High-resolution Model Research Articles

Assessing current and future available resources to supply urban water demands using a high-resolution SWAT model coupled with recurrent neural networks and validated through the SIMPA model in karstic Mediterranean environments

Hydrological simulation in karstic areas is a hard task due to the intrinsic intricacy of these environments and the common lack of data related to their geometry. Hydrological dynamics of karstic sites in Mediterranean semiarid regions are difficult to be modelled mathematically owing to the existence of short wet episodes and long dry periods. In this paper, the suitability of an open-source SWAT method was checked to estimate the comportment of a karstic catchment in a Mediterranean semiarid domain (southeast of Spain), which wet and dry periods were evaluated using box-whisker plots and self-developed wavelet test. A novel expression of the Nash–Sutcliffe index for arid areas (ANSE) was considered through the calibration and validation of SWAT. Both steps were completed with 20- and 10-year discharge records of stream (1996–2015 to calibrate the model as this period depicts minimum gaps and 1985–1995 to validate it). Further, SWAT assessments were made with records of groundwater discharge and relating SWAT outputs with the SIMPA method, the Spain’s national hydrological tool. These methods, along with recurrent neural network algorithms, were utilised to examine current and predicted water resources available to supply urban demands considering also groundwater abstractions from aquifers and the related exploitation index. According to the results, SWAT achieved a “very good” statistical performance (with ANSE of 0.96 and 0.78 in calibration and validation). Spatial distributions of the main hydrological processes, as surface runoff, evapotranspiration and aquifer recharge, were studied with SWAT and SIMPA obtaining similar results over the period with registers (1980–2016). During this period, the decreasing trend of rainfalls, characterised by short wet periods and long dry periods, has generated a progressive reduction of groundwater recharge. According to algorithms prediction (until 2050), this declining trend will continue reducing groundwater available to meet urban demands and increasing the exploitation index of aquifers. These results offer valuable information to authorities for assessing water accessibility and to provide water demands in karstic areas.

Insights from a topo-bathymetric and oceanographic dataset for coastal flooding studies: the French Flooding Prevention Action Program of Saint-Malo

Abstract. The French Flooding Prevention Action Program of Saint-Malo, France, requires the assessment of coastal flooding risks and the development of a local flood warning system. The first prerequisite is knowledge of the topography and bathymetry of the bay of Saint-Malo; the acquisition of new multibeam bathymetric data was performed in 2018 and 2019 to increase the resolution of the existing topo-bathymetric datasets and to produce two high-resolution (20 and 5 m) topo-bathymetric digital terrain models. Second, the hydrodynamics associated with coastal flooding were investigated through a dense and extensive oceanographic field experiment conducted during winter 2018–2019 using a network of 22 moorings with 37 sensors: the network included 2 directional buoys, 2 pressure tide gauges, 18 wave pressure gauges, 4 single-point current meters, 7 current profilers, and 4 acoustic wave current profilers from mid-depth (25 m) up to the upper beach and the dike system. The oceanographic dataset thus provides an extended overview of the hydrodynamics and wave processes in the bay of Saint-Malo from the coast up to over-flooding and over-topping areas. This dataset helps to identify the physical drivers of the coastal flooding and provides a quantification of their respective contributions. In particular, the wave processes at the foot of the protection structures can be observed: in this macro-tidal environment, during high spring tides, short and infragravity waves propagate up to the protection structures, while the wave set-up remains negligible, and over-topping by sea packs can occur. The combination of high-resolution topo-bathymetric and oceanographic datasets allows the construction, calibration and validation of a wave and hydrodynamic coupled model that is used to investigate flooding processes more deeply and might be integrated into a future local warning system by means of Saint-Malo inter-communality. The topo-bathymetric and oceanographic datasets are available freely at https://doi.org/10.17183/MNT_COTIER_GNB_PAPI_SM_20m_WGS84, https://doi.org/10.17183/MNT_COTIER_PORT_SM_PAPI_SM_5m_WGS84 and https://doi.org/10.17183/CAMPAGNE_OCEANO_STMALO (Shom, 2020a, b, 2021).

High-Resolution Modeling of Summertime Biogenic Isoprene Emissions in New York City.

As cities strive for ambitious increases in tree canopy cover and reductions in anthropogenic volatile organic compound (AVOC) emissions, accurate assessments of the impacts of biogenic VOCs (BVOCs) on air quality become more important. In this study, we aim to quantify the impact of future urban greening on ozone production. BVOC emissions in dense urban areas are often coarsely represented in regional models. We set up a high-resolution (30 m) MEGAN (The Model of Emissions of Gases and Aerosols from Nature version 3.2) to estimate summertime biogenic isoprene emissions in the New York City metro area (NYC-MEGAN). Coupling an observation-constrained box model with NYC-MEGAN isoprene emissions successfully reproduced the observed isoprene concentrations in the city core. We then estimated future isoprene emissions from likely urban greening scenarios and evaluated the potential impact on future ozone production. NYC-MEGAN predicts up to twice as much isoprene emissions in NYC as the coarse-resolution (1.33 km) Biogenic Emission Inventory System version 3.61 (BEIS) on hot summer days. We find that BVOCs drive ozone production on hot summer days, even in the city core, despite large AVOC emissions. If high isoprene emitting species (e.g., oak trees) are planted, future isoprene emissions could increase by 1.4-2.2 times in the city core, which would result in 8-19 ppbv increases in peak ozone on ozone exceedance days with current NOx concentrations. We recommend planting non- or low-isoprene emitting trees in cities with high NOx concentrations to avoid an increase in the frequency and severity of future ozone exceedance events.

High-resolution Observation and Magnetic Modeling of a Solar Minifilament: The Formation, Eruption, and Failing Mechanisms

Minifilaments are widespread small-scale structures in the solar atmosphere. To better understand their formation and eruption mechanisms, we investigate the entire life of a sigmoidal minifilament located below a large quiescent filament observed by Big Bear Solar Observatory/Goode Solar Telescope on 2015 August 3. The Hα structure initially appears as a group of arched threads, then transforms into two J-shaped arcades, and finally forms a sigmoidal shape. Solar Dynamics Observatory (SDO)/Atmospheric Imaging Assembly observations in 171 Å show that two coronal jets occur around the southern footpoint of the minifilament before the minifilament eruption. The minifilament eruption starts from the southern footpoint, then interacts with the overlying filament and fails. The aforementioned observational changes correspond to three episodes of flux cancellations observed by SDO/Helioseismic and Magnetic Imager. Unlike previous studies, the flux cancellation occurs between the polarity where the southern footpoint of the minifilament is rooted and an external polarity. We construct two magnetic field models before the eruption using the flux rope insertion method and find a hyperbolic flux tube above the flux cancellation site. The observation and modeling results suggest that the eruption is triggered by the external magnetic reconnection between the core field of the minifilament and the external fields due to flux cancellations. This study reveals a new triggering mechanism for minifilament eruptions and a new relationship between minifilament eruptions and coronal jets.

Reconstructing Younger Dryas ground temperature and snow thickness from cave deposits

Abstract. The Younger Dryas stadial was characterised by a rapid shift towards cold-climate conditions in the North Atlantic realm during the last deglaciation. While some climate parameters including atmospheric temperature and glacier extent are widely studied, empirical constraints on permafrost temperature and snow thickness are limited. To address this, we present a regional dataset of cryogenic cave carbonates (CCCs) from three caves in Great Britain that formed at temperatures between −2 and 0 °C. Our CCC record indicates that these permafrost temperatures persisted for most of the Younger Dryas. By combining ground temperatures with surface temperatures from high-resolution ground-truthed model simulations, we demonstrate that ground temperatures were approximately 6.6 ± 2.3 °C warmer than the mean annual air temperature. Our results suggest that the observed temperature offset between permafrost and the atmosphere can be explained by an average snow thickness between 0.2 and 0.9 m, which persisted for 233 ± 54 d per year. By identifying modern analogues from climate reanalysis data, we demonstrate that the inferred temperature and snow cover characteristics for the British Isles during the Younger Dryas are best explained by extreme temperature seasonality, comparable to continental parts of today's Arctic Archipelago. Such a climate for the British Isles necessitates a winter sea ice margin at approximately 45° N in the North Atlantic Ocean.

High-resolution diffusion magnetic resonance imaging and spatial-transcriptomic in developing mouse brain

Brain development is a highly complex process regulated by numerous genes at the molecular and cellular levels. Brain tissue exhibits serial microstructural changes during the development process. High-resolution diffusion magnetic resonance imaging (dMRI) affords a unique opportunity to probe these changes in the developing brain non-destructively. In this study, we acquired multi-shell dMRI datasets at 32 µm isotropic resolution to investigate the tissue microstructure alterations, which we believe to be the highest spatial resolution dMRI datasets obtained for postnatal mouse brains. We adapted the Allen Developing Mouse Brain Atlas (ADMBA) to integrate quantitative MRI metrics and spatial transcriptomics. Diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI) metrics were used to quantify brain development at different postnatal days. We demonstrated that the differential evolutions of fiber orientation distributions contribute to the distinct development patterns in white matter (WM) and gray matter (GM). Furthermore, the genes enriched in the nervous system that regulate brain structure and function were expressed in spatial correlation with age-matched dMRI. This study is the first one providing high-resolution dMRI, including DTI, DKI, and NODDI models, to trace mouse brain microstructural changes in WM and GM during postnatal development. This study also highlighted the genotype-phenotype correlation of spatial transcriptomics and dMRI, which may improve our understanding of brain microstructure changes at the molecular level.

How Do CMIP6 HighResMIP Models Perform in Simulating Precipitation Extremes over East Africa?

This work assesses the ability of nine Coupled Model Intercomparison Project phase 6 (CMIP6) High-Resolution Model Intercomparison Project (HighResMIP) models and their ensemble mean to reproduce precipitation extremes over East Africa for the period 1995–2014. The model datasets are assessed against two observation datasets: CHIRPS and GPCC. The precipitation indices considered are CDD, CWD, R1mm, R10mm, R20mm, SDII, R95p, PRCPTOT, and Rx1day. The overall results show that HighResMIP models reproduce annual variability fairly well; however, certain consistent biases are found across HighResMIP models, which tend to overestimate CWD and R1mm and underestimate CDD and SDII. The HighResMIP models are ranked using the Taylor diagram and Taylor Skill Score. The results show that the models reasonably simulate indices, such as PRCPTOT, R1mm, R10mm, R95p, and CDD; however, the simulation of SDII CWD, SDII, and R20mm is generally poor. They are CMCC-CM2-VHR4, HadGEM31-MM, HadGEM3-GC31-HM, and GFDL-CM4. Conversely, MPI-ESM1-2-XR and MPI-ESM1-2-HR show remarkable performance in simulating the OND season while underestimating the MAM season. A comparative analysis demonstrates that the MME has better accuracy than the individual models in the simulation of the various indices. The findings of the present study are important to establish the ability of HighResMIP data to reproduce extreme precipitation events over East Africa and, thus, help in decision making. However, caution should be exercised in the interpretation of the findings based on individual CMIP6 models over East Africa given the overall weakness observed in reproducing mean precipitation.

A High-Precision Sub-Grid Parameterization Scheme for Clear-Sky Direct Solar Radiation in Complex Terrain—Part I: A High-Precision Fast Terrain Occlusion Algorithm

In atmospheric modeling, sub-grid parameterization is an important method for studying the topographic effects of solar radiation using high-resolution Digital Elevation Model (DEM) data. For reducing the amount of computation, some approximate methods that can lead to errors are used in existing sub-grid parameterization schemes for clear-sky direct solar radiation (SPS-CSDSR). The lack of a high-precision fast terrain occlusion algorithm (HPFTOA) remains one of the biggest constraints in this field. This study proposed an HPFTOA. It mainly uses two kinds of acceleration algorithms. One method is to use a dynamic, lossless, and fast occlusion search radius. Another way is to use the rectangular grid for calculations within the accuracy of DEM data to avoid coordinate projection conversions. The test results indicate that the HPFTOA can carry out large-scale computation based on DEM data with a resolution of 90 m. Because it rarely uses approximation algorithms and considers the curvature of the Earth, SPS-CSDSR can achieve unprecedented precision. The HPFTOA can also be used in the fields of mountain solar energy assessment, remote sensing, and telemetry, including terrain-obscuring the probe. As computer performance improves and algorithms and execution code are optimized, the application prospects will be very broad.

Projections of the Adriatic wave conditions under climate changes

Assessing the impact of climate change on wave conditions, including average and extreme waves, is vital for numerous marine-related activities, industries, coastal vulnerability, and marine habitats. Previous research, primarily on a large scale, has investigated this topic, but its relevance for marginal basins like the Adriatic Sea is limited due to the low resolution of the wave models used and atmospheric forcing. To contribute to filling in the gap, here we implemented a high-resolution model (about 2 km) for the period 1992–2050. The future wave climate is simulated for the RCP8.5 emission scenario. This model, developed within the AdriaClim project, comprises, among others, a high-resolution atmospheric downscaling, a circulation Limited Area Model and a spectral wave model. A comparison of our simulation's results with Copernicus Marine Service wave reanalysis on the historical baseline, confirms its accuracy in reproducing both average wave parameters and 95th percentile values, as well as the seasonal cycle, showing the AdriaClim model's suitability as a source to predict future wave climates in the Adriatic Sea. The projected changes suggest a slight increase in average significant wave height and mean wave period, and a more significant decrease at the 95th percentile, with a relevant variability by location and season, partially aligning with previous studies. This study highlights the potential effect of local climate change in coastal areas and the importance of developing long-term simulation with a downscaled modeling system for regional areas.

Atlantic Meridional Overturning Circulation Decline: Tipping Small Scales under Global Warming.

The Atlantic circulation is a key component of the global ocean conveyor that transports heat and nutrients worldwide. Its likely weakening due to global warming has implications for climate and ecology. However, the expected changes remain largely uncertain as low-resolution climate models currently in use do not resolve small scales. Although the large-scale circulation tends to weaken uniformly in both the low-resolution and our high-resolution climate model version, we find that the small-scale circulation in the North Atlantic changes abruptly under global warming and exhibits pronounced spatial heterogeneity. Furthermore, the future Atlantic Ocean circulation in the high-resolution model version expands in conjunction with a sea ice retreat and strengthening toward the Arctic. Finally, the cutting-edge climate model indicates sensitive shifts in the eddies and circulation on regional scales for future warming and thus provides a benchmark for next-generation climate models that can get rid of parametrizations of unresolved scales.

Comprehensive Hydrological Analysis of the Buha River Watershed with High-Resolution SHUD Modeling

This study utilizes the Simulator of Hydrologic Unstructured Domains (SHUD) model and the China Meteorological Forces Dataset (CMFD) to investigate the hydrological dynamics of the Buha River watershed, a critical tributary of Qinghai Lake, from 1979 to 2018. By integrating high-resolution terrestrial and meteorological data, the SHUD model simulates streamflow variations and other hydrological characteristics, providing valuable insights into the region’s water balance and runoff processes. Key findings reveal a consistent upward trend in precipitation and temperature over the past four decades, despite minor deviations in daily precipitation intensity and relative humidity data. The SHUD model demonstrates high accuracy on a monthly scale, with Nash–Sutcliffe Efficiency (NSE) values of 0.72 for the calibration phase and 0.61 for the validation phase. The corresponding Kling–Gupta Efficiency (KGE) values are 0.73 and 0.49, respectively, underscoring the model’s applicability for hydrological forecasting and water resource management. Notably, the annual runoff ratios for the Buha River fluctuate annually between 0.11 and 0.21, with significant changes around 2007 correlating with a shift in Qinghai Lake’s water levels. The analysis of water balance indicates a net leakage over long-term periods, with spatial alterations in leakage and replenishment along the river. Furthermore, snow accumulation, which increases with altitude, significantly contributes to streamflow during the melting season. Despite the Buha River basin’s importance, research on its hydrology remains limited due to data scarcity and minimal human activity. This study enhances the understanding of the Buha River’s hydrological processes and highlights the necessity for improved dataset accuracy and model parameter optimization in future research.

Spatiotemporal distribution of environmental microbiota around animal farms adjacent to produce fields in central coast California

This study aimed to identify different environmental microbiota in animal farms adjacent to produce fields and to understand their potential flow pattern. Soil and water samples were collected from 16 locations during the winter, spring, summer, and fall seasons. In addition, a high-resolution digital elevation model helped to create a stream network to understand the potential flow of the microbiome. Metagenomic analysis of the 16 S rRNA gene revealed that soil and water samples from the four seasons harbor diverse microbiome profiles. The phylogenetic relationship of operational taxonomic units (OTUs) is separated by a maximum of 0.6 Bray-Curtis distance. Similarly, the Principal Component Analysis (P = 0.001) demonstrated the soil and water microbiome clustering across different locations and seasons. The relative abundance of Proteobacteria, Bacteroidetes, and Firmicutes was higher in the water samples than in the soil samples. In contrast, the relative abundance of Actinobacteria and Chloroflexi was higher in the soil compared to the water samples. Soil samples in summer and water samples in spring had the highest abundance of Bacteroidetes and Firmicutes, respectively. A unique microbial community structure was found in water samples, with an increased abundance of Hydrogenophaga and Solirubrobacter. Genera that were significantly abundant at a 1% false discovery rate (FDR) among seasons and soil or water samples, include Nocardioides, Gemmatimonas, JG30-KF-CM45, Massilia, Gaiellales, Sphingomonas, KD4-96, Bacillus, Streptomyces, Gaiella, and Gemmatimonadaceae. The relative abundance of pathogenic genera, including Mycobacterium, Bacteroides, Nocardia, Clostridium, and Corynebacterium, were significantly (at 1% FDR) affected by seasons and environmental type. The elevation-based stream network model suggests the potential flow of microbiomes from the animal farm to the produce fields.

Quantifying the Variability of “Fixed-Width” Buffers on Harvested Lands in Western Oregon and Washington

Abstract In contemporary forest management, buffers of unharvested trees are left along streams to protect riparian and aquatic ecosystems. Buffer regulations often focus on specific minimum width requirements, which aid in straightforward regulation and application, but minimum widths also suggest buffered edges are uniform and contain little variability. Conceptual papers suggest that alternative buffer configurations may offer greater flexibility in landscape-level protection, increase forest complexity, and enhance aquatic and riparian biodiversity. However, before considering alternatives to fixed-width buffers, it is necessary to quantify the inherent variability in current buffer practices present on the landscape. In this study, we used aerial imagery to quantify variability of buffer widths in two hundred randomly selected recently harvested units on managed land in Oregon and Washington with both fish-bearing and non-fish-bearing sections of stream. Wider buffers on larger streams had a greater magnitude of variability, but when normalized by stream size, variation was greater in smaller streams, and overall, variation ranged from 25% to 50% of the mean width. Despite local variability, buffer widths rarely fell below 9.14 m (30 ft). The variation quantified here provides an initial measure of variability to inform future management, given emerging interest in variable retention buffers. Study Implications: In contemporary forest management, riparian and aquatic habitat protection usually relies on minimum buffer width regulations. Minimum requirements create the perception that buffered edges are uniform distances from streams containing little variability, so conceptual papers have suggested alternative buffer configurations with variable retention edges to enhance ecological benefits. However, there are several reasons why, in practice, buffer widths may vary substantially from minimum sizes within and across harvest units under current forest management, but this potential variation has not been quantified. Before considering alternative riparian management options, it is necessary to quantify and understand the inherent variability in current practices. By utilizing high-resolution aerial imagery and digital elevation models, we quantified buffer width variation. Using a set of two hundred recently harvested units, we demonstrate notable buffer width variation across managed Pacific Northwest forests. We attribute the variation in buffer widths to the presence of road crossings, tributary junctions, underlying valley slope and slope variation, and flexibility in regulations that may be overlooked in broad evaluations of strict minimum widths. Understanding fundamental information about buffer width variability provides information about current practices and provides a standard against which proposed increases in variability may be compared.

Limited Benefits of Increased Spatial Resolution for Sea Ice in HighResMIP Simulations

AbstractState‐of‐the‐art coupled climate models struggle to accurately simulate historical variability and trends of Antarctic sea ice, impacting their reliability for future projections. Increasing horizontal resolution is expected to improve the representation of coupled atmosphere‐ice‐ocean processes at high latitudes. Here, we examine the historical changes in the Antarctic sea ice area and volume in High Resolution Model Intercomparison Project simulations against satellite data sets and ocean reanalyzes to assess the benefits of increased spatial resolution. Our results do not show considerable benefits when horizontal resolutions up to 0.25° in the ocean and 25 km in the atmosphere. Limited improvements are reported in the simulated historical sea ice trends, which are nevertheless model‐dependent, and associated with the use of model components with more complex sea‐ice parameterizations. Given the high computational cost of climate‐scale simulations at high spatial resolution, we advocate prioritizing enhancements in sea‐ice physics and the interactions among model components in coupled climate simulations.

Investigating the skills of HighResMIP in capturing historical and future mean precipitation shifts over Pakistan

AbstractClimatic change over the globe due to global warming affects the characteristics of climate variables that have critical implications on large fraction of population that depends on agriculture for livelihood like Pakistan. Consequently, this study examined how high horizontal grid resolution CMIP6 models simulate the observed precipitation variability during 1981–2014 and further explored the future changes during 2017–2050 under high emission scenario SSP5‐8.5 over Pakistan region. The performances of 12 (CMIP6) High Resolution Model Inter‐comparison Project version 1.0 (hereafter; HighResMIP) GCMs and their ensemble means in reproducing the observed climate were calculated at each station in the study domain and formed the basis for deriving HighResMIP ranking. Further, the study employed Shannon's Entropy and a modified version of Criteria Importance through Inter‐Criteria Correlation (D‐CRITIC) method to build an ensemble mean from the best performing models. Evaluation of HighResMIP GCMs performance revealed that most models showed mixed signals in the region, with fewer models such as HadGEM3‐GC31‐HH, HadGEM3‐GC31‐HM and HadGEM3‐GC31‐MM showing good agreement with the observed precipitation. Overall, HighResMIP multi‐model ensemble outperforms precipitation distribution over individual models. D‐CRITIC based ensemble mean implies higher increase in precipitation than entropy approach. Future changes depict an increase in mean annual in the northern region relative to the historical period. A pronounced increase of about 16%–18% in precipitation was noted in HadGEM3‐GC31‐HH and HiRAM‐SIT‐HR. Conversely, FGOAL‐f3‐H project noteworthy reduction (21%) in precipitation in the near future (2017–2050). The projected seasonal precipitation shows upsurge pattern of 5%–28% in pre‐monsoon season, whereas the reduction in monsoon precipitation is projected to be 29%–40%. The findings of this study can help in building future climate resilience and developing strategic policies in Pakistan.

Seasonal Dynamics and Three-Dimensional Hydrographic Features of the Eastern Gulf of Thailand: Insights from High-Resolution Modeling and Field Measurements

Seasonal Dynamics and Three-Dimensional Hydrographic Features of the Eastern Gulf of Thailand: Insights from High-Resolution Modeling and Field Measurements

Composition tracking of natural gas–hydrogen mixtures in pipeline flow using high-resolution schemes

A transient pipeline flow model with gas composition tracking is solved for studying the operation of a natural gas pipeline under nonisothermal flow conditions in a hydrogen injection scenario. Two approaches to high-resolution pipeline flow modeling based on the WENO scheme are presented and compared with the implicit finite difference method. The high-resolution models are capable of capturing fast fluid transients and tracking the step changes in the composition of the transported mixture. The implicit method assumes the decoupling of the flow model components in order to enhance calculation efficiency. The validation of the composition tracking results against actual gas transmission pipeline indicates that both models exhibit good prediction performance, with normalized root mean square errors of 0.406% and 1.48%, respectively. Under nonisothermal flow conditions, the prediction response of the reduced model against a high-resolution flow model, with respect to the mass and energy linepack, is at most 3.20%.

Simulation of a former ice field with Parallel Ice Sheet Model – Snežnik study case

Abstract. In this paper, we present a reconstruction of climate conditions during the Last Glacial Maximum on a karst plateau Snežnik, which lies in Dinaric Mountains (southern Slovenia) and bears evidence of glaciation. The reconstruction merges geomorphological ice limits, classified as either clear or unclear, and a computer modelling approach based on the Parallel Ice Sheet Model (PISM). Based on extensive numerical experiments where we studied the agreements between simulated and geomorphological ice extent, we propose using a combination of a high-resolution precipitation model that accounts for orographic precipitation combined with a simple elevation-based temperature model. The geomorphological ice extent can be simulated with climate to be around 6 °C colder than the modern day and with a lower-than-modern-day amount of precipitation, which matches other state-of-the art climate reconstructions for the era. The results indicate that an orographic precipitation model is essential for the accurate simulation of the study area, with moist southern winds from the nearby Adriatic Sea having a predominant effect on the precipitation patterns. Finally, this study shows that transforming climate conditions towards wetter and warmer or drier and colder does not significantly change the conditions for glacier formation.

In silico studies of the open form of human tissue transglutaminase

Human tissue transglutaminase (tTG) is an intriguing multifunctional enzyme involved in various diseases, including celiac disease and neurological disorders. Although a number of tTG inhibitors have been developed, the molecular determinants governing ligand binding remain incomplete due to the lack of high-resolution structural data in the vicinity of its active site. In this study, we obtained the complete high-resolution model of tTG by in silico methods based on available PDB structures. We discovered significant differences in the active site architecture between our and known tTG models, revealing an additional loop which affects the ligand binding affinity. We assembled a library of new potential tTG inhibitors based on the obtained complete model of the enzyme. Our library substantially expands the spectrum of possible drug candidates targeting tTG and encompasses twelve molecular scaffolds, eleven of which are novel and exhibit higher binding affinity then already known ones, according to our in silico studies. The results of this study open new directions for structure-based drug design of tTG inhibitors, offering the complete protein model and suggesting a wide range of new compounds for further experimental validation.

Optimal site selection and potential power assessment for tidal power generation in the Seto Inland Sea, Japan, based on high-resolution ocean modelling and multicriteria analysis

In response to Japan's ambitious pursuit of carbon neutrality by 2050, this paper investigates the potential for tidal power generation in the Seto Inland Sea (SIS), Japan, utilising high-resolution ocean modelling and an analytic hierarchy process (AHP) combined with GIS-based spatial analysis. The analysis incorporates a 100 m resolution tidal current and water depth layers from the ocean model. The criteria used for evaluation were divided into main criteria, namely, proximity to existing infrastructure, wave height, and shipping density, and subcriteria, namely, distance from ports, power stations, highly populated areas, and coastlines. The identified optimal locations include the Naruto Strait, Akashi Strait, Matsushima Island, Hanaguri Strait, Funaori Strait, Taizaki Island, Kurushima Strait, Obatake Strait, and Tsuwaji Strait. With a focused analysis of the Obatake Strait in Yamaguchi Prefecture, analytical assessments of potential tidal power were conducted by considering two tidal turbines, Openhydro and Voith. The results indicate a power supply for approximately 100,000 households and a reduction of approximately 198,000 t-CO2 per year in the most optimistic scenario. In a less optimistic scenario, with the installation of only 10% of the maximum capacity, a power supply for approximately 10,000 households and a reduction of approximately 19,800 t-CO2 per year are observed. As Japan targets carbon neutrality by 2050, this research offers vital and practical insights for policymakers, energy planners, and environmentalists, identifying the Seto Inland Sea as a strategic area for tidal power development, aligning with Japan's commitment to a sustainable and resilient energy landscape.