ALBERT

Description: We propose a surface melt scheme for glaciated land surfaces, which only requires monthly mean short-wave radiation and temperature as inputs, yet implicitly accounts for the diurnal cycle of short-wave radiation. The scheme is deduced from the energy balance of a daily melt period, which is defined by a minimum solar elevation angle. The scheme yields a better spatial representation of melting than common empirical schemes when applied to the Greenland Ice Sheet, using a 1948–2016 regional climate and snowpack simulation as a reference. The scheme is physically constrained and can be adapted to other regions or time periods.

Description: The Greenland Ice Sheet (GrIS) mass loss has been accelerating at a rate of about 20 ± 10 Gt/yr2 since the end of the 1990's, with around 60 % of this mass loss directly attributed to enhanced surface meltwater runoff. However, in the climate and glaciology communities, different approaches exist on how to model the different surface mass balance (SMB) components using: (1) complex physically-based climate models which are computationally expensive; (2) intermediate complexity energy balance models; (3) simple and fast positive degree day models which base their inferences on statistical principles and are computationally highly efficient. Additionally, many of these models compute the SMB components based on different spatial and temporal resolutions, with different forcing fields as well as different ice sheet topographies and extents, making inter-comparison difficult. In the GrIS SMB model intercomparison project (GrSMBMIP) we address these issues by forcing each model with the same data (i.e., the ERA-Interim reanalysis) except for two global models for which this forcing is limited to the oceanic conditions, and at the same time by interpolating all modelled results onto a common ice sheet mask at 1 km horizontal resolution for the common period 1980–2012. The SMB outputs from 13 models are then compared over the GrIS to (1) SMB estimates using a combination of gravimetric remote sensing data from GRACE and measured ice discharge, (2) ice cores, snow pits, in-situ SMB observations, and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Our results reveal that the mean GrIS SMB of all 13 models has been positive between 1980 and 2012 with an average of 340 ± Gt/yr, but has decreased at an average rate of −7.3 Gt/yr2 (with a significance of 96 %), mainly driven by an increase of 8.0 Gt/yr2 (with a significance of 98 %) in meltwater runoff. Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting the need for accurate representation of the GrIS ablation zone extent and processes driving the surface melt. In addition, a higher density of in-situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 mWE/yr due to large discrepancies in modelled snowfall accumulation. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of same order than RCMs with observations and remain then useful tools for long-term simulations. Finally, it is interesting to note that the ensemble mean of the 13 models produces the best estimate of the present day SMB relative to observations, suggesting that biases are not systematic among models.

Description: Understanding the dynamics of warm climate states has gained increasing importance in the face of anthropogenic climate change, and while it is possible to simulate warm interglacial climates, these simulated results cannot be evaluated without the aid of geochemical proxies. One such proxy is δ18O, which allows for inference about both a climate state's hydrology and temperature. We utilize a stable water isotope equipped climate model to simulate three stages during the Last Interglacial (LIG), corresponding to 130, 125, and 120 kyr before present, using forcings for orbital configuration as well as greenhouse gases. We discover heterogeneous responses in the mean δ18O signal to the climate forcing, with large areas of depletion in the LIG δ18O signal over the tropical Atlantic, the Sahel, and the Indian subcontinent, and with enrichment over the Pacific and Arctic Oceans. While we find that the climatology mean relationship between δ18O and temperature remains stable during the LIG, we also discover that this relationship is not spatially consistent. Our results suggest that great care must be taken when comparing δ18O records of different paleoclimate archives with the results of climate models as both the qualitative and quantitative interpretation of δ18O variations as a proxy for past temperature changes may be problematic due to the complexity of the signals.

Description: The West Antarctic Ice Sheet (WAIS) is considered the major contributor to global sea level rise in the Last Interglacial (LIG) and potentially in the future. Exposed fossil reef terraces suggest sea levels in excess of 7 m in the last warm era, of which probably not much more than 2 m are considered to originate from melting of the Greenland Ice Sheet. We simulate the evolution of the Antarctic Ice Sheet during the LIG with a 3‐D thermomechanical ice sheet model forced by an atmosphere‐ocean general circulation model (AOGCM). Our results show that high LIG sea levels cannot be reproduced with the atmosphere‐ocean forcing delivered by current AOGCMs. However, when taking reconstructed Southern Ocean temperature anomalies of several degrees, sensitivity studies indicate a Southern Ocean temperature anomaly threshold for total WAIS collapse of 2–3°C, accounting for a sea level rise of 3–4 m during the LIG. Potential future Antarctic Ice Sheet dynamics range from a moderate retreat to a complete collapse, depending on rate and amplitude of warming.

Description: The surface mass balance scheme dEBM (diurnal Energy Balance Model) provides a novel interface between the atmosphere and land ice for Earth system modeling, which is based on the energy balance of glaciated surfaces. In contrast to empirical schemes, dEBM accounts for changes in the Earth’s orbit and atmospheric composition. The scheme only requires monthly atmospheric forcing (precipitation, temperature, shortwave and longwave radiation, and cloud cover). It is also computationally inexpensive, which makes it particularly suitable to investigate the ice sheets' response to long-term climate change. After calibration and validation, we analyze the surface mass balance of the Greenland Ice Sheet (GrIS) based on climate simulations representing two warm climate states: a simulation of the mid-Holocene (approximately 6000 years before present) and a climate projection based on an extreme emission scenario which extends to the year 2100. The former period features an intensified summer insolation while the 21st century is characterized by reduced outgoing longwave radiation. Specifically, we investigate whether the temperature–melt relationship, as used in empirical temperature-index methods, remains stable under changing insolation and atmospheric composition. Our results indicate that the temperature–melt relation is sensitive to changes in insolation on orbital timescales but remains mostly invariant under the projected warming climate of the 21st century.

Description: Earth system and climate modelling involves the simulation of processes on a wide range of scales and within and across various compartments of the Earth system. In practice, component models are often developed independently by different research groups, adapted by others to their special interests and then combined using a dedicated coupling software. This procedure not only leads to a strongly growing number of available versions of model components and coupled setups but also to model- and high-performance computing (HPC)-system-dependent ways of obtaining, configuring, building and operating them. Therefore, implementing these Earth system models (ESMs) can be challenging and extremely time consuming, especially for less experienced modellers or scientists aiming to use different ESMs as in the case of intercomparison projects. To assist researchers and modellers by reducing avoidable complexity, we developed the ESM-Tools software, which provides a standard way for downloading, configuring, compiling, running and monitoring different models on a variety of HPC systems. It should be noted that ESM-Tools is not a coupling software itself but a workflow and infrastructure management tool to provide access to increase usability of already existing components and coupled setups. As coupled ESMs are technically the more challenging tasks, we will focus on coupled setups, always implying that stand-alone models can benefit in the same way. With ESM-Tools, the user is only required to provide a short script consisting of only the experiment-specific definitions, while the software executes all the phases of a simulation in the correct order. The software, which is well documented and easy to install and use, currently supports four ocean models, three atmosphere models, two biogeochemistry models, an ice sheet model, an isostatic adjustment model, a hydrology model and a land-surface model. Compared to previous versions, ESM-Tools has lately been entirely recoded in a high-level programming language (Python) and provides researchers with an even more user-friendly interface for Earth system modelling. ESM-Tools was developed within the framework of the Advanced Earth System Model Capacity project, supported by the Helmholtz Association.

Description: We developed a new version of the Alfred Wegener Institute Climate Model (AWI-CM3), which has higher skills in representing the observed climatology and better computational efficiency than its predecessors. Its ocean component FESOM2 (Finite-volumE Sea ice-Ocean Model) has the multi-resolution functionality typical of unstructured-mesh models while still featuring a scalability and efficiency similar to regular-grid models. The atmospheric component OpenIFS (CY43R3) enables the use of the latest developments in the numerical-weather-prediction community in climate sciences. In this paper we describe the coupling of the model components and evaluate the model performance on a variable-resolution (25-125 km) ocean mesh and a 61 km atmosphere grid, which serves as a reference and starting point for other ongoing research activities with AWI-CM3. This includes the exploration of high and variable resolution and the development of a full Earth system model as well as the creation of a new sea ice prediction system. At this early development stage and with the given coarse to medium resolutions, the model already features above-CMIP6-average skills (where CMIP6 denotes Coupled Model Intercomparison Project phase 6) in representing the climatology and competitive model throughput. Finally we identify remaining biases and suggest further improvements to be made to the model.