bluuebunny/crossref_metadata_2025 huggingface dataset:
Mercury methylation and demethylation on impacted wetland soils: effects of temperature
Authors: Sagisaka Sayuri , Mitchell Carl P.
Published: February 2023

The methylation of mercury by anaerobic microbes in wet soils and sediment significantly increases its bioaccumulation potential into wildlife. Methylation is also counter-acted by demethylation processes, with the balance between methylation and demethylation processes ultimately controlling the amount of methylmercury in a system. Given that microbial activities are intricately linked with temperature, climatic changes should impact mercury methylation and demethylation processes, but this is not well-characterized in mercury research. In this presentation, I will discuss the outcome of better understanding mercury methylation and demethylation processes and rates in boreal wetland soils, as affected by temperature. To examine this, we have included a series of controlled, closed-system, flow-through experiments using boreal wetland soils from both forest-impacted and unimpacted wetlands in dark growth chambers across a range of realistic temperatures (5, 10, 15, 20, 25 °C). Mercury methylation and demethylation processes were examined in soil cores using enriched mercury isotope incubations and analyzed against measures of microbial activity and soil/water chemistry. Results from this study are expected to allow us to begin modeling mercury cycling processes with respect to climate and other environmental changes.
Autonomous marine carbon system observations and measurements onboard Boaty McBoatface: Results and analysis from an 8-day mission in the Celtic Sea
Authors: Hammermeister Emily , Loucaides Socratis , Papadimitriou Efstathios , Schaap Allison , Arundell Martin , Chaney Edward , Mowlem Matthew
Published: February 2023

In a world where the climatic response to human carbon emissions has reached a critical point in time, understanding the ocean’s role in carbon cycling has become a major focus for scientific observation and intervention. The development of marine autonomous platforms provides observations of higher spatiotemporal resolution, which can be used to further measure, characterize, and model ocean carbon. As a part of the pioneering OCEANIDS programme, novel carbonate chemistry sensors were integrated on the Autosub Long Range (ALR) Autonomous Underwater Vehicle (Boaty McBoatface) and deployed in the Celtic Sea. The project utilized three autonomous Lab-On-Chip (LOC) sensors measuring pH, Total Alkalinity (TA), and Dissolved Inorganic Carbon (DIC). Together, these sensors enable characterisation of the marine carbonate system based on direct in situ measurements. This unprecedented technology has the potential to improve our understanding of the inorganic carbon cycle in the ocean and enable ocean acidification monitoring at a higher spatial and temporal resolution than currently possible. Additionally, it presents a powerful tool for CO2 leak detection from sub-seafloor carbon captureand storage (CCS) sites and paves the way towards decarbonisation of ocean observations. Preliminary results collected in March 2022 during a multi-day ALR mission in the Celtic Sea from surface waters to 600m depth will be presented. Sensor data will be validated against discrete water samples collected along the ALR’s track. The performance of the new technology and its potential as an observing tool for ocean CO2 observations and constraining the marine carbon cycle will be evaluated. Additionally, sensor post-processing analytical techniques and insights will be discussed.
Communication for emergencies – the need for a new and inclusive ecosystem
Authors: Wales David , Olson Alexandra , Gizikis Alexis
Published: February 2023

“The future of emergency communication requires a new ecosystem that enhances capacity and capability by creating an environment that is accessible, equitable, and anticipates change as a constant state.”This is the key finding of research designed to identify policy recommendations for the EU and which is intended to be of assistance to policymakers at national, regional, and local levels.It recognises that current models of communication in relation to emergencies are typically oriented towards top-down or single-direction communication, flowing from professionals to lay persons. The impact of this legacy approach extends far beyond the obvious and visible delivery mechanisms. It also frames the underpinning research, discussions, and attitudes. As such, it perpetuates existing limitations and biases of the system, for example, an underappreciation of the needs, role, and contribution of citizens and communities.It also means that global aspirations- such as enhancing resilience and integration- can at best only ever be partially achieved because they are only seen through a narrow and restrictive lens. This has profound implications and fundamental changes are required to better accommodate multi-directional communication in which the role of authorities and professionals adapts to one of enablement, rather than control.The primary and overarching recommendation for a new communications ecosystem emerged through considering the wider meaning of specific findings from the research. These are shown below:Bridge the communication gaps between professionals and citizens. For example in relation to language (terminology), content, risk tolerance, stereotypes, desired outcomes/priorities, and assumptions.
Recognise that communication is a continuous activity that is reliant on creating the right conditions for it to be effective.
Design consistent messaging and communication that is inclusive and adaptable to specific needs.
Recognise communication as a learning opportunity and actively design in opportunities to exploit this throughout the cycle.
Communication strategies should recognise and positively support the opportunities that emergencies provide for citizens, communities, and formal agencies to enhance integration and resilience.
In proposing this paper to the EGU General Assembly 2023, we hope it may represent a valuable opportunity to consider opportunities to align the work of the climate and crisis sectors in this area. Hopefully, in doing so, we will learn from each other and make the task of those using our work easier and more effective.Note: The authors were funded by the ENGAGE project to produce the report referenced in this abstract. ENGAGE is an EU-funded project, which started in July 2020 and whose mission is to identify novel knowledge, impactful solutions, and emergency response guidelines for exploiting Europe ́s societal resilience. 
Process-Based Estimates of Seasonal Streamflow for Ungauged Catchments
Authors: Wang Zeqiang , Woods Ross , Howden Nicholas , Berghuijs Wouter
Published: February 2023

The seasonal water balance is at the core of overall catchment responses, but current methods to simulate seasonal water availability at ungauged locations are unreliable. Here we enhance two simple models from Woods (2003 and 2009, Advances in Water Resources) to estimate actual evaporation, changes in storage, and streamflow, using summary statistics of precipitation, temperature, and potential evaporation from the CAMELS-US dataset. Specifically, we first use sinusoidal functions to simulate observed precipitation, temperature, and potential evaporation to quantify several parameters (e.g., climate dryness index). We then use these variables and parameters to force our simple model representing the main hydrological processes to generate estimated streamflow. We then assess the model’s ability to simulate the seasonal flow regime across many catchments worldwide. Finally, we identify the dominant variables and processes controlling the seasonal water balance and discuss the limitations of our model. This allows finding in which situations we can reliably estimate seasonal variation in catchment streamflow without flow measurements, and other cases where model refinement is needed. Our study is important to improve our understanding of seasonal catchment hydrology and for predicting the seasonal hydrological differences between various hydro-climatic conditions or catchments, especially in locations with sparse measurements.
Field investigation and movement deposition scale forecasting of a typical high-locality landslide in the dry season
Authors: Gao Zemin , Ding Mingtao , Hassan Muhammad , Liu Xingwang
Published: February 2023

Abstract: During the dry season of December 2020, two sliding subzones of the Qingliu landslide in southwest China slid out of stability, severely damaging the buildings on the slope. To investigate the mechanism and movement of landslides in the dry season, we employed high-resolution unmanned aerial vehicle mapping, electrical resistivity tomography, on-site union boreholes, groundwater detection, deep displacement monitoring, and numerical simulation to analyze the deep geotechnical structural characteristics, groundwater types and runoff paths, and destabilization range and movement processes at different times. Preliminary analysis showed that the slow infiltration of rainwater during the rainy season and infiltration of snow melt in winter, topography, and loess clay layers of the slide zone type are related to the triggers of landslide instability. Four layers of rock-soil stratification interfaces with different resistivity values, revealed by electrical resistivity tomographycomprising loess-like pulverized clay, gravelly pulverized clay, and bedrock, existed at different burial depths in the longitudinal section. Borehole and displacement monitoring revealed the existence of a primary slip surface and several secondary slip surfaces, with an average thickness of 16-22 m and a maximum daily displacement at the slip surface of approximately 2.29 mm. The deepest groundwater level of the water-bearing section in the borehole was 25.8 m, and it percolates and drains through fractures in the loess-like layer. Startup acceleration, deceleration pileup, front-edge pileup stopping, and middle- to rear-edge pileup stopping are the four primary discrete element simulation forecasting movement phases. The findings help deepen the understanding of similar dry-season landslides and their disaster-causing effects.Fig. 1 Geographical situation and geo-tectonic setting of H01 and H02 zoning of Qingliu landslide, Li County, Southwest China. (a. 1:500,000 regional geological map; b. High-resolution UAV orthophotography and geometric interpretation)
Electron acceleration by intense whistler-mode waves at foreshock transients
Authors: Shi Xiaofei , Artemyev Anton , Angelopoulos Vassilis , Liu Terry , Zhang Xiao-Jia
Published: February 2023

The shock wave is a primary interface for plasma heating and charged particle acceleration. In collisionless solar wind plasma, such acceleration is attributed to the wave-particle resonant interactions. This letter focuses on electron acceleration by one of the most widespread high-frequency electromagnetic wave emissions, whistler-mode waves. Using spacecraft observations of the Earth's foreshock transient, we demonstrate that intense whistler-mode waves may resonate nonlinearly with $\sim 10-100$eV solar wind electrons and accelerate them to $\sim 100-500$eV. Accelerated electron population has a butterfly pitch-angle distribution, in agreement with theoretical predictions. The presented evidence of the efficiency of nonlinear resonant acceleration suggests that this mechanism may play an important role in solar wind electron injection into the shock-drift acceleration.
Novel insights into the biochemical drivers shaping hydrogen isotope values of sugar and cellulose within a plants’ leaf
Authors: Schuler Philipp , Rehmann Oliver , Vitali Valentina , Saurer Matthias , Buchmann Nina , Gessler Arthur , Lehmann Marco
Published: February 2023

Recent methodological achievements in determining the non-exchangeable hydrogen isotopic composition (δ2Hne) of non-structural carbohydrates such as sugars allow to disentangle of so far hidden hydrogen isotope (2H) fractionation processes influencing δ2Hne of plant carbohydrates. We conducted two climate chamber experiments to have a closer look at the basic biochemical drivers of the photosynthetic 2H fractionation between water and sugar and the post-photosynthetic 2H fractionation between sugars and cellulose in leaves: First, we studied the impact of the different biochemical reactions in 10 species with C3, 7 species with C4, and 8 species with CAM carbon fixation pathways, and their response to changes in temperature and vapor pressure deficit (VPD). Second, we investigated the impact of a temperature increase from 10 to 40°C in 5°C steps under a constant VPD on leaf level photosynthesis and metabolic functioning of 7 plant species. The first experiment revealed distinct differences in the photosynthetic 2H fractionation between C3, C4, and CAM plants. In addition, the observed intensity and direction of the shifts in δ2Hne in response to changes in temperature and VPD in C3 plants was species specific, absent in C4 plants, and again species-specific in CAM plants. However, post-photosynthetic 2H fractionation was very similar among the three types of carbon fixation. We demonstrate that, in contrary to widespread believes, the 2H enrichment during post-photosynthetic 2H fractionation is driven by the carbohydrate metabolism, and not by an isotopic exchange with surrounding water. The results of the second experiment identified a plants’ metabolic activity, and its response to changes in temperature, as a major driver of the post-photosynthetic 2H fractionation of leaf sugars in C3 species. Our results clearly demonstrate that δ2Hne of plant carbohydrates are driven by plants metabolism and its response to the environment, which are species-specific. This will help to improve our current ability to interpret δ2Hne chronologies in tree rings and other plant archives, and to use 2H fractionation in carbohydrates as a novel proxy to study a plants’ metabolic properties.
Probing the 4D evolution of active magmatic systems through magnetotelluric monitoring
Authors: Hill Graham , Moorkamp Max , Avram Yann , Hogg Colin , Mateschke Kati , Gahr Sofia , Schultz Adam , Bowles-Martinez Esteban , Peacock Jared , Karcioglu Gokhan , Chen Chaojian , Cimarelli Corrado , Carrichi Luca , Ogawa Yasuo
Published: February 2023

Detection of geophysical signatures associated with a geologic event, such as a volcanic eruption, is key to understanding the underlying physical processes and making an accurate hazard assessment. Magma reservoirs are the main repositories for eruptible magma, and understanding them requires the ability to detect and interpret changes in the magmatic system from surface measurements. Traditionally, monitoring for these changes has been done with seismic and geodetic approaches, both of which require dynamic ‘active’ changes within the magmatic system. Seismic monitoring relies on the number and location of earthquakes, to indicate magma migrating within the magmatic system. In contrast, geodetic efforts rely on identifying ground inflation events which have traditionally been interpreted to represent recharge of magma from a deep parental source into shallower crustal reservoirs. Neither of these techniques is sensitive to the petrology or temperature of the magma though. Thus, additional monitoring techniques able to detect ‘static’ phase changes in the evolving magma and the thermal structure of the magma reservoir are needed. The magnetotelluric method, measures subsurface electrical properties and is sensitive to both ‘magma on the move’ and these petrological changes that occur within the magma reservoir itself. Using Mount St Helens where a detailed magnetotelluric survey was completed during the most recent dome building eruptive phase 2005-06, and is now in a period of quiescence, we compare the original measurements from 2005-06 to repeated measurements in the same locations in 2022 to develop the temporal analysis approaches required for monitoring application. In addition to the repeat campaign we have deployed 4 long-term monitoring stations with continuous data observation and telemetry to local servers. First, qualitative, comparisons of the data from different time periods indicate some significant changes in subsurface conductivity. We will present an overview of the newly acquired data and the monitoring setup and discuss where the most significant changes occur.
Stochastic Generation of Snow Depth in Canada
Authors: Abdelmoaty Hebatallah , Papalexiou Simon
Published: February 2023

Snow depth is a significant component in the hydrological cycle and global energy and water balances, contributing to climate change impacts. Weather stations with gauges for snow depth are scarce, especially in complex terrain regions, and require high accuracy for measurements. Advances in observational systems offer unconventional solutions yet are expensive. To bridge these gaps, stochastic generation methods offer a cost-effective solution to reproduce time series of hydrological variables, preserving their stochastic properties. Stochastic generation methods are well-established for total precipitation but lack snow depth generation. Here, we introduce a stochastic method to exclusively generate snow depth time series that preserve their distinct statistical properties on different time scales. We use 450 observed snow depth time series and 470 CMIP6 simulations to detect Canada's observed and physical statistical properties. The results indicate that snow depth has a light tail, and the distribution might change daily. The probability of zero snow depth shows a clear seasonal pattern. The synthetic snow depth time series can be an alternative to climate models’ outputs, offering a computationally effective solution to investigate the snow depth variability. This method advances the generation of stochastic time series of snow depth and can be applied to investigate catastrophes from snowmelt processes and avalanches that lead to severe damage and fatalities.
Novel ExpliSyT method to Correct Dynamic Measurements from Spaceborne Doppler Cloud Profiling Radars
Authors: Sy Ousmane O. , Tanelli Simone
Published: February 2023

Spaceborne Doppler profiling radars (SDPR) are among the leading instruments considered by space agencies to study atmospheric dynamics. For instance, the European and Japan space agencies are developing the Earth Cloud Aerosol Radiation Explorer (EarthCARE) mission, which will carry the first spaceborne Doppler profiling radar [1,2], while NASA is currently developing the Atmosphere Observing System mission, with a constellation of Doppler radars [3]. However, operating an SDPR from low-Earth Orbit (LEO) is challenging due to the large instantaneous speed of the spacecraft (VSAT ~7200 m/s), which affects velocity measurements by broadening the Doppler spectrum that is being measured. Three major error sources that are caused by this spectral broadening are 1) Non-Uniform BeamFilling (NUBF) biases, 2) prohibitive broadening of the measured spectral widths, and 3) a noisiness of the velocity and width measurements [4,5].In this presentation we will discuss a novel method that we have developed to overcome NUBF and spectral broadening errors that affect SDPR measurements. This method, coined the ExpliSyT approach, is based on the explicit hierarchical representation of the various Doppler moments. For instance, it allows to correct for the broadening of the measured spectral width (second-order Doppler moment), using the measured mean velocity (first-order Doppler moment) and reflectivity factor (zeroth-order Doppler moment). The resulting corrections enable accuracte retrievals of the full spectrum, which in turns enables a higher-order Doppler characterization of atmospheric dynamics. The method will be illustrated with simulations of EarthCARE’s radar, and of a notional Displaced Phase Center Antenna (DPCA) configuration developed at JPL [6]. The DPCA configuration uses a pair of collimated antennas to reduce the severity of the spacecraft-induced fading. REFERENCES:[1] A.J. Illingworth et al., “The EarthCARE satellite: The next step forward in global measurements of clouds, aerosols, precipitation, and radiation,” Bull. Amer. Meteorol. Soc., vol. 96, no. 8, pp. 1311–1332, 2015.[2] H. Kumagai, H. Kuroiwa, S. Kobayashi, and T. Orikasa, “Cloud profiling radar for EarthCARE mission,” Proc. SPIE, vol. 4894, pp. 118–125, Apr. 2003.[3] https://aos.gsfc.nasa.gov/[4] R. Meneghini and T. Kozu, Spaceborne Weather Radar. Boston, MA, USA: Artech House, 1990.[5] P. Kollias, S. Tanelli, A. Battaglia, and A. Tatarevic, “Evaluation of EarthCARE cloud profiling radar Doppler velocity measurements in particle sedimentation regimes,” J. Atmos. Ocean. Technol., vol. 31, no. 2, pp. 366–386, Feb. 2014.[6] S. L. Durden, P. R. Siqueira, and S. Tanelli, “On the use of multi-antenna radars for spaceborne Doppler precipitation measurements,” IEEE Geoscience and Remote Sensing Letters, vol. 4, no. 1, pp. 181–183, 2007.
A framework for attributing runoff changes based on a monthly water balance model: An assessment across China
Authors: He Yufen , Yang Hanbo , Liu Ziwei , Yang Wencong
Published: February 2023

During the last decades, significant changes in runoff (Q) have been reported in many regions, and attributing the changes is of great significance for water resource management. The conventionally used elasticity method based on the Budyko hypothesis neglects the impacts of climate seasonality on annual Q change (ΔQ), and it is not yet well understood how the climate change and anthropogenic activities influence seasonal Q. Therefore, we propose a framework based on the ABCD model to explicitly identify the effects of climate change and anthropogenic disturbance on annual and seasonal ΔQ, and further apply it in 191 catchments across China from 1960 to 2000. The trend in annual Q exhibits a significant (α= 0.05) decreasing trend in most northern catchments and increasing trend in some catchments of the lower reaches of Yangtze River and Southeast Basin. The trend in seasonal Q in the northern catchments shows decreasing trend during all seasons, while most in the southern catchments shows increasing trend especially in summer. Regarding the causes for annual ΔQ, climate change has positive and negative effects in 60 % and 40 % catchments, respectively, and is the dominant factor in the catchments of the Yangtze River Basin, Southeast Basin and Pearl River Basin. Human activities have positive and negative effects in 20 % and 80 % catchments, respectively, and are the dominant factor in north China. Precipitation is the dominant climatic driver in 72 % catchments. For the causes for seasonal ΔQ, climate change increases Q in southeastern catchments during all seasons, while it decreases Q in northern catchments during autumn and winter. Human activities decrease Q in more than half of the catchments except in winter. The climate seasonality cannot be ignored and our proposed framework is superior to the elasticity method in capturing the impacts of climate seasonality on ΔQ. The elasticity method causes more than 5 % deviation of the contribution ratio of climate change to ΔQ in 48 catchments. In addition, this framework is reliable on multi-annual timescales and provides important reference for water resource management.
Multi-source water vapor tomography based on ray-tracing technique
Authors: Shangguan Ming , Dang Meng , Cheng Xu
Published: February 2023

GNSS water vapor tomography has proven to be a near-real-time cost-effective method to obtain the three-dimensional distribution of atmospheric water vapor. Many previous studies have used various methods to derive the GNSS water vapor tomography. However, the number and distribution of GNSS signals limit the accuracy and spatial resolution of GNSS water vapor tomography, which could cause an ill-posed inverse problem. This study tries to use multi-source observations (GNSS, MODIS and ERA5) in Hongkong with the help of the ray-tracing technique to increase the number of signals and voxels crossed by rays for the water vapor reconstruction. Water vapor tomography are derived based on multi-source data and validated with the radiosonde data. Experimental results demonstrate that the proposed method is helpful to improve the quality of water vapor tomography.
Algorithm Stability and the Long-Term Geospace Data Record from TIMED/SABER
Authors: Mlynczak Martin
Published: February 2023

The ability of satellite instruments to accurately observe long-term changes in atmospheric temperature depends on many factors including the absolute accuracy of the measurement, the stability of the calibration of the instrument, the stability of the satellite orbit, and the stability of the numerical algorithm that produces the temperature data. We present an example of algorithm instability recently discovered in the temperature dataset from the SABER instrument on the NASA TIMED satellite. The instability resulted in derived temperatures that were substantially colder than anticipated from mid-December 2019 to mid-2022. This algorithm-induced change in temperature over one to two years corresponded to the expected change over several decades from increasing anthropogenic CO2. This paper highlights the importance of algorithm stability in developing Geospace Data Records (GDRs) for Earth’s mesosphere and lower thermosphere. A corrected version (Version 2.08) of the temperatures from SABER is described.
Development of a Rapid Seismic Loss Prediction Model for Residential Buildings using Machine Learning - Christchurch, New Zealand
Authors: Roeslin Samuel
Published: February 2023

The 2010-2011 Canterbury Earthquake sequence (CES) led to unprecedented building damage in the Canterbury region, New Zealand. Commercial and residential buildings were significantly affected. Due to New Zealand’s unique insurance setting, around 80% of the losses were covered by insurance (Bevere & Balz, 2012; King et al., 2014). The Insurance Council of New Zealand (ICNZ) estimated the total economic losses to be more than NZ$40 billion, with the Earthquake Commission (EQC) and private insurers covering NZ$10 billion and NZ$21 billion of the losses, respectively (ICNZ, 2021). As a result of the CES and the 2016 Kaikoura earthquake, EQC’s Natural Disaster Fund was depleted (EQC, 2022). This highlighted the need for improved tools enabling damage and loss analysis for natural hazards.This research project used residential building claims collected by EQC following the CES to develop a rapid seismic loss prediction model for residential buildings in Christchurch. Geographic information systems (GIS) tools, data science techniques, and machine learning (ML) were used for the model development. Before the training of the ML model, the claims data was enriched with additional information from external data sources. The seismic demand, building characteristics, soil conditions, and information about the liquefaction occurrence were added to the claims data. Once merged and pre-processed, the aggregated data was used to train ML models based on the main events in the CES. Emphasis was put on the interpretability and explainability of the model. The ML model delivered valuable insights related to the most important features contributing to losses. Those insights are aligned with engineering knowledge and observations from previous studies, confirming the potential of using ML for disaster loss prediction and management. Care was also put into the retrainability of the model to ensure that any new data from future earthquake events can rapidly be added to the model. 
Establishing a macroscopic-scale rainfall climate and water resources estimation model by machine learning method
Authors: Weng Zi-Han , Lin Yuan-Chien
Published: February 2023

With the impact of climate change and the main rainfall seasons in Taiwan are concentrated in the plum rain season from May to June and the typhoon season from July to September each year.There are significant differences in rainfall and spatial and temporal distribution between the wet season and the dry season,the droughts will occur and even lead to severe water shortages, such as the worst drought in half a century in 2021.From a macroscopic spatial scale, for example, the El Niño phenomenon and solar activity may have a certain impact on the overall climate and water resources of the earth.Therefore, this study analyzes the correlation between rainfall and large-scale influencing factors such as sunspots, El Niño-Southern Oscillation,and uses machine learning models to predict and classify rainfall under different conditions,the prediction accuracy rate through historical data can reach 89.9% , with sunspots as the most significant factor. It is hoped that relevant units can provide reference for water resources management and planning.
Observational constraints on economic impact assessments of climate change simulated by an impact emulator
Authors: Shiogama Hideo , Takakura Jun’ya , Takahashi Kiyoshi
Published: February 2023

Since many new generation earth system models (ESMs) have been suggested to be ‘hot models’ that overestimate future global warming, the IPCC AR6 used the constrained range of global warming instead of that in the raw ensemble. However, it is not clear how this advance in climate science can contribute to reducing climate-related uncertainties in impact assessments. Here, we show that the climate-related uncertainty of the economic impact of climate change in the world can be observationally constrained. By applying an impact emulator of Takakura et al. (2021, https://doi.org/10.5194/gmd-14-3121-2021), we estimate the economic impacts in nine sectors based on 67 ESMs’ future climate change projections. The impacts in eight sectors are closely related to the recent past trend of global mean temperature. Observational constraints lower the upper bound of the aggregate economic impact simulated by the single emulator from 2.9% to 2.5% of the world gross domestic product and reduce 31% of variance under the RCP4.5 or SSP2-4.5 scenarios. Please see Shiogama et al. (2022, https://doi.org/10.1088/1748-9326/aca68d) for more details.
On the Open Solar Magentic Flux Problem
Authors: Arge Charles , Leisner Andrew , Wallace Samantha , Henney Carl
Published: February 2023

The solar magnetic fields emerging from the photosphere are comprised of a combination of “closed” and “open” fields. The closed magnetic field lines are defined as those having both ends rooted in the solar surface and not extending beyond the critical point, while the “open” field lines are those having one end that extends out into interplanetary space with the other end rooted at the Sun’s surface. Of course, there are no truly “open” magnetic field lines, and those that are dragged out into interplanetary space by the solar wind eventually close in the far reaches of the outer heliosphere. Since the early 2000’s, the amount of total unsigned open magnetic flux estimated by coronal models have been in significant disagreement with in situ spacecraft observations, especially during solar maximum, with factors of two or more differences not uncommon. Estimates of total open unsigned magnetic flux using coronal hole observations (e.g., using EUV or He 10830) are in general agreement with the coronal model results and thus are in similar disagreements with in situ observations. Several possible sources producing these discrepancies have been postulated over the years such as problems with the photospheric magnetic field measurements, underestimates of the polar field strengths, coronal mass ejection (CME) magnetic fields that are still closed but counted as open, the time-dependent nature of the magnetic field (i.e., the opening and closing of magnetic fields), and the manner in which in situ observations are used to estimate total open unsigned magnetic flux. This paper provides a brief review of the problem and some of the proposed explanations to account for the discrepancies. It concludes with compelling new evidence that appears to largely resolve the problem.
A case study on multiple self-interactions of MSTID bands: New insights
Authors: Sarkhel Sumanta , Patgiri Dipjyoti , Rathi Rahul , Yadav Virendra , Chakrabarty Dibyendu , Mondal Subarna , Sunil Krishna Mallepulla Venkata , K. Upadhayaya Arun , G. Vivek Chiranjeevi , Kannaujiya Suresh , Sunda Surendra
Published: February 2023

In this study, we report a special event of nighttime southwestward propagating medium scale traveling ionospheric disturbances (MSTIDs) observed in O(1D) 630.0 nm airglow images from an all-sky imager at Hanle (32.7°N, 78.9°E; Mlat. ~24.1°N), Ladakh, India on a geomagnetically quiet (Ap = 7) night of 15 September 2018. The time sequence of airglow images unveiled two dynamic interactions between multiple dark bands of MSTID. Following the first interaction, one of the interacting bands decayed possibly due to the entrance of plasma from the ambient higher plasma density region. Shortly after this interaction, the other interacting dark band was involved in the second interaction with a third dark band which resulted in the co-alignment of the two interacting bands. Following this co-alignment, one of the bands started rotating prominently that led to further separation of these two co-aligned bands. These changes in the MSTID phase fronts (bands) are explained based on the development of the polarization electric fields arising out of the interactions. This investigation combines the all-sky 630.0 nm airglow imaging observations with TEC maps constructed, for the first time over the Indian sector, from 67 Global Navigation Satellite System (GNSS) measurements to capture the MSTID over this region. The investigation reveals a few important features of self-interactions of MSTID bands over the geomagnetic low-mid latitude transition region which is important to assess their impact over low latitudes. The highlights of these results will be discussed in the meeting.
Application of the Raman lidar for remote sensing of CO2 VMRs at several CO2 emission source areas.
Authors: Kim Daewon , Lee Hanlim
Published: February 2023

We, for the first time, developed a Raman lidar system which can remotely detect surface CO2 volume mixing ratio (VMR). Indoor CO2 cell measurements show that the accuracy of the Raman lidar is calculated to be 99.89%. We carried out the field measurement using our Raman lidar at an artificial CO2 leakage site where a CO2 leakage spot is located 0.2 km away from the Raman lidar. The results show good agreement between CO2 VMRs measured by the Raman lidar system (CO2 VMRRaman LIDAR) and those measured by in situ instruments (CO2 VMRIn-situ). The correlation coefficient (R), mean absolute error (MAE), root mean square error (RMSE), and percentage difference between CO2 VMRIn-situ and CO2 VMRRaman LIDAR are 0.81, 0.27%, 0.37%, and 4.92%, respectively. Surface CO2 VMRs were retrieved at several distances from the Raman Lidar. The average values of R, MAE, and RMSE between CO2 VMRIn-situ and CO2 VMRRaman LIDAR are 0.92, 2.78 ppm, and 3.26 ppm, respectively. We detected CO2 emitted from a stack of a resource recovery facility 450 m away from Raman lidar. CO2 VMRRaman LIDAR was in the range of 600 to 1400 ppmv.
Nitrous oxide emissions from streams in agricultural and natural areas
Authors: Audet Joachim , Veraart Annelies J. , Wrage-Mönnig Nicole , Carstensen Mette Vodder
Published: February 2023

Streams and rivers have been highlighted as significant but poorly constrained sources of nitrous oxide (N2O), a greenhouse gas ≈300 times more potent than carbon dioxide. A large share of stream N2O emissions arises from the use of nitrogen (N) fertilizers by agriculture and therefore most of the research on N2O emissions from streams has focused on agricultural areas, especially on fertile calcareous soils having near-neutral pH.However, recent research suggests that streams located in regions having low pH (<5.5) and high iron content in soils may promote disproportionally high N2O emissions. We tested this hypothesis by investigating the drivers of N2O emissions in agricultural and natural streams located in regions of Denmark where soils with low pH and high iron contents are prevalent.We measured N2O emissions monthly for a year in 10 streams located in agricultural and natural areas. Furthermore, we also measured N2O emissions four times a year in 80 streams covering a broad gradient of land-use and soil properties.The preliminary results indicate that, within agricultural and natural areas, streams with low pH have higher emissions of N2O than those with higher pH. We will compare our results with the estimates calculated using the IPCC methodology and discuss the implications of our findings for national greenhouse gas inventories.
The Contribution of GNSS Calibrated Water Vapor from Sentinel-3A/3B OLCI Sensors to Enhancing the WRF Forecasting Performance
Authors: Liu Zhizhao , Gong Yangzhao , Chan Pak Wai , Hon Kai Kwong
Published: February 2023

Assimilation of accurate external satellite-based water vapor data has been demonstrated to be able to improve the Numerical Weather Prediction (NWP) model’s forecasting performance. In this study, two types of near-infrared Precipitable Water Vapor (PWV) data from the Ocean and Land Colour Instrument (OLCI) of the Sentinel-3A and -3B satellites are assimilated into the Weather Research and Forecasting (WRF) model to enhance the weather forecasting performance over the South China area. One type is the raw PWV products obtained directly from the Sentinle-3A and -3B satellites; the other type is the Sentinel-3A and -3B PWV calibrated by PWV from Global Navigation Satellite System (GNSS). The Back Propagation Neural Network (BPNN) model is used in the PWV calibration. Correspondingly, two WRF assimilation schemes are adopted to assimilate the Sentinel-3 raw PWV and Sentinel-3 calibrated PWV. Additionally, the WRF without data assimilation scheme is used as the background run to investigate the impact of data assimilation. Three WRF experimental schemes are performed for two periods, i.e., February 2020 (dry period) and July 2020 (wet period). The forecasting performance of these three WRF schemes are evaluated by observations from GNSS, radiosonde, and surface meteorological stations. The comparison results with GNSS PWV show that assimilation of Sentienl-3 calibrated PWV can improve PWV forecasting accuracy by 5.6% for February period for the first 6 h after data assimilation. Evaluated by radiosonde profiles, the assimilation of Sentinel-3 both raw and calibrated PWV can improve WRF humidity and temperature forecasting accuracy over the July period. The accuracy improvement can be up to 9.2% (at 2 km to 3 km of altitude) for water vapor mixing ratio and 6.0% for temperature (at 4 km to 5 km of altitude). The WRF rainfall evaluation result has been validated by rainfall observations from meteorological stations and it shows that the assimilation of Sentinel-3 PWV can improve the rainfall forecasting performance over the July period. The rainfall forecasting success rates of three schemes of assimilating no data, Sentinel-3 raw PWV, and Sentinel-3 calibrated PWV are 69.4%, 69.6%, and 71.1%, respectively, over the July 2020 in the South China region.
Flooding Hazard of Union Station and Impact of Ridership due to Climate Change-an Example of Banqiao Main Station
Authors: Lin Yong-Jun , Chang Hsiang-Kuan , Ke Kai-Yuan , Lai Jihn-Sung , Tan Yih-Chi
Published: February 2023

This study adopts the rainfall scenario generated by TCCIP (The Taiwan Climate Change Projection Information and Adaptation Knowledge Platform) based on IPCC AR5, which provides the 95th percentile of Taipei’s maximum 24-hour cumulative rainfall due to climate change. The baseline of this scenario is 404 mm for 1979-2008, and the projected rainfall is 517 mm for the future mid-century (2039-2065).The flooding potentials of the Taipei Mass Rapid Transit (MRT) stations are obtained by applying the scenarios of rainfalls and the corresponding rainfall patterns of each rainfall station to a two-dimensional flood model. The flooding simulations of baseline and future scenarios show that Jingan Station and Fu-Jen University Station have the highest flooding potential, with a maximum flooding depth of 2 meters. The flooding hazard factors include flooding depth, flow velocity, and rising rate of water surface level. We adopted those factors to analyze the flooding hazard at Banqiao Main Station, which unites Banqiao Railway Station, a high-speed rail station, and Banqiao MRT station. It has a severe flooding potential and a large traffic volume. Because the mid-century rainfall is 1.43 times that of the baseline, the corresponding flooded area of the future scenario is also increased. As a result, the flooding hazards around the exits of Banqiao Main Station are high within the 300 m buffer for the baseline. In contrast, the very high flood hazard was found in a 200m-300m buffer for the future scenario.  MRT Banqiao Station has 5 entrances/exits, while Banqiao Railway Station has 6 entrances/exits, a total of 11. The average daily ridership at this union station before Covid-19 is 159,239 people/day. The impact ratio of the ridership is set by the degree of flood hazard for each entrance/exit. In the future scenario, the number of affected people is roughly estimated to be 11,611 people/day, which is about 7% of daily ridership before Covid-19.
Overshooting the critical threshold for the Greenland ice sheet
Authors: Bochow Nils , Poltronieri Anna , Rypdal Martin , Robinson Alexander , Boers Niklas
Published: February 2023

Global sea level rise due to the melting of the Greenland ice sheet (GrIS) in response to anthropogenic global warming poses a severe threat to ecosystems and human society (IPCC, 2021). Modelling and paleoclimatic evidence suggest that rapidly increasing temperatures in the Arctic can trigger positive feedback mechanisms, and the GrIS is hypothesised to exhibit multiple stable states (Gregory et al., 2020). Consequently, critical transitions are expected when the global mean surface temperature crosses specific thresholds, and there is substantial hysteresis between the alternative stable states (Robinson et al., 2012). Here, we investigate the impact of different climate scenarios that overshoot temperature goals and then return to lower temperatures at different pace. Our results show that both the maximum GMT and the time span of overshooting given GMT targets are critical in determining GrIS stability. We find an abrupt loss of the ice sheet for a threshold temperature, preceded by several intermediate stable states. We show that even temporarily overshooting the temperature threshold may lead to catastrophic consequences in specific scenarios. On the other hand, overshoots might be tolerable if GMTs are subsequently reduced below 1.5°C GMT above pre-industrial levels within a few centuries. Even without a transition to a new ice sheet state the short-term global sea level rise can exceed several metres before returning to moderate GMTs.Allan, R. P., Hawkins, E., Bellouin, N., & Collins, B. (2021). IPCC, 2021: Summary for Policymakers (V. Masson-Delmotte, P. Zhai, A. Pirani, S. L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M. I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J. B. R. Matthews, T. K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, & B. Zhou, Eds.). Cambridge University Press. https://centaur.reading.ac.uk/101317/Gregory, J. M., George, S. E., & Smith, R. S. (2020). Large and irreversible future decline of the Greenland ice sheet. The Cryosphere, 14(12), 4299–4322. https://doi.org/10.5194/tc-14-4299-2020Robinson, A., Calov, R., & Ganopolski, A. (2012). Multistability and critical thresholds of the Greenland ice sheet. Nature Climate Change, 2(6), 429–432. https://doi.org/10.1038/nclimate1449
Experimentally revisiting the REE partition coefficients between zircon and silicate melt
Authors: Shang Sheng , Lin Yanhao
Published: February 2023

Zircon is an important silicate mineral to help understand the evolution of geochemistry and genesis of magma in early planets. The composition of evolved magma can be deduced from the concentrations of elements in zircon and their partition coefficients between zircon and silicate melt. Although the phosphorus (P) contents range from ~100 to ~100000 ppm in extraterrestrial zircon, the effects of P on REE partition coefficients between zircon and silicate melt are still debated. Here we have studied the effect of P contents on the partition coefficients of elements between zircon and silicate melt using high-temperature experiment. With the increase of phosphorus content, the partition coefficients of alkaline elements and Al between zircon and silicate melt show a negative and positive trend, respectively, and there is no effect on itself and Ti. It is worth mentioning that phosphorus content has a negligible effect on REE partitioning, indicating that the REE partition coefficients in this study can be applied to extraterrestrial zircon even with varying P concentrations. After filtering out altered zircon and combining the experimentally updated partition coefficients of REE, the characteristic of evolved melt equilibrated with early protogenetic zircon can thus be yielded and then help to understand early magmatism on the planets. 
Probabilistic Seismic Hazard Assessment of Assam, North-East India with the Incorporation of Topography Based VS30 Values
Authors: Borah Mayuri , Dubey Ramanand , Das Josodhir
Published: February 2023

In this study, Probabilistic seismic hazard assessment (PSHA) is performed for Assam, North-East (NE) India. NE India being bounded by latitude 200-300 N and longitude 870-980 E, is considered as one of the most earthquake-prone areas in the world. As per seismic zoning map of India (IS 1893 (2016), Part 1), most of the states in NE region have been placed in seismic zone V, which has the highest zone factor in the country. Among the eight north-eastern states, Assam serves as the gateway to the other seven states. As this region lies on one of the most vigorous tectonic plates in the world, it has experienced several devastating earthquakes in the past. Considering the seismicity of this region, seismic hazard assessment plays a significant role to assess the seismic risk for the future. The NE India region is broadly divided into four seismogenic sources, and further sub-divided into nine seismogenic sources based on the tectonic features and seismicity characteristics. For the study of hazard assessment, a unified moment magnitude catalogue has been used, where the events are assembled from various databases (ISC, IMD, USGS-NEIC). The catalogue has been declustered and the seismicity parameters are calculated for each source zone. The hazard maps have been presented at the bedrock level, in terms of peak ground acceleration (PGA) and spectral acceleration (Sa) values. The PGA values vary in between 0.16-0.57 g, while the Sa values are obtained in the range of 0.12-0.77 g. Further, topography based VS30 values have been considered for all the source zones and hazard maps are prepared with the incorporation of the site-specific VS30 values. These hazard maps are expected to give insight to the local site-specific seismic hazard variation for the Assam region and would be useful for the preparedness of risk and disaster mitigation measures.Keywords: PSHA, NE India, Assam, PGA, Hazard Map