We compare the results from simulations of the present and the last interglacial, with and without acceleration of the orbital forcing, using a comprehensive coupled climate model. In low latitudes, the simulation of long-term variations in interglacial surface climate is not significantly affected by the use of the acceleration technique and hence model–data comparison of surface variables is therefore not hampered but major repercussions of the orbital forcing are obvious below thermocline.

We present a new mathematical formalism that serves to represent exchanges of inorganic matter between the atmosphere gas phase and the aerosol aqueous phase. In a global modelling framework, taking into account these processes may help represent many important features more accurately, such as the formation of cloud droplets or the radiative properties of the atmosphere. The formalism strives to keep an appropriate balance between accuracy and computation efficiency requirements.

We present an approach to derive the adjoint state of the C++ coded Ice Sheet System Model. The approach enables data assimilation of observations to improve projections of polar ice sheet mass balance and contribution to sea-level rise. It is applicable to other Earth science frameworks relying on C++ and parallel computing, is non-intrusive, and enables computation of transient adjoints for any type of physics, hence providing insights into the sensitivities of any model to its inputs.

This study proposed a new cloud retrieval method based on the particle filter (PF). The PF cloud retrieval method is compared with the Multivariate and Minimum Residual (MMR) method that was previously established and verified. Cloud retrieval experiments involving a variety of cloudy types are conducted with the PF and MMR methods with measurements of Infrared radiances on multi-sensors onboard both GOES and MODIS, respectively.

This paper analyses methods to assimilate chemical measurements in air quality models. We developed a reduced-order atmospheric chemistry model, which was used to compare results from different assimilation algorithms. Using an ensemble variational method (4DEnVar), we exploited the dynamical information provided by hourly measurements of chemical concentrations to diagnose model biases and improve next-day forecasts for several species of interest for air quality.

High energy atmospheric physics includes terrestrial gamma-ray flashes, electron–positron beams and gamma-ray glows from thunderstorms. It requires appropriate models for the interaction of energetic particles with the atmosphere. We benchmark general purpose and custom-made codes against each other. We focus on basic tests, namely on the evolution of particles through air in the absence of electric and magnetic fields, providing a first benchmark for present and future custom-made codes.

Slope units are morphological mapping units bounded by drainage and divide lines that maximize within-unit homogeneity and between-unit heterogeneity. We use r.slopeunits, a software for the automatic delination of slope units. We outline an objective procedure to optimize the software input parameters for landslide susceptibility (LS) zonation. Optimization is achieved by maximizing an objective function that simultaneously evaluates terrain aspect segmentation quality and LS model performance.

As a consequence of greenhouse gas emissions, changes in ocean temperature, salinity, circulation and sea level are expected in coming decades. Among the models used for climate projections for the 21st century, there is a large spread in projections of these effects. The Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) aims to investigate and explain this spread by prescribing a common set of changes in the input of heat, water and wind stress to the ocean in the participating models.

The nonlinMIP model intercomparison project is described. nonlinMIP provides experiments that account for state-dependent regional and global climate responses. The experiments have two main applications: 1) to focus understanding of responses to CO₂ forcing on states relevant to specific policy or scientific questions (e.g. change under low-forcing scenarios, the benefits of mitigation, or from past cold climates to the present day), or 2) to understand state dependence of climate responses.

FLEXPART is a community model used by many scientists. Here, an alternative FLEXPART model version has been developed, tailored to use with the output data generated by the Norwegian Earth System Model (NorESM1-M). The model provides an advanced tool to analyse and diagnose atmospheric transport properties of the climate model NorESM. To validate the model, several tests were performed that offered the possibility to investigate some aspects of offline global dispersion modelling.

Stratospheric sulfate aerosols from volcanic eruptions have a significant impact on the Earth's climate. The Easy Volcanic Aerosol (EVA) volcanic forcing generator provides a tool whereby the optical properties of volcanic aerosols can be included in climate model simulations in a self-consistent, complete, and flexible manner. EVA is based on satellite observations of the 1991 Pinatubo eruption but can be applied to any real or hypothetical eruption of interest.

Marine phytoplankton plays a prominent role in regulating Earth’s climate. Numerical models are important tools that help us investigate the interactions between these microbes and their environment. We proposed PhytoSFDM as an open-source model to quantify size structure and functional diversity of marine phytoplankton communities. This tool allows us, in a manageable and computationally efficient way, to study patterns in planktonic ecosystems and their feedbacks with a changing environment.

The Coordinated Regional Downscaling Experiment (CORDEX) is a diagnostic MIP in CMIP6. CORDEX builds on a foundation of previous downscaling intercomparison projects to provide a common framework for downscaling activities around the world. The CORDEX Regional Challenges provide a focus for downscaling research and a basis for making use of CMIP6 global output to produce downscaled projected changes in regional climates, and assess sources of uncertainties in the projections.

This study compares the 20th century multi-annual climate variability modes in reanalysis data sets (ERA-20C and 20CR) and 12 climate model simulations using the randomised multi-channel singular spectrum analysis. The reanalysis data sets are remarkably similar on all timescales, except that the spectral power in ERA-20C is systematically slightly higher than in 20CR. None of the climate models closely reproduce all aspects of the reanalysis spectra, although many aspects are represented well.

Ice sheets are part of the climate system and interact with the atmosphere and the ocean. OBLIMAP is a powerful tool to map climate fields between GCMs and ISMs (ice sheet models), which run on grids that differ in curvature, resolution and extent. OBLIMAP uses optimal aligned oblique projections, which minimize area distortions. OBLIMAP 2.0 allows for high-frequency embedded coupling and masked mapping. A fast search strategy realizes a huge performance gain and enables high-resolution mapping.

Crop growth and agricultural management can affect climate at various spatial and temporal scales through the exchange of heat, water, and gases between land and atmosphere. Therefore, simulation of fluxes for heat, water, and gases from agricultural land is important for climate simulations. We developed a new land surface model combined with a crop growth model, called MATCRO-Rice. The main objective of this paper is to present the full description of MATCRO-Rice.

We conducted two types of validation for the simulations by MATCRO-Rice developed by Masutomi et al. (2016). The results of the validation indicate that MATCRO-Rice has a high ability to accurately and consistently simulate latent heat flux, sensible heat flux, net carbon uptake by crops, and crop yield.

It is known that Earth system models have challenges to predict correct levels of soil carbon stocks. Quantification of those stocks is a prerequisite for reliable prediction of future carbon exchange between biosphere and atmosphere. Here, we tested Yasso07 and ROMULv soil carbon models against empirical data from Finland. We found that both the role of understorey vegetation and the impact of drought to decomposition should be incorporated into soil models to have realistic soil carbon stocks.

Recent progress in computing power has enabled climate models to simulate more processes in detail and on a smaller scale. Here we present a common protocol for these high-resolution runs that will foster the analysis and understanding of the impact of model resolution on the simulated climate. These runs will also serve as a more reliable source for assessing climate risks that are associated with small-scale weather phenomena such as tropical cyclones.

Refining model resolution is helpful for representing climate processes. With resolution increasing, the computational cost will become very huge. We designed a new solver to accelerate the high-resolution ocean simulation so as to reduce the computational cost and make full use of the computing resource of supercomputers. Our results show that the simulation speed of the improved ocean component with 0.1° resolution achieves 10.5 simulated years per wall-clock day on 16875 CPU cores.

We developed a plant hydraulics model for tropical forests based on established plant physiological theory, and parameterized it by conducting a pantropical hydraulic trait survey. We show that a substantial amount of trait diversity can be represented in the model by a reduced set of trait dimensions. The fully parameterized model is able capture tree-level variation in water status and improves simulations of total ecosystem transpiration, showing how to incorporate hydraulic traits in models.

The ability of chemical transport model PMCAMx to reproduce ground and satellite aerosol optical depth (AOD) measurements over Europe is evaluated. PMCAMx reproduces AOD values over Spain, the UK, central Europe, and Russia with a fractional bias of less than 15 % and a fractional error of less than 30 %. The model overestimates the AOD over northern Europe probably due to an overestimation of organic aerosol and sulfates, and underestimates over the Balkans due to an underestimation of sulfates.

Microphysical process rates, such as the formation, growth, and evaporation of precipitation, affect the variances, covariances, and fluxes of moisture and heat content. These effects appear as covariance terms within the Reynolds-averaged predictive equations for the scalar (co)variances and fluxes. Using a multivariate probability density function (PDF) and a simple warm-rain microphysics scheme, these microphysical covariance terms can be obtained by analytic integration over the PDF.

Estimation of pollutant releases into the atmosphere is an important problem in the environmental sciences. We formulate a probabilistic model, where a full Bayesian estimation allows estimation of all tuning parameters from the measurements. The proposed algorithm is tested and compared with the state-of-the-art method on data from the European Tracer Experiment (ETEX), where advantages of the new method are demonstrated.