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Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multimodel predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño Southern Oscillation. [ABSTRACT FROM AUTHOR]

Many atmospheric global circulation models have large biases in predicting meridional and vertical winds and fluxes of gas species in remote regions such as the middle and upper atmosphere. In this study, we make sensitivity simulations to recognize the role of vital processes associated with dynamical coupling between different atmospheric layers, namely dynamical and thermal impacts of mesoscale orographic gravity waves (OGWs) generated by the Earth's topography and changes from the easterly to westerly QBO phases in the lower equatorial atmosphere. We improved parameterizations of OGW dynamical and thermal effects and QBO flows and implemented them into a general circulation model of the middle and upper atmosphere used in different countries. With this model, we study the sensitivity of meridional circulation and vertical velocity to stationary OGWs and to changes in QBO phases at altitudes up to 100 km in January. We also considered respective changes in vertical ozone fluxes in the atmosphere. Accounting stationary OGW effects gives changes up to 40% in the meridional velocity and associated ozone fluxes in the stratosphere. Transitions from the easterly to westerly QBO phase in tropics may significantly alter the meridional and vertical circulation of the middle atmosphere at middle and high latitudes: up to 60% from the peak respective values. The improved parameterizations of OGW and QBO effects have impacts on other features of the general circulation model, improving the simulation of general circulation, planetary and tidal wave coupling in the lower, middle and upper atmosphere. [ABSTRACT FROM AUTHOR]

Numerical simulations provide a considerable aid in studying past climates. Out of the various approaches taken in designing numerical climate experiments, transient simulations have been found to be the most optimal when it comes to comparison with proxy data. However, multi-millennial or longer simulations using fully coupled general circulation models are computationally very expensive such that acceleration techniques are frequently applied. In this study, we compare the results from transient simulations of the present and the last interglacial with and without acceleration of the orbital forcing, using the comprehensive coupled climate model CCSM3 (Community Climate System Model 3). Our study shows that in most parts of the world, the simulation of long-term variations in interglacial surface climate is not significantly affected by the use of the acceleration technique (with an acceleration factor 10) and, hence, large-scale model-data comparison of surface variables is not hampered. However, in high-latitude regions where the surface climate has a direct connection to the deep ocean, e.g. in the Southern Ocean or the Nordic Seas, acceleration-induced biases in sea-surface temperature evolution may occur with potential influence on the dynamics of the overlying atmosphere. [ABSTRACT FROM AUTHOR]

The Ent Terrestrial Biosphere Model (Ent TBM) is a mixed-canopy dynamic global vegetation model developed specifically for coupling with land surface hydrology and general circulation models (GCMs). This study describes the leaf phenology submodel implemented in the Ent TBM version 1.0.1.0.0, coupled to the carbon allocation scheme of the Ecosystem Demography (ED) model. The phenology submodel adopts a combination of responses to temperature (growing degree days and frost-hardening), soil moisture (linearity of stress with relative saturation), and radiation (light length). Growth of leaves, sapwood, fine roots, stem wood, and coarse roots is updated on a daily basis. We evaluate the performance in reproducing observed leaf seasonal growth as well as water and carbon fluxes for four plant functional types at five Fluxnet sites, with both observed and prognostic hydrology, and observed and prognostic seasonal leaf area index. The phenology submodel is able to capture the timing and magnitude of leafout and senescence for temperate broadleaf deciduous forest (Harvard Forest and Morgan-Monroe State Forest, US), C3 annual grassland (Vaira Ranch, US), and California oak savanna (Tonzi Ranch, US). For evergreen needleleaf forest (Hyytiäla, Finland), the phenology submodel captures the effect of frost-hardening of photosynthetic capacity on seasonal fluxes and leaf area. We address the importance of customizing parameter sets of vegetation soil moisture stress response to the particular land surface hydrology scheme. We identify model deficiencies that reveal important dynamics and parameter needs. [ABSTRACT FROM AUTHOR]

The article presents a study which explored the mid-Pliocene and pre-indusrial atmosphere general circulation models (AGCM) simulations, with Norwegian Earth System Model (NorESM-L). The study evaluated he potential uncertainties in the analysis of climate anomalies in the mid-Pliocene period. Results showed that the uncertainties in mid-Pliocene climate anomaly analyses are large in terms of regional scale, but small on a global scale.

In this article we propose two conformal mapping based grid generation algorithms for global ocean general circulation models (OGCMs). Contrary to conventional, analytical forms based dipolar or tripolar grids, the new algorithms are based on Schwarz-Christoffel (SC) conformal mapping with prescribed boundary information. While dealing with the basic grid design problem of pole relocation, these new algorithms also address more advanced issues such as smoothed scaling factor, or the new requirements on OGCM grids arisen from the recent trend of high-resolution and multi-scale modeling. The proposed grid generation algorithm could potentially achieve the alignment of grid lines to coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the generated grids are still orthogonal curvilinear, they can be readily utilized in existing Bryan-Cox-Semtner type ocean models. The proposed methodology can also be applied to the grid generation task for regional ocean modeling where complex land-ocean distribution is present. [ABSTRACT FROM AUTHOR]

We demonstrate that both the current (New Dynamics), and next generation (ENDGame) dynamical cores of the UK Met Office global circulation model, the UM, reproduce consistently, the long-term, large-scale flows found in several published ide- alised tests. The cases presented are the Held-Suarez test, a simplified model of Earth (including a stratosphere), and a model of a hypothetical Tidally Locked Earth (TLE). Furthermore, we show that using simplifications to the dynamical equations, which are expected to be justified for the physical domains and flow regimes we have studied, and which are supported by the ENDGame dynamical core, also produces matching long-term, large-scale flows. Finally, we present evidence for differences in the detail of the planetary (meridional) flows and circulations resulting from improvements in the ENDGame formulation over New Dynamics. Specifically, we find greater symmetry in the meridional circulations of the Tidally Locked Earth test case using the ENDGame formulation, which is a better match to our physical expectations of the flow for such a slowly rotating Earth-like system. [ABSTRACT FROM AUTHOR]

In this study we present first results of a new isotope-enabled general circulation model setup. The model consists of a fully coupled atmosphere-ocean model ECHAM5/MPIOM, enhanced by the interactive land surface scheme JSBACH and an explicit hydrological discharge scheme to close the global water budget. Stable water isotopes H182O and HDO have been incorporated into all relevant model components. Results of two equilibrium simulations under pre-industrial and last glacial maximum conditions are analysed and compared to observational data and paleoclimate records for evaluating the model's performance of simulating spatial and temporal variations in the isotopic composition of the Earth's water cycle. For the pre-industrial climate, many aspects of the simulation results of meteoric waters are in good to very good agreement with both observations and earlier atmosphere-only simulations. The model is capable of adequately simulating the large spread in the isotopic composition of precipitation between low and high latitudes. A comparison to available ocean data also shows a good model-data agreement, however a strong bias of too depleted ocean surface waters is detected for the Arctic region. Simulation results under last glacial maximum boundary conditions also fit to the wealth of available isotope records from polar ice cores, speleothems, as well as marine calcite data. Data-model evaluation of the isotopic composition in precipitation reveals a good match of the model results and indicates that the temporal glacial-interglacial isotope-temperature relation was substantially lower than the present spatial gradient for most mid- to high-latitudinal regions. As compared to older atmosphere-only simulations, a remarkable improvement is achieved for the modelling of the deuterium excess signal in Antarctic ice cores. Our simulation results indicate that cool sub-tropical and mid-latitudinal sea surface 25 temperatures are key for this progress. A recently discussed revised interpretation of the deuterium excess record of Antarctic ice cores in terms of marine relative humidity changes on glacial-interglacial timescales is not supported by our model results. [ABSTRACT FROM AUTHOR]

The article presents a study which developed a parameterization of black carbon (BC) aging to be used in general circulation models (GCMs). The BC aging rate is expressed as the rate of conversion from hydrophobic to hydrophilic BC modes. It notes that the use of the developed parameterization in GCMs will lead to more reliable estimates of BC spatial distribution.

The development and verification of the convective module of IL-GLOBO, a Lagrangian transport model coupled online with the Eulerian general circulation model GLOBO, is described. The online-coupling promotes the full consistency between the Eulerian and the Lagrangian components of the model. The Lagrangian convective scheme is derived based on the Kain-Fritsch convective parameterisation used in GLOBO. A transition probability matrix is computed using the fluxes provided by the Eulerian KF parameterisation. Then, the convection redistribution of Lagrangian particles is implemented via a Monte Carlo scheme. The formal derivation is described in details and, consistently with the Eulerian module, includes the environmental flux in the transition probability matrix to avoid splitting of the convection and subsidence processes. Consistency of the Lagrangian implementation with its Eulerian counterpart is verified by computing environment fluxes from the transition probability matrix and comparing them to those computed by the Eulerian module. Assessment of the impact of the module is made for different latitudinal belts, showing that the major impact is found in the tropics, as expected. Concerning vertical distribution, the major impact is observed in the boundary layer at every latitude, while in the tropical area, the influence extends to very high levels. [ABSTRACT FROM AUTHOR]

We present a simple method to generate a perturbed parameter ensemble (PPE) of a fully-coupled atmosphere-ocean general circulation model (AOGCM), HadCM3, without requiring flux-adjustment. The aim was to produce an ensemble that samples parametric uncertainty in some key variables and displays a similar range of behavior as seen in multi-model ensembles (MMEs). Six atmospheric parameters, a sea-ice parameter and an ocean parameter were jointly perturbed within a reasonable range to generate an initial group of 200 members. To screen out implausible ensemble members, 20 yr pre-industrial control simulations were run and members whose tempera10 ture response to the parameter perturbations was projected to be outside the range of 13.6±2 °C, i.e. near to the observed pre-industrial global mean, were discarded. 21 members, including the standard unperturbed model, were accepted, covering almost the entire span of the eight parameters, challenging the argument that without fluxadjustment parameter ranges would be unduly restricted. This ensemble was used in 3 experiments; a 800 yr pre-industrial, a 150 yr quadrupled CO2, and a 150 yr 1% CO2 rise per annum simulation. The behavior of the PPE for the pre-industrial control compared well to the CMIP3 ensemble for a number of surface and atmospheric column variables with the exception of a few members in the Tropics. However, we find that members of the PPE with low values of the entrainment rate coefficient show very large increases in upper tropospheric and stratospheric water vapor concentrations in response to elevated CO2 and some show implausibly high climate sensitivities, and as such some of these members will be excluded from future experiments with this ensemble. The outcome of this study is a PPE of a fully-coupled AOGCM which samples parametric uncertainty with a range of behavior similar to the CMIP3 ensemble and a simple methodology which would be applicable to other GCMs. [ABSTRACT FROM AUTHOR]

The article provides information on the ECHAM/MESSy Atmospheric Chemistry (EMAC) model which is coupled to the ocean general circulation (GCM) model MPIOM using the Modular Earth Submodel Sytem (MESSy) interface. It reveals that the coupling method is tested for different model configurations, proving to be very flexible in terms of parallel decomposition. In addition, the climate model simulation (CMIP3) performed with EMAC-MPIOM show that the results are comparable to those of other GCM.

The article presents a description and evaluation of the Commonwealth Scientific and Industrial Research Organization (CSIRO) Mk3L climate system model. It is inferred that the model is designed for millenial-scale climate simulation which includes representations of the atmosphere, ocean, sea ice, and land surface. Moreover, CSIRO Mk3L offers a combination of computational efficiency and a stable and realistic control climatology.

The article discusses a research study which evaluates a climate simulation through the Global Environmental and Ecological Simulation of Interactive Systems and Modular Ocean Model version 2 (GENMOM). Findings reveal that the said model developed a global temperature bias of 0.6 degree-Celsius. It indicates the development of a split intertropical convergence zone (ITCZ) and weaker-than-observed overturning circulation as the two main weaknesses depicted in the simulations.

The article reports on the implementation of the HadGEM2-ES Coupled Model Intercomparison Project (CMIP5), a standard experimental protocol for studying the output of general circulation models (GCMs). It covers the greenhouse gas concentrations, aerosol precursors, stratospheric and tropospheric ozone assumptions, as well as implementation of land-use change and natural forcings for the experiments. It also details how the HadGEM2-ES ensemble members were initialised from the control run.

The article describes the energy and water components of the Joint UK Land Environment Simulator (JULES). It reveals that JULES can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. In addition, JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

The article focuses on the use of multivariate probability density function (PDF) to solve scale gap problems on climate models and to analyze cloud fraction, condensate and droplet. It mentions the use of grid flow description language (GFDL) single column model (SCM) simulations and general circulation models to determine aerosol concentration and cloud droplet number concentration in low-level clouds. It suggests assessing the effect of aerosols in droplet number and on cloud properties.

The article presents a case study on the GEWEX Cloud System Study (GCSS) cirrus cloud working group's inter-comparison of model simulations. These ranges from microphysical and dynamical models to general circulation models (GCMs). An overview of how it was developed and based on the March 9, 2000 Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) intensive observation period (IOP) is presented.

This paper describes and analyzes the Reed-Jablonowski (RJ) tropical cyclone (TC) test case used in the 2016 Dynamical Core Model Intercomparison Project (DCMIP2016). The intermediate complexity test case analyzes the evolution of a weak vortex into a TC in an idealized tropical environment. Simulations from general circulation models (GCMs) that participated in DCMIP2016 are analyzed in this study at 50 km horizontal grid spacing, with 5 of these models also providing simulations at 25 5 km grid spacing for an analysis on the impact of finer grid spacing. Evolution of minimum surface pressure (MSP) and maximum 1 km azimuthally averaged wind speed (MWS), the wind-pressure relationship, radial profiles of wind speed and surface pressure, and wind composites are documented for all participating GCMs at both horizontal grid spacings. While results are generally similar between all models, some GCMs reach significantly higher storm intensities than others, ultimately impacting specific characteristics of their horizontal and vertical structure. TCs simulated at 25 km grid spacings retained these differences, but reach higher intensities and are more compact than their 50 km counterparts. These results indicate dynamical core choice is an essential factor in GCM development, and future work should be conducted to explore how specific differences within the dynamical core affect TC behavior in GCMs. [ABSTRACT FROM AUTHOR]

We introduce ModE-Sim, a medium size ensemble of simulations with the atmospheric general circulation model ECHAM6 in its LR version (T63/approx. 1.8°horizontal with 47 vertical levels) that covers the period from 1420 to 2009. With 60 ensemble members between 1420 and 1850 and 36 ensemble members from 1850 to 2009 ModE-Sim consists of 31620 simulated years in total. The dataset forms the input for a data assimilation procedure that combines historical climate informations with additional constraints from a climate model to produce a novel gridded 3-dimensional dataset of the modern era. Additionally, ModE-Sim on its own is also suitable for many other applications as its various subsets can be used as initial condition and boundary condition ensemble to study climate variability. The main intention of this paper is to give a comprehensive description of the experimental setup of ModE-Sim and to provide an evaluation of the two key variables 2m-temperature and precipitation. We demonstrate ModE-Sim's ability to represent their mean state, to produce a reasonable response to external forcings and to sample internal variability. At the example of heat waves we show that the ensemble is even capable of capturing extreme events. [ABSTRACT FROM AUTHOR]

Most radiation schemes in weather and climate models use the 'correlated k-distribution' (CKD) method to treat gas absorption, which approximates a broadband spectral integration by N pseudo-monochromatic calculations. Larger N means more accuracy and a wider range of gas concentrations can be simulated, but at greater computational cost. Unfortunately, the tools to perform this efficiency-accuracy trade-off (e.g., to generate separate CKD models for applications such as short-range weather forecasting to climate modelling) are unavailable to the vast majority of users of radiation schemes. This paper describes the experimental protocol for the Correlated K-Distribution Model Intercomparison Project (CKDMIP), whose purpose is to use benchmark line-by-line calculations: (1) to evaluate the accuracy of existing CKD models, (2) to explore how accuracy varies with N for CKD models submitted by CKDMIP participants, (3) to understand how different choices in way that CKD models are generated affects their accuracy for the same N, and (4) to generate freely available datasets and software facilitating the development of new gas-optics tools. The datasets consist of the high-resolution longwave and shortwave absorption spectra of nine gases for a range of atmospheric conditions, realistic and idealized. Thirty-four concentration scenarios for the well-mixed greenhouse gases are proposed to test CKD models from palaeo- to future-climate conditions. We demonstrate the strengths of the protocol in this paper by using it to evaluate the widely-used Rapid Radiative Transfer Model for General Circulation Models (RRTMG). [ABSTRACT FROM AUTHOR]

Parameterized boundary layer turbulence and moist convection remain some of the largest sources of uncertainty in general circulation models. High-resolution climate modeling aims to reduce that uncertainty by explicitly attempting to resolve deep moist convective motions. An example of such a model is the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM) with a target global resolution of 3.25 km, allowing for a more accurate representation of complex mesoscale deep convective dynamics. Yet, small-scale planetary boundary layer turbulence and shallow convection still need to be parameterized, which in SCREAM is accomplished through the TKE-based Simplified Higher-Order Closure (SHOC)--a simplified version of the assumed doubled-Gaussian PDF higher-order closure method. In this paper, we implement a stochastic multiplume Mass-Flux (MF) parameterization of dry and shallow convection in SCREAM to go beyond the limitations of double-Gaussian PDF closures and couple it to SHOC (SHOC+MF). The new parameterization implemented in a single-column model type version of SCREAM produces results for two shallow cumulus convection cases (marine and continental shallow convection) that agree well with the reference large-eddy simulation data, thus improving the general representation of the thermodynamic quantities and their turbulent fluxes as well as cloud macrophysics in the model. Furthermore, SHOC+MF parameterization shows weak sensitivity to the vertical grid resolution and model time step. [ABSTRACT FROM AUTHOR]

In this paper we develop a novel framework aimed to significantly reduce biases related to marine stratocumulus clouds in general circulation models (GCMs) while circumventing excessive computational cost requirements. Our strategy is to increase the horizontal resolution using a regionally refined mesh (RRM) over our region of interest in addition to using the Framework for Improvement of Vertical Enhancement (FIVE) to increase the vertical resolution only for specific physical processes that are important for stratocumulus. We apply the RRM off the coast of Peru in the Southeast Pacific, a region that climatologically contains the most marine stratocumulus in the subtropics. We find that our new modeling framework is able to replicate the results of our high resolution benchmark simulation with much fidelity, while reducing the computational cost by several orders of magnitude. In addition, this framework is able to greatly reduce the longstanding biases associated with marine stratocumulus in GCMs when compared to the standard resolution control simulation. [ABSTRACT FROM AUTHOR]

The newly developed fast Earth system model CLIMBER-X is presented. The climate component of CLIMBER-X consists of a 2.5D semi-empirical statistical-dynamical atmosphere model, a 3D frictional-geostrophic ocean model, a dynamic-thermodynamic sea ice model and a land surface model. All model components are discretized on a regular lat-lon grid with a horizontal resolution of 5° × 5°. The model has a throughput of ~10,000 simulation years per day on a single node with 16 CPUs on a high performance computer and is designed to simulate the evolution of the Earth system on temporal scales ranging from decades to > 100,000 years. A comprehensive evaluation of the model performance for present day and the historical period shows that CLIMBER-X is capable of realistically reproducing many observed climate characteristics, with results that generally lie within the range of state-of-the-art general circulation models. The analysis of model performance is complemented by a thorough assessment of climate feedbacks and model sensitivities to changes in external forcings and boundary conditions. CLIMBER-X also includes a detailed representation of the global carbon cycle and is coupled to an ice sheet model, which will be described in separate papers. CLIMBER-X is available as open--source code and is expected to be a useful tool for studying past climate changes and for the investigation of the long-term future evolution of the climate. [ABSTRACT FROM AUTHOR]

Wind stress and turbulent heat fluxes are the major driving forces which modify the ocean dynamics and thermodynamics. In the NEMO ocean general circulation model, these turbulent air-sea fluxes (TASFs), which are components of the ocean model boundary conditions, can critically impact the simulated ocean characteristics. This paper investigates how the different bulk parametrizations to calculated turbulent air-sea fluxes in the NEMO4 (revision 12957) drives substantial differences in sea surface temperature (SST). Specifically, we study the contribution of different aspects and assumptions of the bulk parametrizations in driving the SST differences in NEMO global model configuration at ¼ degree of horizontal resolution. These include the use of the skin temperature instead of the bulk SST in the computation of turbulent heat flux components, the estimation of wind stress and the estimation of turbulent heat flux components which vary in each parametrization due to the different computation of the bulk transfer coefficients. The analysis of a set of short-term sensitivity experiments, where the only experimental change is related to one of the aspects of the bulk parametrizations, shows that parametrization-related SST differences are primarily sensitive to the wind stress differences across parametrizations and to the implementation of skin temperature in the computation of turbulent heat flux components. Moreover, in order to highlight the role of SST-turbulent heat flux negative feedback at play in ocean simulations, we compare the TASFs differences obtained using NEMO ocean model with the estimations from Brodeau et al. (2017), who compared the different bulk parametrizations using prescribed SST. Our estimations of turbulent heat flux differences between bulk parametrizations is weaker with respect to Brodeau et al. (2017) differences estimations. [ABSTRACT FROM AUTHOR]

The influence of climate on landform evolution has received great interest over the past decades. While many studies aim at determining erosion rates or parameters of erosion models, feedbacks between tectonics, climate and landform evolution have been discussed, but addressed quantitatively only in a few modeling studies. One of the problems in this field is that coupling a large-scale landform evolution model with a general circulation model would dramatically increase the theoretical and numerical complexity. Only a few simple models are available so far that allow a numerical efficient coupling between topography-controlled precipitation and erosion. This paper fills this gap by introducing a quite simple approach involving two vertically integrated moisture components (vapor and cloud water). The interaction between both components is linear and depends on altitude. This model structure is in principle the simplest approach that is able to predict both orographic precipitation at small scales and a large-scale decrease in precipitation over continental areas without introducing additional assumptions. Even in combination with transversal dispersion and height-dependent evapotranspiration, the model is of linear time complexity and increases the computing effort of efficient large-scale landform evolution models only moderately. Even simple numerical experiments applying such a coupled landform evolution model show the strong impact of spatial precipitation gradients on mountain range geometry including steepness and peak elevation, position of the principal drainage divide, and drainage network properties. [ABSTRACT FROM AUTHOR]

The model's ability to reproduce the state of the simulated object or particular feature or phenomenon is always a subject of discussion. Multidimensional model quality assessment is usually customized to the specific focus of the study and often to a limited number of locations. In this paper, we propose a method that provides information on the accuracy of the model in general, while all dimensional information for posterior analysis of the specific tasks is retained. The main goal of the method is to perform clustering of the multivariate model errors. The clustering is done using the K-means algorithm of unsupervised machine learning. In addition, the potential application of the K-means clustering of model errors for learning and predicting is shown. The method is tested on the 40-year simulation results of the general circulation model of the Baltic Sea. The model results are evaluated with the measurement data of temperature and salinity from more than one million casts by forming a two-dimensional error space and performing a clustering procedure in it. The optimal number of clusters that consist of four clusters was determined using the Elbow cluster selection criteria and based on the analysis of the different number of error clusters. In this particular model, the error cluster of good quality of the model with a bias of 0.4°C (std=0.8°C) for temperature and 0.6gkg-1 (std=0.7gkg-1) for salinity made up 57% of all comparison data pairs. The prediction of centroids from a limited number of randomly selected data showed that the obtained centroids gained a stability of at least 100000 error pairs in the learning dataset. [ABSTRACT FROM AUTHOR]

Lockdowns to avoid the spread of COVID-19 have created an unprecedented reduction in human emissions. While the country-level scale of emissions changes can be estimated in near-real-time, the more detailed, gridded emissions estimates that are required to run General Circulation Models (GCM) of the climate will take longer to collect. In this paper we use recorded and projected country-and-sector activity levels to modify gridded predictions from the MESSAGE-GLOBIOM SSP2-4.5 scenario. We provide updated projections for concentrations of greenhouse gases, emissions fields for aerosols and precursors, and the ozone and optical properties that result from this. The codebase to perform similar modifications to other scenarios is also provided. We outline the means by which these results may be used in a model intercomparison project (CovidMIP) to investigate the impact of national lockdown measures on climate. This includes three strands: an assessment of short-term effects (5-year period), of longer-term effects (30 years) and an investigation into the separate effects of changes in emissions of greenhouse gases and aerosols. This last strand supports possible attribution of observed changes in the climate system, hence these simulations will also form part of the Detection and Attribution Model Intercomparison Project (DAMIP). [ABSTRACT FROM AUTHOR]

Weather forecasts rely heavily on general circulation models of the atmosphere and other components of the Earth system. National meteorological and hydrological services and intergovernmental organisations, such as the European Centre for Medium-Range Weather Forecasts (ECMWF), provide routine operational forecasts on a range of spatio-temporal scales, by running these models in high resolution on state-of-the-art high-performance computing systems. Such operational forecasts are very demanding in terms of computing resources. To facilitate the use of a weather forecast model for research and training purposes outside the operational environment, ECMWF provides a portable version of its numerical weather forecast model, OpenIFS, for use by universities and other research institutes on their own computing systems. In this paper, we describe a new project (OpenIFS@home) that combines OpenIFS with a citizen science approach to involve the general public in helping conduct scientific experiments. Volunteers from across the world can run OpenIFS@home on their computers at home and the results of these simulations can be combined into large forecast ensembles. The infrastructure of such distributed computing experiments is based on our experience and expertise with the climateprediction.net and weather@home systems. In order to validate this first use of OpenIFS in a volunteer computing framework, we present results from ensembles of forecast simulations of tropical cyclone Karl from September 2016, studied during the NAWDEX field campaign. This cyclone underwent extratropical transition and intensified in mid-latitudes to give rise to an intense jet-streak near Scotland and heavy rainfall over Norway. For the validation we use a two thousand member ensemble of OpenIFS run on the OpenIFS@home volunteer framework and a smaller ensemble of the size of operational forecasts using ECMWF's forecast model in 2016 run on the ECMWF supercomputer with the same horizontal resolution as OpenIFS@home. We present ensemble statistics that illustrate the reliability and accuracy of the OpenIFS@home forecasts as well as discussing the use of large ensembles in the context of forecasting extreme events. [ABSTRACT FROM AUTHOR]

When solving hydrodynamic equations in spherical/cylindrical geometry using explicit finite difference schemes, a major difficulty is that the time step is greatly restricted by the clustering of azimuthal cells near the pole due to the Courant-Friedrichs-Lewy condition. This paper adapts the azimuthal averaging-reconstruction (Ring Average) technique to finite difference schemes in order to mitigate the time step constraint in spherical/cylindrical coordinates. The finite-difference Ring Average technique averages physical quantities based on an effective grid and then reconstructs the solution back to the original grid in a piece-wise, monotonic way. The algorithm is implemented in a community upper atmospheric model Thermosphere-Ionosphere Electrodynamics General Circulation Model (TIE-GCM), with horizontal resolution up to 0.625 × 0.625 in the geographic longitude-latitude coordinates, which enables the capability of resolving critical mesoscale structures within the TIE-GCM. Numerical experiments have shown that the Ring Average technique introduces minimal artifacts in the polar region of the GCM solutions, which is a significant improvement compared to the commonly used low-pass filtering techniques such as the fast Fourier transform method. Since the finite-difference adaption of the Ring Average technique is a post-solver type algorithm, which requires no changes to the original computational grid and numerical algorithms, it has also been implemented in much more complicated models with extended physical/chemical modules such as the coupled Magnetosphere Ionosphere Thermosphere (CMIT) model and the Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension (WACCM-X). The implementation of the Ring Average techniques in both models enables CMIT and WACCM-X to perform global simulations with a much higher resolution than that used in the community versions. The new technique is not only a significant improvement in space weather modeling capability, but can also be adapted to more general finite difference solvers for hyperbolic equations in spherical/polar geometries. [ABSTRACT FROM AUTHOR]

A simplified model of the Atmospheric Boundary Layer (ABL) of intermediate complexity between a bulk parameterization and a three-dimensional atmospheric model is developed and integrated to the Nucleus for European Modelling of the Ocean (NEMO) general circulation model. An objective in the derivation of such simplified model called ABL1d is to reach an apt representation in ocean-only numerical simulations of some of the key processes associated to air/sea interactions at the characteristic scales of the oceanic mesoscale. In this paper we describe the formulation of the ABL1d model and the strategy to constrain this model with large-scale atmospheric data available from reanalysis or real-time forecasts. A particular emphasis is on the appropriate choice and calibration of a turbulent closure scheme for the atmospheric boundary layer. This is a key ingredient to properly represent the air/sea interaction processes of interest. We also provide a detailed description of the NEMO-ABL1d coupling infrastructure and its computational efficiency. The resulting simplified model is then tested for several boundary-layer regimes relevant to either ocean/atmosphere or sea-ice/atmosphere coupling. The coupled system is also tested with a realistic 0.25° resolution global configuration. The numerical results are evaluated using standard metrics from the literature to quantify the wind/sea surface temperature (a.k.a. thermal feedback effect), wind/currents (a.k.a. current feedback effect) and ABL/sea-ice couplings. With respect to these metrics, our results show very good agreement with observations and fully coupled ocean-atmosphere models for a computational overhead of about 9% in term of elapsed time compared to standard uncoupled simulations. This moderate overhead, largely due to I/O operations, leaves room for further improvement to relax the assumption of horizontal homogeneity behind ABL1d and thus to further improve the realism of the coupling while keeping the flexibility of ocean-only modelling. [ABSTRACT FROM AUTHOR]

The implementation of a new Arctic regional coupled sea ice-ocean-atmosphere model (ArcIOAM) and its preliminary results in the year of 2012 are presented in this paper. A newly developed coupler, C-Coupler2 (the Community Coupler 2), is used to couple the Arctic sea ice-oceanic configuration of the MITgcm (Massachusetts Institute of Technology general circulation model) with the Arctic atmospheric configuration of the Polar WRF (Weather Research and Forecasting) model. ArcIOAM is demonstrated with focus on seasonal simulation of the Arctic sea ice and ocean state in the year of 2012. The results obtained by ArcIOAM, along with the experiment of one-way coupling strategy, are compared with available observational data and reanalysis products. From the comparison, results obtained from two experiments both realistically capture the sea ice and oceanic variables in the Arctic region over a 1-year simulation period. The two-way coupled model has better performance in terms of sea ice extent, concentration, thickness and SST, especially in summer. This indicates that sea ice-ocean-atmosphere interaction takes a crucial role in controlling Arctic summertime sea ice distribution. The coupled model and documentation are available at (last access: 9 June 2020), and the source code is maintained at (last access: 7 April 2020). [ABSTRACT FROM AUTHOR]

The single column model (SCM) functionality of the Energy Exascale Earth System Model version 1 (E3SMv1) is described in this paper. The E3SM SCM was adopted from the SCM used in the Community Atmosphere Model (CAM), but has evolved significantly since then. We describe changes made to the aerosol specification in the SCM, idealizations, and developments made so that the SCM uses the same dynamical core as the full general circulation model (GCM) component. Based on these changes, we describe and demonstrate the seamless capability to "replay" a GCM column using the SCM. We give an overview of the E3SM case library and briefly describe which cases may serve as useful proxies for replicating and investigate some long standing biases in the full GCM runs, while demonstrating that the E3SM SCM is an efficient tool for both model development and evaluation. [ABSTRACT FROM AUTHOR]

A quasi-global eddying ocean hindcast simulation using a new version of our model called OFES2 (Ocean General Circulation Model for the Earth Simulator version 2) was conducted to overcome several issues with unrealistic properties in its previous version OFES . This paper describes the model and the simulated oceanic fields in OFES2 compared with OFES and also observed data. A sea-ice model and a tidal mixing scheme were implemented in OFES2, which was forced by a newly created surface atmospheric dataset called JRA55-do and simulated the oceanic fields from 1958 to 2016. We found several improvements in OFES2 over OFES: smaller biases in the global sea surface temperature and sea surface salinity and the water properties in the Indonesian and Arabian Seas. The time series of the Niño3.4 and Indian Ocean Dipole (IOD) indexes are somewhat better in OFES2 than in OFES. Unlike the previous version, OFES2 reproduces more realistic anomalous low sea surface temperatures during a positive IOD event. One possible cause for these improvements in El Niño and IOD events is the replacement of the atmospheric dataset. On the other hand, several issues remained unrealistic, such as the pathways of the Kuroshio and Gulf Stream and the unrealistic spreading of salty Mediterranean overflow. Given the worldwide use of the previous version and the improvements presented here on it, the output from OFES2 will be useful in studying various oceanic phenomena with broad spatiotemporal scales. [ABSTRACT FROM AUTHOR]

This paper describes the implementation of a coupling between a three-dimensional ocean general circulation model (NEMO) and a wave model (WW3) to represent the interactions of the upper oceanic flow dynamics with surface waves. The focus is on the impact of such coupling on upper-ocean properties (temperature and currents) and mixed-layer depths (MLD) at global eddying scales. A generic coupling interface has been developed and the NEMO governing equations and boundary conditions have been adapted to include wave-induced terms following the approach of McWilliams et al. (2004) and Ardhuin et al. (2008). In particular, the contributions of Stokes-Coriolis, Vortex and surface pressure forces have been implemented on top of the necessary modifications of the tracer/continuity equation and turbulent closure scheme (a 1-equation TKE closure here). To assess the new developments, we perform a set of sensitivity experiments with a global oceanic configuration at 1/4° resolution coupled with a wave model configured at 1/2° resolution. Numerical simulations show a global increase of wind-stress due to the interaction with waves (via the Charnock coefficient) particularly at high latitudes. The modifications brought to the TKE closure scheme and the inclusion of a parameterization for Langmuir turbulence lead to a significant increase of the mixing thus helping to deepen the MLD. This deepening is mainly located in the Southern Hemisphere and results in reduced sea-surface currents and temperatures. [ABSTRACT FROM AUTHOR]

The Canadian Earth System Model version 5 (CanESM5) is a global model developed to simulate historical climate change and variability, to make centennial scale projections of future climate, and to produce initialized seasonal and decadal predictions. This paper describes the model components and their coupling, as well as various aspects of model development, including tuning, optimization and a reproducibility strategy. We also document the stability of the model using a long control simulation, quantify the model's ability to reproduce large scale features of the historical climate, and evaluate the response of the model to external forcing. CanESM5 is comprised of three dimensional atmosphere (T63 spectral resolution/2.8°) and ocean (nominally 1°) general circulation models, a sea ice model, a land surface scheme, and explicit land and ocean carbon cycle models. The model features relatively coarse resolution and high throughput, which facilitates the production of large ensembles. CanESM5 has a notably higher equilibrium climate sensitivity (5.7 K) than its predecessor CanESM2 (3.8 K), which we briefly discuss, along with simulated changes over the historical period. CanESM5 simulations are contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6), and will be employed for climate science and service applications in Canada. [ABSTRACT FROM AUTHOR]

This paper presents the new adaptive dynamical core wavetrisk. The fundamental features of the wavelet-based adaptivity were developed for the shallow water equation on the β-plane in Dubos and Kevlahan (2013) and extended to the icosahedral grid on the sphere in Aechtner et al. (2015). The three-dimensional dynamical core solves the compressible hydrostatic multilayer rotating shallow water equations on a multiscale dynamically adapted grid. The equations are discretized using a Lagrangian vertical coordinate version of dynamico introduced in Dubos et al. (2015). The horizontal computational grid is adapted at each time step to ensure a user-specified relative error in either the tendencies or the solution. The Lagrangian vertical grid is remapped using an adaptive Lagrangian-Eulerian (ALE) algorithm onto the initial hybrid σ pressure-based coordinates as necessary. The resulting grid is adapted horizontally, but uniform over all vertical layers. Thus, the three-dimensional grid is a set of columns of varying sizes. The code is parallelized by domain decomposition using mpi and the variables are stored in a hybrid data structure of dyadic quad trees and patches. A low storage explicit fourth order Runge-Kutta scheme is used for time integration. Validation results are presented for three standard dynamical core test cases: mountain-induced Rossby wave train, baroclinic instability of a jet stream and the Held and Suarez simplified general circulation model. The results confirm good strong parallel scaling and demonstrate that wavetrisk can achieve grid compression ratios of several hundred times compared with an equivalent static grid model. [ABSTRACT FROM AUTHOR]

The CFMIP Diagnostic Codes Catalogue assembles cloud metrics, diagnostics and methodologies, together with programs to diagnose them from General Circulation Model (GCM) outputs written by various members of the CFMIP community. This aims to facilitate use of the diagnostics by the wider community studying climate and climate change. This paper describes the diagnostics and metrics which are currently in the catalogue, together with examples of their application to model evaluation studies and a summary of some of the insights these diagnostics have provided on the main shortcomings in current GCMs. Analysis of outputs from CFMIP and CMIP6 experiments will also be facilitated by the sharing of diagnostic codes via this catalogue. Any code which implements diagnostics relevant to analysing clouds - including cloud-circulation interactions and the contribution of clouds to estimates of climate sensitivity in models - and which is documented in peer-reviewed studies can be included in the catalogue. We very much welcome additional contributions to further support community analysis of CMIP6 outputs. [ABSTRACT FROM AUTHOR]

Global Circulation Models (GCMs) are the best tool to understand climate change, as they attempt to represent all the important Earth system processes, and including anthropogenic perturbation through fossil fuel burning. However, GCMs are computationally very expensive, which limits the number of simulations that can be made. Pattern-scaling is an emulation technique that takes advantage of the fact that local and seasonal changes in surface climate are often approximately linear in amount of warming over land and globe. This allows interpolation away from a limited number of available GCM simulations, to assess alternative future emissions scenarios. In this paper we present a pattern-scaling set consisting of spatial climate change patterns along with parameters for an energy balance model that calculates the amount of global warming. The set is derived from 22 GCMs of the WCRP CMIP3 database, setting the basis for similar eventual pattern development for CMIP5 ensemble. Critically it extends the use of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) framework to enable scanning across full uncertainty in GCMs for impacts studies. Across models, the presented climate patterns represent consistent global mean trends, with maximum four GCMs exhibiting opposite sign of the trend per variable (relative humidity). The described new climate regimes are generally warmer, wetter (but with less snowfall), cloudier and windier, and with decreased relative humidity. Overall, the patterns of the analysed variables explain one-third of regional change in decadal averages (mean Percentage Variance Explained, PVE, 34.25 ± 5.21), but signal in some models exhibits much more linearity (e.g. MIROC3.2(hires):41.53) than in others (GISS_ER: 22.67). The two most often considered variables: near-surface temperature and precipitation, have PVE of 85.44 ± 4.37 and 14.98 ± 4.61, respectively. The dataset is available for download and researchers in the areas of ecosystem modelling and climate change impact assessment are already starting to use it. Besides allowing time-efficient assessment for non-standard future scenarios of changed greenhouse gas (GHG) concentrations, it enables understanding of new representations of land surface processes, and including climate-carbon cycle feedbacks. Current and potential future applications of such modelling system are discussed. [ABSTRACT FROM AUTHOR]

This paper accompanies the second OBLIMAP open source release. The package is developed to map climate fields between a general circulation model (GCM) and an ice sheet model (ISM) in both directions by using optimal aligned oblique projections, which minimize distortions. Both grids may be irregularly spaced and the ratio of the grids is allowed to differ largely. The stand-alone version of OBLIMAP is a powerful tool to map various differently gridded datasets on one uniform ISM grid with an optimal centered projection. This is demonstrated by relevant applicatons concerning the major ice caps. As this applies also for the reverse mapping direction, it can be used as an off-line coupler. Besides, OBLIMAP 2.0 is an embeddable GCM-ISM coupler, suited for high frequent on-line coupled experiments. A new fast scan method is presented as an alternative for the former time consuming grid search strategy, realising a performance gain of several orders of magnitude and enabling the mapping of high resolution datasets with a much larger number of grid nodes. Further a highly flexible masked mapping option is added. The limitations of the fast scan method with respect to unstructured and adaptive grids are discussed together with several proposed parallel implementations in order to achieve another performance gain. [ABSTRACT FROM AUTHOR]

The article discusses the combination of the strong points of general circulation models (GCMs) and Earth system models of intermediate complexity (EMICs) for the development of a loosely coupled model (LCM) that represents the outputs of a GCM-based Earth system model. Smaller computational resources were used for the representation. Uncertainty in global climate change can be studied through LCM which has a highly tunable nature.