For designing of Ground Source Heating Systems (GSHS) Thermal Response Tests (TRT) are used for a long time. TRTs generally provide a profound basis for the final implementation of a GSHS. They obtain the effective thermal conductivity and thermal resistance of a borehole. Until today several TRT types have been introduced and defined as Geothermal Response Test (GRT), Enhanced GRT (EGRT), Constant Heat Flux TRT (chTRT), Constant temperature (ctTRT ) etc.. These models mainly focus on closed heat exchangers in shallow boreholes. However, recent developments in medium depth drilling technologies make deeper boreholes more economic. Furthermore, advanced methodologies for obtaining thermal conductivities in deep and open boreholes are progressing. In this study, we introduce a new simple thermal conductivity obtaining methodology that can be used for deep and open boreholes. Generally, TRTs are applied with the circulation of water inside pipes or immersing probes in water. In case of water circulation in deep boreholes, different heat flux values will be attributed to different layers. Moreover, by introducing a constant heat flux similar to conventional TRT into water-filled boreholes or water-filled pipes, convective movements of water will occur and thermal conductivities cannot be obtained. However, immersed probes as a heat source might prevent water convection cells inside a pipe or a borehole. In deep boreholes, the heat flux is depended on the thermal conductivity of each layer. Thus, deep boreholes require a discrete heat introduction into every single layer of different thermal conductivity in order to keep the temperature constant. The thermal conductivity of each layer can be approximated and integrated over the total length of a deep borehole. This effect is analytically and numerically investigated in this study.

We reprocessed and interpreted Chang’E-4 Lunar Penetrating Radar (LPR) data collected until 14th February 2023, exploiting a new Deep Learning-based algorithm to automatically extract reflectors from a processed radar dataset. The results are in terms of horizon probability and have been interpreted by integrating signal attribute analysis with orbital imagery. The approach provides more objective results by minimizing the subjectivity of data interpretation allowing to link radar reflectors to their geological context and surface structures. For the first time, we imaged dipping layers and at least 20 shallow buried crateriform structures within the regolith using LPR data. We further recognized four deeper structures similar to craters, locating ejecta deposits related to a crater rim crossed by the rover path and visible in satellite image data.

The Glass Window Bridge Located in Eleuthera, The Bahamas, is the only bridge connecting Eleuthera’s northern and southern mainland, facing the Atlantic Ocean to the east and the Great Bahama Bank to the west. This bridge is under constant threat from hurricanes and large swells in the Atlantic Ocean. The existing bridge has been subject to severe damage arising from wave impact forces since its construction. In addition, severe overtopping of the cliffs near the Glass Window Bridge causes damage to the roads and severe erosion, that over the years has created unique geologic features. As the global climate warms and sea level rises (SLR), coastal areas will be subject to more extreme flooding and intense hurricanes. Therefore, assessing the impact of potential SLR on the GW bridge and guiding bridge wave mitigation measures are of crucial need. A 3D Digital Terrain Model (DTM) of the bridge site and adjacent ocean bathymetry is constructed from satellite data. This study develops a multiphase computational fluid dynamics (CFD) model based on the DTM to study the impact of wave-breaking for three major historical storm events, and for three different estimates of SLR for the year 2100. Our results suggest that, due to SLR, the islands are subjected to increased overtopping, which occurs even during normal wave conditions. Notably, nonlinear increases in wave splash extent and wave-induced bridge loads are observed as SLR increases. Our results indicate that SLR additionally magnifies the erosional energy, accelerating further changes in the geological features of the island.

Iron is present in magmas at concentrations ranging from less than 1 wt% to more 8 than 10 wt% in two valence state. In general, Fe2+ is a network modifier in the melt structure while Fe3+ is a weak network former. The ratio Fe3+/(Fe3+ + Fe2+) depends on temperature, pressure, oxygen fugacity and melt composition. Parametric models allow its calculation, but the complex links between melt composition, iron oxidation state and coordination can be further rationalized using a ionic-polymeric model. Constraining concentration and oxidation state of iron is critical for determining magma density and viscosity, which drive exchanges of matter and heat in the Earth. At high pressures, changes in the coordination of elements, including iron, yield a stiffening and densification of magmas, potentially influencing dynamic and geochemical processes. Near surface, crystallization of Fe-bearing phases changes the residual melt composition, including iron content and oxidation state as well as volatile concentration, ultimately driving large changes in density and viscosity of magmas, and, hence, in the dynamic of fluid flow in volcanic systems. The complex interplay between magma iron content and oxidation state, major element chemistry, crystal and volatile content thus can play a large role on the dynamic of volcanic systems.

This study examines how greenhouse gas (GHG) production and organic matter (OM) transformations in coastal wetland soils vary with the availability of oxygen and other terminal electron acceptors. We also evaluated how OM and redox-sensitive species varied across different size fractions: particulates (0.45-1μm), fine colloids (0.1-0.45μm), and nano particulates plus truly soluble (<0.1μm; NP+S) during 21-day aerobic and anaerobic slurry incubations. Soils were collected from the center of a freshwater coastal wetland (FW-C) in Lake Erie, the upland-wetland edge of the same wetland (FW-E), and the center of a saline coastal wetland (SW-C) in Washington state. Anaerobic methane production for FW-E soils were 47 and 27,537 times greater than FW-C and SW-C soils, respectively. High particulate Fe2+ and dissolved sulfate concentrations in FW-C and SW-C soils suggest that iron and/or sulfate reduction inhibited methanogenesis. Aerobic CO2 production was highest for both freshwater soils, which had a higher proportion of OM in the NP+S fraction (64±28% and 70±10% for FW-C and FW-E, respectively) and C:N ratios reflective of microbial detritus (1.7±0.2 and 1.4±0.3 for FW-E and FW-C, respectively) compared to SW-C, which had a higher fraction of particulate (58±9%) and fine colloidal (19±7%) OM and C:N ratios reflective of vegetation detritus (11.2 ± 0.5). The variability in GHG production and shifts in OM size fractionation and composition observed across freshwater and saline soils collected within individual and across different sites reinforce the high spatial variability in the processes controlling OM stability, mobility, and bioavailability in coastal wetland soils.

Quantifying the anthropogenic fluxes of CO2 is important to understand the evolution of carbon sink capacities, on which the required strength of our mitigation efforts directly depends. For the historical period, the global carbon budget (GCB) can be compiled from observations and model simulations as is done annually in the Global Carbon Project’s (GCP) carbon budgets. However, the historical budget only considers a single realization of the Earth system and cannot account for internal climate variability. Understanding the distribution of internal climate variability is critical for predicting the future carbon budget terms and uncertainties. We present here a decomposition of the GCB for the historical period and the RCP4.5 scenario using single model large ensemble simulations from the Max Planck Institute Grand Ensemble (MPI-GE) to capture internal variability. We calculate uncertainty ranges for the natural sinks and anthropogenic emissions that arise from internal climate variability, and by using this distribution, we investigate the likelihood of historical fluxes with respect to plausible climate states. Our results show these likelihoods have substantial fluctuations due to internal variability, which are partially related to ENSO. We find that the largest internal variability in the MPI-GE stems from the natural land sink and its increasing carbon stocks over time. The allowable fossil fuel emissions consistent with 3°C warming may be between 9–18 PgCyr-1. The MPI-GE is generally consistent with GCP’s global budgets with the notable exception of land-use change emissions in recent decades, highlighting that human action is inconsistent with climate mitigation goals.

Climate change tends to be addressed by accurate statistics and modelling, but it is generally perceived abstractly, being considered a distant psychological risk in which impacts and effects are spatially and temporally differentiated. In other words, people’s attitude towards climate change is that it will impact other individuals and communities that are geographically, temporally, and even generationally removed from themselves. However, due to the hybrid nature of climate change as both a physical and social phenomenon, individuals are not ‘blank slates’ receiving information and facing climate change. Many have argued that deepening personal experience could be the first step for reducing individual and community psychological distance of climate change while increasing the potential for behavior change. Considering that agriculture affects and is affected by climate change in several ways, farmers can provide first-hand observations of climate change impacts and testing different adaptation options. This contribution provides an overview of the intellectual structure of farmers’ behavior on climate change awareness, perceived risks, and adaptation capacity. A portfolio of 108 survey studies published in the last decade was selected for a comprehensive analysis. Exploratory variables such as farmers’ socio-demographic characteristics, level of climate change awareness, major perceived impacts, and adaptation measures, parameters, and barriers have been reported. In addition to the bibliographic analysis, the first results from a survey conducted in different irrigation systems in northern Italy will be tested to identify(dis)similar trends in farmers’ behavior. The identification of not only farmers’ behavior gaps but also their causing reasons will contribute to focus attention on most concerning issues and provide more accurate bottom-up knowledge to managers and decision-makers.

Land use sector is important in stabilizing global mean temperature rise to 2 °C or less, because land use changes are likely to affect the climate system. Changes in the extent and magnitude of local-to-regional climate by anthropogenic modifications of land use are still largely debated. In this study, we simulate and analyze the climate response to different ranges of idealized extreme land cover changes with two regional climate models (COSMO-CLM v.4.8 and WRF v.3.9.1 in EURO-CORDEX (European branch of the international Coordinated Regional climate Downscaling Experiment-CORDEX initiative) domain. Different experiments are envisioned in this study, including a control run and simulations based on idealized extensive deforestation (replacement of today forestland to bare land or herbaceous vegetation) or afforestation (conversion of today cropland to evergreen needle-leaf forest or deciduous broad-leaf forest). The simulations also include more realistic land cover changes across different land cover classes. The investigated parameters will be the changes of temperature, precipitation, and frequency of temperature extremes at both the entire EURO-CORDEX domain (regional scale) and the changed grids (local scale). Results will also be compared to observation data gathered from satellite retrievals. In the grid cell affected by land cover change, we expect to find temperature changes that are more significant than in non-affected areas. A latitudinal pattern and seasonal variability should also emerge. Of particular interest will be the understanding of the spatial patterns of the climate response to the individual types of land cover changes, their sensitivity to space and location, and the analysis of possible correlations with key vegetation and climate parameters. As biophysical effects from land cover changes shape European climate in different ways, further developments and better understanding of land-climate interactions can ultimately assist decision makers to modulate land management strategies at different scales in light of climate change mitigation and adaptation.

A document by Zijing Wang. Click on the document to view its contents.

Many physical processes in the field of rock physics are influenced by the presence of fractures and microcracks. Therefore, intact rock samples are often used for reproducible experimental studies, and cracks are artificially created by various methods. For this, one possibility is the use of thermal treatments. In this work, twelve thermal treatments, differing in the applied maximum temperature and the applied cooling condition (slow versus fast cooling) are experimentally studied for dry Bianco Carrara marble under ambient conditions. Two sizes of cylindrical core samples are investigated to identify a potential size effect. As effective quantities on the core-scale, the bulk volume, the bulk density, and the P- and S-wave velocities, including shear wave splitting, are examined. To obtain a three-dimensional insight into the mechanisms occurring on the micro-scale level, micro X-Ray Computed Tomography (micro-XRCT) imaging is employed. For both cooling conditions, with increasing maximum temperature, the bulk volume increases, and the propagation velocities significantly drop. This behavior is amplified for fast cooling. The bulk volume increase is related to the initiated crack volume as micro-XRCT shows. Based on comprehensive measurements, a logarithmic relationship between the relative bulk volume change and the relative change of the ultrasound velocities can be observed. Although there is a size effect for fast cooling, the relationship found is independent of the sample size. Also the cooling protocol has almost no influence. A model is derived which predicts the relative change of the ultrasound velocities depending on the initiated relative bulk volume change.

Extensive research has shown that wind has a strong influence on estuarine circulation and salt transport. However, the response to wind forcing in estuarine systems presents challenges due in part to the complexities of realistic forcing conditions, system states, and geomorphologies. To further advance the understanding of estuarine responses to wind forcing, a comprehensive analysis of stratification and mixing during a typical southeast wind event was conducted in Mobile Bay, a microtidal, wide, shallow, and river-dominated estuary in the northern Gulf of Mexico. An analysis of the vertical salinity variance and its associated budget terms shows that the system generally becomes less stratified and fully mixed across much of the system; however, there was significant spatial heterogeneity in physical processes driving the evolution of the water column stratification over the course of the event. Surprisingly, in some regions of the bay, dissipation of salinity variance was secondary to contributions from straining and advection. Furthermore, local wind stress and remote wind driven Ekman transport affected stratification responses and their relative impacts varied spatially across the estuary. Direct turbulent mixing from local wind stress and straining dominated the stratification responses away from the main tidal inlet where estuarine-shelf exchange (i.e., current velocity structure and advection of salinity) from Ekman transport controlled the vertical mixing. This detailed case study highlights the complexity of wind influences in a system like Mobile Bay, a representative typical of the northern Gulf of Mexico and other coastal region.

A document by Emma Liu. Click on the document to view its contents.

Geologic carbon storage is required for achieving negative CO2 emissions to deal with the climate crisis. The classical concept of CO2 storage consists in injecting CO2 in geological formations at depths greater than 800 m, where CO2 becomes a dense fluid, minimizing storage volume. Yet, CO2 has a density lower than the resident brine and tends to float, challenging the widespread deployment of geologic carbon storage. Here, we propose for the first time to store CO2 in supercritical reservoirs to reduce the buoyancy-driven leakage risk. Supercritical reservoirs are found at drilling-reachable depth in volcanic areas, where high pressure (p>21.8 MPa) and temperature (T>374 ºC) imply CO2 is denser than water. We estimate that a CO2 storage capacity in the range of 50-500 Mt yr-1 could be achieved for every 100 injection wells. Carbon storage in supercritical reservoirs is an appealing alternative to the traditional approach.

Why do some Martian dust storms, in some Mars years, expand to reach planet-encircling status, while the majority do not? In what ways do the largest regional events differ from those that become global? Comparisons of observations from these two categories of events may help answer these questions. The dust storm season of 2018, which included a global-scale dust event, was preceded by five successive dust storm seasons in which only regional-scale events were observed. The recent record thus presents an opportunity for making quantitative comparisons between regional-scale and global-scale dust events. Observations by the Mars Climate Sounder, on board the Mars Reconnaissance Orbiter spacecraft, provide unique 4D information on temperatures and aerosol loading of the Mars atmosphere, to altitudes of >80 km. Available MCS observations span the past eight Mars years. We have previously employed MCS observations to characterize the evolution in latitude, longitude, and altitude of atmospheric dust clouds during the initiation phase of the 2018 global event. Other atmospheric fields provide complementary information. For instance, observed changes with time in atmospheric ‘dynamical heating’ also help characterize the response of the Mars atmosphere to added dust loading. In this process, the atmosphere in regions far removed from the locations where dust is lifted may be warmed by adiabatic compression within the descending branches of Hadley-like meridional circulation cells. We will present and interpret MCS observations of these and other phenomena for selected large regional-scale dust events of Mars Years 29-33 (from 2009 through 2017), and draw comparisons with observations obtained during the 2018 global event. We will additionally explore the implications of the results within the context of current hypotheses for the triggering of the largest dust storms on sub-seasonal time scales.

A document by Sharanya J. Majumdar. Click on the document to view its contents.

Stable water isotopes in inland Antarctic ice cores are powerful paleoclimate proxies; however, their relationship with dynamical atmospheric circulations remains controversial. Using a water isotope climate model (MIROC5-iso), we assessed the influence of the Last Glacial Maximum (LGM; ~21,000 years ago) sea surface temperatures (SST) and sea ice (SIC) on Antarctic precipitation isotopes (δ18Op) through atmospheric circulation. The results revealed that the synoptic circulation mostly maintained southward moisture transport, reaching inland Antarctica. The steepened meridional SST gradient in the mid-latitudes increased δ18Op in inland Antarctica by enhancing the baroclinic instability and synoptic moisture transport. In contrast, enhanced SIC reduced the atmospheric humidity around Antarctica and lowered δ18Op through extensive surface cooling and transport from the ocean. These findings elucidate the isotopic proxies and enable us to constrain the southern hemisphere atmospheric circulation, including the westerlies, using ice cores during past climates, including the LGM.

Snow interacts with its environment in many ways, is constantly changing with time, and thus has a highly heterogeneous spatial and temporal variability. Therefore, modeling snow variability is difficult, especially when additional components such as vegetation add complexity. To increase our understanding of the spatio-temporal variability of snow and to validate snow models, we need reliable observation data at similar spatial and temporal scales. For these purposes, airborne LiDAR surveys or time series derived from snow sensors on the point scale are commonly used. However, these are limited either to one point in space or in time. We present a new, extensive dataset of snow variability in a sub-alpine forest in the Alptal, Switzerland. The core dataset consists of a dense sensor network, repeated high-resolution LiDAR data acquired using a fixed-wing UAV, and manual snow depth and snow density measurements. Using machine learning algorithms, we determine four distinct spatial clusters of similar snow depth dynamics. These clusters are characterized and further used to derive daily snow depth and snow water equivalent (SWE) maps. The results underline the complex relation of topography and canopy cover towards snow accumulation and ablation. The derived products are the first to our knowledge that provide daily, high-resolution snow depth and SWE based almost exclusively on field data. They are therefore ideally suited for the validation of distributed snow models. Our approach can be applied to other project areas and improve our understanding of the spatio-temporal variability of snow in forested environments.

Projected changes in climate are likely to affect not only its mean state but also its variability. As such, improving our understanding of the spectrum of climate variability and how different feedbacks in the climate system influence it is of vital importance. We perform a process-based examination of variability with respect to changing orbital insulation, ice coverage, and land/sea distribution during the Last Glacial Maximum and the Holocene. To this end, we adapt a two-dimensional energy balance model [Zhuang, North & Stevens, 2017] to run transient simulations. The model is forced by carbon dioxide and solar insolation changes for the last Glacial cycle. We evaluate the model’s ability to reproduce changes in local to global, seasonal to millennial temperature distributions during the Last Glacial Maximum and the Holocene. We compare the simulated states and the transient evolution to those obtained by comprehensive coupled climate models. Finally, we test the mean-state dependence of temperature variability over a large range of model configurations and discuss implications for future climate.