This study presents the global climate model IPSL‐CM6A‐LR developed at Institut Pierre‐Simon Laplace (IPSL) to study natural climate variability and climate response to natural and anthropogenic ...forcings as part of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). This article describes the different model components, their coupling, and the simulated climate in comparison to previous model versions. We focus here on the representation of the physical climate along with the main characteristics of the global carbon cycle. The model's climatology, as assessed from a range of metrics (related in particular to radiation, temperature, precipitation, and wind), is strongly improved in comparison to previous model versions. Although they are reduced, a number of known biases and shortcomings (e.g., double Intertropical Convergence Zone ITCZ, frequency of midlatitude wintertime blockings, and El Niño–Southern Oscillation ENSO dynamics) persist. The equilibrium climate sensitivity and transient climate response have both increased from the previous climate model IPSL‐CM5A‐LR used in CMIP5. A large ensemble of more than 30 members for the historical period (1850–2018) and a smaller ensemble for a range of emissions scenarios (until 2100 and 2300) are also presented and discussed.
Plain Language Summary
Climate models are unique tools to investigate the characteristics and behavior of the climate system. While climate models and their components are developed gradually over the years, the sixth phase of the Coupled Model Intercomparison Project (CMIP6) has been the opportunity for the Institut Pierre‐Simon Laplace to develop, test, and evaluate a new configuration of its climate model called IPSL‐CM6A‐LR. The characteristics and emerging properties of this new model are presented in this study. The model climatology, as assessed from a range of metrics, is strongly improved, although a number of biases common to many models do persist. The equilibrium climate sensitivity and transient climate response have both increased from the previous climate model IPSL‐CM5A‐LR used in CMIP5.
Key Points
The IPSL‐CM6A‐LR model climatology is much improved over the previous version, although some systematic biases and shortcomings persist
A long preindustrial control and a large number of historical and scenario simulations have been performed as part of CMIP6
The effective climate sensitivity of the IPSL model increases from 4.1 to 4.8 K between IPSL‐CM5A‐LR and IPSL‐CM6A‐LR
Based on the fifth phase of the Coupled Model Intercomparison Project (CMIP5)-generation previous Institut Pierre Simon Laplace (IPSL)
Earth system model, we designed a new version, IPSL-CM5A2, ...aiming at running multi-millennial simulations typical of deep-time paleoclimate studies. Three priorities were followed during the setup of the model: (1) improving the overall model computing performance, (2) overcoming a persistent cold bias depicted in the previous model generation and (3) making the model able to handle the specific continental configurations of the geological past. These developments include the integration of hybrid parallelization Message Passing Interface – Open Multi-Processing (MPI-OpenMP) in the atmospheric model of the Laboratoire de Météorologie Dynamique (LMDZ), the use of a new library to perform parallel asynchronous input/output by using computing cores as “I/O servers” and the use of a parallel coupling library between the ocean and the atmospheric components. The model, which runs with an atmospheric resolution of 3.75∘×1.875∘ and 2 to 0.5∘ in the ocean, can now simulate ∼100 years per day, opening new possibilities towards the production of multi-millennial simulations with a full Earth system model. The tuning strategy employed to overcome a persistent cold bias is detailed. The confrontation of a historical simulation to climatological observations shows overall improved ocean meridional overturning circulation, marine productivity and latitudinal position of zonal wind patterns. We also present the numerous steps required to run IPSL-CM5A2 for deep-time paleoclimates through a preliminary case study for the Cretaceous. Namely, specific work on the ocean model grid was required to run the model for specific continental configurations in which continents are relocated according to past paleogeographic reconstructions. By briefly discussing the spin-up of such a simulation, we elaborate on the requirements and challenges awaiting paleoclimate modeling in the next years, namely finding the best trade-off between the level of description of the processes and the computing cost on supercomputers.
The implementation of boundary conditions is a key aspect of climate simulations. We describe here how the Climate Model Intercomparison Project Phase 6 (CMIP6) forcing data sets have been processed ...and implemented in Version 6 of the Institut Pierre‐Simon Laplace (IPSL) climate model (IPSL‐CM6A‐LR) as used for CMIP6. Details peculiar to some of the Model Intercomparison Projects are also described. IPSL‐CM6A‐LR is run without interactive chemistry; thus, tropospheric and stratospheric aerosols as well as ozone have to be prescribed. We improved the aerosol interpolation procedure and highlight a new methodology to adjust the ozone vertical profile in a way that is consistent with the model dynamical state at the time step level. The corresponding instantaneous and effective radiative forcings have been estimated and are being presented where possible.
Plain Language Summary
Climate Model Intercomparison Project Phase 6 is an international project to compare the results from climate model simulations performed according to a common protocol. Such simulations require boundary conditions (called “climate forcings”), which are fed to the models in order to represent, for example, long‐lived greenhouse gases, ozone, atmospheric aerosols, or land surface properties. The same forcing data sets are used by the different modeling groups who carry out the Climate Model Intercomparison Project Phase 6 simulations; however, their implementation may differ as it depends on the model structure. This article gives details of how these forcing data were implemented in the IPSL‐CM6A‐LR model. Some of the forcing data are common to all types all simulations, whereas others depend on the runs considered. Radiative forcings, as estimated in the model, are presented for some of the forcing mechanisms.
Key Points
We present how the CMIP6 forcing data were implemented in the IPSL‐CM6A‐LR climate model for the realization of the CMIP6 set of climate simulations
An improved conservative interpolation procedure for emissions is detailed and illustrated to compute tropospheric aerosols
We present a new methodology to adjust the prescribed ozone vertical profile to match the model atmospheric dynamical state around the tropopause
Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the ...Paris Agreement. This study provides a consolidated synthesis of CH4 andN2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27 + UK). We integrate recent emission inventory data, ecosystem process-based model results and inverse modeling estimates over the period 1990–2017. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported to the UN climate convention UNFCCC secretariat in 2019. For uncertainties, we used for NGHGIs the standard deviation obtained by varying parameters of inventory calculations, reported by the member states (MSs) following the recommendations of the IPCC Guidelines. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model-specific uncertainties when reported. In comparing NGHGIs with other approaches, a key source of bias is the activities included, e.g., anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 TgCH4yr-1 (EDGAR v5.0) and 19.0 TgCH4yr-1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 TgCH4yr-1. The estimates of TD total inversions give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher-resolution atmospheric transport models give a mean emission of 28.8 TgCH4yr-1. Coarser-resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 TgCH4yr-1) and surface network (24.4 TgCH4yr-1). The magnitude of natural peatland emissions from the JSBACH–HIMMELI model, natural rivers and lakes emissions, and geological sources together account for the gap between NGHGIs and inversions and account for 5.2 TgCH4yr-1. For N2O emissions, over the 2011–2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 TgN2Oyr-1, respectively, agreeing with the NGHGI data (0.9 ± 0.6 TgN2Oyr-1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 TgN2Oyr-1, respectively. The TD and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at the EU+UK scale and at the national scale. The referenced datasets related to figures are visualized at 10.5281/zenodo.4590875 (Petrescu et al., 2020b).
Natural organic matter (OM) has a complex structure whose complete structural and chemical description remains a challenge. Rock-Eval® device constitutes a rapid and affordable method for obtaining ...key quantitative and qualitative parameters on OM. Previous studies on soil samples proposed to deconvolute or to split into temperature slices Rock-Eval® S2 pyrograms in order to distinguish and quantify chemical fractions of increasing thermal lability. In order to provide support for such an assumption, this work proposes a methodological approach based on coupling a temperature-programmed pyrolyser to a standard mass spectrometer (Py-MS). In this manuscript, we compare results acquired by Rock-Eval® pyrolysis with those from Total Ion Current (TIC) traces obtained by Py-MS on a set of reference soil samples, completed by dissolved OM, source rock and coal samples, in order to test the extent to which this approach can be generalized. Our results show good quantitative and qualitative agreements between the two methods. This comparison is a prerequisite before going further and addressing the molecular significance of S2 pyrograms deconvolution through the examination of m/z fragments abundance curves.
•Environmental samples were submitted to both programmed Py-MS and Rock-Eval pyrolysis.•A difference of temperature of maximum released is noted between the two methods.•It results from distinct time of transit of pyrolysates to the detector.•Py-MS results are quantitatively comparable to those of Rock-Eval pyrolysis.•Py-MS response differs upon the type of organic matter.
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.
This paper presents the major characteristics of the Institut Pierre Simon Laplace (IPSL) coupled ocean-atmosphere general circulation model. The model components and the coupling methodology are ...described, as well as the main characteristics of the climatology and interannual variability. The model results of the standard version used for IPCC climate projections, and for intercomparison projects like the Paleoclimate Modeling Intercomparison Project (PMIP 2) are compared to those with a higher resolution in the atmosphere. A focus on the North Atlantic and on the tropics is used to address the impact of the atmosphere resolution on processes and feedbacks. In the North Atlantic, the resolution change leads to an improved representation of the storm-tracks and the North Atlantic oscillation. The better representation of the wind structure increases the northward salt transports, the deep-water formation and the Atlantic meridional overturning circulation. In the tropics, the ocean-atmosphere dynamical coupling, or Bjerknes feedback, improves with the resolution. The amplitude of ENSO (El Niño-Southern oscillation) consequently increases, as the damping processes are left unchanged.
Climate change is a global challenge with multiple far-reaching consequences, including the intensification and increased frequency of many extreme weather events. In response to this pressing issue, ...we present ClimaMeter, a platform designed to assess and contextualise extreme weather events relative to climate change. The platform offers near real-time insights into the dynamics of extreme events, serving as a resource for researchers, policymakers, and being a science dissemination tool for the general public. ClimaMeter currently analyses heatwaves, cold spells, heavy precipitation and windstorms. This paper 5 elucidates the methodology, data sources, and analytical techniques on which ClimaMeter relies, providing a comprehensive overview of its scientific foundation. To illustrate Climameter, we provide four examples, the December 2022 North American Winter Storm, the August 2023 Guangdong-Hong Kong Flood, the late 2023 French Heatwave and the July 2023 windstorm Poly. They underscore the role of ClimaMeter in fostering a deeper understanding of the complex interactions between climate change and extreme weather, with the hope of ultimately contributing to informed decision-making and climate resilience.
Analyses of extreme weather events and their impacts often requires big data processing of ensembles of climate model simulations. Researchers generally proceed by downloading the data from the ...providers and processing the data files “at home” with their own analysis processes. However, the growing amount of available climate model and observation data makes this procedure quite awkward. In addition, data processing knowledge is kept local, instead of being consolidated into a common resource of reusable code. These drawbacks can be mitigated by using a web processing service (WPS). A WPS hosts services such as data analysis processes that are accessible over the web, and can be installed close to the data archives.
We developed a WPS named ‘flyingpigeon’ that communicates over an HTTP network protocol based on standards defined by the Open Geospatial Consortium (OGC), to be used by climatologists and impact modelers as a tool for analyzing large datasets remotely.
Here, we present the current processes we developed in flyingpigeon relating to commonly-used processes (preprocessing steps, spatial subsets at continent, country or region level, and climate indices) as well as methods for specific climate data analysis (weather regimes, analogues of circulation, segetal flora distribution, and species distribution models). We also developed a novel, browser-based interactive data visualization for circulation analogues, illustrating the flexibility of WPS in designing custom outputs.
Bringing the software to the data instead of transferring the data to the code is becoming increasingly necessary, especially with the upcoming massive climate datasets.
•A tool for remote processing of climate model data is presented.•Reduces the difficulties of climate model data analysis.•Standardized scientific methods for climate impact and extreme weather events.•Able to communicate with other web services.
Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating ...anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990–2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 Tg CO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588 (± 463 Tg CO2). The inversion reports 2700 Tg CO2 (± 480 Tg CO2), which is well in line with the national inventories. Over 2011–2015, the CO2 land sources and sinks from NGHGI estimates report −90 Tg C yr−1 ± 30 Tg C yr−1 while all other BU approaches report a mean sink of −98 Tg C yr−1 (± 362 Tg of C from dynamic global vegetation models only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr−1 ± 400 Tg C yr−1). This concludes that (a) current independent approaches are consistent with NGHGIs and (b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of “CO2 flux” obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4626578 (Petrescu et al., 2020a).
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