bluuebunny/crossref_metadata_2025 huggingface dataset:
A protocol for assessing the effectiveness of electrical resistivity imaging for agricultural dike investigation
Authors: Lelièvre Peter , Vandenberg Elias , Hebb Heidi , Butler Karl , Lu Xushan , Farquharson Colin
Published: February 2023

DC electrical resistivity surveying has shown much promise for investigating dikes and other earthen flood barriers. We are interested in the applicability of such data for aiding with maintenance and construction efforts in the Tantramar region of New Brunswick and Nova Scotia, Canada, where agricultural dikes form an important part of critical flood prevention infrastructure. Specifically, our goal is to develop efficient field survey and data processing protocols for detecting possible internal issues in the dikes ahead of further, more detailed geophysical surveying. The field survey protocol must be cost and time effective, given the large lengths of dikes that must be surveyed. The Tantramar dikes are expected to exhibit strong subsurface heterogeneity but accurately characterizing their internal structure may be challenging. Dikes have significant 3D geometry and traditional 2D DC surveying, and subsequent 2D inversion, fails to provide reliable and interpretable results. 3D surveying and inversion may be required but this represents significantly higher field costs. We performed a detailed synthetic inverse modelling study to help design our field surveying protocols. We used a representative model of a dike in the Tantramar region and we worked with the specifics of the surveying equipment available to us. We investigated and compared three possible data acquisition layouts proposed by other authors, we thoroughly compared the results of 2D versus 3D inversion on those layouts, and we performed a detailed investigation to assess best practices for 3D inversion mesh design. We are also incorporating joint interpretation with EM data, collected using mobile survey devices such as the Geonics EM31. Results from synthetic forward and inverse modelling are helping us develop future field data collection, processing and modelling protocols.
Groundwater recharge estimation and uncertainty analysis for various soils in Austria
Authors: Stumpp Christine , Schübl Marleen , Brunetti Giuseppe
Published: February 2023

Groundwater recharge is a key component of the hydrologic cycle, yet its direct measurement is difficult. An alternative is its inverse estimation with a combination of physically based numerical models and soil water observations. However, simulated water fluxes are affected by model predictive uncertainty which are often not considered when simulating and predicting groundwater recharge rates. Therefore, the objective of this study was to use of long-term soil water content measurements at 14 locations from the Austrian soil water monitoring program to quantify and compare local, potential groundwater recharge rates, their temporal variability, and predict future changes in potential groundwater recharge for different climate scenarios. Observations were coupled with a Bayesian probabilistic framework to calibrate the model HYDRUS-1D and assess the effect of model predictive uncertainty on simulated recharge fluxes. Estimated annual potential recharge rates ranged from 44 mm/a to 1319 mm/a with a relative uncertainty (95% interquantile range/median) in the estimation between 1-39%. Recharge rates decreased longitudinally, with high rates and lower seasonality at western sites and low rates with high seasonality and extended periods without recharge at the southeastern and eastern sites of Austria.  Higher recharge rates and lower actual evapotranspiration were related to sandy soils. Future recharge predictions at the median remained close to past rates, except for sites in the East, where they increased. In general, predictions varied drastically between different climate models and emission scenarios, especially for the summer months. Across all projections, an increase in winter recharge at the western sites was predicted, due to higher temperatures with less snow accumulation and/or higher amounts of winter precipitation, followed by decreasing recharge rates in spring. Decreasing tendencies in groundwater recharge were stronger at western sites and at higher altitudes, with longer drought periods lasting until later within the calendar year. Uncertainty in recharge prediction was largely dominated by the difference in climate projections, only at the dry sites in the East and for shorter time periods, soil hydraulic parameter uncertainties played a role.
Indian Ocean heat transport and its role in developing SST pattern in the post-monsoon season in CMIP6 models
Authors: Saran Rajendran , Sandeep Sukumaran
Published: February 2023

The cross-equatorial oceanic heat transport (OHT) in the Indian Ocean during boreal summer is an integral component of the Indian summer monsoon (ISM). This OHT is believed to be a crucial factor in the interannual variability of ISM. Thus, a deeper understanding of OHT in climate model simulations is needed for the understanding of the simulated interannual variability of monsoon. Here we examine the Indian Ocean meridional OHT and how the OHT in the summer monsoon season impacts the development of SST patterns in the post-monsoon season. Our results show that the post-monsoon SST positively correlates with OHT during the summer monsoon in western IO and negatively correlates in the southeastern Indian Ocean. Further, it reveals that the OHT during summer monsoon explains the dipole pattern of SST in the post-monsoon over the equatorial Indian Ocean. This study also investigates how anomalous OHT during monsoon months contributes to the persistence of marine heat waves (MHW) in the post-monsoon season. Both CMIP6 models and observations suggest enhanced and persistent MHWs in the post-monsoon season are linked to stronger OHT during the summer season.
Quantification of pre-operational seismic hazard of deep geothermal systems exemplified in the greater Ruhr region (Germany)
Authors: Kruszewski Michal , Verdecchia Alessandro , Heidbach Oliver , Harrington Rebecca M. , Healy David
Published: February 2023

In 2018, after more than 700 years, the last black coal mine ceased operation in the greater Ruhr region in western Germany. In addition to the repurposing of the unused subsurface infrastructure for heat storage projects, the utilization of deep geothermal resources, located below mining levels in the Devonian Massenkalk formations, is the most promising way of facilitating the green energy transition in this highly populated region. The operation of fluid injection or withdrawal during geothermal production alters subsurface stress and poses questions about the possible reactivation of faults in the greater Ruhr region, with strong implications for seismic hazard potential. Deep geothermal resources depend on permeable pathways (i.e., fault zones and fracture networks) in the subsurface, which are known to have certain intrinsic pre-operational seismic hazard. In this study, we evaluate the probability of reactivation (using the so-called slip tendency and fracture susceptibility indicators) and dilation tendency of major faults accounting for uncertainties of in situ stress conditions, fault geometries, and frictional properties. Furthermore, we investigate the spatio-temporal evolution of the slip tendency of a major fault in the region during geothermal operations utilizing coupled thermo-hydro-mechanical numerical models. This study benefits from a recently published in situ stress database of the greater Ruhr region derived from 429 hydrofracturing tests performed across several coal mines. The assessment of fault reactivation utilizing probabilistic and coupled numerical modelling approaches, as presented in this study, aims at de-risking the exploration of deep geothermal systems in the greater Ruhr region and can hopefully serve as an example for quantification of pre-operational seismic hazards in other regions. Based on preliminary results, we find that the NW-SE striking faults are much more prone to reactivation, in comparison to the NE-SW ones, which are oriented unfavorably under prevailing stress conditions. We also find that thermal stress contributes significantly to fault stability, especially during long-term geothermal production.
Poroviscoelastic Dynamics of Mushy Magmatic Systems
Authors: Castelino Jennifer , Ebmeier Susanna , Pegler Samuel , Harlen Oliver
Published: February 2023

Historically in volcanology, it was thought that a magmatic system consisted of a simple spherical liquid chamber of magma, surrounded by host rock. However, recent evidence suggests that large volumes of melt are disseminated in crystal mush regions, leading to large trans-crustal mushy-magmatic systems. The presence of a crystal mush has many implications for the characteristics of surface displacements caused by magma movements, such as during an intrusion or eruption. While many previous studies have modelled ground deformation due to magma mobilisation using a simple point source or dislocation model embedded in an elastic half space, few studies have accounted for the existence of mush as a poroelastic or viscoelastic material. Current studies suggest that surface deformation can be caused by both poroelastic and viscoelastic deformation of the mush. With our model we account for this behaviour on a poroviscoelastic spectrum demonstrating the significance of this rheology for observations of deformation. We expand on existing poroelastic and viscoelastic models to produce an encompassing poroviscoelastic model that can predict the characteristics of measurable deformation at the Earths surface. In order to do this, we first present a one-dimensional generalised model that describes the behaviour of a poroviscoelastic material. We then adapt this model to a relevant three-dimensional geometries to provide tools for analysing the impact of magma intrusion or eruption for a given system and to provide insight into resulting deformation signals.
Boulders-induced geomorphic adjustment at a range of spatial scales in experimental landscapes
Authors: Nativ Ron , Goren Liran , Habousha Kobi , Laronne John , Turowski Jens
Published: February 2023

The portion of boulders considered to be rarely mobile is thought to impact the geomorphic response of landscapes to tectonic activity and climate. Recent studies demonstrated that boulders modify hillslope and river processes, implying that their long-lasting presence is consequential for landscape form. Understanding the relationship between geomorphic features and boulders thus poses vital information for extracting valuable geomorphic parameters. However, due to the scarcity of data encompassing both boulder parameters and associated hillslope and river morphologies, the impact of boulders on landscape form remains unclear. We have investigated the roles of boulders in landscape modification by conducting a laboratory experiment at a landscape scale. The experiment included an initial phase, where a fluvial topography evolved under uniform uplift and rainfall by incision into a substrate crafted of saturated silica powder. The second phase simulated landscape response to the emplacement of boulders along main trunk channels. Spheres with uniform sizes of 1.5 mm were placed along seven main trunks belonging to basins that drain the eastern experimental mountain flank, and the experiment was allowed to continue. 3D models of the evolving topography were generated every 20\30 minutes. Our analysis reveals that following the emplacement of boulders, the landscape changed its form at a range of spatial scales. At the cross-section scale, the hydraulic geometry scaling relationships were altered where boulders were present in the channel. At the catchment scale, topographic inversion was observed, with tributaries transforming into ridges. At the channel profile scale, perched reaches bounded by knickzones developed. Concurrently, the main drainage divide migrated towards the boulder-covered flank. This multitude of modifications in landscape features at a wide range of scales is interpreted to result from extensive and persistent boulder cover inhibiting local fluvial vertical erosion. The altered morphologies presumably promote a new erosional steady-state under the influence of boulder cover.
A parsimonious and efficient statistical method to correct large scale precipitation products: Empirical Conditional Probability (ECP)method
Authors: Azimi Shima , Massari Christian , Barbetta Silvia , Rigon Riccardo
Published: February 2023

Satellite-based precipitation products show significant bias with respect to ground-based data which prevents their use in several geophysical applications. In this study, we developed a method, the “Empirical Conditional Probability (ECP) method”, to augment the information of remotely sensed precipitation products using ground-based observation. The method relaxes the assumption of Gaussianity typical of many statistical processors which is a strong limitation specifically for the heavily skewed and intermittent daily precipitation signal leading to problems such as extrapolation to extreme values. We proposed a non-parametric and parsimonious approach to optimally merge the satellite and ground-based data.The performance of our developed method is investigated in different experiments using the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) precipitation product. Rain gauges are assumed as a priori information (predictors) about the true precipitation and is used to provide its posterior probabilistic estimation by our proposed empirical conditional probability approach. We compare our method with the classical Quantile mapping (QM) correction method to evaluate the added value of our approach.The analysis was carried out in Aosta Valley, a region located in northern Italy with a dense rain gauge network. The time series was split into two sub-periods: 2008-2021 was used for generating the posterior distribution of precipitation and 2005-2007 was used for the validation of the method. The results demonstrated that the corrected CHIRPS product by our method is superior with respect to the original CHIRPS product and the corrected one with QM during both split periods (i.e., it performs better in terms of KGE, R, NSE, and RMSE). In a second experiment, using the proposed method, the posterior probability distribution of precipitation has been obtained according to the kriged ground-based precipitation data. In this way, instead of having gridded single-value data, a range of expected values is available for each pixel.The idea of using uncertainty assessment for the satellite data (specifically precipitation) is going toward having cubic uncertainty-conscious satellite products with a range of expected values. Furthermore, since the ECP method is based on ground data, we investigated the sensitivity of the method to the density of rain gauges.
Flapping of the magnetotail current sheet in a global 6D hybrid-Vlasov simulation.
Authors: Zaitsev Ivan , Cozzani Giulia , Palmu Miro , Pfau-Kempf Yann , Ganse Urs , Battarbee Markus , Alho Markku , Zhou Hongyang , Grandin Maxime , Dubart Maxime , Suni Jonas , Bussov Maarja , Turc Lucile , Horaites Konstantinos , Papadakis Konstantinos , Gordeev Evgenii , Kebede Fasil , Tarvus Vertti , Palmroth Minna
Published: February 2023

Flapping waves are large-scale oscillations of the Earth's magnetotail current layer propagating in a cross-tail direction. In the current study, we investigate the plasma sheet flapping waves observed in a global 6D hybrid-Vlasov simulation of the Earth’s magnetosphere obtained with the Vlasiator code. Applying the timing analysis for 4 virtual spacecraft located in the near tail around X=-14 Re (where Re=6371 km is the Earth radius), we find that the phase velocity of the waves is directed duskwards and has a magnitude comparable to the ion drift velocity in the current sheet centre. We analyse the spatio-temporal characteristics of the waves by the ad-hoc technique of current sheet extremum tracing and we find that the average period of the flapping waves is T~40 s, and the typical wavelength λ=1.6 Re. The necessity to develop a specific technique arises from the large inaccuracy of the timing analysis output for the different positions of the virtual spacecraft constellation. We clearly observe that the area of most intense growth of the flapping oscillations coincides with the vicinity of the ion diffusion region of magnetic reconnection. In order to clarify the origin of the flapping waves, we calculate the dispersion relation for the ion-kink instability, taking the parameters of different ion distributions observed nearby with the reconnection X-line at the different time steps. Notably, the ion distribution has a specific crescent-type shape revealing the meandering motion of ions in the reconnecting current sheet that we identify as ions carrying the non-adiabatic current which is required for the development of the current layer instabilities. The agreement between the predicted values of the frequency and wave vectors and those observed in the simulation gives us evidence that flapping waves in the global hybrid-Vlasov simulation arise due to the development of the ion kink instability in the reconnecting current layer.
Accurate evaluation of the Birch effect requires continuous CO2 measurements and relevant controls
Authors: Kpemoua Tchodjowiè  Israel , Barré Pierre , Houot Sabine , Chenu Claire
Published: February 2023

The influence of dry-wet cycles (DWC) on soil organic carbon (SOC) decomposition is still debated given the somehow controversial results observed in the literature. The objective of this study was to evaluate the effects of DWC on SOC mineralization relative to various moisture controls in 7 treatments from two long-term French field experiments presenting contrasted SOC concentrations. We conducted a laboratory incubation to quantify CO2 emissions upon four soil moisture scenarios: continuously wet (WET), continuously moderately wet (MWET), continuously dry (DRY) and dry-wet cycles (DWC). We also calculated the SOC mineralization that would correspond to the average water content in DWC (mean_DWC). Our results showed that across all treatments the daily carbon mineralization rate increased with soil moisture (WET>MWET>DRY). In DWC scenario, mineralization rates fluctuated with the changes in soil moisture. As soils dried, daily mineralization rates decreased and the subsequent soil rewetting, to pF 1.5, caused a rapid mineralization flush or "Birch effect". However, these flushes did not compensate for the low mineralization rates in the drying phase as the cumulative mineralization was not higher in the DWC scenario compared to the mean_DWC which was the scenario with equivalent water content as the DWC. We also observed that not accounting the CO2 emissions in the drying phase could lead to an overestimation of the effect of DWC. We recommend to measure continuously the soil respiration during dry-wet experiments and to compare the CO2 emitted in DWC with a control that has a water content equivalent to the average water content in DWC. In addition, we questioned the importance of the effect of dry-wet cycles on overall soil respiration.
Linking land use and peat soil distribution and properties in agricultural lands of Latvia
Authors: Kasparinskis Raimonds , Vinogradovs Ivo , Afanasjeva Kristīne , Avotiņš Andris , Dirnēna Baiba , Kukuļs Imants , Nikodemus Oļģerts
Published: February 2023

Agricultural practice on peat soils represents an explicit tradeoff between carbon sequestration and farmland productivity, i.e., peat soils are a pool of carbon and a fragile component of biodiversity but also highly productive farmland. Agricultural land use and land-use change can have a significant impact on peat soil distribution and properties.This study aims to clarify the distribution of various agricultural land uses in peat soils and to analyse potential drivers of the distribution patterns. The presented research is based on the case studies of agricultural activities in peatlands in substantial landscape locations – a) lowland polder in the ancient coastal lagoon; b) drained inland wetland (inland polder); c) marginal upland landscape; d) undulated plains in a mosaic landscape.Our study shows that peatland distribution has reasonably impacted agricultural land use and its intensity, however in different landscapes, it reveals differently. In coastal lowland polders, due to intense agricultural use, peat soils have significant mineralization levels; in inland polders, the mineralisation is more decelerated; in upland and mosaic landscapes the peat soils have faced farmland abandonment. Mineralization of peat depends on plowing, which promotes it, as well as impacts the thickness of the peat layer. If the peat layer is thinner, the faster the loss of organic matter occurs. Peat soils determine the current use of the land. In the depressions of the undulated topography there are land abandonment and overgrowing by bushes, while polder soils are intensively used by plowing. The presented results provide additional criteria for decision support in agricultural land-use planning, i.e., the implication of agri-environmental schemes in agricultural lands on peat soils.
On the ability of OMIP models to simulate the seasonal cycle of the ocean mixed layer depth in pan-Arctic Seas
Authors: Allende Sofía , Fichefet Thierry , Goosse Hugues , Tréguier Anne-Marie
Published: February 2023

In this study, we assess the ability of the ocean-sea ice general circulation models that participated in the Ocean Model Intercomparison Project (OMIP) to simulate the seasonal cycle of the ocean mixed layer depth in pan-Arctic seas. We focus on the central Arctic Ocean, Beaufort, Chukchi, East Siberian, Laptev, Kara, and Barents Seas. All models underestimate the mixed layer depth by about 15m on average during summertime compared to the MIMOC (Monthly Isopycnal/Mixed layer Ocean Climatology) observational data. In fall and winter, differences of several tens of meters are noticed between the models themselves, and between the models and the observational data. Some models generate too deep mixed layers, while others produce too shallow mixed layers. The magnitude of these inter-model variations differs depending on the sea under consideration.In almost all the seas, OMIP models with similar ocean stratification compared to MIMOC observational data display the best mixed layer depth at the end of the winter. Furthermore, all models simulate more or less the same sea ice mass balance and thus salt flux into the ocean during sea ice freezing. We argue that the discrepancies between models are not so much linked to the surface salt balance but rather to the accuracy with which those models reproduce the ocean stratification. To substantiate this behavior, we apply a simple conceptual model, which simulates the fall/winter month-to-month evolution of the mixed layer depth in ice-covered regions. In almost fully sea ice-covered regions such as the central Arctic Ocean, Beaufort, and Chukchi Seas, this simplified dynamics captures very well the behavior of the general circulation models, and this highlights that the main difference between the models is the ocean stratification. At the same time, in the East Siberian, Laptev, and Kara Seas, inter-model variations are not explained by the differences in ocean stratification, even though they contain a significant concentration of sea ice. In not fully sea ice-covered regions, such as the Barents Sea, the mixed layer depth dynamics is different: the retreat of the ice cover during summer is more significant than in fully covered regions, hence favoring exchanges with the atmosphere.
A new process-oriented ensemble hydrological prediction system for flood prediction and water management in the US Pacific Northwest
Authors: Wood Andy , Sturtevant Josh , Mizukami Naoki , Tang Guoqiang
Published: February 2023

Water-related applications and decisionmaking for flood forecasting and seasonal water management commonly rely on hydrologic modeling and forecasting that must provide accurate information over large domains as well as at local watershed scales.  We present progress on an experimentally operational hydrologic forecasting system being developed in a project between NCAR and the US Army Corps of Engineers to increase situational awareness in the US Columbia River basin of the Pacific Northwest, where myriad management concerns include flood risk mitigation, hydropower generation, navigation, water supply, recreation, fisheries and environmental management. The components of the system arise from process-oriented hydrologic modeling, analysis and prediction research that has been developed over the last decade in a collaboration between NCAR, federal US water agencies, and several academic institutions. In particular, a calibrated, watershed-based SUMMA hydrologic model and MizuRoute channel routing model are run in both retrospective and real time modes to provide 3-hourly timestep ensemble flood forecasts for short to medium range lead times, as well as ensemble seasonal streamflow and water supply forecasts up to a 1-year lead time. A 36-member meteorological forcing analysis is used to initialize the model states, while ensemble meteorological forecasts from GEFS, sub-seasonal-to-seasonal (S2S) climate forecasts and ESP are used to drive future flow predictions. We present the current status of the system, which runs in real time at NCAR, and discuss different elements of the forecast approach, including model calibration, ensemble initialization, data assimilation, downscaling of NWP, S2S climate forecast use, post-processing, and hindcasting. We also discuss project links to a related streamflow forecasting testbed initiative through the new NOAA Cooperative Institute for Research to Operations in Hydrology (CIROH)
Fines migration as a challenge for reservoir-wide chemical stimulation using retarded acid systems
Authors: Grifka Jasmin , Nehler Mathias , Licha Tobias , Heinze Thomas
Published: February 2023

Declining permeability of geothermal reservoirs due to fines migration is often considered with regard to existing fines like clay particles that are mobilized. However, fines are also generated due to dissolution and chemical stimulation techniques can induce the generation of fines. For near-wellbore regions, this is uncritical as fines can be extracted after stimulation using cleaning lifts. With the aim of replacing hydraulic stimulations for enhanced geothermal systems by a reservoir-wide chemical stimulation, the penetration depth of the acids needs to be substantially increased. However, cleaning lifts to remove fines are no longer possible in greater distance from the wellbore, so alternative strategies are required.Flow-through experiments with citric acid on dolostone were used to investigate the dependence of fines generation on the reaction conditions. For all dissolution regimes over a range of different Damköhler numbers, fines were generated and could greatly reduce the permeability of the rock samples. Only when large pathways were created by the dissolution process, the generated fines were transported out of the major pathways as well as dissolved therein, thus not interfering with the increase of permeability due to dissolution. The results highlight the great challenges for reservoir-wide chemical stimulations techniques using retarded acid systems, but also indicate possible solutions.
Observations requirements for marine litter concentration characterization in the Mediterranean Sea
Authors: Soto-Navarro Javier , Jordà Gabriel
Published: February 2023

The main problem of characterizing the spatial distribution and variability of the marine litter (ML) in seas and oceans is the scarcity of observations. ML sampling campaigns are usually concentrated near coastal regions and are carried out during spring – summer months, when the navigation conditions are more favorable.  As a result, the spatial and temporal resolution of the observations does not allow a statistically robust description of the ML average distribution and time evolution. Considering the limited resources and the high cost of the observation campaigns, developing an optimized sampling strategy is a key step to capitalize resources and obtain a robust ML characterization.This study analyzes the temporal and spatial requirements that a sampling should fulfill to obtain accurate estimates of ML concentration in different areas of the Mediterranean Sea. Provided that there are not enough observations to define the underlying statistics of ML concentration we use the outputs of a realistic numerical model as a synthetic reality. Then, we conduct several Monte Carlo experiments simulating different sampling strategies on the model data to obtain the mean ML concentration in a certain region. The spread of values from the ensemble of Monte Carlo members is considered as the uncertainty associated to the estimated mean. Our results suggest that for the same number of observations (i.e. the same observational effort), is better to maintain long observational records rather than to intensify the sampling (i.e. reducing the sampling interval). If the spatial distribution of ML is aimed at, the required spatial density of the sampling depends on the characteristic correlation length scale. Therefore, those regions where the ML concentration structures are larger would require less dense observational samplings.
Climate potential for tourism in Gura Humorului resort, North-East Region of Romania
Authors: Boiciuc Carmen , Roșu Constantin , Bistricean Petruț-Ionel , Mihăilă Dumitru
Published: February 2023

Introduction. In choosing a tourist destination, climatic conditions play an important role. Temperature, humidity, cloudiness, wind speed, etc. have an impact on the activities in any resort. The resort of Gura Humorului (47° 33′ 14″ N, 25° 53′ 21″ E) is located in northern Romania, in the Humorului Depression at an average altitude of 470 m. The resort has a bioclimate with sedative properties, an area of 60.9 sq.km and a population of 13667 (2011). Gura Humorului includes the locality of Voroneț, where the Voroneț Monastery (1488), a monument included in the World Cultural Heritage List, is located.The aim of the study is i) to delimit the periods of the year with thermal comfort/discomfort and ii) to evaluate the climate potential for different outdoor tourist activities in Gura Humorului. As working tools we used the PET bioclimatic index and the climate-tourism scheme (CTIS).Data and methods. We used daily gridded data (air temperature, relative humidity, cloudiness and average wind speed) for the period 1961-2021 (source ANM, www.ogimet.com ) and hourly gridded data for the period 2015-2021 (source National Air Quality Monitoring Network). The data were processed in Excel and RayMan programs to calculate the PET bioclimatic index and to produce the CTIS.Results. An analysis of (PET) by decade at Gura Humorului, for the interval 1961-2021, shows that the comfort range (PET values between 18.1-23.0°C) is installed from the 3rd decade of April and maintained until the 2nd decade of October. If in April-May and October the comfort frequency reaches values of 1 to 20%, in June-August the comfort frequency increases to 30-40%. Cold stress becomes dominant in the cold season from the 2nd decade of October to the 1st decade of April. The lowest PET values correspond to December and January when the frequency of PET˂-10°C values exceeds 30-40%. Heating discomfort occurs on summer days but is not significant in intensity and weight. The CTIS includes the analysis of comfort and discomfort given by PET values, which is harmonised with the other climate indicators. Regarding the restrictions given by wet days, fog, precipitation and strong wind, Gura Humorului has favourable conditions for tourism most of the year. There is also a snow cover from December to March, when winter sports can be practised on the nearby ski slopes. The resort becomes one with an extended tourist season.Conclusions. With comfortable thermo-physiological conditions from May to September, with snow cover from December to March, the resort of Gura Humorului is attractive for outdoor tourist activities for at least 9 months a year. With more flexible management and well-targeted investments, the range of tourist services can be provided at a high and diversified rate for the whole calendar year.
Are remote sensing images accurate enough to detect changes in soil carbon over time? An example from the North Wyke Farm Platform, UK
Authors: Valadares Galdos Marcelo , E. Q. Silvero Nelida
Published: February 2023

Soil scientists, farmers, and policy makers are seeking cost-effective alternatives for measuring, monitoring, and verifying changes in soil carbon as a result of land use change and adoption of sustainable management practices. The increasing interest is in line with the need to establish protocols for accurate representation of changes and variability in soil carbon, especially for sustainability metrics and carbon markets. As conventional soil sampling and laboratory analysis schemes are costly and labour-intensive at large scales, remote sensing-based approaches are promising. Digital soil mapping, which uses satellite images as explanatory variables in regression models, is increasingly used primarily to estimate and monitor changes in soil carbon over time and spatially. This study is intended to demonstrate how satellite images coupled with other environmental covariates and field measurements of soil carbon can be used to build models to explain soil carbon variability and change. The study was conducted at the North Wyke Farm Platform, an experimental farm located in Devon, in which different land-uses and management systems including permanent pasture, high-grass sugar and arable crops have been monitoring since 2012. Soil samples were collected in 2012 in a regular grid scheme and analysed for soil carbon, bulk density and other parameters. Subsequent measurements were also carried out in 2016, 2018, 2019, 2020, and 2021. Soil carbon values were then related to the spectral reflectance of Landsat-8 and terrain variables to build a baseline prediction model. A gradient boosting algorithm, which was parameterised to find the best parameters that minimise the square error of the prediction, was used. After the model was trained and tested for the baseline year, it was applied to satellite images and terrain attributes of the subsequent years and maps of soil carbon was obtained for each year. The predicted values for each year were compared with measured values in each field. Our results demonstrated that Landsat-8 images coupled with terrain attributes were able to explain 33% of the changes in soil carbon observed between 2012 and 2021. Future research is needed to improve these estimates and take full advantage of remote sensing and machine learning models in monitoring, measuring, reporting and verification of soil carbon stocks in agricultural systems. 
Measurements of diffuse emissions of CH4 and NMVOCs from oil production and stationary sources using optical methods.  
Authors: Mellqvist Johan , Samuelsson Jerker , Offerle Brian
Published: February 2023

VOCs correspond to a large number of species which in turn can be categorized into different chemical groups such as: alkanes (e.g. methane, propane, butane etc.), alcohols (e.g. ethanol and propanol, alkenes (e.g. ethene and propene), aromatic hydrocarbons (e.g. benzene and toluene) and aldehydes (e.g. formaldehyde and acetaldehyde). VOCs contributes to the formation of ground level ozone, which is formed through atmospheric chemical reactions of volatile organic compounds and nitrogen oxides (NOx) in the presence of sunlight. Elevated ozone concentrations are known to reduce crop yields and constitute a public health concern and has a climate impact similar to N2O.

Stationary sources such as refineries, storage depots, petrochemical facilities and oil production activities are the largest point sources of VOCs. The emissions are typically dominated by evaporative losses from storage tanks and process equipment, so-called diffuse emissions. Several VOCs are also toxic with direct impact on health such as benzene and formaldehyde.

In this study, we will show results from measurements in 2021 of diffuse emissions of CH4 and NMVOCs from oil production sources in California using optical methods. At Chalmers, several unique optical techniques have been developed. Two of the techniques, the solar occultation flux (SOF) method, Fig 1, and mobile sky DOAS, measure the gas columns of VOCs and NO2, SO2, and formaldehyde, respectively, and from these measurements, it is possible to derive the gas emissions from a certain source by combining with wind speed. The other two techniques, Mobile extractive FTIR and Mobile extractive DOAS yield the ground concentration of multiple species. Emissions of VOCs, methane and air toxics from several of California’s largest-producing oil fields in Kern County were measured. A total of 4500 kg/h of alkanes and 8900 kg/h of methane were measured from 11 fields.  These data have been compared to emission models.
Pursuing a Multi-Model Ensemble Approach to Soil Carbon in Agricultural Systems
Authors: Gustafson David
Published: February 2023

A multi-discliplinary, multi-sectoral team, co-led by the author, is launching a new US-based workgroup with representation from across the rapidly expanding climate smart agricultural community to collaborate on the development and use of an appropriate multi-model ensemble (MME) approach to modeling soil carbon. Although it is not a target of the workgroup at this time, the same modeling approach could eventually be expanded to include methane and nitrous oxide. The workgroup will include the research community, participants in the emerging agricultural carbon marketplace, policy-makers, foundations, and other relevant stakeholders. Such an ensemble approach has ample precedent in modeling other complex processes, such as global climate modeling, weather forecasting, projecting hurricane trajectories, and (perhaps of greatest relevance) predicting crop yields. As demonstrated by the Agricultural Model Intercomparison & Improvement Project (AgMIP),  the median of an MME always gives better predictions than any single model. The workgroup will have two deliverables: (1) a peer-reviewed article in a first-tier journal showing the benefits of the MME approach; and (2) an API (free to anyone) that allows any interested party to deploy the MME approach (which helps address fundamental equity issues in the emerging climate smart ag marketplace).As the effort is undertaken, it will adhere to the following guiding principles:•    The MME approach will be based on individual models that are each publicly available, documented transparently, and based in peer-reviewed literature whenever possible.•    The workgroup will invite participation from all private- and public-sector modeling teams. •    Funding for the effort is being provided via a public-private partnership. The API will be made available to the public free of charge to any interested party.This presentation will describe the current status of the new workgroup and issue an open invitation to interested EGU23 conference participants who wish to become engaged in workgroup activities.
Constraining the radiolytic production of Callisto’s O2 atmosphere
Authors: Carberry Mogan Shane R. , Liuzzo Lucas , Poppe Andrew R. , Simon Sven
Published: February 2023

Herein we constrain the radiolytic production rate of O2 from Callisto's exposed ice patches as well as the corresponding steady-state abundance of O2 in Callisto's atmosphere. That is, by simulating the fluxes of thermal plasma and energetic particles irradiating Callisto's surface, taking into account energy deposition within the atmosphere, we determine the initial source flux of O2 to estimate the corresponding column density for Callisto's O2 component, which we compare to those suggested in the literature. This study provides constraints for Callisto's O2 atmosphere in preparation for future observations, particularly those that will be made by the JUpiter ICy moons Explorer (JUICE) and Europa Clipper spacecraft, as well as the Hubble Space Telescope (HST). Further, based on this analysis at Callisto, we can better our understanding on how the atmospheres of other icy satellites in the Solar System can evolve to their observed state.
Importance of land cover scenarios in a low warming world
Authors: De Hertog Steven , Havermann Felix , Guo Suqi , Pongratz Julia , Manola Iris , Luo Fei , Coumou Dim , Davin Edouard Léopold , Seneviratne Sonia Isabelle , Lejeune Quentin , Menke Inga , Schleussner Carl-Friedrich , Humpenöder Florian , Lawrence Peter , Chini Louise , Hurtt George , Thiery Wim , Popp Alexander
Published: February 2023

Land cover and land management changes (LCLMC) have often been highlighted as crucial regarding climate change, both for mitigation (e.g. afforestation) and adaptation (e.g. irrigation). In order to understand this role we present fully coupled Earth System Model (ESM) simulations using external forcing conditions from the SSP1-1.9 scenario, except for land cover and land management scenarios that follow differing trajectories. First we conduct a short 30-year historical simulation (histCTL) and a future (years 2015-2100) simulation under SSP1-1.9 conditions but with present day land cover kept at constant end of 2014 conditions (futCTL). These allow us to isolate climate changes in response to the SSP1-19 forcing, but in the absence of land cover changes. Secondly we conduct two simulations under SSP1-1.9 forcing, but with land cover and land management following two different trajectories. These trajectories are derived from the scenarios presented in Humpenöder et al. (2022) and represent two strongly diverging worlds with regard to socio-economic development, environmental protection, and land-based mitigation: (i) the future sustainability scenario (futSust) in which the land sector experiences sustainable development and application of mitigation strategies (such as greenhouse gas emission pricing) in all countries, (ii) the future inequality scenario (futIneq) in which these developments mostly happen in OECD countries, with the rest of the world continuing on current trends (including massive tropical deforestation). Each of these simulations have been run with three different ESMs (CESM, MPI-ESM and EC-EARTH) in order to identify how robust these results are over different ESMs.The results of these simulations can be used to increase our understanding of the role of land cover scenarios within a low-warming future as prescribed by the Paris agreement. We can compare the effects of all other forcings (futCTL- histCTL; CO2, aerosols etc.) to the effects of land cover changes in the different scenarios (futSust – futCTL or futIneq-futCTL) as well as to the difference between the future sustainability and the inequality narratives (futSust-futIneq). These results will be analysed for temperature and moisture fluxes, mainly focusing on warm and dry extremes and how land cover scenarios affect these. ReferencesHumpenöder, F., Popp, A., Schleussner, C. F., Orlov, A., Windisch, M. G., Menke, I., Pongratz, J., Havermann, F., Thiery, W., Luo, F., Jeetze, P. V., Philipp Dietrich, J., Lotze-Campen, H., Weindl, I. & Lejeune, Q. (2022). Overcoming global inequality is critical for land-based mitigation in line with the Paris Agreement. Nature Communications, 13(1), 1-15.
Use of machine learning for drain flows predictions in tile-drained agricultural areas
Authors: Mahmood Hafsa , P. A. Ferre Ty , J. M. Schneider Raphael , Stisen Simon , R. Frederiksen Rasmus , V. Christiansen Anders
Published: February 2023

Temporal drain flow dynamics and their underlying controlling factors are important for understanding the needs for water resource management in tile drained agricultural areas. The use of physics-based water flow models to understand tile drained systems is quite common. These physics-based models are complex and have high computational demand due to the high spatial and temporal dimensionality of the problem. We examine whether machine learning (ML) models can offer a simpler tool for water management. The main aim of our study is to assess the potential of ML tools for predicting drain flow with varying climate parameters and hydrogeological properties in different catchments in Denmark. We rely on unique data containing time series of daily drain flow in 26 field-scale tile drained catchments in Denmark: climate data (precipitation, potential evapotranspiration, temperature); geological properties (clay fraction, first sand layer thickness, first clay layer thickness); and topographical indexes (curvature, topographical wetness indexes, topographical position index, elevation etc.). The ML algorithm XGBoost is used to predict drain flow in the 26 drain catchments based on both static and dynamic variables. This algorithm also provides an independent measure of the value of information contained in variables related to climate, geology and topography for the prediction of tile drain flows. The ML approach examined could provide a more transferable, faster, and less computationally expensive tool to predict drain flow dynamics. Simultaneously, the results of the study offer insight into the underlying factors that control drain flow, allowing for improved data collection and physics-based model development.
Bayesian hierarchical modeling characterizes spatio-temporal variability in phosphorus export across the contiguous United States
Authors: Karimi Kimia , Obenour Daniel
Published: February 2023

Phosphorus (P) inputs from anthropogenic activities are subject to riverine (hydrologic) P export, causing water quality problems in lakes and coastal systems. Nutrient budgets have been used as a quantitative means of assessing the amount of nutrients imported to and exported from a system. However, at large spatial scales, estimates of hydrologic P losses are usually not available or assumed as a fixed fraction of the budget terms. In addition, fluxes in nutrient budgets are generally not quantified at regular intervals. In this study, we estimate P losses across 150 US watersheds at an approximately 4-digit Hydrologic Unit Code (HUC 4) watershed scale from 1997-2017. To explain the spatio-temporal variability in these estimates, we develop a Bayesian model based on various anthropogenic P inputs (e.g., fertilizer, animal manure, point sources, and atmospheric deposition) and outputs (crop removal) from national inventories, climatic factors, background soil P content, and watershed characteristics. In addition, a hierarchical approach accounts for additional sources of variability across different regions. Model results help us identify hot spots of P loss, along with the primary factors contributing to these losses. Results indicate that the greatest P losses (per unit area) occur in the Mid-Atlantic and Great Lakes regions, mainly due to high anthropogenic inputs. Additionally, the Upper Colorado region is found to have the highest temporal variability in P loss, whereas the Lower Mississippi region has the lowest.