The HadGEM2-ES implementation of CMIP5 centennial simulations

Jones, Chris D.; Hughes, John; Bellouin, Nicolas; Hardiman, Steven C.; Jones, Gareth S.; Knight, Jeff; Liddicoat, Spencer; O’Connor, Fiona M.; Andres, R. J.; Bell, Christopher J.; Boo, Kyung‐On; Bozzo, Alessio; Butchart, Neal; Cadule, Patricia; Corbin, K. D.; Doutriaux-Boucher, Marie; Friedlingstein, Pierre; Gornall, Jemma; Gray, Lesley J.; Halloran, Paul R.; Hurtt, George C.; Ingram, William; Lamarque, Jean‐François; Law, R. M.; Meinshausen, Malte; Osprey, Scott; Palin, Erika J.; Chini, L. P.; Raddatz, Thomas; Sanderson, Michael; Sellar, Alistair; Schurer, Andrew; Valdes, Paul J.; Wood, Nigel; Woodward, Stephanie; Yoshioka, M.; Zerroukat, M.

doi:10.5194/gmd-4-543-2011

Cited by 814 publications

(449 citation statements)

References 79 publications

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“…Afterwards, the "RCP6.0" simulation, which is initialized with the historical simulation, is employed. Details of those simulations are described by Jones et al (2011). The simulation of SSTs in HadGEM2 has been significantly improved over the predecessor model HadGEM1, namely, the prominent cold bias in HadGEM1 has been reduced in HadGEM2, and the representation of ENSO has been improved (see also Figs.…”

Section: Sea Surface Temperatures and Sea-ice Concentrationsmentioning

confidence: 99%

“…S36). This development is linked to the prescribed emissions of tropospheric ozone precursors, in particular methane, according to the RCP6.0 scenario (Meinshausen et al, 2011).…”

Section: Tropospheric and Stratospheric Ozonementioning

confidence: 99%

“…The future solar forcing, to be used for the projections, has been prepared according to the solar forcing used for CMIP5 simulation of HadGEM2-ES, where the SSTs and SICs are taken from Jones et al (2011;see also Sect. 3.3).…”

Section: Transient Spectrally Resolved Irradiancesmentioning

confidence: 99%

“…noaa.gov). Where no observations were available, historical and projected mixing ratios of the greenhouse gases and SF 6 were taken from Meinshausen et al (2011) and extended with the RCP6.0 scenario as proposed by Eyring et al (2013b). Mixing ratios of ozone depleting substances were As the mixing ratios recommended by CCMI are only available as global and annual averages, we conducted the following approach: a climatological annual cycle and the latitudinal distribution of each species are calculated from the observed mixing ratios (see above) and applied to the prescribed globally and annually averaged mixing ratios.…”

Section: Prescribed Boundary Conditions: Gas-phase Speciesmentioning

confidence: 99%

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Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51

et al. 2016

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Abstract. Three types of reference simulations, as recommended by the Chemistry-Climate Model Initiative (CCMI), have been performed with version 2.51 of the European Centre for Medium-Range Weather Forecasts -Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model: hindcast simulations , hindcast simulations with specified dynamics , i.e. nudged towards ERA-Interim reanalysis data, and combined hindcast and projection simulations . The manuscript summarizes the updates of the model system and details the different model set-ups used, including the on-line calculated diagnostics. Simulations have been performed with two different nudging setups, with and without interactive tropospheric aerosol, and with and without a coupled ocean model. Two different vertical resolutions have been applied. The on-line calculated sources and sinks of reactive species are quantified and a first evaluation of the simulation results from a global perspective is provided as a quality check of the data. The focus is on the intercomparison of the different model set-ups. The simulation data will become publicly available via CCMI and the Climate and Environmental Retrieval and Archive (CERA) database of the German Climate Computing Centre (DKRZ). This manuscript is intended to serve as an extensive reference for further analyses of the Earth System Chemistry integrated Modelling (ESCiMo) simulations.

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Section: Sea Surface Temperatures and Sea-ice Concentrationsmentioning

confidence: 99%

“…S36). This development is linked to the prescribed emissions of tropospheric ozone precursors, in particular methane, according to the RCP6.0 scenario (Meinshausen et al, 2011).…”

Section: Tropospheric and Stratospheric Ozonementioning

confidence: 99%

Section: Transient Spectrally Resolved Irradiancesmentioning

confidence: 99%

Section: Prescribed Boundary Conditions: Gas-phase Speciesmentioning

confidence: 99%

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Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51

et al. 2016

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“…A box defined by about 1°of latitude and 1°of longitude represents an area of 100 km by 200 km. The atmosphere is divided into 38 unequal levels and the level near the land and ocean surface is about 20 m deep (Jones et al, 2011).…”

Section: Future Climate Change Scenario and Gcmmentioning

confidence: 99%

Evaluation of a multi-site weather generator in simulating precipitation in the Qiantang River Basin, East China

Pan

et al. 2014

J. Zheijang Univ.-Sci.

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Abstract:Recent years have seen a surge in assessment of potential impacts of climate change. As one of the most important tools for generating synthetic hydrological model inputs, weather generators have played an important role in climate change impact analysis of water management. However, most weather generators like statistical downscaling model (SDSM) and long Ashton research station weather generator (LARS-WG) are designed for single site data generation. Considering the significance of spatial correlations of hydro-meteorological data, multi-site weather data generation becomes a necessity. In this study we aim to evaluate the performance of a new multi-site stochastic model, geo-spatial temporal weather generator (GiST), in simulating precipitation in the Qiantang River Basin, East China. The correlation matrix, precipitation amount and occurrence of observed and GiST-generated data are first compared for the evaluation process. Then we use the GiST model combined with the change factor method (CFM) to investigate future changes of precipitation (2071-2100) in the study area using one global climate model, Hadgem2_ES, and an extreme emission scenario RCP 8.5. The final results show that the simulated precipitation amount and occurrence by GiST matched their historical counterparts reasonably. The correlation coefficients between simulated and historical precipitations show good consistence as well. Compared with the baseline period , precipitation in the future time period (2071-2100) at high elevation stations will probably increase while at other stations decreases will occur. This study implies potential application of the GiST stochastic model in investigating the impact of climate change on hydrology and water resources.

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Meeting the radiative forcing targets of the representative concentration pathways in a world with agricultural climate impacts

et al. 2014

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This study assesses how climate impacts on agriculture may change the evolution of the agricultural and energy systems in meeting the end-of-century radiative forcing targets of the representative concentration pathways (RCPs). We build on the recently completed Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) exercise that has produced global gridded estimates of future crop yields for major agricultural crops using climate model projections of the RCPs from the Coupled Model Intercomparison Project Phase 5 (CMIP5). For this study we use the bias-corrected outputs of the HadGEM2-ES climate model as inputs to the LPJmL crop growth model, and the outputs of LPJmL to modify inputs to the GCAM integrated assessment model. Our results indicate that agricultural climate impacts generally lead to an increase in global cropland, as compared with corresponding emissions scenarios that do not consider climate impacts on agricultural productivity. This is driven mostly by negative impacts on wheat, rice, other grains, and oil crops. Still, including agricultural climate impacts does not significantly increase the costs or change the technological strategies of global, whole-system emissions mitigation. In fact, to meet the most aggressive climate change mitigation target (2.6 W/m 2 in 2100), the net mitigation costs are slightly lower when agricultural climate impacts are considered. Key contributing factors to these results are (a) low levels of climate change in the low-forcing scenarios, (b) adaptation to climate impacts simulated in GCAM through inter-regional shifting in the production of agricultural goods, and (c) positive average climate impacts on bioenergy crop yields.

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The HadGEM2-ES implementation of CMIP5 centennial simulations

Cited by 814 publications

References 79 publications

Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51

Earth System Chemistry integrated Modelling (ESCiMo) with the Modular Earth Submodel System (MESSy) version 2.51

Evaluation of a multi-site weather generator in simulating precipitation in the Qiantang River Basin, East China

Meeting the radiative forcing targets of the representative concentration pathways in a world with agricultural climate impacts

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