Changes in severe indices as simulated by two french coupled global climate models

International audienceExtremes are assessed here in an attempt to validate the two French models in their representation of the second part of the 20th century, using different sources of gridded observational datasets. Models show some ability to simulate extremal behaviour of the climate even if discrepancies are noticeable between models and observations. These may be partly due to the low resolution used for the present study simulations. Extreme indices, calculated using the STARDEX (STAtistical and Regional dynamical Downscaling of EXtremes for European regions) methodology, are investigated in different IPCC (International Panel on Climate Change) scenarios performed by the French community. Investigation of 21st century severe indices simulated in these simulations shows some interesting features. In some parts of the world, extreme temperatures experience a more rapid increase than the mean, suggesting that the Power Density Function (PDF) may not only be shifted toward higher temperatures but also changed in its shape. Extremes of precipitation also experience a change toward more intense precipitation events in winter and longer dry events in summer. Approaching future changes in extreme indices through their relationship to mean annual temperature may be a useful approach in multi-model studies, since it provides a measure of the sensitivity of extremes to warming conditions in these models

The METAFOR project: preserving data through metadata standards for climate models and simulations

Climate modeling is a complex process, requiring accurate and complete metadata in order to identify, assess and use climate data stored in digital repositories. The preservation of such data is increasingly important given the development of ever-increasingly complex models to predict the effects of global climate change. The EU METAFOR project has developed a Common Information Model (CIM) to describe climate data and the models and modelling environments that produce this data. There is a wide degree of variability between different climate models and modelling groups. To accommodate this, the CIM has been designed to be highly generic and flexible, with extensibility built in. METAFOR describes the climate modelling process simply as "an activity undertaken using software on computers to produce data." This process has been described as separate UML packages (and, ultimately, XML schemas). This fairly generic structure canbe paired with more specific "controlled vocabularies" in order to restrict the range of valid CIM instances. The CIM will aid digital preservation of climate models as it will provide an accepted standard structure for the model metadata. Tools to write and manage CIM instances, and to allow convenient and powerful searches of CIM databases,. Are also under development. Community buy-in of the CIM has been achieved through a continual process of consultation with the climate modelling community, and through the METAFOR team’s development of a questionnaire that will be used to collect the metadata for the Intergovernmental Panel on Climate Change’s (IPCC) Coupled Model Intercomparison Project Phase 5 (CMIP5) model runs

Requirements for a global data infrastructure in support of CMIP6

The World Climate Research Programme (WCRP)’s Working Group on Climate Modelling (WGCM) Infrastructure Panel (WIP) was formed in 2014 in response to the explosive growth in size and complexity of Coupled Model Intercomparison Projects (CMIPs) between CMIP3 (2005–2006) and CMIP5 (2011–2012). This article presents the WIP recommendations for the global data infrastruc- ture needed to support CMIP design, future growth, and evolution. Developed in close coordination with those who build and run the existing infrastructure (the Earth System Grid Federation; ESGF), the recommendations are based on several principles beginning with the need to separate requirements, implementation, and operations. Other im- portant principles include the consideration of the diversity of community needs around data – a data ecosystem – the importance of provenance, the need for automation, and the obligation to measure costs and benefits. This paper concentrates on requirements, recognizing the diversity of communities involved (modelers, analysts, soft- ware developers, and downstream users). Such requirements include the need for scientific reproducibility and account- ability alongside the need to record and track data usage. One key element is to generate a dataset-centric rather than system-centric focus, with an aim to making the infrastruc- ture less prone to systemic failure. With these overarching principles and requirements, the WIP has produced a set of position papers, which are summa- rized in the latter pages of this document. They provide spec- ifications for managing and delivering model output, includ- ing strategies for replication and versioning, licensing, data quality assurance, citation, long-term archiving, and dataset tracking. They also describe a new and more formal approach for specifying what data, and associated metadata, should be saved, which enables future data volumes to be estimated, particularly for well-defined projects such as CMIP6. The paper concludes with a future facing consideration of the global data infrastructure evolution that follows from the blurring of boundaries between climate and weather, and the changing nature of published scientific results in the digital age

Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0

The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text-based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non-specialists to access CMIP data in a new, user-friendly way

Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5

We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes

Copernicus Marine Service ocean state report, issue 4

This is the final version. Available from Taylor & Francis via the DOI in this record. FCT/MCTE

Solar forcing and climate variability in the North Atlantic during the last millennium: comparison between models and reconstructions

International audienceStudying the climate of the last millennium allows replacing the present climate change in a long term context. Since it is a relatively well-documented period, it provides an interesting base to assess the secular variability of the climate, free of anthropogenic greenhouse gas influence. Considering this, the climate of the last millennium is likely to have been driven by natural forcings, such as major volcanic eruptions or solar variability. We present here the results of the simulations performed with the IPSLCM4v2 climate model for the French ANR ESCARSEL project (reconstruction of the climate of the last millennium). In order to understand the role of the solar variability during this period, we have forced the model with a reconstruction of the Total Solar Irradiance since 1000AD (Crowley et al., 2000). The results are compared with various reconstructions based on proxy data, from the hemispheric to the continental scale. A new reconstruction of the temperature in Europe since 600AD (annual April to September mean, based on tree rings data) has been achieved within the ESCARSEL project. This dataset provides the possibility to compare the spatial response of the model to the solar forcing with the corresponding temperature patterns recorded in the proxys. As a first step we present the results on the long term variability, before focusing on selected periods to assess the spatial behaviour of the model to different value of the total solar irradiance. Crowley et al. 2000, Causes of climate change over the past 1000yrs, Science 289, 27

Influence of solar variability, CO2 and orbital forcing between 1000 and 1850 AD in the IPSLCM4 model

International audienceStudying the climate of the last millennium gives the possibility to deal with a relatively well-documented climate essentially driven by natural forcings. We have performed two simulations with the IPSLCM4 climate model to evaluate the impact of Total Solar Irradiance (TSI), CO 2 and orbital forcing on secular temperature variability during the preindustrial part of the last millennium. The Northern Hemisphere (NH) temperature of the simulation reproduces the amplitude of the NH temperature reconstructions over the last millennium. Using a linear statistical decomposition we evaluated that TSI and CO 2 have similar contributions to secular temperature variability between 1425 and 1850 AD. They generate a temperature minimum comparable to the Little Ice Age shown by the temperature reconstructions. Solar forcing explains ∼80% of the NH temperature variability during the first part of the millennium (1000-1425 AD) including the Medieval Climate Anomaly (MCA). It is responsible for a warm period which occurs two centuries later than in the reconstructions. This mismatch implies that the secular variability during the MCA is not fully explained by the response of the model to the TSI reconstruction. With a signal-noise ratio (SNR) estimate we found that the temperature signal of the forced simulation is significantly different from internal variability over area wider than ∼5.10 6 km 2 , i.e. approximately the extent of Europe. Orbital forcing plays a significant role in latitudes higher than 65 • N in summer and supports the conclusions of a recent stud