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Introducing CRYOWRF v1.0: multiscale atmospheric flow simulations with advanced snow cover modelling

Most current generation climate and weather models have a relatively simplistic description of snow and snow–atmosphere interaction. One reason for this is the belief that including an advanced snow model would make the simulations too computationally demanding. In this study, we bring together two state-of-the-art models for atmosphere (WRF) and snow cover (SNOWPACK) and highlight both the feasibility and necessity of such coupled models to explore underexplored phenomena in the cryosphere.

Robust global detection of forced changes in mean and extreme precipitation despite observational disagreement on the magnitude of change

Precipitation change is an important consequence of climate change, but it is hard to detect and quantify. Our intuitive method yields robust and interpretable detection of forced precipitation change in three observational datasets for global mean and extreme precipitation, but the different observational datasets show different magnitudes of forced change. Assessment and reduction of uncertainties surrounding forced precipitation change are important for future projections and adaptation.

The IPCC Sixth Assessment Report WGIII climate assessment of mitigation pathways: from emissions to global temperatures

Assessing hundreds or thousands of emission scenarios in terms of their global mean temperature implications requires standardised procedures of infilling, harmonisation, and probabilistic temperature assessments. We here present the open-source “climate-assessment” workflow that was used in the IPCC AR6 Working Group III report. The paper provides key insight for anyone wishing to understand the assessment of climate outcomes of mitigation pathways in the context of the Paris Agreement.

Rapid attribution analysis of the extraordinary heat wave on the Pacific coast of the US and Canada in June 2021

In June 2021, the Pacific Northwest of the US and Canada saw record temperatures far exceeding those previously observed. This attribution study found such a severe heat wave would have been virtually impossible without human-induced climate change. Assuming no nonlinear interactions, such events have become at least 150 times more common, are about 2 ℃ hotter and will become even more common as warming continues. Therefore, adaptation and mitigation are urgently needed to prepare society.

Evidence of localised Amazon rainforest dieback in CMIP6 models

Despite little evidence of regional Amazon rainforest dieback, many localised abrupt dieback events are observed in the latest state-of-the-art global climate models under anthropogenic climate change. The detected dieback events would still cause severe consequences for local communities and ecosystems. This study suggests that 7±5 % of the northern South America region would experience abrupt downward shifts in vegetation carbon for every degree of global warming past 1.5 °C.

Global biomass burning fuel consumption and emissions at 500m spatial resolution based on the Global Fire Emissions Database (GFED)

We present a global fire emission model based on the GFED model framework with a spatial resolution of 500 m. The higher resolution allowed for a more detailed representation of spatial heterogeneity in fuels and emissions. Specific modules were developed to model, for example, emissions from fire-related forest loss and belowground burning. Results from the 500 m model were compared to GFED4s, showing that global emissions were relatively similar but that spatial differences were substantial.

HORAYZON v1.2: an efficient and flexible ray-tracing algorithm to compute horizon and sky view factor

Terrain horizon and sky view factor are crucial quantities for many geoscientific applications; e.g. they are used to account for effects of terrain on surface radiation in climate and land surface models. Because typical terrain horizon algorithms are inefficient for high-resolution (< 30 m) elevation data, we developed a new algorithm based on a ray-tracing library. A comparison with two conventional methods revealed both its high performance and its accuracy for complex terrain.

Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not

The task of evaluating competing models is fundamental to science. Models are evaluated based on an objective function, the choice of which ultimately influences what scientists learn from their observations. The mean absolute error (MAE) and root-mean-squared error (RMSE) are two such functions. Both are widely used, yet there remains enduring confusion over their use. This article reviews the theoretical justification behind their usage, as well as alternatives for when they are not suitable.

The eWaterCycle platform for open and FAIR hydrological collaboration

With the eWaterCycle platform, we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both open science and FAIR science. The eWatercyle platform gives easy access to well-known hydrological models, big datasets and example experiments. Using eWaterCycle hydrologists can easily compare the results from different models, couple models and do more complex hydrological computational research.

Towards automatic finite-element methods for geodynamics via Firedrake

Firedrake is a state-of-the-art system that automatically generates highly optimised code for simulating finite-element (FE) problems in geophysical fluid dynamics. It creates a separation of concerns between employing the FE method and implementing it. Here, we demonstrate the applicability and benefits of Firedrake for simulating geodynamical flows, with a focus on the slow creeping motion of Earth’s mantle over geological timescales, which is ultimately the engine driving our dynamic Earth.

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