Effects of Dynamic Vegetation on Global Climate Simulation Using the NCEP GFS and SSiB4/TRIFFID

Abstract. The mid-Pliocene (3.3 to 3.0 million yr ago), a globally warm period before the Quaternary, is recently attracting attention as a new target for paleoclimate modelling and data-model synthesis. This paper reports set-ups and results of experiments proposed in Pliocene Model Intercomparison Project (PlioMIP) using a global climate model, MRI-CGCM2.3. We conducted pre-industrial and mid-Pliocene runs by using the coupled atmosphere-ocean general circulation model (AOGCM) and its atmospheric component (AGCM) for the PlioMIP Experiments 2 and 1, respectively. In addition, we conducted two types of integrations in AOGCM simulation, with and without flux adjustments on sea surface. General characteristics of differences in the simulated mid-Pliocene climate relative to the pre-industrial in the three integrations are compared. In addition, patterns of predicted mid-Pliocene biomes resulting from the three climate simulations are compared in this study. Generally, difference of simulated surface climate between AGCM and AOGCM is larger than that between the two AOGCM runs, with and without flux adjustments. The simulated climate shows different pattern between AGCM and AOGCM particularly over low latitude oceans, subtropical land regions and high latitude oceans. The AOGCM simulations do not reproduce wetter environment in the subtropics relative to the present-day, which is suggested by terrestrial proxy data. The differences between the two types of AOGCM runs are small over the land, but evident over the ocean particularly in the North Atlantic and polar regions.

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Climate change, historical data and catastrophe modelling

10.5194/egusphere-egu2020-20647 ◽

2020 ◽

Author(s):

Richard Dixon ◽

Sam Franklin ◽

Len Shaffrey ◽

Debbie Clifford

Keyword(s):

Climate Change ◽

Historical Data ◽

Global Climate ◽

Climate Simulation ◽

Daily Maximum ◽

Limited Information ◽

Exposure Data ◽

European Industry ◽

Catastrophe Modelling ◽

European Insurance

<p>This presentation will discuss climate change in the context of catastrophe modelling and tail risk. Given that the catastrophe modelling industry typical only has short historical records that provide limited information as to whether hazard is non-stationary, what are the methods and datasets that may aid the catastrophe modelling community to better understand how and whether risk is changing temporally?&#160;</p><p>The issues will be framed by using examples of output from a multi-year multi-ensemble 60km global climate simulation, where extra-tropical windstorm daily maximum gust data has been converted into yearly aggregate European insurance loss with the help of PERILS European industry exposure data. The data is used to show how reliance on single historical datasets can produce misleading trends in catastrophe losses - but also potentially point to underlying trends in risk that single historical datasets may not be able to detect.</p>

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Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0

Geoscientific Model Development ◽

10.5194/gmd-11-1665-2018 ◽

2018 ◽

Vol 11 (4) ◽

pp. 1665-1681 ◽

Cited By ~ 35

Author(s):

Oliver Fuhrer ◽

Tarun Chadha ◽

Torsten Hoefler ◽

Grzegorz Kwasniewski ◽

Xavier Lapillonne ◽

...

Keyword(s):

Graphics Processing Units ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Atmospheric Model ◽

Climate Simulation ◽

Performance Portability ◽

Domain Specific ◽

Hardware Architectures ◽

Graphics Processing

Abstract. The best hope for reducing long-standing global climate model biases is by increasing resolution to the kilometer scale. Here we present results from an ultrahigh-resolution non-hydrostatic climate model for a near-global setup running on the full Piz Daint supercomputer on 4888 GPUs (graphics processing units). The dynamical core of the model has been completely rewritten using a domain-specific language (DSL) for performance portability across different hardware architectures. Physical parameterizations and diagnostics have been ported using compiler directives. To our knowledge this represents the first complete atmospheric model being run entirely on accelerators on this scale. At a grid spacing of 930 m (1.9 km), we achieve a simulation throughput of 0.043 (0.23) simulated years per day and an energy consumption of 596 MWh per simulated year. Furthermore, we propose a new memory usage efficiency (MUE) metric that considers how efficiently the memory bandwidth – the dominant bottleneck of climate codes – is being used.

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Improvement of ENSO Simulation Based on Intermodel Diversity

Journal of Climate ◽

10.1175/jcli-d-14-00376.1 ◽

2015 ◽

Vol 28 (3) ◽

pp. 998-1015 ◽

Cited By ~ 39

Author(s):

Yoo-Geun Ham ◽

Jong-Seong Kug

Keyword(s):

Interannual Variability ◽

El Niño ◽

Climate Models ◽

El Nino ◽

Southern Oscillation ◽

Global Climate ◽

Coupled Model ◽

Global Climate Models ◽

Climate Simulation ◽

Central Pacific

Abstract In this study, a new methodology is developed to improve the climate simulation of state-of-the-art coupled global climate models (GCMs), by a postprocessing based on the intermodel diversity. Based on the close connection between the interannual variability and climatological states, the distinctive relation between the intermodel diversity of the interannual variability and that of the basic state is found. Based on this relation, the simulated interannual variabilities can be improved, by correcting their climatological bias. To test this methodology, the dominant intermodel difference in precipitation responses during El Niño–Southern Oscillation (ENSO) is investigated, and its relationship with climatological state. It is found that the dominant intermodel diversity of the ENSO precipitation in phase 5 of the Coupled Model Intercomparison Project (CMIP5) is associated with the zonal shift of the positive precipitation center during El Niño. This dominant intermodel difference is significantly correlated with the basic states. The models with wetter (dryer) climatology than the climatology of the multimodel ensemble (MME) over the central Pacific tend to shift positive ENSO precipitation anomalies to the east (west). Based on the model’s systematic errors in atmospheric ENSO response and bias, the models with better climatological state tend to simulate more realistic atmospheric ENSO responses. Therefore, the statistical method to correct the ENSO response mostly improves the ENSO response. After the statistical correction, simulating quality of the MME ENSO precipitation is distinctively improved. These results provide a possibility that the present methodology can be also applied to improving climate projection and seasonal climate prediction.

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Numerical Simulations of Heavy Rainfalls by a Global Cloud-Resolving Model

Journal of Disaster Research ◽

10.20965/jdr.2008.p0033 ◽

2008 ◽

Vol 3 (1) ◽

pp. 33-38 ◽

Cited By ~ 3

Author(s):

Masaki Satoh ◽

◽

Keyword(s):

Weather Forecasting ◽

Global Climate ◽

Climate Simulation ◽

Short Term ◽

Cloud Resolving Model ◽

Numerical Weather Forecasting ◽

Simulation Results ◽

Tropical Weather ◽

The Tropics

The Global Cloud-Resolving Model is a next-generation atmospheric global model with potential to open up new areas in numerical weather forecasting and climate simulation. The new model, called NICAM, has shown realistic behavior for precipitation systems over the global domain, particularly over the tropics. One impact of the global cloud-resolving model is the attainment of realistic simulation of rainfall in the tropics realizing a multiscale nature from kilometer to planetary, because rainfall in the tropics affects short-term local tropical weather and the long-term global climate. We review the global cloud-resolving model using simulation results from NICAM, and discuss its applicability in reducing natural weather disasters.

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Northern Hemisphere blocking simulation in current climate models: evaluating progress from the Climate Model Intercomparison Project Phase 5 to 6 and sensitivity to resolution

Weather and Climate Dynamics ◽

10.5194/wcd-1-277-2020 ◽

2020 ◽

Vol 1 (1) ◽

pp. 277-292 ◽

Cited By ~ 1

Author(s):

Reinhard Schiemann ◽

Panos Athanasiadis ◽

David Barriopedro ◽

Francisco Doblas-Reyes ◽

Katja Lohmann ◽

...

Keyword(s):

Climate Models ◽

Climate Model ◽

Global Climate ◽

Model Development ◽

Global Climate Models ◽

Assessment Model ◽

Climate Simulation ◽

Cmip5 Models ◽

Model Intercomparison ◽

Intercomparison Project

Abstract. Global climate models (GCMs) are known to suffer from biases in the simulation of atmospheric blocking, and this study provides an assessment of how blocking is represented by the latest generation of GCMs. It is evaluated (i) how historical CMIP6 (Climate Model Intercomparison Project Phase 6) simulations perform compared to CMIP5 simulations and (ii) how horizontal model resolution affects the simulation of blocking in the CMIP6-HighResMIP (PRIMAVERA – PRocess-based climate sIMulation: AdVances in high-resolution modelling and European climate Risk Assessment) model ensemble, which is designed to address this type of question. Two blocking indices are used to evaluate the simulated mean blocking frequency and blocking persistence for the Euro-Atlantic and Pacific regions in winter and summer against the corresponding estimates from atmospheric reanalysis data. There is robust evidence that CMIP6 models simulate blocking frequency and persistence better than CMIP5 models in the Atlantic and Pacific and during winter and summer. This improvement is sizeable so that, for example, winter blocking frequency in the median CMIP5 model in a large Euro-Atlantic domain is underestimated by 33 % using the absolute geopotential height (AGP) blocking index, whereas the same number is 18 % for the median CMIP6 model. As for the sensitivity of simulated blocking to resolution, it is found that the resolution increase, from typically 100 to 20 km grid spacing, in most of the PRIMAVERA models, which are not re-tuned at the higher resolutions, benefits the mean blocking frequency in the Atlantic in winter and summer and in the Pacific in summer. Simulated blocking persistence, however, is not seen to improve with resolution. Our results are consistent with previous studies suggesting that resolution is one of a number of interacting factors necessary for an adequate simulation of blocking in GCMs. The improvements reported in this study hold promise for further reductions in blocking biases as model development continues.

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Unprecedented cloud resolution in a GPU-enabled full-physics atmospheric climate simulation on OLCF’s summit supercomputer

The International Journal of High Performance Computing Applications ◽

10.1177/10943420211027539 ◽

2021 ◽

pp. 109434202110275

Author(s):

Matthew R Norman ◽

David A Bader ◽

Christopher Eldred ◽

Walter M Hannah ◽

Benjamin R Hillman ◽

...

Keyword(s):

High Resolution ◽

Climate Model ◽

Global Climate ◽

Global Climate Model ◽

Climate Simulation ◽

Modeling Framework ◽

Multi Scale ◽

Scale Modeling ◽

Computational Capability ◽

Parallel Data

Clouds represent a key uncertainty in future climate projection. While explicit cloud resolution remains beyond our computational grasp for global climate, we can incorporate important cloud effects through a computational middle ground called the Multi-scale Modeling Framework (MMF), also known as Super Parameterization. This algorithmic approach embeds high-resolution Cloud Resolving Models (CRMs) to represent moist convective processes within each grid column in a Global Climate Model (GCM). The MMF code requires no parallel data transfers and provides a self-contained target for acceleration. This study investigates the performance of the Energy Exascale Earth System Model-MMF (E3SM-MMF) code on the OLCF Summit supercomputer at an unprecedented scale of simulation. Hundreds of kernels in the roughly 10K lines of code in the E3SM-MMF CRM were ported to GPUs with OpenACC directives. A high-resolution benchmark using 4600 nodes on Summit demonstrates the computational capability of the GPU-enabled E3SM-MMF code in a full physics climate simulation.

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