We present an ocean model of the natural radioactive isotopes thorium-230 and protactinium-231. These isotopes are often used to investigate past ocean circulation and particle transport. They are removed by particles produced by plankton and from uplifted desert dust that is deposited into the ocean. We approach observed dissolved and adsorbed Th-230 and Pa-231 activities. The Pa-231 / Th-230 sedimentation ratio is reproduced as well; this quantity can be used as a proxy for ocean circulation.

C-Coupler2 is a new version of C-Coupler with a series of new enhancements. It is ready for use to develop various coupled or nested models. It has passed a number of test cases involving model coupling and nesting, and with various MPI process layouts between component models, and has already been used in several real coupled models. Its source code can be downloaded from https://github.com/C-Coupler-Group/c-coupler-lib.

The oxygen-18 signal recorded in fossil planktonic foraminifers has been used for over 50 years in many geoscience applications. However, different planktonic foraminifer species from the same sediment core generally yield distinct oxygen-18 signals, as a consequence of their specific living habitat in the water column and along the year. To explicitly take into account this variability for five common planktonic species, we developed the portable module FAME (Foraminifers As Modeled Entities).

The Earth’s land surface hydrology and physics can be represented in highly sophisticated models known as land surface models. The Land surface Data Toolkit (LDT) software was developed to meet these models’ input processing needs. LDT supports a variety of land surface and hydrology models and prepares the inputs (e.g., meteorological data, satellite observations to be assimilated into a model), which can be used for inter-model studies and to initialize weather and climate forecasts.

libcloudph++ is a free and open-source library of schemes representing cloud microphysics (e.g. condensation of water vapour into cloud droplets, collisions between water drops, precipitation) in numerical models. This work adds new schemes that represent aqueous chemical reactions in water drops. The schemes focus on the oxidation of SO₂ by O₃ and H₂O₂. The libcloudph++ is now capable of resolving the changes in aerosol sizes caused by both collisions between water drops and aqueous oxidation.

Using a virtual machine environment, a low-resolution configuration of the United Kingdom Chemistry and Aerosols (UKCA) composition-climate model has been developed. This configuration, while not suitable for long simulations, is an excellent test-bed for new model developments and can be used to train new users in how to use UKCA. This work was motivated by the desire to improve the usability of UKCA, and to encourage more users to become involved with the code development process.

We present recommendations for the global data infrastructure needed to support CMIP scientific design and its future growth and evolution. We follow a dataset-centric design less prone to systemic failure. Scientific publication in the digital age is evolving to make data a primary scientific output, alongside articles. We design toward that future scientific data ecosystem, informed by the need for reproducibility, data provenance, future data technologies, and measures of costs and benefits.

This paper presents climate model configurations of the European Centre for Medium-Range Weather Forecasts Integrated Forecast System (ECMWF-IFS) for different combinations of ocean and atmosphere resolution. These configurations are used to perform multi-decadal experiments following the protocols of the High Resolution Model Intercomparison Project (HighResMIP) and phase 6 of the Coupled Model Intercomparison Project (CMIP6).

For various applications, a regional or local characterization of rainfall is required, particularly at the watershed scale, where there is spatial heterogeneity. Furthermore, simple models are needed that can simulate various scenarios of climate change including changes in seasonal wetness and rainstorm intensity. To this end, we have developed the STOchastic Rainstorm Model (STORM). We explain its developments and data requirements, and illustrate how it simulates rainstorms over a basin.

Accurate air quality forecasts are critical to protecting human health and the environment. This paper shows how ensemble assimilation of MOPITT CO compact phase space retrieval (CPSR) profiles in WRF-Chem/DART provides significant improvements in the air quality forecasts over the CONUS when compared to independent remote (IASI CO retrieval profiles) and in situ (IAGOS/MOZAIC) observations. It also extends the CPSR algorithm to assimilation of truncated retrieval profiles.

MPAS-Albany Land Ice (MALI) is a new variable-resolution land ice model that uses unstructured grids on a plane or sphere. MALI is built for Earth system modeling on high-performance computing platforms using existing software libraries. MALI simulates the evolution of ice thickness, velocity, and temperature, and it includes schemes for simulating iceberg calving and the flow of water beneath ice sheets and its effect on ice sliding. The model is demonstrated for the Antarctic ice sheet.

In the same way that the fruit fly or the yeast cell serve as model systems in biology, climate scientists use a range of computer models to gain a fundamental understanding of our climate system. These models range from extremely simple models that can run on your phone to those that require supercomputers. Sympl and climt are packages that make it easy for climate scientists to build a hierarchy of such models using Python, which facilitates easy to read and self-documenting models.

This study focuses on the impact of the model vertical mixing parameterisation on the representation of the mixed layer depth (MLD) in ocean forecast models. We compare data from two recent versions of the OceanMAPS forecast system, and find that while there were large improvements in the later version of the model, the skill of each parameterisation varies with spatial location.

The paper presents the comparison of ECMWF-IFS model simulation of aerosol backscatter profiles to long-term measurements of an extended ceilometer network. A significant influence of the numerical description of the hygroscopic growth of sea salt aerosols on the agreement between model and observations was found. Consideration of the nonsphericity of dust particles in the model reduced the attenuated backscatter of dust by ~&thinp;30 % and improved the agreement between model and observations.

In this paper we present a global aerosol–chemistry–climate model with the focus on its representation for atmospheric aerosol particles. In the model, aerosols are simulated using the aerosol module SALSA2.0, which in this paper is compared to satellite, ground, and aircraft-based observations of the properties of atmospheric aerosol. Based on this study, the model simulated aerosol properties compare well with the observations.

Climate models have been run using observed sea surface temperatures to identify biases in the atmospheric circulation. In this work, land surface temperatures are also constrained, which is not routinely done. Experiments include increasing sea surface temperatures, quadrupling atmospheric carbon dioxide and increasing solar radiation. The response of the land surface is then allowed or suppressed, and the global climate is evaluated. Information on how to obtain the model data is also given.

We describe a new coupling between the Glacial Systems Model and the LOVECLIM intermediate complexity climate model. The coupling is distinguished from that of previous studies by greater completeness and accuracy, with the intent of capturing the major feedbacks between ice sheets and climate on glacial cycle timescales. The fully coupled model will be used to examine the ice/climate phase space of past glacial cycles.

We present a new modeling framework called Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines a data-constrained C-cycle analysis with data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. GOLUM-CNP provides a traceable tool, where a consistency between different datasets of global C, N, and P cycles has been achieved.

Lagrangian cloud models are a powerful tool to understand cloud microphysics and are increasingly used in the cloud physics community. In this study we present a method designed to improve the warm cloud precipitation process in such models. Our results indicate that using this method is essential for a proper representation of the collisional process of warm clouds, while maintaining an appropriate computational demand.