bluuebunny/crossref_metadata_2025 huggingface dataset:
STAR-ESDM: A New Bias Correction Method for High-Resolution Station- and Grid-Based Climate Projections
Authors: Hayhoe Katharine , Stoner Anne Marie , Scott-Fleming Ian , Ibrahim Hamed
Published: March 2021

The Seasonal Trends and Analysis of Residuals (STAR) Empirical-Statistical Downscaling Model (ESDM) is a new bias correction and downscaling method that employs a signal processing approach to decompose observed and model-simulated temperature and precipitation into long-term trends, static and dynamic annual climatologies, and day-to-day variability. It then individually bias-corrects each signal, using a nonparametric Kernel Density Estimation function for the daily anomalies, before reassembling into a coherent time series.

Comparing the performance of this method in bias-correcting daily temperature and precipitation relative to 25km high-resolution dynamical global model simulations shows significant improvement over commonly-used ESDMs in North America for high and low quantiles of the distribution and overall minimal bias acceptable for all but the most extreme precipitation amounts (beyond the 99.9th quantile of wet days) and for temperature at very high elevations during peak historical snowmelt months.

STAR-ESDM is a MATLAB-based code that minimizes computational demand to enable rapid bias-correction and spatial downscaling of multiple datasets. Here, we describe new CMIP5 and CMIP6-based datasets of daily maximum and minimum temperature and daily precipitation for nearly 10,000 weather stations across North and Central America, as well as gridded datasets for the contiguous U.S., Canada, and globally. In 2022, we plan to extend the station-based downscaling globally as well, since point-source projections can be of use in assessment of climate impacts in many fields, from urban health to water supply.

The projections have furthermore been translated into a series of impact-relevant indicators at the seasonal,  monthly, and daily scale including multi-day heat waves, extreme precipitation events, threshold exceedences, and cumulative degree-days for individual RCP/ssp scenarios as well as by global mean temperature thresholds as described in Hayhoe et al. (2018; U.S. Fourth National Climate Assessment Volume 1 Chapter 4).

In this presentation we describe the methodology, briefly highlight results from the evaluation and comparison analysis, and summarize available and forthcoming projections using this computational framework.
Quasi-Real Time Monitoring of Lightning and Weather in the Philippines and Western North Pacific for the Severe Weather Intensity Prediction
Authors: Sato Mitsuteru , Takahashi Yukihiro , Kubota Hisayuki , Noda Akira , Hamada Junichi , Lopez Glenn Vincent C.
Published: March 2021

As many severe weather events, such as torrential rainfall, tropical cyclones, tornados, and downbursts, are closely related to lightning activities, a continuous monitoring of thunderstorms is a key component for the prediction of the severe weather intensity development and for mitigating the natural disasters caused by these severe weather events.  The integration of lightning data has the high potential contributing to short term forecasts of thunderstorms, further meteorological studies, and supplement disaster risk response strategies.  This presents the activities and current status of the Understanding Lightning and Thunderstorm (ULAT) project, which is led by Hokkaido University and other Japanese institutes and Advanced Science and Technology Institute (ASTI), Department of Science and Technology (DOST) in the Philippines supported by the Japan International Cooperation Agency (JICA) and Japan Science and Technology Agency (JST).  The ULAT Project is aimed at the following: a) establishment of a dense network of lightning and weather detectors in Metro Manila and nearby municipalities in order to provide thunderstorm “now-casting” and supplement weather-related research and disaster response studies and strategies; b) establishment of a ground receiving station for the direct reception of the satellite imagery and utilization of existing ground receiving facilities in order to develop effective observation methods by comparing 3D structures of thunderclouds from satellite images with lightning/precipitation data; c) establishment of a methodology for short term forecasts; and d) development of software for sharing information on short term forecast weather to concerned agencies.  Especially for the purpose a), we have developed new lightning and weather observation systems, called as P-POTEKA and V-POTEKA.  These systems can be automatically operated without any daily maintenance.  So far, we have installed 35 P-POTEKA systems in Metro Manila and 7 and 4 V-POTEKA systems in the Philippines and in Indonesia, Palau, Guam, and Okinawa in Japan, respectively.  At the presentation, we will show the updated status of this project and will show the initial results derived from the cross correlation analyses between lightning activities monitored by V-POTEKA systems and the intensity developments of tropical cyclones.

(This research is supported by Science and Technology Research Partnership for Sustainable Development (SATREPS), funded by Japan Science and Technology Agency (JST) / Japan International Cooperation Agency (JICA).)
Modeling snow slab failure in propagation saw test using Drucker-Prager model
Authors: Upadhyay Agraj , Mahajan Puneet , Sharma Rajneesh
Published: March 2021

Abstract

Fracture propagation in weak snow layers followed by the failure of overlying homogeneous snow slab leads to the formation of snow slab avalanches. The extent of fracture propagation in the weak layer and size of the avalanche release area depends on the mechanical behavior of overlying snow layers. To model the snow slab failure in slab avalanche formation process, in present work, mechanical behavior of natural snow is studied through high strain rate (1×10-4 s-1 or higher) uniaxial tension and compression experiments on natural snow layers. Uniaxial loading and unloading experiments are also carried out to understand the permanent strains at high strain rates. Elastic modulus of snow is derived from loading unloading test data and compared with the tangent modulus obtained from maximum slope of the stress-strain curve. Tensile and compressive strengths are derived from peak load at failure and fracture energy is derived from post peak stress-strain curve. For a density range of 100-400 Kg/m3 the range of obtained mechanical properties of natural snow are: Elastic modulus: 0.1-45 MPa, Tensile strength: 0.24-20 kPa, Compressive strength: 0.1-105 kPa, Fracture energy: 0.007-0.15 J/m2. For low density snow (<150 Kg/m3) tensile and compressive strength values are quite close but for higher densities compressive strength is significantly higher than the tensile strength. At low strain rates (<1×10-4 s-1) snow generally exhibit no failure and large permanent deformations whereas, at high strain rates (1×10-3 s-1 or higher) failure strains are generally in the range 0.05-1.5 %. In all cases a sharp decrease in load at failure suggests a near brittle failure. By fitting the experimental dataset with power law, density dependent expressions for elastic modulus, tensile and compressive strength are obtained. On the basis of the experimental observations, a continuum elastic-plastic-damage material model is considered to model mechanical behavior of snow layers. To model the asymmetry in tensile and compressive strengths, pressure dependent Drucker-Prager model is considered for yield criterion and model parameters (friction angle and cohesion) are obtained using density dependent expressions of tensile and compressive strength of snow. Effective plastic strain based damage initiation and evolution models are used to model quasi-brittle failure of snow. This model has been used for modeling the snow slab failure in two dimensional propagation saw tests and the obtained results on the influence of slab density, thickness and slope angle on slab failure have been presented.
Effects of Ocean Acidification on Viral Ecological Characteristics
Authors: Yang Yunlan , Jiao Nianzhi , Zhang Rui
Published: March 2021

Ocean acidification, as a major consequence of excessive emissions of anthropogenic carbon dioxide (CO2), bring about changes in environmental chemistry and marine organism. Evaluation of the response of viruses to ocean acidification is crucial to explore the virus-mediated biogeochemical processes in future ocean. Here we investigated the viral production, decay and virus-host interactions with elevated pCO2 by simulating cultivating experiments in natural environments and laboratory. In the field studies, elevated pCO2 increased lytic viral production in the light compared with the ambient CO2 concentration, but no significant effect was found on lysogenic viral production and viral decay, implying that ocean acidification potentially stimulated the viral propagation in light-dependent microbes while a negligible influence was found on viral structure and life strategy. Consequences of the abundance and infectivity of podoroseophage R2C and siphoroseophage R4C under laboratory incubation verified that viral particles were relatively stable in the acidified ocean, but elevated pCO2 decreased viral infectivity via influencing the indefinite heat labile and high molecular weight dissolved materials in seawater. Strikingly, elevated pCO2 boosted the metabolism of uninfected Synechococcus sp. CB0101 and played a positive effect on the burst size of cyanophage S-CBM2 during the infection, whereas no significant influence was found on the latent period and burst size of siphoroseophage R4C. These results suggesting that the interactions between viruses and heterotrophic bacteria, autotrophic bacteria responded differently to ocean acidification. Thus, ocean acidification was considered as a contributor to viral production via influencing the metabolism of photosynthetic microbes and the interactions between viruses and photosynthetic microbes.
Co-evolution of carbon cycle and air quality fluxes constrained by CMS-Flux and MOMO-Chem assimilation systems
Authors: Bowman Kevin , Miyazaki Kazuyuki , Liu Junjie , Bloom Anthony
Published: March 2021

Rapid regional changes in anthropogenic emissions in response to the COVID-19 pandemic have underscored the contribution of fossil fuel (FF) emission uncertainty to regional carbon budgets.  Typical methods for spatially-explicit FF emissions are dependent on national reporting, which can incur substantial latencies.  However, the concomitant changes in short-lived pollutants from common emission sources point to opportunities to develop independent low-latency estimates of fossil fuel emissions and to better understand anthropogenic processes. Here we combine state-of-the-art Multiple Model Multi Constituent chemical data assimilation system (MOMO-Chem) with bottom-up FF emissions to repartition the net carbon fluxes from the NASA Carbon Monitoring System Flux (CMS-Flux) project.  To that end, we implement a novel Kalman filtering algorithm that predicts emission ratio co-evolution of air quality (AQ) and carbon species.  Based upon top-down estimates of AQ emissions, FF CO2 emissions and uncertainties can be rapidly determined.  We show overall good agreement between predicted FF fluxes and the latest bottom-up inventories.  These data are in turn used to interpret the decadal evolution of CMS-Flux net carbon exchange.  This approach is an important step in quantifying both regional fossil fuel and natural carbon fluxes contributions to the atmospheric CO2 growth rate.
Estimation of All-weather Downward Longwave Radiation over the Tibetan Plateau
Authors: Ding Lirong , Long Zhiyong , Zhou Ji , Wang Shaofei , Zhang Xiaodong
Published: March 2021

The downward longwave radiation (DLR) is a critical parameter for radiation balance, energy budget, and water cycle studies at regional and global scales. The accurate estimation of the all-weather DLR with a high temporal resolution is important for the estimation of the surface net radiation and evapotranspiration. However, the most DLR products involve instantaneous DLR estimates based on polar orbiting satellite data under clear-sky conditions. To obtain an in-depth understanding of the performances of different models in the estimation of the DLR over the Tibetan Plateau, which is a focus area of climate change study, this study tested eight methods under clear-sky conditions and six methods under cloudy conditions based on ground-measured data. The results show that the Dilley and O’Brien model and the Lhomme model are most suitable under clear-sky conditions and cloudy conditions, respectively. For the Dilley and O’Brien model, the average root mean square error (RMSE) of the DLR under clear-sky conditions is approximately 22.5 W/m2 at nine ground sites; for the Lhomme model, the average RMSE is approximately 23.2 W/m2. Based on the estimated cloud fraction and meteorological data provided by the China land surface data assimilation system (CLDAS), the hourly all-weather daytime DLR with 0.0625° over the Tibetan Plateau was estimated. The results show that the average RMSE of the estimated hourly all-weather DLR was approximately 26.4 W/m2. With the combined all-weather DLR model, the hourly all-weather daytime DLR dataset with a 0.0625° resolution from 2008 to 2016 over the Tibetan Plateau was generated. This dataset can better contribute to studies associated with the radiation balance and energy budget, water cycle, and climate change over the Tibetan Plateau.
Progress towards small-scale field trials of coastal enhanced weathering of olivine
Authors: Romaniello Stephen , Stopnitzky Shanee , Green Tom , Montserrat Francesc , Matzner Eric , Moreau Cheyenne , Syverson Drew , Lopez Paloma , Hayden Matthew , Sulpis Olivier , Ley Brian
Published: March 2021

Slow progress towards achieving global greenhouse gas emissions targets significantly increases the likelihood that future climate efforts may require not only emissions cuts but also direct climate mitigation via negative emissions technologies (IPCC AR5). Currently, such technologies exist at only a nascent stage of development, with significant uncertainties regarding their feasibility, cost, and potential unintended consequences and/or co-benefits.

Coastal enhanced weathering of olivine (CEWO) has been suggested as one potential pathway for achieving net negative CO2 emissions at scale. CEWO involves the mining of olivine-rich ultramafic rocks (such as dunite) for incorporation during beach augmentation and restoration work. While grinding this rock into increasingly fine particle sizes is essential for increasing its surface area and reactivity, this step is also costly and energetically expensive. CEWO attempts to minimize this cost and energy penalty by relying on wave and tidal action to provide ongoing physical weathering of olivine grains once distributed on beaches. Laboratory experiments and carbon emissions assessments of CEWO suggest that these approaches may be technically feasible and carbon negative, but significant uncertainties remain regarding the real-world kinetics of coastal olivine dissolution. Furthermore, concerns about the fate and ecological impact of nickel (Ni) and chromium (Cr)—potentially toxic trace metals found in olivine—require careful evaluation.

In 2019, Project Vesta was established as a nonprofit, philanthropically funded effort to evaluate the technical feasibility and ecological impacts of CEWO through a dedicated research program ultimately culminating in small-scale, real-world field trials of CEWO. This presentation will provide an overview and discussion of our overall research strategy, share insights from interim modeling and mesocosm experiments designed to ensure the practicality and safety of future field experiments, and explain our approach for ensuring transparent, responsible, and ethical research oversight and governance.
Magnetic-local-time dependency of radiation belt electron precipitation: impact on ozone in the polar middle atmosphere
Authors: Verronen Pekka T. , Marsh Daniel R. , Szeląg Monika E. , Kalakoski Niilo
Published: March 2021

The radiation belts are regions in the near-Earth space where solar wind electrons are captured by the Earth’s magnetic field. A portion of these electrons is continuously lost into the atmosphere where they cause ionization and chemical changes. Driven by the solar activity, the electron forcing leads to ozone variability in the polar stratosphere and mesosphere. Understanding the possible dynamical connections to regional climate is an ongoing research activity which supports the assessment of greenhouse-gas-driven climate change by a better definition of the solar-driven variability. In the context of the Coupled Model Intercomparison Project Phase 6 (CMIP6), energetic electron and proton precipitation is included in the solar-forcing recommendation for the first time. For the radiation belt electrons, the CMIP6 forcing is from a daily zonal-mean proxy model. This zonal-mean model ignores the well-known dependency of precipitation on magnetic local time (MLT), i.e. its diurnal variability. Here we use the Whole Atmosphere Community Climate Model with its lower-ionospheric-chemistry extension (WACCM-D) to study effects of the MLT dependency of electron forcing on the polar-ozone response. We analyse simulations applying MLT-dependent and MLT-independent forcings and contrast the resulting ozone responses in monthly-mean data as well as in monthly means at individual local times. We consider two cases: (1) the year 2003 and (2) an extreme, continuous forcing. Our results indicate that the ozone responses to the MLT-dependent and the MLT-independent forcings are very similar, and the differences found are small compared to those caused by the overall uncertainties related to the representation of electron forcing in climate simulations. We conclude that the use of daily zonal-mean electron forcing will provide an accurate ozone response in long-term climate simulations.
Paleomagnetism and magnetostratigraphy of Tarkhanian sediments of the Eastern Paratethus (Skelya section, Kerch peninsula, Crimea)  
Authors: Pilipenko Olga , Rostovtseva Yuliana
Published: March 2021

A detailed paleomagnetic study of Tarkhanian sediments of Skelya section was carried out with the goal to obtained magnetostratigraphy data. The Skelya section is located on the Azov sea side of Kerch peninsula, Crimea (45o42′N, 36o53′E). The Tarkhanian sediments of Skelya section are represented mainly of clays and have a total thickness of ~ 100 m. According to GTS (2012), the Tarkhanian stage of Miocene is related to the lower part of the Langhian of the General Stratigraphic Scale. Standard paleomagnetic measurements have been carried out to investigate magnetic parameters: natural remenent magnetization, magnetic susceptibility, saturation remanent magnetization, anhysteretic   remanent magnetization varied through out the section. The remanent coercitivity force, determined from backfield demagnetization measurements, range between ~34 and 67 mT.   The composition of the ferromagnetic fraction was examined using temperature dependences of saturation remanent magnetic moment. The thermomagnetic analysis showed that the blocking temperatures are  about 320 oC and 410-470 oC and  greigite and titanomagnetite  are the main carriers of NRM in the section.  The biplot of  IRM-100 mT / SIRM versus  ARM40mT /SARM showed that the ratios fall down into the field around the titanomagnetite and greigite areas. The pseudo-single domain  state of titanomagnetite and greigite was determined from their Mrs/Ms and Bcr/Bc ratios by Day-plot. Paleomagnetic studies have shown that the interval of the Kuvinian beds in its upper part is composed of sediments of reversal polarity magnetization. The rocks of the Terskian and Argunian beds are characterized by intervals of normal and reversed polarity magnetization. This work was supported by Russian Science Foundation, project № 19-77-10075.
Predictably Predictable -  The Role of Catchment Characteristics and Complexity.
Authors: Eugeni Sophia , Vaags Eric , Weijs Steven V.
Published: March 2021

Accurate hydrologic modelling is critical to effective water resource management. As catchment attributes strongly influence the hydrologic behaviors in an area, they can be used to inform hydrologic models to better predict the discharge in a basin. Some basins may be more difficult to accurately predict than others. The difficulty in predicting discharge may also be related to the complexity of the discharge signal. The study establishes the relationship between a catchment’s static attributes and hydrologic model performance in those catchments, and also investigates the link to complexity, which we quantify with measures of compressibility based in information theory. 

The project analyzes a large national dataset, comprised of catchment attributes for basins across the United States, paired with established performance metrics for corresponding hydrologic models. Principal Component Analysis (PCA) was completed on the catchment attributes data to determine the strongest modes in the input. The basins were clustered according to their catchment attributes and the performance within the clusters was compared. 

Significant differences in model performance emerged between the clusters of basins. For the complexity analysis, details of the implementation and technical challenges will be discussed, as well as preliminary results.
Ensemble generation of regional ocean physics and biogeochemical model uncertainties, empirical consistency and suitability for probabilistic forecasting
Authors: Vervatis Vassilios , De Mey-Frémaux Pierre , Lemieux-Dudon Bénédicte , Karagiorgos John , Ayoub Nadia , Sofianos Sarantis
Published: March 2021

The study builds upon two Copernicus marine projects, SCRUM and SCRUM2, focusing on ensemble forecasting operational capabilities to better serve coastal downscaling. Both projects provided coupled physics-biogeochemistry ensemble generation approaches, tools to strengthen CMEMS in the areas of ocean uncertainty modelling, empirical ensemble consistency and data assimilation, including methods to assess the suitability of ensembles for probabilistic forecasting. The study is conducted by performing short- to medium-range ensembles in the Bay of Biscay, a subdomain of the IBI-MFC. Ensembles were generated using ocean stochastic modelling and incorporating an atmospheric ensemble. Sentinel 3A data from CMEMS TACs and arrays were considered for empirical consistency, using innovation statistics and approaches taking into account correlated observations. Finally, several properties of ensembles were estimated as components of known probabilistic skill scores: the Brier score (BS), and the CRPS. This was done for pseudo-observations (Quasi-Reliable test-bed) and for real verifying observations in a coastal upwelling test case.
3D Reconstruction of Typhoon and Thunderstorm Cloud Top Using Airborne Camera 
Authors: Algodon Meryl , Takahashi Yukihiro , Sato Mitsuteru , Kubota Hisayuki , Ishida Tetsuro , Yamashita Kozo , Castro Ellison , Perez Gay Jane , Marciano Joel Joseph , Matsumoto Jun , Hamada Jun-ichi , Tsuboki Kazuhisa , Yamada Hiroyuki
Published: March 2021

Typhoons are extreme weather phenomena that inflict damages and casualties around globe. These phenomena are difficult to study because of their chaotic behaviour but the capacity to measure their intensity can help mitigate the hazards that they bring. In the past, several attempts have been done to relate typhoon's intensity with the structural evolution of its eye. This suggests the possible relation between the typhoon intensity with typhoon eye altitude. In this research, we visualize Typhoon Trami’s structure by reconstructing the three-dimensional model inside its eye and analyze the information of its cloud top altitude. An experiment was conducted under the SATREPS/ULAT project (SATREPS: Science and Technology Research Partnership for Sustainable Development, ULAT: Understanding Lightning and Thunderstorm) where images of Typhoon Trami were taken from an aircraft last September 26, 2018. Aircraft images were used to reconstruct the 3D model inside the typhoon eye because they provide closer views of the typhoon than that of geostationary satellite images, making it easier to reconstruct a 3D model. The 3D reconstruction generated covers 43 km region of the typhoon eye at 20.2 m/pixel spatial resolution. Three cross-sections of the 3D model were analyzed, and the resulting altitude distribution was compared with the cloud-top altitude estimated by mapping the brightness temperature of the Himawari Thermal Infrared Band 13 with cloud-top height as measured by NOAA sonde data. From the 3D model, the altitude distribution ranges from 5.3 km to 14.3 km which corresponds with the altitude estimated from the brightness temperature of 6.5 km to 14.3 km. However, regions of altitude difference can also be observed between the two methods. This study shows that a three-dimensional model could be a good mode of typhoon visualization as it shows a more detailed typhoon structure such as the stairstep structures that was detected at some regions within the typhoon eye. This research was supported by SATREPS, funded by Japan Science and Technology Agency (JST) / Japan International Cooperation Agency (JICA).
Insight into municipal solid waste fly ash (MSWFA) heavy metals speciation by selective extractions and geochemical modelling
Authors: Bernasconi Davide , Caviglia Caterina , Destefanis Enrico , Pastero Linda , Bonadiman Costanza , Pavese Alessandro , Agostino Angelo , Boero Renato
Published: March 2021

Nowadays municipal solid waste incineration (MSWI) has become a widespread and consolidated technology for MSW treatment all over the world. Indeed, it allows to reach up to 90% of waste volume reduction, while also producing energy. However, the incineration process has some drawbacks, one of which is the production of different residues that must be disposed of. Specifically, particular attention must be paid to fly ash (FA), which generally represents one of the most dangerous residues. FA is collected by the flue gas purification system and counts for around the 5% w/w of total incinerated waste. MSWI FA is regulated as a hazardous waste, mainly due to high concentrations of heavy metals (Pb, Cr, Zn, Cd) and soluble salts (chlorides and sulfates). Moreover, the average size of FA particles can be as low as 50-20 µm, thus determining a high surface area, which can increase toxic elements release into the environment. Therefore, many preliminary physicochemical stabilization treatments have been proposed over the years for their possible reuse as construction materials (e.g. water washing, thermal treatment, etc..). However, a detailed characterization of the residue in terms of heavy metals speciation is often overlooked. Indeed, this represents necessary information in order to understand and control the residue behavior in a reuse scenario and to design stabilization treatments as effective as possible.

In this work the analysis of heavy metals distribution and speciation of Turin MSW FA has been conducted, by combining both experimental treatments and geochemical modelling. In particular, a 4-step sequential extraction method has allowed to evaluate how heavy metals are distributed among four fractions with different physicochemical properties and, then, to deduct preliminary considerations about their leaching availability. In addition, pH-dependant leaching tests coupled by geochemical modelling using Virtual MINTEQ software has provided a more detailed insight into heavy metals speciation, by proposing possible phases which are often not detected by bulk analytical techniques. Finally, a general assessment of the hazardousness of Turin FA is discussed.
In-situ measurements of the HDO/H2O Isotopic ratio in the Asian Summer Monsoon trace strong convective activity
Authors: Clouser Benjamin , Singer Clare , Khaykin Sergey , Krämer Martina , Lykov Alexey , Bucci Sylvia , Legras Bernard , Borrmann Stephan , Cairo Francesco , Mitev Valentin , Matthey Renaud , Ravegnani Fabrizio , Rolf Christian , Ulanovsky Alexey , Viciani Silvia , D'Amato Francesco , Volk C Michael , Yushkov Vladimir , Stroh Fred , Moyer Elisabeth
Published: March 2021

In-situ measurements of the HDO/H2O isotopic ratio from the Chicago Water Isotope Spectrometer (ChiWIS) during the 2017 StratoClim campaign help diagnose convective processes in the Asian Monsoon. Isotopic measurements show enormous diversity in isotopic composition, likely reflecting degree of recent convective influence. Eight flights in July—August sampled a wide range of convective influence at near-tropopause altitudes, with timescales of minutes to weeks, and mean isotopic compositions from -700 per mil in recent convective outflow to -350 per mil in more aged air that is at least several days from last convective influence. Above the tropopause, we use isotopic composition to understand the fate of convective remnants. Isotopic measurements suggest much in-situ cirrus measured during  StratoClim campaign is actually secondary cirrus which has reformed in an area of prior convective moistening. These flights allow detailed comparison between North American and Asian monsoons, and we compare StratoClim results to both satellite and in-situ measurements in other monsoon and tropical locations. Finally, we discuss prospects for detection and interpretation of convective remnants during the in the 2021/2022 ACCLIP campaign.
Comparison of External ULF wave Sources in Driving Radiation Belt Electron Dynamics
Authors: Niu Zhe , Degeling Alexander , Shi Quanqi
Published: March 2021

For the study of Earth's radiation belts, an outstanding problem is the identification and prediction of dynamic variations of Earth's trapped energetic particles, in particular during geomagnetic storms. Statistical studies indicate that different types of geomagnetic storms (e.g. CIR and CME driven storms) have differing efficiencies in their ability to cause energization, transport and loss of energetic particles. This is most likely due to differences in the dominant mechanisms by which particles are affected between the storm types, and the locations within the magnetosphere where these mechanisms operate. For example, the dominant external generation mechanism for Pc5 ULF waves during CME driven storms may be magnetopause buffeting across the dayside, while for CIR driven storms the Kelvin-Helmholtz Instability (KHI) along the morning and evening flanks is more likely dominant. This changes the location and efficiency by which ULF waves can resonantly interact with radiation belt particles in these two storm types.

In this study, we use a 2D MHD wave model to investigate how the dominant generation mechanism in the case of CIR and CME driven storms determines the ability for externally generated wave power to penetrate deeply into the magnetosphere. In order to do this, we model ideal MHD waves in a 2D box model magnetosphere with a parabolic magnetopause boundary layer. We consider how fluctuations in dynamic pressure generate magnetopause buffeting perturbations that launch MHD fast mode waves, following the approach of Degeling et al., JGR 2011. We also include in our simulation a simple model for magnetosheath flow, and calculate the local linear KHI growth rate for perturbations along the magnetopause flanks as a function of frequency to provide a KHI driven wave source.
Investigation of the ionospheric plasma parameters variations in the range of planetary waves periods using Warsaw ionosonde and Belsk observatory data
Authors: Riabova Svetlana , Shalimov Sergei
Published: March 2021

There has long been interest in the sources of ionospheric variability, especially in how this variability can be caused by the dynamics of the neutral atmosphere. Many studies have found planetary wave fluctuations in ionospheric parameters, especially f0F2, with periods ranging from 2 to 20 days. We investigate variations of the geomagnetic field and critical frequency of the F2-layer in the range of planetary waves in winter. We used the data of geomagnetic monitoring at the Central Geophysical Observatory at Belsk of Institute of Geophysics of the Polish Academy of Sciences (Poland, Belsk) and the results of high-frequency sounding of the ionosphere in the form of ionograms obtained by the Space Research Center of the Polish Academy of Sciences (Poland, Warsaw).  In the spectra of temporal variations of the geomagnetic field and the critical frequency of the ionospheric F2 layer in the range of planetary waves periods in winter season, we found both harmonics associated with the modulation effect of longer-period (annual and 11-year) variations and tidal effects, and a harmonic corresponding to a quasi 16-day planetary wave. Possible mechanisms of their manifestations in the upper atmosphere are discussed.
Comparative study of halo CME arrival predictions
Authors: Yordanova Emiliya , Dumbovic Mateja , Temmer Manuela , Scolini Camilla , Magdalenic Jasmina , J. Thompson William , Sorriso-Valvo Luca , P. Dimmock Andrew , Rosenqvist Lisa
Published: March 2021

Halo coronal mass ejections (CMEs) are one of the most effective drivers of intense geomagnetic storms. Despite the recent advances in space weather forecasting, the accurate arrival prediction of halo CMEs remains a challenge.  This is because in general CMEs interact with the background solar wind during their propagation in the interplanetary space. In addition, in the case of halo CMEs, the accurate estimation of their kinematics is difficult due to projection effects in the plane-of-sky.

In this study, we are revisiting the arrival of twelve geoeffective Earth-directed fast halo CMEs using an empirical and a numerical approaches. For this purpose we refine the input to the Drag-based Model (DBM) and to the EUropean Heliospheric Forecasting Information Asset (EUHFORIA), which are recently available for users from the ESA Space Situational Awareness Portal (http://swe.ssa.esa.int).

The DBM model has been tested using different values for the input drag parameter.  On average, the predicted arrival times are confined in the range of ± 10 h. The closest arrival to the observed one has been achieved with a drag value higher than the recommended for fast CMEs. Setting a higher drag also helped to obtain a closer to the observed CME arrival speed prediction. These results suggest that the exerted solar wind drag was higher than expected. Further, we are searching for clues about the CME propagation by performing EUHFORIA runs using the same CME kinematics. Preliminary results show that both models perform poorly for CMEs that have possibly undergone CME-CME interaction, underlying again the importance of taking into account the state of the interplanetary space in the CME forecast.
Depth and composition dependent nanopore structures of Indian shale gas reservoirs: An implication on storage potential
Authors: Bal Abinash , Misra Santanu , Mukherjee Manab
Published: March 2021

We investigated the nanopore structures of shale samples obtained from Cambay and Krishna-Godavari (KG) basins in India using low-pressure N2 sorption method. The samples occurred at variable depths (1403-2574m and 2599-2987m for Cambay and KG basins, respectively) and have wide ranges of clay contents (56-90%) both in volume and mineralogy. The results of this study indicate the specific surface area (SSA) and pore diameters of the samples share a non-linear negative correlation. The SSA is a strong function of the clay content over the samples’ depth. The specific micropore volumes of the KG basin have relatively higher (8.29-24.4%) than the Cambay basin (0.1-3.6%), which leads to higher SSA in the KG basin. From different statistical thickness equations, the Harkins Jura equation was found to be most suitable for the computation of BJH pore size distribution and t-plot inversion in shale. Shale samples from Cambay basin show unimodal pore size distribution, with a modal diameter of 4-5nm, while in the KG basin, show bi-modal to multimodal pore size distribution, mostly ranges from 3-12 nm. In the fractal FHH method, fractal exponent Df-3 provides a better realistic result than fractal dimensions calculated from (Df-3)/3. In our samples, pore surface fractal dimension (Df1) show a positive correlation with SSA and a negative correlation with pore diameter, and pore structure fractal dimension (Df2) shows a negative correlation both with clay(%) and depth. The experimental data obtained in this study are instrumental in developing the pore-network model to assess the hydrocarbon reserve and recovery in shale.
Physical-biological interactions limit the resilience of coastal wetlands to sea level rise
Authors: Rodriguez Jose , Breda Angelo , Saco Patricia , Sandi Steven , Saintilan Neil , Riccardi Gerardo
Published: March 2021

Predictions of the effects of sea-level rise over the next century on coastal wetlands vary widely due to uncertainties on environmental variables, but also due to simplifications on the simulation methodologies used. Here, we investigate how accretion and migration processes affect wetland response to sea level rise (SLR) using a computational framework that includes all relevant hydrodynamic, sediment transport and vegetation dynamics mechanisms that affect wetland evolution, and it is efficient enough computationally to allow the simulation of long time periods. We apply this framework to different settings typically found in coastal wetlands around the world, comprising different vegetation types, different sediment loads, obstructions to flow and drainage structures, both natural and man-made. We find that the vast majority of wetland settings analysed are unable to cope with high SLR rates and disappear before the end of the century. Our findings are consistent with paleo-records that indicate limits on the accretion capacity of coastal wetlands during periods of high SLR rates.
Recent trends in air-sea CO2 fluxes and ocean acidification in the Arabian Sea
Authors: Lachkar Zouhair , Mehari Michael , De Verneil Alain , Lévy Marina , Smith Shafer
Published: March 2021

Recent observations and modeling evidence indicate that the Arabian Sea (AS) is a net source of carbon to the atmosphere. Yet, the interannual variability modulating the air-sea CO2 fluxes in the region, as well as their long-term trends, remain poorly known. Furthermore, while the rising atmospheric concentration of CO2 is causing surface ocean pH to drop globally, little is known about local and regional acidification trends in the AS, a region hosting a major coastal upwelling system naturally prone to relatively low surface pH. Here, we simulate the evolution of air-sea CO2 fluxes and reconstruct the progression of ocean acidification in the AS from 1982 through 2019 using an eddy-resolving ocean biogeochemical model covering the full Indian Ocean and forced with observation-based winds and heat and freshwater fluxes. Additionally, using a set of sensitivity simulations that vary in terms of atmospheric CO2 levels and physical forcing we quantify the variability of fluxes associated with both natural and anthropogenic CO2 and disentangle the contributions of climate variability and that of atmospheric CO2 concentrations to the long-term trends in air-sea CO2 fluxes and acidification. Our analysis reveals a strong variability in the air-sea CO2 fluxes and pH on a multitude of timescales ranging from the intra-seasonal to the decadal. Furthermore, a strong progression of ocean acidification with an important penetration into the thermocline is simulated locally near the upwelling regions. Our analysis also indicates that in addition to the increasing anthropogenic CO2 concentrations in the atmosphere, recent warming and monsoon wind changes have substantially modulated these trends regionally.
Application of organic fertilizers alter the physical and biogeochemical properties of agricultural topsoil and subsoil
Authors: Neumeier Anke , Guigue Julien , Ostovari Yaser , Muskolus Andreas , Martens Henk , Mešinović Emina , Kögel-Knabner Ingrid , Creamer Rachel , Van Groenigen Jan Willem , Vidal Alix
Published: March 2021

Sustainable agricultural practices aim to ensure the rebuilt of soil organic carbon (SOC) stocks and to sustain soil fertility. One of the levers is the use of carbon and nutrient inputs in the form of organic amendments, such as farmyard manure, slurry and biogas digestate. These organic fertilizers represent a promising alternative to the mineral fertilizers, which are mainly made from non-renewable resources. The use mineral fertilizers is indeed associated with an excessive use of natural resources and a loss of biodiversity. The effect of organic amendments compared with traditional mineral fertilizers on SOC stocks and soil fertility are uncertain in the longer-term. We aimed at investigating the effects of mineral and organic fertilizers (i.e., manure, pig slurry and biogas digestate) on topsoil and subsoil biogeochemistry, after eight years of application. For this purpose, we sampled soil cores down to a depth of one meter in a randomized field experiment in Germany, running since 2011. A full-profile assessment of the carbon and nitrogen distribution, stability and bioavailability was achieved using a combination of classical bulk physico-chemical analyses (e.g., SOC and nitrogen contents, texture, pH, bulk density) and state-of-the-art imaging techniques. Selected samples were analysed for aggregate size distribution, as well as organic carbon and nitrogen contents and allocation within these aggregates. Further, undisturbed core-samples were scanned using a hyperspectral camera in the Vis-NIR range to reveal hotspots of carbon storage at the soil profile scale. Soil carbon distribution was predicted as a function of spectral response, using a variety of machine learning approaches. The application of organic fertilizers (whatever their nature) resulted in higher SOC contents in the first 10 cm, as compared to the control and the mineral fertilizer treatments. The SOC stocks were + 21-33 % higher in the soil treated with organic fertilizers as compared to the control treatment. The application of mineral fertilizer or digestate, as compared to the control, resulted in higher relative amount of microaggregates (versus macroaggregates) (+ 19-40 %) in the soil down to 80 cm. These results will provide essential information to develop management strategies that increase nutrient recycling as well as SOC stocks.
The 2018–2019 weak El Niño: Predicting the risk of a dengue outbreak in Machala, Ecuador
Authors: Petrova Desislava , Rodó Xavier , Sippy Rachel , Ballester Joan , Mejía Raul , Beltrán-Ayala Efraín , Borbor-Cordova Mercy , Vallejo G. Mauricio , A. Olmedo Alberto , Stewart-Ibarra Anna , Lowe Rachel
Published: March 2021

Sea surface temperature conditions in the central-eastern tropical Pacific indicated a mild El Niño event in October 2018, which continued throughout the spring of 2019. The global El Niño Southern Oscillation (ENSO) forecast consensus was that these generally weak warm patterns would persist at least until the end of the summer. El Niño and its impact on local climatic conditions in southern coastal Ecuador influence the inter-annual transmission of dengue fever in the region. In this study, we use an ENSO model to issue forecasts of El Niño for the year 2019, which are then used to predict local climate variables, precipitation and minimum temperature, in the city of Machala, Ecuador. All these forecasts are incorporated in a dengue transmission model, specifically developed and tested for this area, to produce out-of-sample predictions of dengue risk. Predictions are issued at the beginning of January 2019 for the whole year, thus providing the longest forecast lead time of 12 months. Preliminary results indicated that the mild El Niño event did not provide the optimum climate conditions for dengue transmission, with the model predicting a very low probability of a dengue outbreak during the typical peak season in Machala in 2019. This is contrary to 2016, when a large El Niño event resulted in excess rainfall and warmer temperatures in the region, and a dengue outbreak occurred 3 months earlier than expected. This event was successfully predicted using a similar prediction framework to the one applied here. With the present study, we continue our  efforts to build and test a climate service tool to issue early warnings of dengue outbreaks in the region.
Benefits of low-impact development in rural areas
Authors: Chou Kuan Lin
Published: March 2021

In Taiwan, it is easy to encounter typhoons or heavy rain events with high rainfall intensity, and urban areas are prone to flooding and causing disasters. Rural areas are no exception. Flooding can cause crop necrosis. The reason may be attributed to the rural areas’s old drainage system or not yet complete drainage system, so the goal is to find the most suitable low-impact development facilities through model simulation, evaluate whether various low-impact developments are feasible, and how much flooding depth and savings can be reduced after installation. How much water is used for future irrigation as a decision-making benefit, and the scope of the setting is planned according to the flow sharing plan set by the government, hoping to provide effective improvement in rural areas.
Jupiter's envelope is not homogeneous
Authors: Miguel Yamila , Bazot Michael , Guillot Tristan , Galanti Eli , Kaspi Yohai , Howard Saburo
Published: March 2021

The amount and distribution of heavy elements in Jupiter’s interior is crucial to understand how the planet was formed and evolved. The results provided by the Juno mission in the last years have fundamentally changed our view of the interior of Jupiter. The remarkably accurate gravity data, including odd gravity harmonics, have allowed us to put constrains on the zonal flows, the extent of differential rotation and lead us to find that Jupiter has most likely a dilute core. In this study we do interior structure calculations using a Bayesian statistical approach and fitting all observational constrains, to show that a non-homogenous envelope is also a constraint set up by the Juno measurements, which is helping us to get closer to unveiling Jupiter’s deep secrets. 
Understanding the trends and controlling factors of Indian Ocean acidification
Authors: Madkaiker Kunal , Valsala Vinu
Published: March 2021

The Indian Ocean (IO) is witnessing acidification of its surface waters as a consequence of the continuous rising of atmospheric CO2 concentration thus disrupting the biological and chemical balance of the ecosystem in the region. The basin wide spatial variability of biogeochemical properties induces spatial variability of surface water pH. This study investigates the seasonality and trends of surface pH over the IO bioprovinces and regionally assesses the individual contribution of the factors affecting its variability. Simulations from global ocean models (OTTM and ROMS) coupled with suitable biogeochemical modules were validated with pH observations over the basin, and used to discern the regional response of pH seasonality (1990-2010) and trend (1961-2010) to changes in ocean temperature (SST), Dissolved Inorganic Carbon (DIC), Total Alkalinity (ALK) and Salinity (S). DIC and SST are the major contributors to the seasonal variability of pH in almost all bioprovinces consistent in both model simulations. The acidification in IO basin of 0.0675 units during 1961-2010 is attributed to 69.28% contribution of DIC followed by 13.82% contribution of SST. For most of the regions DIC remains a dominant contributor to changing trend in pH except for the Northern Bay of Bengal and Around India (NBoB-AI) region, wherein pH trend is dominated by ALK (55.6%) and SST (16.8%). The interdependence of SST and S over ALK is significant in modifying the carbonate chemistry and biogeochemical dynamics of NBoB-AI and a part of tropical, subtropical IO. The strong negative correlation between SST and pH infers the increasing risk of acidification in the bioprovinces with the rising SST.

This study is an attempt to identify the regional influencers of pH variability so that adequate mitigation action can be planned and the acidification can be decelerated in near future.