bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance Simulation and Preliminary Measurements of a Raman Lidar for the Retrieval of CO2 Atmospheric Profiles
Authors: Di Paolantonio Marco , Di Girolamo Paolo , Dionisi Davide , Di Bernardino Annalisa , Di Iorio Tatiana , Franco Noemi , Giuliano Giovanni , Iannarelli Anna Maria , Liberti Gian Luigi , Summa Donato
Published: February 2023

Within the frame of the project CONCERNING (COmpact RamaN lidar for Atmospheric CO2 and ThERmodyNamic ProfilING), we investigated the feasibility and the limits of a ground-based Raman lidar system dedicated to the measurement of CO2 profiles. The performance of the lidar system was evaluated through a set of numerical simulations. The possibility of exploiting both CO2 Raman lines of the ν1:2ν2 resonance was explored. An accurate quantification of the contribution of the Raman O2 lines on the signal and other (e.g., aerosol, absorbing gases) disturbance sources was carried out. The signal integration over the vertical and over time required to reach a useful signal to noise ratio both in day-time and night-time needed for a quantitative analysis of carbon dioxide sources and sinks was evaluated. The above objectives were obtained developing an instrument simulator software consisting of a radiative transfer model able to simulate, in a spectrally resolved manner, all laser light interaction mechanisms with atmospheric constituents, a consistent background signal, and all the devices present in the considered Raman lidar experimental setup. The results indicate that the simulated lidar system, provided to have a low overlap height, could perform measurements on the low troposphere (<1 km) gradients (1-5 ppm) with sufficient precision both in day-time and night-time with an integration time of 1-3 h and a vertical resolution of 75 m. The selected Raman lidar setup is currently being tested and we aim to present preliminary results during the conference.
Temporal analysis of wildfire emissions in the Northwest of Spain using ESA CCI data
Authors: Oliva Patricia , Quishpe César
Published: February 2023

The Northwest of the Iberian Peninsula is one of the European regions with the highest frequency of forest fires. However, in the last decade fires in this region have burned larger areas and later in the fire season. Assessing the damage caused by fire and the pollutants released in the burning process is important to understand the effects on ecosystems and the carbon cycle, the recurrence of fires, and the effect on human health. In this work, we performed the estimation of emissions released in Galicia (Northwest Spain) in the last six years combining existing ESA CCI products. To quantify the area burned, we used the products from the Burned Area Algorithm developed within the Fire Climate Change Initiative (FireCCI) project. Then, the characterization and quantification of the total biomass were obtained from the Biomass CCI project at 100 m resolution by extracting the mean biomass by vegetation type from CORINE Land cover 2018. The burning efficiency factor was fitted using burn severity estimates from the dNBR calculation on the Sentinel-2 data. The emissions factors were selected from the literature. Our results show that during the last few years, there is a positive trend of annual emissions in Galicia. The sporadic maximums were registered in the years 2017 and 2022 when the climatic conditions aggravated the fire behaviour. In addition, Galicia is the region of Spain that registers the highest average estimates of emissions from fires since a high percentage of the affected area is occupied by pine and eucalyptus forests. These emissions contribute to a drastic decrease in air quality influencing the climate and affecting public health. Finally, we verified that adapting the burning efficiency factors to the specific conditions of the affected ecosystem generates more precise emission estimates.
Estimation of persistence on glacial lakes in tropical Andes mountain-range with 2000-2020 period LANDSAT series images
Authors: Pozo Jesús , Celmi Gladis , Fernandez Juan , Curo Yadira , Mejía Mayra , Robles Danny , Castañeda Alberto
Published: February 2023

Peruvian mountain-range glaciers are characterized by the presence of numerous lakes of glacial origin, whose dynamics show a great temporal-spatial variability due to factors such as glacial melting and precipitation of different types, seasons, and intensities, engaging also river flow, usually for the benefit of population settlements. Therefore, it is important to determine its continuity to consider them permanent resources of water. Previously, the evaluation of this parameter was made traditionally, by looking at optical satellite imagery. However, this process ends up being too long and complicated as there are up to 3000 lakes in some mountain ranges.
We propose a methodology with the objective of estimating the temporal persistence of glacial lakes mainly performed in Google Earth Engine, convenient for the flexibility, data-size issues, and quick computations of statistical approach. This process is based on LANDSAT 7 and 8 normalized difference water index (NDWI) time series data products, comprised of 252 images of the Ampato glacier mountain-range across the calendar years 2000-2020. Initially, we extract the NDWI values for each polygon -from the INAIGEM 2020 glacial lake Inventory- and image and apply different NDWI thresholds and ways to mean them. Finally, we get a representative conversion of the value to mark their existence and do the percentage calculations over the evaluation period.
NDWI threshold of 0.05 and median values were chosen to obey previous evaluations and have tight results. We observe that between 86 and 99% of images were available for the 518 polygons of this area, indicating suitability to support subsequent conclusions. The final persistence values vary between 50% and 99% for lakes greater than 5000 m², while lesser lakes present values between 25 and 75% of persistence during the evaluation period, corresponding to weather modulating factors in a shorter scale such as seasonality, ENSO events, extreme precipitation, etc. The presented investigation could have relevant applications from water management, ecology, tourism, to climate investigation, as a way to sophisticate the processes of a more exact and specific glacial lake Inventory in Peru or other parts of the sphere.
 
Multidecadal Modulations of ENSO influence on Tropical Atlantic cyclogenesis
Authors: Losada Teresa , Badiane Adama , Rodríguez-Fonseca Belén , González-Alemán Juan Jesús , Dieng Abdou Lahat , Sall Saidou Moustapha
Published: February 2023

The impact of ENSO (El Niño Southern Oscillation) events on the development of tropical cyclones in the Eastern Tropical North Atlantic is highlighted, focusing on decadal variations of the interannual relationship at the Senegalese coast, which is the main cyclone development region (MDR). The enhancement of North Atlantic tropical cyclones by the Atlantic Niño and the Pacific El Niño Southern Oscillation (ENSO) is diagnosed. An approach based on  composites of anomalous positive or negative years in terms of cyclone activity is used. Based on 20yr-correlations between the number of cyclones that are born in the MDR and ENSO index, we have selected two different periods of study (period1 (P1): 1954-1973; and period2 (P2): 1986-2005). Results show an increase in the SST impact in cyclone generation from P1 to P2 and intensification of cyclones number over the Senegalese coasts. Likewise, the spatial distribution of the dynamic and thermodynamic parameters used in this composite study shows strong variations between the two periods. Our findings suggest that decadal changes in climatological conditions have a significant effect on the MDR. Additionally, the changes in the interannual signal appear to be related to the concomitant action of interannual SST anomalies over the whole tropical basins.  
Identifying pyroregions in mainland Portugal with clustering methods using GIS
Authors: Barbosa Bruno , Gonçalves Ana , Oliveira Sandra , Rocha Jorge , Caetano Mario
Published: February 2023

Wildfires occur unevenly in the territory, driven by different biophysical and social factors. Understanding the spatial and temporal distribution of wildfires can help identifying common characteristics and/or dissimilarities between regions. In this research, we use specific fire metrics, from historical fire data, to explore the possibility to identify groups of municipalities based on their pyrosimilarities. We apply a clustering model based on the method k means to identify and compare groups of municipalities (defining pyroregions) of mainland Portugal (n=277), using fire data from the last 22 years (between 2000 and 2021). The fire metrics used were: (a) cumulative percentage of total burned area, (b) cumulative percentage of burned area in the summer months, (c) mean annual number of fires and (d) GINI index applied for burned area over time. We used tools available in Geographic Information Systems (ArcGIS Pro) linked with python programming, to apply the cluster method and map the results. Our preliminary results divided the mainland in 5 clusters. CL1 (n=66) is seen in the west coast and is characterised by a burned area concentrated in a few years (high Gini index), but the fires occur mainly outside the summer months; CL2 (n=50) cover municipalities in the northeast and is characterised by a high mean number of fires dispersed over the years (low GINI index); CL3 (n=26) located in the central Portugal has a high percentage of cumulative burned area throughout the years, but with low number of fires, concentrated in time; CL4 (n=63) covers the municipalities in the southwest and south and shows a low mean number of fires but  these occur mainly in the summer season and, CL5 (n=55) appears throughout the country, but is more concentrated in the west and is characterised by intermediate values in all analysed metrics. The extreme wildfires that occurred in 2017 in Portugal influence the clustering; for example, CL1 occurs on the west central coast, where the consolidated maritime pine forest has burned in October 2017, outside the summer months. The next steps of this analysis are: (i) apply other clustering methods to compare with these clusters identified with k means and their characteristics and (ii) analyse the explanatory variables that influence these fire patterns. This work was funded by FCT, I.P.: BB and AG in the scope of PhD projects [2022.12095.BD], [2020.07651.BD], SO under the contract ‘2020.03873.CEECIND′, Centre for Geographical Studies—University of Lisbon and FCT under Grant number [UIDB/00295/2020 + UIDP/ 00295/2020].
A comparison of methods for determining the number of classes in unsupervised classification of climate models
Authors: Boland Emma , Jones Dani , Atkinson Erin
Published: February 2023

Unsupervised classification is becoming an increasingly common method to objectively identify coherent structures within both observed and modelled climate data. However, the user must choose the number of classes to fit in advance. Typically, a combination of statistical methods and expertise is used to choose the appropriate number of classes for a given study, however it may not be possible to identify a single ‘optimal’ number of classes. In thiswork we present a heuristic method for determining the number of classes unambiguously for modelled data where more than one ensemble member is available. This method requires robustness in the class definition between simulated ensembles of the system of interest. For demonstration, we apply this to the clustering of Southern Ocean potential temperatures in a CMIP6 climate model, and compare with other common criteria such as Bayesian Information Criterion (BIC) and the Silhouette Score.
Climate change unbalances biogeochemical cycles of C, N and P in Mediterranean forests
Authors: Villa-Sanabria Elena , Gallardo Antonio , Gutiérrez Eduardo , Serrano María S. , Homet Pablo , Gómez-Aparicio Lorena
Published: February 2023

Mediterranean forests are considered to be highly vulnerable ecosystems to climate change because they are water- and nutrient-limited. However, experimental evidence of the combined effects of increasing drought and warming on biogeochemical cycles in these ecosystems is still extremely scarce. To fill this gap, we analyzed during four consecutive years the impacts of rainfall reduction (RE; ambient vs. ~30% reduction in rainfall), soil warming (W; ambient vs. ~ 1 °C increase) and their interaction on biogeochemical cycling of C, N and P in Mediterranean forests. Rainfall exclusion translated into quick significant reductions of soil organic matter (SOM), enzymatic activity (β-glucosidase, urease and acid phosphatase activities) and nutrient availability (ammonium, nitrate and phosphorus) one year after the application of the treatments. These effects were consistent over time. Warming acted synergistically with rainfall reduction to further decrease C-related variables (SOM and β-glucosidase). SOM reduction in forest soils might be the result of delayed leaf senescence as a drought tolerant trait in the forest trees. Warming also had direct positive effects on N- and P- related variables that partially counteracted the negative effects of rainfall reduction on these variables. Overall, our results showed that the different components of climate change (drought and warming) have complex direct and interactive effects on biogeochemical cycles of Mediterranean forests that differ among soil nutrients (C, N, P). Consequently, drought and warming might cause an unbalance in natural biogeochemical cycles of Mediterranean forests, with important consequences for ecosystem functioning.
Hydrological upheaval across multiple early Eocene hyperthermal events in the north African arid zone
Authors: Fokkema Chris , Agterhuis Tobias , Kelly Liam , Mannucci Agnese , Theijse Basse , Bialik Or , Bijl Peter , Brinkhuis Henk , Dickens Gerald , Galeotti Simone , Peterse Francien , Sluijs Appy
Published: February 2023

Rapid climatic and carbon cycle upheavals in the early Eocene have been of strong interest for the past decades. Multiple of these events represent global warming events (i.e. hyperthermals), including the Paleocene Eocene Thermal Maximum (PETM; 56 Ma), but global data coverage is still too limited to fully resolve the spatial patterns of climate, ecosystems and hydrology for the other hyperthermals. This is particularly due to the lack of continuous continental margin sequences suitable for high-resolution paleoclimate reconstructions.We present high-resolution, multi-proxy records of climatic and environmental changes across multiple hyperthermals from Core RH-323, Northern Negev Desert, Israel. Lower Eocene sediments, dominantly orbitally paced alternations of marls and chalk, were deposited in the Tethys Ocean at a latitude of ~15º N, on the northward dipping slope of the presumably dry northern bound of the African continent. They provide a unique opportunity to capture tropical climate variability and continental-hydrological response to hyperthermals. We reconstruct regional variability of (sub)surface temperature, plankton ecology and continental hydrology by TEX86 paleothermometry, bulk carbonate isotope ratios, magnetic susceptibility, bulk-XRF and dinoflagellate cyst (dinocyst) assemblages.We identify various hyperthermal events, including the PETM, ETM2 and ETM3, based on combined chemo- and biostratigraphy. During the PETM, TEX86-based temperatures indicate a warming of 3­–4 ºC, coinciding with a high abundance of representatives of the classic warm water dinocyst genus Apectodinium. The PETM is marked by a thin marl-rich interval at the onset, followed by a carbonate-rich interval during the body, suggesting very different hydrological forcing of siliciclastic input than recorded at mid-latitude sites. We interpret this to reflect strong seasonality (possibly monsoon like) with periods of intense precipitation followed by prolonged drought. Interestingly, subsequent smaller hyperthermals seem to predominantly coincide with increased siliciclastic content, thus representing episodes of increased (seasonal) precipitation.
Numerical modelling of mudflows impacting settlements: a case study
Authors: Leonardi Alessandro , La Porta Giulia , Pirulli Marina
Published: February 2023

Mudflows are common natural hazards, often originating from the liquefaction of shallow landslides triggered by rainfall. The numerical back-analysis of past events is key in projecting the application of numerical models towards forward analysis. However, the complex multi-physics nature of the problem hampers the development of comprehensive frameworks. Notwithstanding, calibrated numerical models, able to simulate all aspects of the problem (triggering and runout) can still be valuable tools for aiding the design of countermeasures. This can currently only happen if calibration is performed on the specific site, or on sites with very similar geomorphological and geological characteristics.In this presentation, the application of a coupled triggering and runout model is explored. Two study cases of well-known events occurring in Southern Italy are presented. A pseudo-plastic model is used for the post-triggering rheology. The resolution of the runout simulation is down to the level of the specific exposed element (houses, roads). This allows for an ad-hoc assessment of risk on key pieces of infrastructure. The results reveal interesting aspects related to how the complex topographic features of settlements challenge the traditional workflow for back-analysis. In particular, the channelization of flows within the settlement itself leads to an overestimation of hazard, unless care is placed to resolve the triggering phase down to the sub-basin scale.   REFERENCESNg, C. W. W., Leonardi, A., Majeed, U., Pirulli, M., & Choi, C. E. (2023). A Physical and Numerical Investigation of Flow–Barrier Interaction for the Design of a Multiple-Barrier System. Journal of Geotechnical and Geoenvironmental Engineering, 149(1). https://doi.org/10.1061/(asce)gt.1943-5606.0002932Pasqua, A., Leonardi, A., & Pirulli, M. (2022). Coupling Depth-Averaged and 3D numerical models for the simulation of granular flows. Computers and Geotechnics, January, 104879. https://doi.org/10.1016/j.compgeo.2022.104879
Exploration of microbial-mineral interactions with the Noachian Martian breccia composed of ~4.5 Gyr old crustal materials from Mars
Authors: Milojevic Tetyana , Koelbl Denise , Bruner Robert , Morgan Matthew L.
Published: February 2023

In the past year we have been witnessing several important missions to Mars, including Mars 2020 Perseverance rover that landed to Jezero Crater to search for signs of ancient life. Multiple lines of evidence indicate an active hydrogeological history of Mars and chemolithoautotrophy-suited environments within its Noachian terrains. As a result, one of the primary aims of Mars missions is to search for signs of ancient life and collect a suite of samples to be returned to Earth via a Mars Sample Return mission. Being a few steps away from retrieving and returning the first Mars samples, we need to gain extensive knowledge how to access their potential biogenicity. In this connection, a valuable source of information can be extracted from microbial fingerprints of chemolithotrophic life based on Martian materials. Chemolithoautotrophy is the most ancient microbial form of life, which enables the transition of energy from a stone to the energy of a living entity. In our project, we investigate interactions of a wide variety of chemolithoautotrophs with Martian mineral materials (Martian meteorites and regolith simulants). Our recent research on the genuine Noachian Martian breccia “Black Beauty” permitted visualization and nanometer-scale imaging of microbial life designed and cultivated on Martian materials(1). Here we report on laboratory-scaled microbially assisted chemolithoautotrophic biotransformation(1) of the Noachian Martian breccia Northwest Africa (NWA) 7034 composed of ancient (~4.5 Gyr old) crustal materials from Mars. Nanoanalytical hyperspectral analysis provides clues for the trafficking and distribution of meteorite inorganic constituents in the microbial cell(1). We decipher biomineralization patterns associated with the biotransformation and reveal microbial nanometer-sized lithologies located inside the cell and on its outer surface layer(1). These investigations provide an opportunity to trace the putative bioalteration processes of the Martian crust and to assess the potential biogenicity of Martian materials. Our study on the Noachian Martian breccia composed of ~4.5 Gyr old crustal materials from Mars, delivered a prototype of microbial life experimentally designed on a real Martian material(1). This life of a pure Martian design is a rich source of Mars relevant biosignatures. 1. Milojevic, T., Albu, M., Kölbl, D. et al. Chemolithotrophy on the Noachian Martian breccia NWA 7034 via experimental microbial biotransformation. Commun Earth Environ 2, 39 (2021). https://doi.org/10.1038/s43247-021-00105-x
Subseasonal forecasting of temperature and precipitation over India using a machine learning approach
Authors: Jadhav Prajwal , Op Sreejith , Thelliyil Sabeerali
Published: February 2023

Subseasonal forecasting is forecasting of the weather parameters, mainly temperature and precipitation, two weeks to two months in advance. Sub-seasonal variability accounts for a substantial portion of the summer rainfall over India. Prediction of sub-seasonal climate is of immense societal importance in agriculture planning, water management, emergency planning, etc. Using various weather parameters and ECMWF dynamical model forecasts as predictors, this study tries to investigate the weekly forecast of temperature and precipitation at 2-week, 3-week, and 4-week forecast horizon over India using a computationally inexpensive machine learning model-MultiLLR, which prunes out irrelevant predictors and integrates remaining predictors linearly for each target date. The model’s predictions calculated over the years 2019-2022 are as skilful as IMD’s Extended Range Forecasting System (ERFS). The skill of the model is better in the coastal region than in the inland part of India.
A comparison of GRACE/-FO and altimetry derived regional hydrological mass balance: example of the Caspian Sea
Authors: Gauer Louis-Marie , Chanard Kristel , Fleitout Luce
Published: February 2023

Monitoring the evolution of freshwater water resources worldwide is challenging yet essential to prevent severe water scarcity. In that regard, the Gravity Recovery and Climate Experiment and Follow-On satellite missions (GRACE/-FO) have successfully proven to complement in-situ hydrological observations by giving access to variations in continental water storage through measurements of the Earth’s gravity field since 2002.However, the measurement noise and errors inherent to the GRACE/-FO missions design and data processing cause estimation bias and spatial leakage that limit applications to large-scale hydrological basins and complicate geophysical interpretation. Moreover, missing observations during and between the missions, and in particular the 11-month gap between missions make if difficult to monitor long-term mass variations. To overcome these issues, we build a procedure, based on a spectral analysis by Multichannel – Singular Spectrum Analysis (M-SSA), that uses spatio-temporal correlations of the GRACE/-FO time series to fill data gaps and reduce a significant portion of the distinctive noise pattern while maintaining the best possible spatial resolution. This processing reveals hydrological signals that are less well or not resolved by other processing strategies.We seek validation of the GRACE/-FO M-SSA solution by comparison with independent estimates of regional hydrological mass balance. We first develop a new forward modeling approach to derive regional hydrological balance that accounts for potential bias caused by necessary filtering of the GRACE/-FO data. In particular, we account for signal leakage of a known source while estimating regional mass balance.The Caspian Sea, due to its relative isolation, large size and significant mass variations over the past decades,  offers an interesting example to validate mass balance derived from GRACE/-FO measurements. We compare space-gravity derived hydrological mass balance with independent altimetry data, accounting for thermosteric effects using in-situ data and ground deformation caused by mass redistribution, and show consistent results on the long term variations. However, we also discuss potential causes of a significant discrepancy in seasonal amplitude.
Co-Evolution of Structure, Heterogeneity, and Function During Pedogenesis
Authors: Totsche Kai Uwe ,   MAD Soil Consortium
Published: February 2023

Besides roots and earthworms, microorganisms play a fundamental role in the formation, stabilization, and turnover of “structure” in natural soil. While the former two are also important “bioturbators”, the role of microorganisms evolves from their particle enmeshment (e.g., fungal hyphae) and colonization and alteration of the fluid exposed surfaces in soil, the biogeochemical interfaces. The interdependences and feedbacks of soil structure dynamics and the activity of soil biota affect the fluid flow and the transport of matter and information in dynamic ways by altering the spatial assignment of soil materials, but also by changing their mechanical and surface properties as well as the hydraulic and pneumatic characteristics of the dynamics void-network system. These alterations and structural reorganizations occur at spatial scales already at the submicron scales with yet far-reaching consequences for soil functions at the pedon scale and beyond. Understanding the coevolution of structure and heterogeneity and the insight to which extent this coevolution impacts soil properties and functions is progressively evolving, allowing unraveling of their implications for soil quality and the soil-based ecosystem services. This presentation compiles the current understanding of the interplay of abiotic and biotic forcings for structural dynamics and its consequences on the processes and functions in soils. It builds on synthesizing the evidence, findings, and outcomes of field surveys, computer simulations, and experimental pedogenesis.
Modeling wildfire dynamics and future projections under climate change scenarios: the FLAM approach
Authors: Krasovskiy Andrey , Corning Shelby , Boere Esther , Khabarov Nikolay , Cimdins Reinis , Kraxner Florian
Published: February 2023

We will present approaches to modeling wildfire dynamics using the IIASA’s wildFire cLimate impacts and Adaptation Model (FLAM). FLAM operates with a daily time step and uses mechanistic algorithms to parametrize the impacts of climate, human activities, and fuel availability on wildfire probabilities, frequencies, and burned areas. Validation on historical data and future projections under climate change scenarios will be discussed at various scales and resolutions.  We will present results for the following case-studies: (i) projections of global burned areas driven by climate change scenarios until 2100; (ii) modeling burned areas and adaptation options in Europe; (iii) modeling burned areas and their feedback to land-use change in Indonesia with a particular emphasis on extreme fires due the impacts of El Niño southern oscillation using historical data and the delta approach for future scenarios; (iv) regional variability and driving forces behind forest fires in Sweden. Our results support international analyses that, irrespective of changes in management, it is evident that climate change is very likely to increase the frequency and impact of wildland fires in the coming decades.
Investigation of Boundary Layer Aerosol Processes with Turbulence-Resolving Lidar
Authors: Alnayef Osama , Behrendt Andreas , Lange Diego , Späth Florian , Wulfmeyer Volker , Abbas Syed
Published: February 2023

Our research focuses on the vertical transport of aerosol particles, and the properties of these aerosol particles in dependence on relative humidity. For this, we use the synergy of Raman and Doppler lidar systems operated during the Land-Atmosphere Feedback Experiment (LAFE) (see https://www.arm.gov/research/campaigns/sgp2017lafe).We will present our first results of investigating the aerosol flux. For this, we use the aerosols backscatter coefficient and vertical wind velocity collected with Raman lidar and Doppler lidar.The LAFE project was executed at the Southern Great Plains (SGP) site of the Atmospheric Radiation Measurement (ARM) program in August 2017 in the USA.  In addition, data collected at the Land-Atmosphere Feedback Observatory (LAFO) at the University of Hohenheim, Germany is used. Results of the combined aerosol backscatter measurements with water-vapor and temperature lidar measurements to detail insights into the relative humidity dependencies on the growth of aerosols.
Space-time multivariate techniques: a comparative analysis on environmental data
Authors: Cappello Claudia , De Iaco Sandra , Palma Monica , Muehlmann Christoph , Nordhausen Klaus
Published: February 2023

In environmental sciences, it is common to collect and analyze spatio-temporal multivariate data concerning several variables which are measured in time over a spatial domain. The spatio-temporal data are usually sparce in space, due to the high cost of the equipment, and temporal dense since the required variables are regularly sampled in time.In the literature different methods have been proposed for the analysis of such spatio-temporal data which exhibit a correlation in space and time as well as in-between variables. Among them it is worth recalling the generalization of Blind Source Separation technique for multivariate space-time random field (stBSS) and the space-time linear coregionalization model (ST-LCM). These methods are useful to simplify the spatio-temporal multivariate analysis since by a linear transformation of the original observations only the independent components which exhibit a spatio-temporal correlation are retained (lower than the number of observed variables) and modelled.In this paper a multivariate study regarding seven environmental variables (evapotranspiration level, minimum and maximum temperature, minimum and maximum humidity, wind speed and precipitation) measured between 2000 and 2022 in Veneto region (Italy) will be proposed.  Both the stBSS and the joint diagonalization of the empirical covariance matrix approach will be used to identify the hidden components, and properly chosen spatio-temporal models will be fitted to the latent components. Note that for the first approach a BSS model for the multivariate random field will be assumed, whereas for second one a space-time linear coregionalization model (ST-LCM) for the independent components will be fitted to the matrix-valued covariance function estimated for seven relevant environmental variables.Finally, the fitted models have been used to predict evapotranspiration levels and a comparison of the values obtained by using the two different techniques will be provided.
Ocean color through satellite lidars: the COLOR project
Authors: Dionisi Davide , Bucci Simone , Cesarini Claudia , Colella Simone , D'Alimonte Davide , Di Ciolo Lorenzo , Di Girolamo Paolo , Di Paolantonio Marco , Franco Noemi , Gostinicchi Giacomo , Kajiyama Tamito , Liberti Gian Luigi , Organelli Emanuele , Santoleri Rosalia
Published: February 2023

During the last decade, new applications exploiting data from satellite borne lidar measurements demonstrated that these sensors can give valuable information about ocean optical properties [1,2,3]. Within this framework, COLOR (CDOM-proxy retrieval from aeOLus ObseRvations) consisted in a 18-month feasibility study approved by ESA within the Aeolus+ Innovation program. COLOR had the objective to evaluate and document the feasibility of deriving an in-water prototype product from the analysis of the signal acquired by the ESA Earth Explorer Wind Mission ADM-Aeolus (Atmospheric Dynamics Mission). In particular, COLOR project focused on the AEOLUS potential retrieval of the diffuse attenuation coefficient for downwelling irradiance (Kd [m-1]) from the ocean sub-surface backscattered component of the 355 nm received lidar signal.The core activity of the project was the characterization of the signal from the AEOLUS ground bin through two parallel and strongly interacting activities: a) Radiative transfer numerical modelling; b) AEOLUS data analysis. The main result of the project will be presented together with the discussion of the perspectives of the satellite lidar missions dedicated to ocean color. [1]  M. J. Behrenfeld et al. (2019). Global satellite-observed daily vertical migrations of ocean animals», Nature, vol. 576, n. 7786, Art. n. 7786, dic. 2019, doi: 10.1038/s41586-019-1796-9.[2] Jamet, C., Ibrahim, A., Ahmad, Z., Angelini, F., Babin, M., Behrenfeld, M. J., et al. (2019). Going beyond standard ocean color observations: lidar and polarimetry. Front. Mar. Sci. 6:251. doi: 10.3389/fmars.2019.00251[3]  D. Dionisi, V. E. Brando, G. Volpe, S. Colella, e R. Santoleri (2020). Seasonal distributions of ocean particulate optical properties from spaceborne lidar measurements in Mediterranean and Black sea», Remote Sens. Environ., vol. 247, pag. 111889, set. 2020, doi: 10.1016/j.rse.2020.111889.
Moisture sources of summer precipitation over easternChina during 1979–2009: A Lagrangian transient simulation
Authors: Hu Qin
Published: February 2023

Using the Lagrangian model FLEXPART and the quantitative method WaterSip, moisture sources of summer (June–July–August) precipitation overeastern China are investigated for the period 1979–2009 in this study. It is found that the Indochinese Peninsula plus southern China, the South ChinaSea, the northwestern Pacific Ocean, the Asian continent, and the Bay of Bengal are the major moisture sources in our results, and the moisture from eastern China, the Arabian Sea, and the Indian subcontinent also has minor contributions. Note that the contribution of the oceanic sources substantially surpasses that of the continental sources, and the contributions of sources exhibit interannual variations during 1979–2009, especially in the Indochinese Peninsula plus southern China, the South China Sea, the northwestern Pacific Ocean, the Asian continent, and the Bay of Bengal. Moreover, moisture sources have evident monthly variations and seasonal cycle features, which are responsible for supplying moisture to precipitating over eastern China in the different monsoonal periods. In addition, the major moisture sources for different intensities of precipitation over eastern China vary considerably; for light and moderate precipitation, a great amount of moisture originates from the local and northwestern continental regions and eastern oceanic regions adjacent to eastern China, while more moisture comes from southwestern oceanic sources and the surrounding continental regions of them for heavy precipitation.
Influence of wind-wave/swell interactions on the air-water momentum flux
Authors: Buckley Marc , Tenhaus Janina , Matt Silvia , Savelyev Ivan
Published: February 2023

The ocean surface is, more often than not, riddled with locally generated, growing wind-waves interacting with remotely generated swells. In moderate to high wind speeds, these complex interactions may strongly influence the occurrence of wave breaking as well as airflow separation events, which, in turn, control air-sea fluxes of momentum and scalars.We present laboratory measurements of air and water dynamics in the vicinity of wind-modulated mechanically generated waves, at a 10 m fetch, using Particle Image Velocimetry. Using flow vorticity and turbulence estimates above and below the waves, we are able to quantify airflow separation and wave breaking events.We observe modulations of the airflow by locally generated wind waves, including small sheltering events downwind of sharp wave crests. We will discuss the influence of local vs peak wind-wave conditions (e.g., wave age, slope), on wind-wave momentum and energy flux mechanisms.
Metop ASCAT soil moisture trends: Mitigating the effects of long-term land cover changes
Authors: Hahn Sebastian , Wagner Wolfgang , Alves Oto , Muguda Sanjeevamurthy Pavan , Vreugdenhil Mariette , Melzer Thomas
Published: February 2023

The Satellite Application Facility on Support to Operational Hydrology and Water Management (H SAF) is providing surface soil moisture data record products based on a change detection technique applied to the Advanced Scatterometer (ASCAT) on-board the series of Metop satellites. At the moment two of the three Metop satellites are still operational (Metop-B and Metop-C), while the first satellite (Metop-A), launched in 2007, completed its mission in November 2021. Thus, the latest ASCAT surface soil moisture data record product covers a period of more than 15 years (2007-2022).First analysis of long-term trends in the H SAF ASCAT surface soil moisture data record product have indicated strong anomalies for specific regions around the globe. Trend similarities have been found compared to other data sets such as soil moisture information provided by the ERA5 land surface model. However, certain soil moisture anomaly pattern did not match spatially or in their trend direction. It has been observed that land cover changes contribute to the overall ASCAT backscatter signal with a noticeable impact on the retrieved soil moisture information especially over longer time periods (>10 years). Most notably are areas with slowly changing ground conditions such as growing cities or regions suffering deforestation.In this study we want to present a new method to mitigate the effects of long-term land cover changes based on a regular re-calibration of the dry and wet backscatter reference. It is important to address and remove this non-climatic effects from the surface soil moisture data record products to correctly detect and monitor climate extremes.
Stress transfer between volcanic dyke and seismic activity accompanying the 2021 and 2022 Fagradalsfjall eruptions, Iceland
Authors: Fischer Tomáš , Vlček Josef , Hrubcová Pavla , Doubravová Jana , Ágústsdóttir Þorbjörg , Guðnason Egill Árni
Published: February 2023

The 2021 Fagradalsfjall volcanic eruption in the Reykjanes Peninsula, Iceland, was preceded by an intensive earthquake swarm lasting one month. At the end of July 2022, a new intensive earthquake swarm occurred, which was followed on 3 August 2022 by a new effusive flow at the extension of the 2021 effusive fissure. We analyze seismic data of both swarms recorded by the Reykjanet local seismic network to trace the processes leading to the eruption to understand the relation between seismic activity and magma accumulation.Precise relocations of the 2021 swarm show two hypocenter clusters in the depth range of 1-6 km. The WSW-ENE trending cluster of the 2021 and previous swarms show a stepover of ∼1 km offset, forming a pull-apart basin structure at the intersection with the dyke. This is the place where the 2021 eruption occurred, suggesting that magma erupted at the place of crustal weakening. The pre-eruption seismic activity in 2021 started with a ML 5.3 earthquake of 24 February 2021, which triggered the aftershocks on the oblique plate boundary and in the magmatic dyke area, in both cases in an area of elevated Coulomb stress. The co-existence of seismic and magmatic activity suggests that the past seismic activity weakened the crust in the eruption site area, where magma accumulated. The following ML 5.3 earthquake of 24 February 2021 also triggered the seismic swarm and likely perturbed the magma pocket which led to the six-months lasting eruption that started on 19 March.The relocations of the July 2022 earthquake swarm show that only the northern part of the dyke-related swarm was activated compared to the 2021 swarm and both eruptions are located at the southern tip of the 2022 swarm. We compare the space-time and statistical characteristics of the 24 February 2021 aftershock sequence and of the 2021 and 2022 swarms to relate them to the different expected origin of these seismic activities.
Application of a deep learning framework to explore transfer learning for dune mapping across regions
Authors: Nowatzki Maike , Thomas David , Bailey Richard
Published: February 2023

Dune mapping is a traditional task for aeolian geomorphologists and has made use of satellite imagery since the 1970s (Breed & Grow, 1979). Labour-intensive manual mapping approaches are increasingly substituted by (semi-)automated ones that apply progressive Machine Learning algorithms (Zheng et al., 2022). Advanced techniques such as neural networks enable the creation of powerful computational models to automatically map dune fields (Shumack et al., 2020; Rubanenko et al., 2021). Globally available satellite imagery datasets and the progression of computational infrastructure and power facilitate the operation of increasingly elaborate models and their application to spatially extensive regions. A lack of training and validation datasets for such dune mapping models and the subjective and time-consuming nature of their creation, however, remains a challenge.We present a framework that uses Deep Learning and different types of satellite imagery to map dune crests. It comprises automated modules to (1) retrieve and pre-process training and prediction data, (2) train a neural network (U-Net; Ronneberger et al., 2015), and (3) identify dune crests in unlabelled target areas applying the trained model. The framework has shown good performance mapping linear dunefields in the Kalahari Desert using a small training and validation dataset (130 labelled 960mx960m tiles).Addressing the lack of global training data, we use our model to explore the possibilities of transfer learning and the universality of regional training datasets. In our main case study, we assess whether a model trained on satellite data of linear dunes in the Kalahari can be applied to map linear dunes in regions containing morphologically similar dunes in the Australian deserts. Breed, C. S., & Grow, T. (1979). Morphology and distribution of dunes in sand seas observed by remote sensing. A study of global sand seas, 1052, 253-302.Ronneberger, O., Fischer, P., & Brox, T. (2015, October). U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention (pp. 234-241). Springer, Cham.Rubanenko, L., Pérez-López, S., Schull, J., & Lapôtre, M. G. (2021). Automatic Detection and Segmentation of Barchan Dunes on Mars and Earth Using a Convolutional Neural Network. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 9364-9371.Shumack, S., Hesse, P., & Farebrother, W. (2020). Deep learning for dune pattern mapping with the AW3D30 global surface model. Earth Surface Processes and Landforms, 45(11), 2417-2431.Zheng, Z., Du, S., Taubenböck, H., & Zhang, X. (2022). Remote sensing techniques in the investigation of aeolian sand dunes: A review of recent advances. Remote Sensing of Environment, 271, 112913.
First Simultaneous Lidar Observations of Thermosphere-Ionosphere Sporadic Ni and Na (TISNi and TISNa) Layers (∼105–120 km) Over Beijing (40.42°N, 116.02°E)
Authors: Wu Fuju , Chu Xinzhao , Du Lifang , Jiao Jing , Zheng Haoran , Xun Yuchang , Feng Wuhu , Plane John M. C. , Yang Guotao
Published: February 2023

We report the first simultaneous lidar observations of thermosphere-ionosphere sporadic nickel and Na (TISNi and TISNa) layers in altitudes ∼105–120 km over Yanqing (40.42°N, 116.02°E), Beijing. From two years of data spanning April 2019 to April 2020 and July 2020 to June 2021, TISNi layers in May and June possess high densities with a maximum of 818 cm −3 on 17 May 2021, exceeding the density of main layer peak (∼85 km) by ∼4 times. They correlate with strong sporadic E layers observed nearby. TISNa layers occur at similar altitudes as TISNi with spatial-temporal correlation coefficients of ∼1. The enrichment of Ni in TISNi is evident as the [TISNi]/[TISNa] column abundance ratios are ∼1, about 10 times the main layer [Ni]/[Na] ratios. These results are largely explained by neutralization of converged Ni + and Na + ions via recombination with electrons. Calculations show direct recombination dominating over dissociative recombination above ∼105 km.
A cumulant analysis of ocean waves fluctuations over the global ocean, using CFOSAT data
Authors: Benbelkacem Amine , Schmitt François , Huang Yongxiang
Published: February 2023

The China France Oceanography Satellite (CFOSAT) was launched in October, 2018 and records over the oceans the wind field as well as the ocean waves. We consider here the ocean wave data, which are given through the significant wave height (Hs). We analyse along-track fluctuations of $Hs$ by considering its fluctuations of the form $y_r = \Delta_r Hs = Hs(x+r)-Hs(x) $, with values of the spatial scale $r$ between 12.5 km and a global and large scale of 2000 km. For this we consider a cumulant approach: we estimate the cumulant generating function (of $\log y_r$) $\Psi(q) = \log $. This function is considered in a log-stable framework, where its development is non-analytical of the form $\Psi(q)= C_1 q + C_{\alpha} q^{\alpha}$, where $C_1$ is the first cumulant ($C_1 = < \log y_r>$), $0< \alpha \leq 2$ is the non-analycity parameter and $C_{\alpha}$ a parameter. The analysis is done by partionning the global ocean into several oceans: Indian ocean, South and North Pacific, South and North Atlantic. The statistics of the three parameters are considered over the scale $r$ and for each ocean. This provides a global view of the significant wave height multi-scale fluctuations and is complementary to a previous analysis done using Fourier spectral analysis (Gao et al 2021).
Fourier Transform Infrared data analysis to analyse the environmental impact of coal mine waste
Authors: Kamps Oscar , Maghsoudi Fardad , Desta Feven , Buxton Mike
Published: February 2023

In the current energy transition, many governments have made plans to reduce energy production by coal. Therefore, Germany has set the ambition to close coal mines in 2030 (Wehrmann et al., 2021). The many years of mining produced a large amount of mine waste, used as a landfill. In the TRIM4mining project, a consortium of industry and academia investigate the environmental impact of coal mine waste. The samples used for this study are from the Schleenhein and Profen lignite mines in East Germany. Throughout the project, various samples were collected of specific lithologies in the mine, lithology mixtures and two drill cores of 50 meters drilled on the mine waste dump.This study focuses on testing the applicability of Fourier Transform Infrared Spectroscopy (FTIR) for analysing lignite waste material samples. Here, the data is discussed regarding the liquefaction potential, acidification potential, secondary recovery, and heavy metal concentration. An additional abstract is submitted to present the result on how FTIR data can be used for regression modelling with the aim to integrate geochemistry and spectral infrared data for mine waste characterization.  Preliminary results have shown clear spectral features that can be used to distinguish coal, silt, sand and clay material. Every meter of the waste material is measured to allow a core logging analysis. Besides the interpretation of the coal, clay, sand and silt fraction, various data analysis techniques are applied to interpret smaller variations in the FTIR data, that could be of interest to the environmental impact of coal mine waste.