characteristics. Specifically, we divided the forest into five groups of stock volume density values and then analyzed their drought response differences. To depict forest response to drought intensity, the standardized precipitation evapotranspiration index (SPEI) was chosen as the explanatory variable, and the change in remote sensing-based enhanced vegetation index (deficit of MODIS-EVI, dEVI) was chosen as the response variable of drought stress. Given that the SPEI has different time scales, we first analyzed the statistical dependency of SPEIs with different time scales (1 to 36 months) to the response variable (i.e., dEVI). The optimal time scale of SPEI (SPEI opt ) to interpret the maximum variation of dEVI (R-square) was then chosen to build the ultimate statistical models for the five groups of stock volume density. The main findings were as follows: (1) the impacts of drought showed hysteresis and cumulative effects, and the length of the hysteresis increased with stock volume densities; (2) forests with high stock volume densities required more soil water and were therefore more sensitive to the changes in water deficit; (3) compared with the optimal time scale of SPEI (SPEI opt ), the SPEI with the commonly used time scale (e.g., 1, 6, and 12 months) could not well reflect the impacts of drought on forests and the simulation error of dEVI increased with stock volume densities; and (4) forests with higher stock volume densities were likely to experience a greater risk of degradation following higher atmospheric concentrations of greenhouse gases (Representative Concentration Pathway (RCP) 8.5). As a result, both the time scale of the meteorological drought index and the spatial difference in forest stock volumes should be considered when evaluating forest drought responses at regional and global scales.

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“…The simulations were conducted using the coupled atmospheric-ocean-aerosol model NorESM1-M [Bentsen et al, 2013;Iversen et al, 2013]. NorESM1-M is an Earth System Model that for the atmospheric part of the model uses a modified version of the Community Atmospheric Model version 4 [CAM4; Neale et al, 2013]-CAM4-Oslo [Kirkevåg et al, 2013].…”

Section: Climate Modelmentioning

confidence: 99%

Climate effects of a hypothetical regional nuclear war: Sensitivity to emission duration and particle composition

et al. 2016

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Here, we use a coupled atmospheric-ocean-aerosol model to investigate the plume development and climate effects of the smoke generated by fires following a regional nuclear war between emerging third-world nuclear powers. We simulate a standard scenario where 5 Tg of black carbon (BC) is emitted over 1 day in the upper troposphere-lower stratosphere. However, it is likely that the emissions from the fires ignited by bomb detonations include a substantial amount of particulate organic matter (POM) and that they last more than 1 day. We therefore test the sensitivity of the aerosol plume and climate system to the BC/POM ratio (1:3, 1:9) and to the emission length (1 day, 1 week, 1 month). We find that in general, an emission length of 1 month substantially reduces the cooling compared to the 1-day case, whereas taking into account POM emissions notably increases the cooling and the reduction of precipitation associated with the nuclear war during the first year following the detonation. Accounting for POM emissions increases the particle size in the short-emission-length scenarios (1 day/1 week), reducing the residence time of the injected particle. While the initial cooling is more intense when including POM emission, the long-lasting effects, while still large, may be less extreme compared to the BC-only case. Our study highlights that the emission altitude reached by the plume is sensitive to both the particle type emitted by the fires and the emission duration. Consequently, the climate effects of a nuclear war are strongly dependent on these parameters.

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The Norwegian Earth System Model, NorESM1-M – Part 1: Description and basic evaluation of the physical climate

Cited by 836 publications

References 162 publications

Internal variability in simulated and observed tropical tropospheric temperature trends

Internal variability in simulated and observed tropical tropospheric temperature trends

Stock Volume Dependency of Forest Drought Responses in Yunnan, China

Climate effects of a hypothetical regional nuclear war: Sensitivity to emission duration and particle composition

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