bluuebunny/crossref_metadata_2025 huggingface dataset:
Insight into lithospheric mantle beneath Devès volcanic field recorded by xenoliths from Mt. Coupet (Massif Central, France): preliminary data
Authors: Mazurek Hubert , Matusiak-Małek Magdalena , Puziewicz Jacek , Aulbach Sonja , Ntaflos Theodoros
Published: March 2024

Mafic volcanic rocks occurring in Devès volcanic field (3.5 – 0.5 Ma) are rich in peridotitic xenoliths sampling the southern domain of the French Massif Central (FMC). The origin of the relative fertile composition of the continental lithospheric mantle (CLM) beneath FMC is widely discussed in literature and two competing major mechanisms are proposed: 1) extraction of small amounts of partial melt(s), 2) refertilization by upwelling asthenospheric melts [1, 2]. Data from xenoliths at individual localities contribute to this discussion, providing insight into the local conditions of CLM and documenting its regional variability. In this study, we present major and trace elements chemistry of peridotites from Mt. Coupet xenolith suite.Mt. Coupet peridotites (n = 24) are represented by porphyroclastic to fine–granular lherzolites, which are characterized by within-sample chemical homogeneity. Between samples, olivine Fo varies from 88.63 to 90.85. The Mg# and Al content in orthopyroxene (Opx) are: 0.90 – 0.92 and 0.12 – 0.20 a pfu, respectively. In clinopyroxene (Cpx), Mg# is 0.89 – 0.94 and Al content is 0.11 – 0.32 a pfu. In spinel, Cr# and Mg# are: 0.04 – 0.39 and 0.62 – 0.80, respectively. The REE patterns in Cpx vary, but are always above PM values (in 10 samples analyzed). Based on these patterns, three groups are recognized: (1) LREE–depleted, (2) LREE–enriched, and (3) spoon–shaped (i.e. LREE-enriched with inflection from La to Sm). Other trace elements contents, e.g. U, Th, Nb, Ta, Ti and Sr also differ between samples. Only 10 of the 24 samples are in major-element chemical equilibrium based on Opx–Cpx thermometry [3]. Thus, calculated temperatures are: 900 – 1070 ℃, suggesting sampling of a considerable depth interval if equilibrated to a conductive geotherm. No relationship between textures, geochemistry and thermometry were observed. By analogy to literature data [2, 4] we assume that the Mt. Coupet xenolith suite represents lithospheric mantle typical for the southern domain in FMC. Studies of REE and trace elements on greater number of samples from Mt. Coupet are, however, required to provide more profound interpretation which could contribute to the discussion on the structure and thermochemical evolution of CLM beneath FMC.Funding. We gratefully acknowledge funding by the project of Polish National Centre of Research 2021/41/B/ST10/00900 to JP. [1] Lenoir et al. (2000). EPSL 181, 359-375.[2] Puziewicz et al. (2020). Lithos 362–363, 105467.[3] Brey and Köhler (1990). JoP 31, 1353-1378.[4] Uenver-Thiele et al. JoP 58, No. 3, 395–422.
Studying the pre-industrial to present-day radiative forcing from wildfire aerosols using EC-Earth
Authors: Mourgela Rafaila Nikola , Boleti Eirini , Seiradakis Konstantinos , Wyser Klaus , Le Sager Phillipe , Gkouvousis Angelos , Voulgarakis Apostolos
Published: March 2024

The occurrence of more frequent and extensive wildfires is a widely discussed potential consequence of climate change, stemming from a vicious cycle of cause and effect in which wildfires are taking part. Global and regional wildfire patterns and changes are driven by climate-related factors such as land cover, heat waves, and rainfall patterns. Wildfires can, in turn, cause climate perturbations through the emissions of greenhouse gases and aerosols, and through the alteration of landscapes. For these reasons, understanding wildfires and their interactions with the Earth’s atmosphere is crucial for assessing a potentially important climate feedback.The current study focuses on the interconnection between wildfires and the atmosphere, and more precisely on the radiative effect of wildfire emissions on a global scale. To achieve this, simulations using the EC-Earth Earth System Model (ESM) were employed. More specifically, a 30-year atmosphere-only (fixed-SST) control simulation was performed for the pre-industrial period, and repeated with the wildfire aerosol emissions set to present-day values. Using the output of these simulations, we estimate the global effective radiative forcing (ERF) of wildfire-emitted aerosols from pre-industrial times to the present day. We also identify which regions experience stronger forcing from wildfire emissions, and separate the role of black carbon and organic carbon in driving this forcing. Finally, we identify mechanisms that lead to fast atmospheric adjustments following wildfire emissions, including changes in temperatures, humidity, precipitation, and clouds. This analysis contributes to the better understanding of the historical evolution of radiative forcing and the role of wildfires in the climate system. 
Establishment of a German peatland monitoring programme for climate protection - Open land (MoMoK). Monitoring network and data collection.
Authors: Frank Stefan , Dettmann Ullrich , Piayda Arndt , Tiemeyer Bärbel
Published: March 2024

Peat and other organic soils store large amounts of soil organic matter, which is highly vulnerable to drainage. Thus, drained organic soils contribute around 7% to the total German greenhouse gas (GHG) emissions and around 44% to the emissions from agriculture and agriculturally used soils, despite covering less than 7% of agricultural area in Germany. With approximately 90% of the total emissions, carbon dioxide (CO2) is the most important GHG with regards to drained organic soils. To evaluate possible GHG mitigation measures such as classical re-wetting, paludiculture or adjusted water management compared to the still widespread status quo of drainage-based peatland agriculture, an improved data set on GHG emissions, in particular CO2, and their drivers is needed. Furthermore, spatial data and upscaling methods need to be improved.To meet these needs, a long-term monitoring programme for organic soils is currently (2020-2025) being set up for open land at the Thünen Institute of Climate-Smart Agriculture. A consistent long-term monitoring of soil surface motions, representatively covering a broad range of organic soils and land use types will be combined with the repeated measurement of soil organic carbon (SOC) stocks to assess CO2 emissions using standardized and peat-specific methods. Land use types comprise grassland, arable land, paludiculture as well as unutilized re-wetted and semi-natural peatlands. At each of the envisaged approximately 150 monitoring sites important parameters such as groundwater table, vegetation and soil properties are monitored. Together with the updated map of organic soils, all collected data form the basis for improving regionalisation approaches for drivers – particularly water levels and SOC stocks – and CO2 emissions from organic soils in Germany. Here, we will present the structure of the monitoring programme, the used methods for data collection as well as the current status of site establishment.
Remotely sensed monitoring of urban greening in China from 1990-2019 to support SDG
Authors: Zhang Ping , Wu Hao , Chen Hao , Sun Qiangqiang
Published: March 2024

Understanding and accurate identification of long-term urban greening dynamics in China are critical for the sustainable urban management (Sustainable Development Goals, SDG11) and living environment of humans. But it was often challenging because a lack of continuous high-frequent data at high spatial resolution and over large time scales. Here, we proposed a framework for identifying detailed evolution processes and regime shifts in relation to urban greening based on characterization of urban greenness in continuous fields over space and time. We utilized annual, fractional estimates of urban green vegetation (GV) endmember time series from per-pixel Landsat composites, using a standardized spectral mixture Vegetation-Impervious surface-Soil (VIS) model in China over the past three decades. A Google Earth Engine platform-based non-linear model (logistic curves) was developed to derive the magnitude, timing and duration of urban greening at a per-pixel basis during these time series records. These parameters were combined to characterize heterogeneous pattern of urban greening throughout the entire China in 1990-2019. We found that the unmixed fractions of urban GV exhibited a generally consistent agreement with estimated fractions from high-spatial-resolution Google earth images (RMSE =11.30%), demonstrating its high suitability and reliability. Using detailed geographic process model with logistic trajectory fitting curves, our findings indicate that the ratio of the area with significant greening trends during 1990-2019 account for nearly 3.0% to the overall urbanized area in China. These greening changes are predominantly distributed in eastern coastal region and northeast Plain. In particular, the Jing-jin-ji, Ha-Chang and Middle-Southern Liaoning are the top three urban agglomerations contributing the greening for this period. Notably, Urumqi, the capital city in north-western China, has the highest ratio of the area with significant increasing GV relative to the urbanized space of the entire city, due to great achievements of urban green construction (i.e., the newly established parks or street plants), and relatively low greenness before 1990. Based on the derived change parameters, our results also reveal the economic impacts on the timing of urban greening are prevalent. For instance, the timing of turning points for urban greening in three major highly-urbanized and developed urban agglomerations, that is, the Jing-jin-ji, Yangtze River Delta, Pearl River Delta showed 2-3 years earlier than other regions. Compared to the state-of-the-art approaches, this framework has the potential to detect high-frequent urban greening process as continuous spatial and time fields with multi-dimensional thematic, thus could help support sustainable urban management practices.
Fault irregularity of recent large strike slip earthquakes revealed by satellite imagery
Authors: Yu Chen , Han Bingquan , Song Chuang , Li Zhenhong , Aoki Yosuke
Published: March 2024

The geometric complexity of strike-slip faults, such as stepovers, bends and branches, is a pivotal indicator of segmented fault rupture. These features act as barriers to the activity of strike-slip faults, leading to uneven stress distribution along the fault zone, thereby influencing the initiation, propagation, and termination of earthquake ruptures.The East Anatolian Fault (EAF) is a significant sinistral strike-slip fault, connecting with the North Anatolian Fault (NAF) to the north and the Dead Sea Fault (DSF) to the south. Located in southeastern Turkey, it plays a crucial role in accommodating the relative motion between the northward-moving Arabian Plate and the westward-moving Anatolian Block. Despite the relative quietude of the EAF since the beginning of the 20th century, historical seismic activity indicates its potential to generate devastating earthquakes, as evidenced by a series of relatively large earthquakes occurring between 1822 and 1905. On January 24, 2020, the Pütürge segment at the northeastern end of the EAF experienced the Mw6.8 Elaziğ earthquake (2020 event). Subsequently, on February 6, 2023, the southwestern segment of the EAF witnessed the Turkey–Syria Earthquake Sequence (2023 event). The consecutive occurrence of these two seismic events has provided an opportunity to investigate the tectonic activity characteristics and seismic triggering relationships of the EAF.In this study, we take the two events that occurred on the EAF in 2020 and 2023 as the time nodes and take the EAF as the research object. Utilizing InSAR technology, the research investigated the deformation during seismic cycles (interseismic, coseismic, and postseismic) based on Sentinel-1 radar data. We computed interseismic deformation velocities from 2015 to 2020 and displacement time series from February 2020 to February 2023, as well as from February 2023 to September 2023. Subsequently, this study extensively considered the geometric complexity of faults and established an elastic triangular dislocation model. Based on this model, we derived the interseismic fault slip distribution for the EAF from 2015 to 2020, as well as coseismic and postseismic fault slip distributions for the 2020 and 2023 events. The results indicate that: 1) The slip rate along the EAF exhibits a decreasing trend from the northeastern end (5 mm/yr) to the southwestern end (2 mm/yr); 2) The interseismic slip deficits of the EAF correlate well with the coseismic fault slip distribution of the 2020 and 2023 events; 3) The postseismic fault slip following the 2020 and 2023 events primarily occurs at coseismic slip deficit areas.
Improvements in rain gauge design and measurements to minimise under-catch errors
Authors: Dutton Mark , Balsamo Domenico
Published: March 2024

Precipitation measurements provide historic and near real-time data for Met Services and ground truth references for modelling and forecasting.  Current methods suffer from well-known under-catch problems1.  These are caused by wind effect2 on the gauge, out-splash, evaporation, and internal tipping bucket (‘counting’) errors.  Thereby causing water-balance errors for Hydrology scientists.  Good gauge design and correct siting can minimise these errors but not eliminate them.Over 10 years of research, into the best aerodynamic shape for a precipitation gauge, was carried out to minimize out-splash and maximize catch3.  Comparison field work1 and Computational Fluid Dynamic4 (CFD) research was undertaken between standard straight-sided, ‘chimney’ shaped, aerodynamic shaped and pit-installed (out of the wind) gauges.  This research demonstrated that it may be possible to quantify under-catch using gauge rim-based wind data, drop-size and drop-type information.  Field comparison between the “new instrument” and pit gauge will be needed.  Once quantified at source, it can then be used to accurately correct live data.This new instrument uses ultrasonic wind sensors and Doppler-Shift measuring techniques to obtain wind versus rainfall catch data.  Also using optical and/or impact sensing techniques we can measure the individual drop size and count the drops involved in a rain event.  By adding weighing technology to the tipping bucket design and improving calibration methods, we can improve resolution and detect evaporation losses.  Also power efficient and controlled heating to allow the inclusion of solid precipitation measurements.  Then finally use machine learning (ML) techniques to correct the errors.Therefore, the aim of this project is to design a simple to use intelligent instrument to minimise and possibly eliminate under-catch measurement errors balancing out the water budget.  Allow installation of the instruments at ground and raised levels without increase in errors caused predominately by the wind.  Create near real-time and historic field precipitation data, both corrected and non-corrected to be use by Met Services and Hydrology modelling scientists.References 1. Sevruk, B. Methods of correction for systematic error in point precipitation measurement for operational use, World Meteorological Organization - Operational Hydrology, Report No. 21, 1982.2. Pollock, M. D., et al. Quantifying and mitigating wind induced undercatch in rainfall measurements, Water Resources Research, 54, 2018.3. Strangeways, Ian. Improving precipitation measurement. International Journal of Climatology. 24. 1443 - 1460. 10.1002/joc.1075, 2004.4. Colli, M., et al.  A Computational Fluid-Dynamics Assessment of the Improved Performance of Aerodynamic Rain Gauges. Water Resources Research. 54. 10.1002/2017WR020549, 2018.
A critical look at the reported errors of geodetic products
Authors: Karbon Maria , Belda Santiago , Acuze Esther , Moreira Mariana , Escapa Alberto , Ferrándiz Jose Manuel
Published: March 2024

Geodesy provides the highest precision and accuracy International Terrestrial Reference Frame, International Celestial Reference Frame and Earth Orientation Parameters. However, in our processing chain, we take mathematical shortcuts, drop higher order polynomials, assume linearity where it is no longer valid, omit correlations and colored noise, and use outdated models. If intra- or inter-technique combinations are done, they happen at different stages, and different methods are employed. The datums applied to the reference frames are inherited over decades, accumulating all uncertainties of their predecessors. Dependencies between the reference frames and the EOP are largely ignored. Finally we inflate our errors by a predefined factor, to somehow account for all of that.This is just a short list of the inconsistencies within our main products. Even for a specialist it will be almost impossible to list them all, for a mere end-user its an insurmountable task. In this work we will investigate these central products of geodesy, focusing mainly on the errors, their derivation, and significance from a user perspective. We look exemplarily at various official IVS and IAG products, and their reported errors. We investigate how transparent their nature and derivation is for the final user, if the parameters in question follow our physical understanding of the matter, and what insight we might gain from them.
Trends in Warm Season Mesoscale Convective Systems OverAsia in 2001–202
Authors: Guo Yuanjing , Fu Qiang , Leung L. Ruby , Na Ying , Lu Riyu
Published: March 2024

Mesoscale convective systems (MCSs) frequently occur over Asia during the warm season, often producing intense precipitation with associated socioeconomic impacts. Here we reveal significant trends in MCS occurrence frequency and related precipitation in Asia during the warm season (March–September) in 2001–2020, using a tracking method that combines cloud and precipitation criteria with high-resolution satellite data from the Global Precipitation Measurement mission. To examine whether there are differences between MCSs of different scales, both meso-α scales (MαCSs) and meso-β scales (MβCSs), with horizontal scales of 200–2,000 km and 20–200 km, are tracked. The distribution pattern of frequency and related precipitation of both MαCSs and MβCSs are quite similar and manifest positive trends over East Asia (EA) and Northeast Asia, and negative trend over Southeast Asia (SEA). The MCS precipitation trend contributes significantly to total precipitation trend, with MαCSs contributing the most. Our analysis indicates the trend in lower-tropospheric water vapor flux convergence has a similar spatial pattern to the MCS frequency and related precipitation trend. Based on an atmospheric moisture flux decomposition analysis, the water vapor flux convergence trend can largely be explained by the change in horizontal wind convergence, while the specific humidity trend driven largely by temperature change plays a minor role. The trend in wind convergence in EA and SEA is possibly related to the evident trend in the lower-tropospheric anticyclone over the western North Pacific and SEA, which might be due to the relatively stronger warming in the Indian Ocean during the past two decades.
Exploring the 2019 Ridgecrest seismic data with unsupervised deep learning 
Authors: Mouaoued Sarah , Campillo Michel , Seydoux Léonard
Published: March 2024

We analyze the seismic data continuously recorded in the vicinity of the Mw7.4 2019 Ridgecrest earthquake with an unsupervised deep learning method proposed by Seydoux et al. (2020), in search of seismic signatures of physical signatures of the earthquake preparation phase. We downloaded data from the 3 different stations B918, with a 100 Hz sampling frequency, SRT and CLC with a 40 Hz sampling frequency. Using a scattering network combined with an independent component analysis, we define stable waveform features and cluster the continuous signals extracted from a sliding window before proposing cluster-based interpretations of the seismic signals. We also further discuss our results with external datasets such as independently-obtained seismicity catalogs in the area. We also investigate a manifold-learning-based representation (UMAP) of the data in 2D from the scattering network. According to our first results merged with a catalog analysis we are able to separate various events from the noise and identify several types of seismicity and noises. 
Origin of the trends in Antarctic sea ice extent over the period 1958-2023 
Authors: Goosse Hugues , Dalaiden Quentin , Francis Feba , Fogt Ryan
Published: March 2024

The Antarctic sea ice extent has displayed several regime shifts over the past 65 years. Consistent lines of evidence indicate a decline in Antarctic sea ice extent from 1958 to 1978, which precedes the availability of continuous satellite observations. Subsequently, there was a significant sea ice expansion over 1979–2015 before the large drop observed in the past few years that led to record lows. The origin of those shifts and contrasting trends are analyzed here using a new reconstruction of atmospheric temperature, sea level pressure and sea ice extent spanning the period 1958-2023. We employ a data assimilation method that combines long simulations as well as large ensembles performed with climate models with long-term station-based records of temperature and sea level pressure at mid and high latitudes of the Southern Hemisphere. The reconstruction is thus totally independent from sea ice extent observations that are used as validation, showing the good performance of the method. In contrast to previous reconstructions and estimates, reconstructing simultaneously the atmospheric circulation, temperature, and sea ice extent ensures compatibility among the variables and thus a more straightforward dynamical interpretation. Our reconstruction indicates that no change in the reconstructed atmospheric circulation could be directly related to the regime shifts in sea ice extent trends but the covariance structure of the temperature strongly varies across periods, with more homogenous temperature anomalies for the early and recent periods and a more complex spatial pattern for the years 1979–2015. This might suggest a time-dependent contribution of the ocean, which will be further analyzed in a simulation performed with the NEMO model driven by the ERA5 reanalysis.
Assessing snow and glacier melt contributions using conceptual modelling approach in the Upper Indus Basin
Authors: Malla Mani Kanta , Arya Dhyan Singh
Published: March 2024

The Hindukush-Karakoram-Himalaya (HKH) region, a vital water source for over 800 million people across the Indus, Ganges, and Brahmaputra river basins, relies heavily on the continuous freshwater supply derived from its extensive snow and ice reservoirs. Estimating snow and glacier melt in this complex hydrological setting poses challenges, particularly concerning the intricate interactions among various hydrological processes. Conceptual models have experienced exponential growth in hydrological modelling due to their cost-effectiveness in computational requirements while maintaining the accuracy of simulated streamflow. Snow and glacial melt modules are generally integrated into the hydrological model to accurately represent the intricate interactions among snow, glaciers, and precipitation in mountainous catchments. The present study focused on incorporating snow and glacier modules using a degree-day factor approach into a four-parameter conceptual Hydrological model GR4J. The model will be calibrated and validated in the Upper Indus basin's glaciated sub-basins, Astore and Hunza. The study will use the ERA5 Reanalysis-based precipitation, temperature for meteorological forcing and GloFAS discharge data used as observed streamflow. The results obtained will help understand the applicability of conceptual hydrological models in capturing hydrological processes and the potentiality of the reanalysis data in the absence of observed data and will give an idea about the snow and glacier melt contributions. Looking ahead, the study will be further helpful in studying the impacts of climate change in assessing future water availability under different scenarios.
CME-CME-CIR interaction - comparison of "homologous" events from two different solar rotations 
Authors: Temmer Manuela , Dumbovic Mateja , Martinic Karmen , Cappello Greta M. , Remeshan Akshay K. , Milosic Daniel , Koller Florian , Calogovic Jasa , Matkovic Filip
Published: March 2024

Solar cycle 25 might be close to its expected peak and related activity is at a high. In 2023 many complex events were observed remotely and measured in-situ. Some of them even caused aurorae in low latitudes, repeatedly confirming that the interaction between multiple CMEs, as well as CIRs, lead to extreme conditions in near-Earth space. We study a set of “homologous” events on the Sun, where several CMEs interacted and additionally interfered by a high-speed stream from a coronal hole. The two sets of events involve the same active regions and coronal hole but are separated by a full solar rotation. We point out the complexity for each set of events and aim to understand how the global magnetic field configuration leads to a general similarity in the activation of the CME source regions. The studied in-situ measurements are connected to the solar surface observations and interpreted by processes caused due to shock-magnetic obstacle interaction.
Peatland ecohydrology and redox potential
Authors: Koskinen Markku , Marttunen Sofia , Korrensalo Aino , Lohila Annalea , Li Xuefei , Zak Dominik , Vránova Valerie , Ojanen Paavo , Minkkinen Kari , Mäkiranta Päivi , Aurela Mika , Virtanen Tarmo , Kreyling Jürgen , Brendel Meline , Pihlatie Mari , Knorr Klaus-Holger , Laiho Raija
Published: March 2024

Anoxic conditions in soils cause microbial populations dependent on oxidation of organic carbon to subsitute alternate terminal electron acceptors (TEA) for oxygen to facilitate the reactions they acquire energy with. Most commonly available alternate TEAs include nitrate, manganese, iron(III) and sulphate, in descending energetic yield. Oxidation by reducing these TEAs offers the microbes more energy per reaction than methanogenesis, and thus they are in principle preferred over it. Different moieties in organic matter itself can also act as TEAs and support non-methanogenic anaerobic decomposition, the most widely known of these being quinones.Each redox pair (comprising the oxidised and reduced species of a TEA) in principle supports a known electron activity (pe) in solution when they are present in roughly equal activities in the solution. Pe can be measured by an electrode and compared to a reference electrode comprising of a known redox pair, thus creating an electric potential known as redox potential (Eh, mV). Continuous Eh measurements are emerging as a tool for ecosystem monitoring, particularly on peatlands and wetlands. Because redox conditions are intrinsically linked to environmental outcomes such as carbon dioxide, nitrous oxide and methane fluxes and phosphorus and iron leaching, there are great hopes that measurements and modelling of redox conditions will improve our understanding of and ability to predict processes in peatlands under sub- and anoxic conditions, and to model the changes in these processes under different management scenarios, such as drainage, restoration, continuous-cover forestry or paludiculture.Here we present long-term Eh measurements from several boreal peatlands of varying ecohydrological characteristics (ombrotrophic pine bog-mesoeutrophic flark fen) and drainage state (pristine, forestry drained, agricultural). We see the differences in the Eh profiles and their dynamics caused by the dominant water table level (WTL) and the nutrient status, but also that WTL is not sufficient to predict temporal changes in redox conditions. We further explore possible connections between Eh measurements and microform- and ecosystem-level flux measurements.We also present results of a laboratory incubation experiment showing that iron is the most important mineral TEA in a range of boreal peatland types.
Land subsidence model inversion with the structural noise of tectonic motion and unknown groundwater abstraction
Authors: Aichi Masaatsu
Published: March 2024

The recent progresses in the monitoring techniques for land subsidence such as InSAR or GNSS provide the huge datasets available for the calibration of numerical models. However, the observed land surface displacement possibly includes the structural noise caused by the tectonic motion or land subsidence caused by unknown groundwater abstraction while the land subsidence model usually considers the effect only from the known groundwater abstraction. Then, the land subsidence model inversion is not straightforward because such structural noises may affect the inversion results if the observed land surface displacement is directly used for the calibration target.The author proposes a new evaluation function based on the rotation energy of the estimated structural noise to avoid the interference from the structural noise in the inversion procedure. By replacing the typical evaluation function such as root mean square error with the proposed evaluation function, the inversion procedure can focus only on the reproducibility of the land subsidence caused by the known groundwater abstraction.The performance of the proposed method was tested by the several synthetic land subsidence data composed of the displacement caused by the known and unknown groundwater abstraction calculated by the numerical model with the assumed physical parameter distribution, the typical tectonic motion, and the random noise. The proposed method successfully separated the land subsidence caused by the known groundwater abstraction and other components, and successfully reproduced the model parameters used in the numerical model to make synthetic land subsidence data.
Investigating the life-cycle of convective clouds from 4D observational data
Authors: Brüning Sarah , Tost Holger
Published: March 2024

Convective clouds play a crucial role for understanding the Earth’s climate. Current advancements of remote sensing instruments allow us to obtain valuable information on the spatio-temporal dynamics of convective clouds on multiple scales. Nevertheless, a continuous coverage of high-resolved 4D observational data to investigate the 3D properties of rapidly developing convective clouds is generally not available.In this study, we leverage 4D radar reflectivities (in dBZ) derived from the extrapolation of passive and active remote sensing sensors with machine learning to close this gap. Using data with a spatial resolution of 3 km and a temporal resolution of 15 minutes, we receive a continuous perspective on the evolution of the cloud vertical column along the different stages of the cloud life-cycle. For this purpose, we apply an object-based algorithm to detect the centroid of convective cores and their anvil at each time step. Based on these centroids, we extract the 3D cloud field and track the horizontal and vertical movement through space and time. Afterwards, we filter all tracks using the vertical extension and maximum reflectivity of the associated cloud field to exclude erroneous features.Here, we present an evaluation of the algorithm and its ability to investigate the 4D spatio-temporal properties of convective clouds. We set out to compare convective systems of different sizes over both oceans and continents to analyze the impact of varying environmental conditions on the cloud vertical motions along the cloud life-cycle.
Integrating High-Resolution Tracer Data with Soil Moisture and Precipitation Dynamics to Characterize Streamflow Age Distribution in a Headwater Catchment
Authors: Turk Hatice , Hrachowitz Markus , Schulz Karsten , Strauss Peter , Blöschl Günter , Stumpp Christine , Stockinger Michael
Published: March 2024

The partitioning of rainfall into different hydrological components, such as lateral subsurface flow,  overland flow, and soil water storage, is essential for understanding and predicting streamflow responses and contaminant transport. This study investigates flow processes within shallow sub-surface layers and streamflow responses in an agricultural headwater catchment by utilizing high-resolution data of oxygen (δ18O) and hydrogen (δ2H) stable isotopes of water. We used weekly data from grab and event streamflow samples (ranging from 15 minutes to 2 hours based on the anticipated event length) in a tracer-based transport model to estimate water travel times and examine how catchment characteristics and climate factors influence storage water release and travel time distributions with a StorAge Selection function approach. We tested two conditions for the activation of preferential flow paths: i) based on soil moisture only, and ii) based on both soil moisture and precipitation intensity. The results show that calibrating a tracer-based transport model, coupled with soil moisture and precipitation intensity data, improve the tracer simulation of quick responses in stream flow (increase in Nash-Sutcliffe Efficiency from 0.21 to 0.51) and can greatly enhance the accuracy of streamflow age distribution estimates in headwater catchment compared to using soil moisture data only. Particularly in summer months with intense precipitation, the catchment shows dominant infiltration-excess overland flow processes resulting in young water to reach to the stream. The results also demonstrate that during wet conditions, a significant portion of event water bypasses through fast ﬂow paths. These results highlight the importance of tracer data in understanding the interplay between catchment characteristics, rainfall intensity, and water storage release.
The COllaborative Carbon Column Observing Network (COCCON) quality management.
Authors: Alberti Carlos , Hase Frank , Dubravica Darko , Dehn Angelika , Castracane Paolo
Published: March 2024

Year after year, the effects of climate change are more dramatic and evident, and it is no longer possible to hide them, which requires immediate action against anthropogenic emissions of greenhouse gases (GHGs) in Earth’s atmosphere, mainly carbon dioxide (CO2) and methane (CH4). The scientific community plays an important role in continuously developing and improving current instrumentation and methods, which enable high-resolution measurements to monitor, track, quantify, and verify the concentration and emissions of GHGs in the atmosphere.Measuring GHGs with high accuracy in the atmosphere is challenging, but achieving measurements with global coverage is even more demanding, and only satellites can provide such data sets. However, they require ground-based column-integrating measurements for validation. For this purpose, the Total Carbon Column Observing Network (TCCON) was created; however, due to its high operational costs and the need for trained expertise on-site, the number of sites is limited (~ 26). Moreover, these stations are stationary, so performing observations of selected GHG source regions with several spectrometers is impossible. The COllaborative Carbon Column Observing Network (COCCON) was initiated to overcome these limitations and to supplement the existing TCCON stations. The standard instrument used by COCCON is the portable FTIR spectrometer EM27/SUN, developed by KIT in cooperation with Bruker Optics from 2011 onwards. Although this instrument has a lower spectral resolution (0.5 cm-1) in comparison to the TCCON instrument (0.002 cm-1), it delivers XCO2, XCH4, XH2O, and XCO with sufficient quality to complement TCCON satellite validation efforts.COCCON data are tied to the trace gas scale as realized by the TCCON reference. COCOON ensures a high degree of internal consistency across the participating spectrometers, defines common standards for data processing, and performs quality assurance checks on individual spectrometers to ensure the quality of the network. The services of COCCON are enabled by ESA support. Meanwhile, one hundred twenty spectrometers have been optimized and characterized by the centralized testing facility operated at KIT, and many more units are expected to be commissioned in the months ahead. This contribution presents the current status of the activities of the central QA/QC facility: methods, results, and foreseen improvements.
Alkalization of seawater enhances calcification of large benthic foraminifers.
Authors: Kinoshita Shunichi , Hashimoto Yuri , Kuroyanagi Azumi , Suzuki Atsushi
Published: March 2024

There is concern that the increasing pCO2 following the Industrial Revolution Period might lead to ocean acidification, which could affect calcifying organisms in the oceans. Recently, negative emission technology has been attracting attention as an effective countermeasure for greenhouse gas emissions. In the ocean, ocean alkalinization technology is proposed to neutralize acidified oceans and enhance the absorption capacity of CO2 in the oceans. The potential effectiveness of ocean alkalinization technology is also suggested by the history of the Earth. During the Cretaceous period, when pCO2 is interpreted >1,000 ppm, calcifying organisms thrived in the Cretaceous oceans. It is hypothesized that it was due to the total alkalinity (TA) of the seawater being maintained higher, thereby kept the calcium carbonate saturation state at necessary. In this study, we examined this hypothesis as well as attempted to predict the effects of the application of current alkalinization techniques in the ocean on calcifying organisms.Clonal populations of large benthic foraminifers were cultured in highly alkalinized seawater under high pCO2 conditions, and amounts of calcification (weight and volume) were measured (Group 1: high TA and high pCO2). Specimens taken from same clonal population were kept in modern surface seawater (Group 2: low TA and low pCO2) as a control treatment. The same experiments were also conducted as Group 3 (low TA and high pCO2) to simulate future ocean acidification conditions, and as Group 4 (high TA and low pCO2) to simulate alkalinized ocean under a low pCO2 environment. It was showed significant differences in the amount of calcification in each of the Groups after three months cultivation. The amount of calcification in Group 1 was almost the same as that in the control treatment, confirming the possibility of maintaining the growth of calcifying organisms by alkalinization. Calcification amount in Group 3 was the smallest among all groups, indicating that future ocean acidification may inhibit calcification of large benthic foraminifers. In addition, the calcification rate was the greatest in Group 4, it is indicated that ocean alkalinization may enhance the calcification of the organisms. Finally, these results suggest that the calcium carbonate saturation state of seawater is an important parameter for calcification.
Use of deep learning and a partial convolutional neural network to gap-fill a long term time series of NO2 columns from satellite impacted by cloud
Authors: ma wanli , Coe Hugh , Topping David , Zheng Zhonghua , Song Congbo , Zhang Hao
Published: March 2024

Satellite monitoring plays a significant role in monitoring nitrogen dioxide (NO2) concentrations in the atmospheric column, but it is often affected by clouds and ice and snow surface. This leads to much missing data. Deep learning with Partial Convolutional Neural Network (PCNN) is adept at handling incomplete or missing data in image processing by focusing only on the known pixels during convolution, thus making approach ideal for tasks such as image restoration, denoising, and enhancing resolution. It is therefore important to reduce such data gaps.. Under cloudy skies, ground-level NO2 often tends to be higher. Clouds are typically associated with low pressure and increased wind speeds in mid-latitudes, leading to enhanced dispersion of pollutant. However, low cloud often occurs during periods of high pressure when boundary layer heights are lower and air pollutants are trapped closer to the ground. Additionally, clouds intensify the Surface Sensible Heat Flux, contributing to the urban heat island effect and potentially increasing NO2 concentrations. On the other hand, clouds decrease Surface Net Solar Radiation, which might mitigate NO2 photolysis. It is therefore likely that NO2 concentrations close to the surface during cloudy conditions will not necessarily be well represented by satellite derived NO2 columns in clear sky conditions.. It becomes necessary to recalibrate satellite-derived data to reflect actual meteorological conditions. In this work we separate out ground-level data from an urban network across Paris, France, into two categories: those with contemporaneous TROPOMI and those without. Each category is then analyzed with the weather conditions at that time. This analysis helps estimate the variance in NO2 concentrations due to cloud presence. Subsequently, the determined percentage difference, indicative of the cloud cover's impact, is applied to the NO2 estimates provided by the PCNN model. This adjustment not only strengthens the data's coverage but also its reliability, reducing the biases in the original satellite data resulting from clear sky viewing only and are therefore a closer representation of the urban atmospheric pollution. This approach, combining technical precision with contextual sensitivity, improves the use of satellite data as a tool for understanding and interpreting urban pollution.
Upper ocean biogeochemical response of Arabian Sea to extremely severe cyclonic storm “Biparjoy”
Authors: Makhan Prashant Kumar , Swain Debadatta
Published: March 2024

Recent warming in the tropical oceans has increased tropical cyclone (TC) activity globally. The Arabian Sea (AS) in the northern Indian Ocean is such a basin with rising TC activity. TCs have the potential to favor the short-term productivity of the ocean through extensive mixing of the upper ocean, bringing about temporary variations in the biogeochemistry. The current study investigates the upper ocean biogeochemical response of AS to a TC utilizing data sets from six Bio-Argos, multi-satellite observations, and biogeochemical models from Copernicus Marine Services. The extremely severe cyclonic storm “Biparjoy”, one of the long-duration TCs in the basin was chosen as a case study. It formed during the onset of the Indian summer monsoon in June 2023 and persisted for eleven days (6th to 16th June 2023). Profiles obtained from the Bio-Argos around the storm track showed extensive cooling (~4 °C) in the upper surface. The strong TC also resulted in significant vertical mixing which brought cold, nutrient-rich water to the upper surface. Dissolved oxygen concentration was observed to have decreased during the cyclone, compared to pre- and post-cyclone periods. Eventually, an increased chlorophyll concentration, persisting for more than a week, was observed along the track in the sub-surface and surface waters after the passage of the storm. Biogeochemical model data was used to analyze the intricate variations in the upper ocean biogeochemistry of AS during the storm. Further analysis for a better understanding of the upper ocean response of the AS to cyclonic storms in recent years is in progress.
 Influence of Basement High and Detachment on the Kinematics of a Fold-and-Thrust Belt in the Central South Yellow Sea Basin with Implications for Hydrocarbon Preservation: Insights from Analog Modeling
Authors: Zhang Penghui , Fu Yilin , Yan Bing
Published: March 2024

This study investigates a fold-and-thrust belt (FTB) beneath the South Yellow Sea Basin, a noteworthy petroleum exploration target, featuring a basement high and a detachment layer. In the central basin, magnetic anomalies reveal the development of the basement high. Seismic reflection data, in conjunction with drilling information, disclose the presence of the Lower Silurian Gaojiabian Formation, exceeding ~500 m, acting as a low-cohesion detachment layer. However, the impact of these features on regional structures and the resulting hydrocarbon preservation conditions remains uncertain. This study explores the kinematic characteristics and deformation localization associated with the basement high and intermediate detachment using four sandbox models and particle velocity analysis within the FTB framework. Model 1, the reference, utilized pure quartz sand without either feature. Model 2 examined the role of the intermediate detachment using glass microbeads, revealing a limited effect in generating typical thin-skinned FTB. Model 3 considered the basement high and found that it strongly influenced the deformation regime of the wedge. Model 4 examined both features and suggested their combined influence on FTB deformation processes. In Model 2, lacking a pre-existing basement high, the intermediate detachment did not contribute to FTB deformation. In Model 3, lacking an intermediate detachment, deformation propagated along the surface of the basement high upon reaching its edge. In Model 4, shortening propagated upward along the edge of the basement high and then into the intermediate detachment, producing comparable structural geometry to the prototype, including both thick- and thin-skinned FTBs in nature. The results indicate that in the central South Yellow Sea Basin, structural layers between the basement high and detachment are likely to experience weak deformation; thus, favorable hydrocarbon preservation conditions can be anticipated in this region. This study holds significant importance in guiding future petroleum exploration efforts in the central South Yellow Sea Basin.
A data driven modeling framework to correlate the flash-floods potential with the Modified Land cover Characteristics in a changing climate: a study over Krishna River basin, India
Authors: Sarkar Sumana , Ramesh Kalidhasan
Published: March 2024

Flash-floods are recurrent natural hazards producing substantial impacts to the human communities. The increase in the frequency and magnitude of flash-floods is associated with the last decades of climate change at a global scale as well as changes affecting the Land Use/Land cover (LULC) characteristics. We employ Machine Learning technniques (Random Forest (RF), Multi layer Perceptron based Artificial Neural Network (MLP-ANN) and Geographical Information System (GIS) framework to deduce the spatial patterns of relationship between the flash-flood potential changes across the study area and the changes in the modified LULC during 2000-2019. High resolution Digital Elevation Model (DEM) and daily precipitation from AgERA5 will be utilized to detect the spatial variability of flash floods through the modified Founier Index. Identifying the probable changes in specific roughness coefficient (through the modified LULC), a geospatial risk based (flash flood potential of high, moderate and low categories) indices will be developed to assess future hydrological hazards.
 