scholarly journals Reduced Complexity Model Intercomparison Project Phase 2: Synthesising Earth system knowledge for probabilistic climate projections

2020 ◽  
Author(s):  
Zebedee R.J. Nicholls ◽  
Malte Alexander Meinshausen ◽  
Jared Lewis ◽  
Maisa Rojas Corradi ◽  
Kalyn Dorheim ◽  
...  
Keyword(s):  
Climate Projections ◽  
Earth System ◽  
Phase 2 ◽  
Model Intercomparison ◽  
Probabilistic Climate Projections ◽  
Intercomparison Project ◽  
Reduced Complexity ◽  
System Knowledge

scholarly journals Reduced Complexity Model Intercomparison Project Phase 2: Synthesising Earth system knowledge for probabilistic climate projections

2021 ◽  
Author(s):  
Zebedee R.J. Nicholls ◽  
Malte Alexander Meinshausen ◽  
Jared Lewis ◽  
Maisa Rojas Corradi ◽  
Kalyn Dorheim ◽  
...  
Keyword(s):  
Climate Projections ◽  
Earth System ◽  
Phase 2 ◽  
Model Intercomparison ◽  
Probabilistic Climate Projections ◽  
Intercomparison Project ◽  
Reduced Complexity ◽  
System Knowledge

scholarly journals Reduced Complexity Model Intercomparison Project Phase 1: introduction and evaluation of global-mean temperature response

2020 ◽  
Vol 13 (11) ◽  
pp. 5175-5190
Author(s):  
Zebedee R. J. Nicholls ◽  
Malte Meinshausen ◽  
Jared Lewis ◽  
Robert Gieseke ◽  
Dietmar Dommenget ◽  
...  
Keyword(s):  
Phase 1 ◽  
Temperature Response ◽  
Earth System ◽  
Model Intercomparison ◽  
Radiative Forcings ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Intercomparison Project ◽  
Reduced Complexity ◽  
Global Mean

Abstract. Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

Probabilistic climate projections with Minimal CMIP Emulator (MCE)

2021 ◽  
Author(s):  
Junichi Tsutsui
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Model Parameters ◽  
Climate Projections ◽  
Second Phase ◽  
Impulse Response Functions ◽  
Model Intercomparison ◽  
Probabilistic Climate Projections ◽  
Intercomparison Project

<p>One of the key applications of simple climate models is probabilistic climate projections to assess a variety of emission scenarios in terms of their compatibility with global warming mitigation goals. The second phase of the Reduced Complexity Model Intercomparison Project (RCMIP) compares nine participating models for their probabilistic projection methods through scenario experiments, focusing on consistency with given constraints for climate indicators including radiative forcing, carbon budget, warming trends, and climate sensitivity. The MCE is one of the nine models, recently developed by the author, and has produced results that well match the ranges of the constraints. The model is based on impulse response functions and parameterized physics of effective radiative forcing and carbon uptake over ocean and land. Perturbed model parameters are generated from statistical models and constrained with a Metropolis-Hastings independence sampler. A parameter subset associated with CO<sub>2</sub>-induced warming is assured to have a covariance structure as diagnosed from complex climate models of the Coupled Model Intercomparison Project (CMIP). The model's simplicity and the successful results imply that a method with less complicated structures and fewer control parameters has an advantage when building reasonable perturbed ensembles in a transparent way despite less capacity to emulate detailed Earth system components. Experimental results for future scenarios show that the climate sensitivity of CMIP models is overestimated overall, suggesting that probabilistic climate projections need to be constrained with observed warming trends.</p>

scholarly journals A return to large-scale features of Pliocene climate: the Pliocene Model Intercomparison Project Phase 2

2020 ◽  
Author(s):  
Alan M. Haywood ◽  
Julia C. Tindall ◽  
Harry J. Dowsett ◽  
Aisling M. Dolan ◽  
Kevin M. Foley ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Temperature Response ◽  
Surface Air Temperature ◽  
Co2 Concentration ◽  
Mean Value ◽  
System Response ◽  
Phase 2 ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract. The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO2 concentration near ~ 400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution and based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.4 and 4.7 °C relative to pre-industrial with a multi-model mean value of 2.8 °C. Annual mean total precipitation rates increase by 6 % (range: 2 %–13 %). On average, surface air temperature (SAT) increases are 1.3 °C greater over the land than over the oceans, and there is a clear pattern of polar amplification with warming polewards of 60° N and 60° S exceeding the global mean warming by a factor of 2.4. In the Atlantic and Pacific Oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. Although there are some modelling constraints, there is a statistically significant relationship between a model's climate response associated with a doubling in CO2 (Equilibrium Climate Sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble earth system response to doubling of CO2 (including ice sheet feedbacks) is approximately 50 % greater than ECS, consistent with results from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea-surface temperatures are used to assess model estimates of ECS and indicate a range in ECS from 2.5 to 4.3 °C. This result is in general accord with the range in ECS presented by previous IPCC Assessment Reports.

Workflow and tools to analyse the PMIP4-CMIP6 ensemble

2021 ◽  
Author(s):  
Anni Zhao ◽  
Chris Brierley
Keyword(s):  
Case Studies ◽  
Coupled Model ◽  
Important Case ◽  
Earth System ◽  
Model Intercomparison ◽  
Past Climate ◽  
The Past ◽  
The Earth ◽  
Intercomparison Project

<p>Experiment outputs are now available from the Coupled Model Intercomparison Project’s 6<sup>th</sup> phase (CMIP6) and the past climate experiments defined in the Model Intercomparison Project’s 4<sup>th</sup> phase (PMIP4). All of this output is freely available from the Earth System Grid Federation (ESGF). Yet there are overheads in analysing this resource that may prove complicated or prohibitive. Here we document the steps taken by ourselves to produce ensemble analyses covering past and future simulations. We outline the strategy used to curate, adjust the monthly calendar aggregation and process the information downloaded from the ESGF. The results of these steps were used to perform analysis for several of the initial publications arising from PMIP4. We provide post-processed fields for each simulation, such as climatologies and common measures of variability. Example scripts used to visualise and analyse these fields is provided for several important case studies.</p>

scholarly journals CAS-ESM2.0 Model Datasets for the CMIP6 Ocean Model Intercomparison Project Phase 1 (OMIP1)

2020 ◽  
Author(s):  
Xiao Dong ◽  
Jiangbo Jin ◽  
Hailong Liu ◽  
He Zhang ◽  
Minghua Zhang ◽  
...  
Keyword(s):  
Sea Ice ◽  
Phase 1 ◽  
Ocean Model ◽  
Meridional Overturning Circulation ◽  
Sea Surface ◽  
Global Ocean ◽  
Quasi Equilibrium ◽  
Earth System ◽  
Model Intercomparison ◽  
Intercomparison Project

AbstractAs a member of the Chinese modeling groups, the coupled ocean-ice component of the Chinese Academy of Sciences’ Earth System Model, version 2.0 (CAS-ESM2.0), is taking part in the Ocean Model Intercomparison Project Phase 1 (OMIP1) experiment of phase 6 of the Coupled Model Intercomparison Project (CMIP6). The simulation was conducted, and monthly outputs have been published on the ESGF (Earth System Grid Federation) data server. In this paper, the experimental dataset is introduced, and the preliminary performances of the ocean model in simulating the global ocean temperature, salinity, sea surface temperature, sea surface salinity, sea surface height, sea ice, and Atlantic Meridional Overturning Circulation (AMOC) are evaluated. The results show that the model is at quasi-equilibrium during the integration of 372 years, and performances of the model are reasonable compared with observations. This dataset is ready to be downloaded and used by the community in related research, e.g., multi-ocean-sea-ice model performance evaluation and interannual variation in oceans driven by prescribed atmospheric forcing.

scholarly journals Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Vimal Mishra ◽  
Udit Bhatia ◽  
Amar Deep Tiwari
Keyword(s):  
Climate Change ◽  
Impact Assessment ◽  
South Asia ◽  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
River Basins ◽  
Climate Projections ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract Climate change is likely to pose enormous challenges for agriculture, water resources, infrastructure, and livelihood of millions of people living in South Asia. Here, we develop daily bias-corrected data of precipitation, maximum and minimum temperatures at 0.25° spatial resolution for South Asia (India, Pakistan, Bangladesh, Nepal, Bhutan, and Sri Lanka) and 18 river basins located in the Indian sub-continent. The bias-corrected dataset is developed using Empirical Quantile Mapping (EQM) for the historic (1951–2014) and projected (2015–2100) climate for the four scenarios (SSP126, SSP245, SSP370, SSP585) using output from 13 General Circulation Models (GCMs) from Coupled Model Intercomparison Project-6 (CMIP6). The bias-corrected dataset was evaluated against the observations for both mean and extremes of precipitation, maximum and minimum temperatures. Bias corrected projections from 13 CMIP6-GCMs project a warmer (3–5°C) and wetter (13–30%) climate in South Asia in the 21st century. The bias-corrected projections from CMIP6-GCMs can be used for climate change impact assessment in South Asia and hydrologic impact assessment in the sub-continental river basins.

scholarly journals The distributed model intercomparison project – Phase 2: Experiment design and summary results of the western basin experiments

2013 ◽  
Vol 507 ◽  
pp. 300-329 ◽  
Author(s):  
Michael Smith ◽  
Victor Koren ◽  
Ziya Zhang ◽  
Fekadu Moreda ◽  
Zhengtao Cui ◽  
...  
Keyword(s):  
Experiment Design ◽  
Distributed Model ◽  
Phase 2 ◽  
Model Intercomparison ◽  
Western Basin ◽  
Intercomparison Project
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