bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of lake drainage events in Antarctica from SAR imagery
Authors: Vomero Mariapina , Thompson Sarah , Cook Sue , Kulessa Bernd
Published: February 2023

Supraglacial lakes are expected to play a crucial role in determining the ice sheet mass balance in a warming climate. Water ponding lowers the albedo of the ice surface, establishing a positive feedback of melting processes that might be further enhanced by the projected rising temperatures. Lake drainages can have particularly large impacts on ice shelves depending on their location and surrounding topography. Drainage events on grounded ice can transport water to the ice/bedrock interface, affecting the sliding of the ice sheet. On floating ice shelves, lake drainage events have been linked to fracture formation potentially leading to ice shelf collapse.Over the past decade, observations of supraglacial lake drainage events have mainly been gathered from the Greenland ice sheet, while observations of drainage events remain rare in Antarctica. While some limited examples have been reported in the literature, it is not yet known how common these events are, the likelihood of their formation from the grounding line, and how their recurrence could impact Antarctic ice shelves. Observations of Antarctic supraglacial lake drainages are challenging as the lakes often have lids of ice covering liquid water, and drainages can occur in winter when low light levels preclude the use of optical sensors. Since Sentinel-1 SAR imagery works independently from light and cloud conditions, it enables continuous monitoring throughout the year providing further insights into their spatial and temporal evolution. The use of Google Earth Engine (GEE) platform for analyzing SAR images and detecting drainage events has shown the value of this platform as a tool to monitor changes over several locations and to efficiently deal with the increasing workload of satellite data. Here we demonstrate the use of SAR backscatter to reliably detect drainage events to map their location also during the winter months and to locate their prevalence around the Antarctic coastline.
Impacts of a layer snow density evolution scheme on the Arctic snow simulation based on the CICE sea-ice model
Authors: Yin Hao , Su Jie
Published: February 2023

Snow plays a vital role in the coupled ocean-ice-atmosphere system with its unique thermodynamic properties. Snow density is set to be a constant (about 320 kg·m-3) in most present sea ice models, ignoring the seasonal evolution of density and relevant thermodynamic regimes. We introduced the layered snow density evolution scheme into the Los Alamos Sea Ice Model (CICE), making it possible to access the diagnostic time-varying snow density. Forcing by ERA5, the modeled results of both CICE and its one-dimension submodule Icepack were compared with buoy observations (Ice Mass Balance buoys, IMB), remote sensing (The advanced Microwave Scanning Radiometer 2, AMSR2), as well as model results from SnowModel-LG, one of the popular snow models with the most sophisticated physical processes.The monthly average snow density absolute bias between the results of the improved CICE and SnowModel-LG, is about 30±13 kg·m-3 in most months except Jul. and Aug. Relatively fresh snow density is found in SnowModel-LG results because most of the winter snow has melted in these two months, while old snow still remains in CICE. This causes a 100~200 kg·m-3 differences of snow density in the two results in this period. The annual mean (1990~2018) contribution of strain compaction, fresh snowfall, and wind compaction on the density evolution is about 1:-16:17.5, respectively, with the effects of the latter two compensating each other and out to a value of the same magnitude as the first component. Verification of the 1D results with 42 IMBs observations showed great agreements among snow depth (Hs), ice thickness (Hi), and snow/ice temperature (Ts/Ti) in the standard Icepack run with constant snow density. Several improvements were found in the new simulations of Hs (reduce 30% of 3 cm overestimation), Hi (reduce 34% of 0.04 m overestimation), and Ts/Ti (increase 50% of 1.4°C underestimation for snow and 10% of 0.7°C underestimation for ice, respectively) with the layered snow scheme in the winter seasons. In 2D CICE model, the implement of new snow parameterization improved the simulation of Hs in the Central Arctic (CA, north of 80°N) obviously. The overestimated 5 cm Hs under the standard CICE run can be reduced about 10% in the new experiment relative to the AMSR2 retrieval snow depth data in winter (Nov.-Apr.) from 2013 to 2018.
Martian Ionospheric Magnetic Fluctuations
Authors: Esman Teresa , Espley Jared , Gruesbeck Jacob , Fowler Christopher , Xu Shaosui , Elrod Meredith , Harada Yuki , Giacalone Joe , Halford Alexa , Verbiscer Anne
Published: February 2023

Understanding the properties and variability of the ionosphere is vital for understanding the atmosphere of Mars. The presence and property of waves provide insight into the plasma and magnetic environment. We conducted a search for 5 - 16 Hz signals below 400 km in magnetic field data from Mars Global Surveyor (MGS), the Mars Atmosphere and Volatile Evolution (MAVEN), and Interior Exploration using Seismic Investigations, Geodesy, and Heat Transport (InSight) missions. We discuss an analysis of 54 identified MAVEN events using multiple instruments and present a case study event. Nearly half the wave events occur near the cusps of strong crustal magnetic fields (CMFs). The stronger regions have fewer events and may be a result of stronger CMFs preventing draped field lines from reaching lower altitudes. A majority of the observed magnetic waves occur on the nightside, are associated with greater fluxes of electrons traveling downward along the local magnetic field compared to those traveling upward, and correspond to increases in thermal plasma density. These aspects indicate electron precipitation was present during these wave events. We conclude that these waves are observed under magnetic field conditions favorable for the penetration of electrons and waves into the lower ionosphere, but that the electron precipitation cannot solely account for the waves or plasma changes.We then discuss our null results regarding Schumann resonances, which are electromagnetic signals generated by lightning that, if they exist on Mars, are expected to propagate at 7-14 Hz. Future studies specifically looking for Schumann resonances will require higher sensitivity instruments and would benefit from additional missions that reach into the ionosphere of Mars. Finally, we comment on the inconsistency between identifying MGS events purely via by-eye analysis versus using quantitative methods for guidance.  
Modification of magnetosheath jet occurrence and properties within CMEs and SIRs
Authors: Koller Florian , Plaschke Ferdinand , Preisser Luis , Temmer Manuela , Roberts Owen , Vörös Zoltan
Published: February 2023

Large-scale solar wind (SW) structures like coronal mass ejections (CMEs) and stream interaction regions (SIRs) significantly alter the plasma within the Earth’s magnetosheath and change the foreshock region. Thus, they modulate the number and the parameters of dynamic pressure transients in the magnetosheath, which we call magnetosheath jets. We use THEMIS spacecraft data from 2008 to 2022 to detect these jets in the magnetosheath and OMNI data for the SW within the same time range. We investigate which properties in each SW structure primarily influence the jet occurrence. We find that CMEs cause a reduction in jet occurrence due to the mix of high magnetic field strength, high plasma beta, low Mach number, and high cone angles. These conditions most likely disrupt the building of a proper foreshock region and thus hinder the major generation mechanism for jets in the magnetosheath. On the other hand, high speed streams in SIRs show favorable conditions for jet generation in all plasma parameters, most importantly due to the high probability for low cone angles, the low density, high velocity, and low magnetic field strength. We analyze how the jet parameters differ in each type of  SW structure and discuss how this influences the geoeffectiveness of jets.
Conductivity Anomalies before M > 6 Earthquakes in China during 2014 – 2019
Authors: Mao Zhiqiang , Chen Chieh-Hung
Published: February 2023

The North-South Seismic Belt of China is one of the most active seismic areas on the Chinese continent.  More than ten strong earthquakes (Ms > 6) have occurred in this region since 2010.  However, Earthquake-related conductivity anomalies are rarely reported for those earthquakes.  In this study, 3-component geomagnetic data recorded at sixty geomagnetic stations are selected to compute the Parkinson vectors to monitor the changes of conductivity before and after the earthquakes.  Considering most fluxgate magnetometers have only been installed since 2014, we concentrate on six Ms > 6 earthquakes occurred during 2014–2019.  To mitigate artificial disturbances, low noise data during the 00:00 – 5:00 LT are utilized.  We compute the background distribution and monitoring distribution using the azimuth of the Parkinson vectors at each station within six years (2014 – 2019) and a 15-day moving window, respectively.  The background distribution is subtracted from the monitoring distributions to mitigate the influences of underlying inhomogeneous tectonic structures.  The obtained difference distributions binned by 10° within 400 km from each station are superimposed during 60 days before and after the earthquake to construct integrated maps.  To analyze the potential frequency characteristics, we compute the results from low to high frequency band.  The results show that for four earthquakes, the conductivity anomalies areas appear near the epicenter 10 to 20 days before earthquakes, while the rest two earthquakes have no anomaly.  The conductivity anomalies appear at all study frequency band from 0.0005 Hz to 0.1 Hz, and significantly at 0.001 – 0.005 Hz before earthquakes.  Meanwhile, we find that the lower frequency band corresponds to larger anomalies area.  These results suggest the change of underlying conductivity near the hypocenter is a possible phenomenon for strong earthquakes, and the frequency characteristics of the seismo-conductivity anomaly during the earthquake are helpful to understand the pre-earthquake anomalous phenomena.
Regional Ocean model validation in simulating the low frequency variability over the Maritime continent
Authors: Zachariah Johnson , Faller Daiane , Gangadharan Nidheesh , Thompson Bijoy , Tkalich Pavel
Published: February 2023

Resolving the regional ocean circulation is a key factor in the understanding of climate-driven oceanic variability. Accurate sea level simulation, in the areas at the interface between land and ocean, could help to mitigate the environmental, social and economic damages caused by sea level rise and extremes. This is particularly the case for the seas in the Southeast Asia region (SAR), where the ocean circulation is complex owing to unique geographic and oceanographic features of the region. In order to overcome the caveats due to sparse sampling of this domain regional configuration of the ocean model (NEMO) is set up for the SAR (90oE-142oE; 18oS-26oN) with 51 vertical sigma levels and hindcast simulations are performed for the period 1958–2021 using the downscaled ERA5 (surface forcings) and ECMWF global ocean reanalysis (ORAS5) data as lateral boundary conditions. This paper describes the dominant phenomena and model performance in simulating the low-frequency variability of the seas in the SAR with a focus on sea level, SST and ocean currents. The comparison of simulations with tide gauges and satellite altimetry observations yields good match. Correlation analysis between the simulations and air-sea coupled phenomena like El Nino southern Oscillation (ENSO) and Pacific decadal oscillation (PDO) reveals significant correlation which provides the confidence for further research of the low-frequency ocean variability in the SAR.
Keywords: Validation (SSH) with Tide-gauges, Satellite, SST with Reanalysis, Observation, Maritime Continent
Assessing the attribution of alpine glacier mass loss to anthropogenic warming over the last millennium using ensemble paleoclimate reconstructions and GCM simulations
Authors: Otto Daniel , Roe Gerard , Christian John
Published: February 2023

The central estimate of the Intergovernmental Panel on Climate Change is that the magnitude of anthropogenic warming since 1850 is equal to 100% of the observed warming. However, the IPCC is notably much more timid in attributing glacier mass loss to anthropogenic warming over the same period. Disagreements have arisen in previous research, primarily stemming from ambiguity in the dynamic disequilibrium of preindustrial glaciers and its lingering effects. Accounting for variability in glacier disequilibrium entering the industrial era, Roe et al., (2021) used simple glacier models and synthetic climate scenarios to estimate  a mass-loss attribution of ˜100% [90-130%, likely range] over the full industrial era. Our work further assesses this claim for a case study of glaciers in North America and the Alps using: i) realistic ice dynamics, ii) observed glacier geometries, iii) ensembles of last-millennium reconstructions (LMR) and GCM simulations, and iv) a comprehensive sensitivity and uncertainty analysis. In addition to CMIP6 past1000 simulations, we use recently developed LMR paleoclimate reconstructions, specifically adapted for melt-season temperatures. By using millennial-scale climate time series, we avoid the need for an accurate initial condition. We simulate glacier mass-balance and length fluctuations over the last millennium for a variety of potential climate histories to produce an uncertainty envelope for each glacier’s preindustrial state. For our case-study of glaciers, we find that all: i) exhibited slow growth over the last millennium, ii) have lost mass over the industrial era, and that iii) the magnitude of industrial-era mass loss for each glacier greatly exceeds natural variability over the last millennium. Given that 100% of industrial-era temperature change is attributable to anthropogenic activity, these results imply that mass loss for these glaciers can be confidently attributed to anthropogenic warming since the beginning of the industrial era (1850 vs. the IPCC’s 1990). Work is ongoing to expand the analysis scope to a larger network of well-observed glaciers, with potential for a global assessment in the future.
Development of an operational snow energy balance model informed by numerical weather prediction and remote sensing for the Western United States
Authors: Skiles McKenzie , Meyer Joachim , Ragar Dillon , Kormos Patrick , Hedrick Andrew
Published: February 2023

The Colorado River, which supplies water to the Western United States (WUS) and Mexico, is fed primarily from snow melting out of the Rocky Mountains. Currently, snowmelt contribution to streamflow is forecast using a calibrated temperature index model (SNOW-17). This approach is simple, and computationally efficient, but loses efficacy when snow conditions are outside the calibration period as temperature index models do not represent all of the physical processes that control accumulation and melt rates. For example, in the southern headwaters of the Colorado River forecasting errors have been related to surface darkening and accelerated melt following episodic dust on snow events. Here, we present an ongoing project to develop and mature a spatially distributed snow energy balance model, informed with numerical weather prediction (NWP) and remote sensing, to support operational decision making. This effort is a collaboration between the University of Utah's Snow Hydrology Research to Operations (Snow HydRO) Laboratory, the USDA-ARS Northwest Watershed Research Center (NWRC), and the Colorado Basin River Forecast Center (CBRFC). The model, iSnobal, is forced with the High Resolution Rapid Refresh (HRRR) NWP and is assessed against in situ observations and snow depth maps from the Airborne Snow Observatory in representative headwater basins. Initial testing of the HRRR-iSnobal combination showed that it can simulate snow accumulation, in terms of both patterns and magnitude, but that snowmelt rates were too slow. This was attributed to inaccurate radiation balance, specifically shortwave radiation due to the traditional treatment of net shortwave, including a 'time since snowfall' albedo decay curve. To account for spatial and temporal variability in snow albedo, daily observations from the spatially and temporally complete MODIS fractional snow products (MODSCAG+MODDRFS) were incorporated to update net solar radiation inputs. The updates were tested in different ways including direct albedo updates, direct decay curve component updates, and basin specific calibration decay curves. Although all remote sensing based update approaches improved snowmelt timing, direct updates had the greatest improvement in years with more intense snow darkening. This presentation will include a summary of current results, updates on incorporation into operational forecasting, and highlight plans for future developments.
Uncertainties in global future projection of potential evapotranspiration using SSP scenarios
Authors: Song Young Hoon , Chung Eun-Sung , Chae Seung Taek , Kim Jin Hyuck
Published: February 2023

Evapotranspiration (ET) is the amount of water lost from the global surface, and it represents water and Earth's energy cycle. The intensity and frequency of climate variables have been changed because of the ongoing climate crisis, leading to increased climate disasters, such as heat waves and droughts. The abrupt climate crisis affects the variation of ET because climate variables highly influence ET. However, the future potential ET (PET) estimates include various uncertainty resulted from the variations in the projection of climate variables. In this context, the uncertainty in the projected future PETs should be quantified for the high reliability. Therefore, this study projected future global PET using Penman-Monteith (PM) for the near (2031-2065) and far (2066-2100) futures and quantified the corresponding uncertainty. The six climate variables of 14 CMIP6 GCMs were used for estimating historical PET which were compared to those from the NCEP/NCAR reanalysis data using the five evaluation metrics. The changes in PETs for four Shared Socio-economic Pathways (SSPs) scenarios were calculated for the near and far futures compared to the historical period (1980-2014). Subsequently, the uncertainties of PETs were quantified using the reliability ensemble average method. As a result, the future PET in high latitudes showed the most significant variability compared to the other latitudes. The future PET in the southern hemisphere was higher than the historical PET. Especially the PET in the mid-latitudes of southern hemisphere was the highest among the other latitudes. In addition, the uncertainty of PET was the highest in the high latitudes of the northern hemisphere while the mid-latitude in the northern was the lowest. This study provides insight into evaluating the global water cycle based on PET and helps establish appropriate policies for climate impact assessment.
A proposal to use “Isoscapes” of fugitive gases from oil and gas wells to facilitate the reduction and attribution of methane emissions and plugging of faulty wells
Authors: Gonzalez Arismendi Gabriela , Muehlenbachs Karlis
Published: February 2023

Canada is the third largest oil and gas producer, with over 500,000 active and inactive wells, mostly located in the Western Canada Sedimentary Basin (WCSB). A large, undetermined fraction of Canada’s GHG emissions emanate from oil and gas infrastructure. Governments and industry are all committed to immediately reducing methane leaks to the atmosphere from surface casing vent flows (SCVF) and ground migration (GM) of both new and old wells. Methane carbon isotopic composition offers insight into the source of unwanted gas emissions. A geospatial tool would help to attribute and reduce GHG emissions from contour maps of ẟ13C of methane and other hydrocarbons of production, SCVF, and GM gases across the WCSB. These “Isoscapes” of production gases vary systematically, reflecting the local geology. SCVF and GM isoscapes are offset from the production ones because the SCVF most often are shallower than the target formations, and the GM gas may be oxidized in soils. The difference between the production and SCVF isoscapes can be used to attribute methane emissions from tanks and production infrastructure, compared to leaks from the wells themselves. The isoscapes directly facilitate the plugging of problem wells.  The maps are based on over 3,000 locations where we used isotope fingerprinting (i.e., Rowe & Muehlenbachs, 1999) to identify the source depth of a leak.  Regulatory measurements mandate that the leaks are sealed at their source depth, greatly adding to the cost of plugging any well. The SCVF isoscapes suggest the likely source depth of an unsampled leaking well, thus greatly simplifying its remediation. Applying such information beyond a local case study may contribute to accounting for the GH contribution from regional oil and gas activities in Canada and elsewhere.  ReferenceRowe, D., & Muehlenbachs, A. (1999). Low-temperature thermal generation of hydrocarbon gases in shallow shales. Nature, 398(6722), 61­-63.
Source characterization of VOCs at a coastal site in Hong Kong
Authors: Yuan Qi , Wang Meng , Wang Tao , Lee Shuncheng
Published: February 2023

Volatile organic compounds (VOCs) are important gaseous constituents in the troposphere, impacting local and regional air quality, human health, and climate both directly and indirectly (IPCC, 2013). With the participation of nitrogen oxides (NOx), oxidation of VOCs leads to tropospheric ozone (O3) formation, causing regional photochemical smog (Atkinson, 2000). In recent years, with the decline of ambient concentrations of other pollutants (e.g., fine particulate matter), the concentrations of O3 in many locations increased. Therefore, accurately apportioning the emission sources of ambient VOCs and then controlling them more effectively will play an important role in reducing O3 and secondary organic aerosol pollution in the atmosphere and improving public health.  In this study, field measurements were conducted at a coastal site (Hok Tsui; HT) in Hong Kong from October to November 2020 with proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS). VOC data coupled with air mass back trajectory cluster analysis and receptor modelling were applied to discuss the pollution pattern, regional transport, and emission sources of ambient VOCs at Hok Tsui in autumn 2020. Seven sources were identified from positive matrix factorization (PMF) analysis, namely vehicular + industrial, solvent usage, primary oxygenated VOCs (OVOCs), secondary OVOCs 1, secondary OVOCs 2 (aged), biogenic emissions, and background + biomass burning, contributing on average to 20.8%, 10.5%, 13.1%, 33.6%, 6.7%, 4.3%, and 10.9% of total VOC mixing ratios, respectively. Secondary OVOCs and vehicular + industrial emissions are the vital sources of ambient VOCs at Hok Tsui supersite. Integrated with backward trajectory analysis, long-range transport of air masses from inland and coastal regions of Southeast China brought more hydrocarbons from vehicular and industrial sources, and consequently more OVOCs in aged air masses. The results of this study highlighted the regional transport of anthropogenic VOCs should be considered in control strategies of VOCs and secondary air pollutants.
Updating sea-level reconstruction since 19
Authors: Wang Jinping , Church John Church , Zhang Xuebin , Chen Xianyao
Published: February 2023

Sea-level rise integrates the responses of several components (ocean thermal expansion, mass loss from glaciers and ice sheets, terrestrial water storage). Before the satellite era, global sea-level reconstructions depend on tide-gauge records and ocean observations. However, the available global mean sea level (GMSL) reconstructions using different methods indicate a spread in sea-level trend over 1900-2008 (1.3~2.0 mm yr-1). With the improved understanding of the causes of sea-level change, here we update the original Church and White (2011) reconstruction by using the latest observations, taking the time-evolving sea-level fingerprint, sterodynamic sea level (SDSL) climate change pattern and local vertical land motion (VLM) into account. The updated trend of GMSL of 1.6 ± 0.2 mm yr-1 (90% confidence level) over 1900-2019 is consistent with the sum of contributions of 1.5 ± 0.2 mm yr-1, slightly lower than 1.8 ± 0.2 mm yr-1 from original reconstruction. The lower trend from the updated reconstruction is mainly due to including residual VLM correction. The trends at tide gauge locations from updated reconstruction agree better with the tide gauge observations, with comparable mean trend of 1.7 mm yr-1 (standard deviation; STD of 2.0 mm yr-1) from observation and 1.7 mm yr-1 (STD of 1.2 mm yr-1) from the updated reconstruction. The inclusion of sea-level fingerprint and SDSL climate change pattern are the dominant contributors for improved reconstruction skill on regional scales at tide gauge locations. This update leads to GMSL solution that are consistent with other reconstructions in terms of long-term trend and 30-year running rate.
Effects of freshwater injection on tidally influenced coastal unconfined aquifers
Authors: Yu Xiayang , Xin Pei , Luo Zhaoyang , Pu Li
Published: February 2023

Freshwater injection is a practical and efficient solution to mitigate seawater intrusion in overexploited coastal aquifers. Previous studies predominantly considered isothermal conditions and overlooked temperature contrasts. How thermal effects of freshwater injection regulate flow processes and salinity distributions is poorly understood. This study investigated the dynamic characteristics of salinity distributions and seawater recirculation in coastal aquifers subjected to freshwater injection and tides. The processes were simulated using SUTRA-MS (a model simulating porewater flow coupled with salt and heat transport). The transience of upper saline plume and saltwater wedge responding to injected freshwater will be discussed here in detail. We will also discuss the thermal plume-induced changes in salinity distributions and water effluxes. Finally, the overshoot of total water efflux in response to the thermal impacts of freshwater injection will be discussed.
An Advanced Deep Learning Rainfall Forecasts Downscaling Method in Taiwan
Authors: Chang Rong-Cih , Cheng Yung-Yun , Chen Buo-Fu
Published: February 2023

Taiwan is a 35,808-km2 island with more than 100 peaks over 3,000 meters. The complex terrain in Taiwan makes forecasters more challenging to forecast rainfall in mesoscale and storm-scale. Besides, the spatial distribution of rainfall stations is quite uneven as well. Moreover, the forecast performance of both the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Global Forecast System (GFS) is limited by Taiwan's complex terrain, having certain systematic deviations in rainfall forecasts. For example, the ECMWF forecast has underestimated heavy rainfall and over-predicted light rain in Taiwan. Consequently, to correct model deviations and provide better rainfall forecast products, advanced statistical or artificial intelligence (AI) methods should be studied.This research applies the U-net neural network to generate downscaling rainfall prediction. We collected precipitation forecast data from the ECMWF (9 km resolution) and the GFS (22 km resolution) during 2021 as the model input. The Quantitative Precipitation Estimation and Segregation Using Multiple Sensor (QPESUMS) radar data from CWB is used as the label data. QPESUMS data can effectively help describe the complete spatial distribution of rainfall. The testing data is from the 2022 whole year. An innovative design of the proposed model is a geographical attention layer (GAL) in the U-net. The GAL helps to learn the geospatial characteristics from the QPESUMS rainfall observation. Moreover, this study uses a scale-separated loss function for model optimization, for which the rainfall is divided into large-scale smoothing and small-scale disturbance fields.Results show that this U-net downscaling model successfully learns the feature and corrects the systematic bias in both global models, such as shifts in the rainfall caused by topographical lift and local circulation. Furthermore, based on the overall statistics of 2021, the performance diagram shows that the AI model corrects the over-prediction of light rain, while the critical success index in heavy rain is improved by 25 to 30%. The ongoing work of this research will apply generative adversarial networks to break the limitation of learning wrong features from the original forecast input data.
Hydrothermal activity characteristics, types of hydrothermal alteration and exploration direction in Gudui high temperature geothermal field, Tibet
Authors: Cao Rui , Dor Ji , Meng Huiren
Published: February 2023

The Qinghai-Tibet Plateau, located in the world-famous Mediterranean-Himalayan tropics, is the most intensely tectonically active region of the Cenozoic in mainland China. Accompanied with a large amount of hydrothermal activity and energy generation, this region had the greatest potential and concentration of high-temperature geothermal resources in mainland China. The Gudui geothermal field, located in the central Cone-oiga rift, is a shallow buried high-temperature geothermal field with the greatest power generation potential. In order to analyze the types and distribution characteristics of sinter and hydrothermal alteration, the favorable exploration direction and heat-controlling structure of Gudui geothermal field, the geothermal geological investigation, microscopic identification, and scanning electron microscope analysis were carried out. The hydrothermal alteration types, such as chloritization, silicification, kaolinization and carbonation, and sinters such as travertine, geyserite and sulphur, were identified. Three groups of faults were developed in the Gudui geothermal field with respect to the heat-controlling structure. The early EW faults are mostly reverse faults, and the later NE or NW secondary faults are mostly extensional faults as the main channels of geothermal fluid.The distribution of hydrothermal alteration is controlled by normal fault, of which alteration center is mainly located at the junctions of faults, and extends along the faults. An obvious hydrothermal alteration zonation was existed in the Gudui geothermal field, which extends from acidic alteration to weak acidic-neutral alteration, and the alteration center is mainly composed of extensively altered silicification or kaolinization zones. The distribution and intensity of hydrothermal alteration implies that the Bushonglanggu and Shagalanga geothermal display area have enormous resource potential. Therefore, geothermal exploration in Gudui geothermal field should focus on the Bushonglanggu and Shagalanga geothermal display area. with respect to hydrothermal deposition, the west area of Gudui geothermal field is dominated by travertine, and the east area is characterized by the coexistence of travertine and siliceous sinter. Furthermore, combined with the dynamic background of Qinghai-Tibet Plateau, an obvious coupling relationship exists between hydrothermal history and the uplift of Qinghai-Tibet Plateau during continent-continent collision and the activity of the Cone-oiga rift.
Data-driven Versus Expertise-based AI Prediction of Industrial Air Pollutants
Authors: Choi Seunghui , Kam Jonghun , Lee Kwanghun
Published: February 2023

With the development of industrialization, air pollution problems are rapidly accelerated. Industrial air pollutants can deteriorate human lives while accelerating global warming. Thus it is important to figure out the variables that affect air pollutants in an industry. With the growth of artificial intelligence, many researches on the prediction of industrial air pollutants have been conducted to prove high performance. Yet the prediction of the air pollutants with the data-driven selected input was not evaluated compared to the expertise-based input. Herein, we predicted emissions of nitrogen oxides (NOx), sulfur oxides (SOx), and total suspended particles (TSP) at once in a heat recovery steam generator system by constructing four different multivariate AI models; a random forest regressor, a shallow long-short term memory (LSTM), a shallow bidirectional LSTM (BiLSTM), and a BiLSTM based autoencoder (BiLSTM-AE). The input of a prediction model was selected by combining the results of three univariate random forest regressors where one model predicts each air pollutant and a multivariate random forest regressor. Through average one-minute predictions to averaged 30-minute predictions, we compared the performances of the AI models. Among all of them, the random forest regressor showed the best performance for predicting NOx and SOx, and the BiLSTM-AE for predicting TSP with respect to the mean absolute error. We also compared the sensitivity by differentiating input variables of the BiLSTM-AE, the data-driven and the expertise-based selection. We constructed a multivariate random forest to examine the importance of each variable in the prediction of three air pollutants. Both the data-driven input and the expertise-based input include the gas turbine variables and some thermal variables as important variables. As a result, the expertise-based input may be good standards, but the data-driven input can be complementary to the expertise-based input for generalization and ease of selection. This study enables self-diagnosis and proactive action for each industry to regulate its air pollutants in advance of the law regulation.
Atmospheric moisture exchanges between the Magdalena River basin and its surroundings.
Authors: Giraldo Ramirez Paola Andrea , Molina Santamaria Ruben Dario , Salazar Villegas Juan Fernando
Published: February 2023

Atmospheric moisture transport is a fundamental process in the climate system, critical for the hydrological cycle and water security on land. Moisture exchanges between a basin and its surroundings determine water availability and may change over time due to climate change and other human impacts. Understanding how and why these atmospheric fluxes change under global change is critical for river basins supporting water security in different regions. Here we focused on the Magdalena River basin in northwestern South America, a critical basin for water and energy security in Colombia. We quantified moisture exchanges for the entire watershed and different segments (defined by the boundaries between neighboring basins). We used monthly data between 1979 and 2021 from the ERA5 reanalysis to look for possible changes, including trends. Our results provide new insights into the dynamics of moisture exchanges between the basin and its surroundings. In addition, we found evidence of statistically significant trends likely related to anthropic effects, mainly deforestation and climate change. These results have implications for water security analyses in this region, where there are few studies of this type, and simultaneously generate new insights for decision-making related to water management and transboundary water security in the Magdalena river basin.
Wildfire burned area detection using with Sentinel-2 and UNet
Authors: Park So Ryeon , Son Sanghun , Bae Jaegu , Lee Doi , Ryu Minji , Seo Jeong Min , Kim Jinsoo
Published: February 2023

Air pollutants, such as large amounts of carbon dioxide produced by fire, are at risk of promoting global warming, causing more frequent and more wildfires all over the world. Large-scale wildfires cause air pollutants to spread, resulting in a significant increase in fine dust concentration. And human damage, property damage, and natural ecosystem damage are increasing. Rapid and accurate information of fire damaged the forest areas using high-resolution satellite imagery is effective in preparing wildfire prevention measures and monitoring burned areas. In this regard, the many research is underway to estimate fire burn damage using the difference spectral feature between healthy forests and burned forests. There are many spectral indices including well-known indices such as NDVI(Normalized Difference Vegetation Index) and NBR(Normalized Burn Ratio). It is possible to estimate burned area by computing a difference image representing a change in the spectral wavelength of the image between pre- and post-fire. In the case of South Korea, it is difficult to estimate wildfires because the spectral characteristics of vegetation vary from each season according to climate. And Compared to other countries, Forest fires are occurring small scale of forest fires less than 2,000ha. In our study, the accuracy was compared by applying various spectral indices to the estimation and evaluation of burned area in South Korea, using one of the deep learning models U-Net. As a result of the IoU value of 0.80 or more, it was confirmed that it was possible to calculate the forest fire damage site.Acknowledgments:This research was supported by a grant (2021-MOIS37-002) of "Intelligent Technology Development Program on Disaster Response and Emergency Management" funded by Ministry of Interior and Safety (MOIS, Korea).This work was supported by the "Graduate school of Particulate matter specialization" of Korea Environmental Industry & Technology Institute grant funded by the Ministry of Environment, Republic of Korea.
Wetland classification of sedimentary plateu on tropical drylands - Brazilian Northeast
Authors: Souza Jonas Otaviano Praça , Silva Mirelle Oliveira
Published: February 2023

Tropical drylands show diverse environmental characteristics worldwide, where the high evapotranspiration rates control the water deficit. In this context, water retention areas such as wetlands are hydro-geomorphological elements essential to ecological and social sustainability. The wetland classification on dryland areas allows better management of these socio-ecological hotspots. This research identifies and classifies wetland areas on the Chapada do Araripe and its surroundings in the centre of Brazilian tropical drylands. The geomorphological unit has 6,000 km², altitudes from 500m to 1100m, and comprises limestones on the base and sandstones on the top layer. The Wetlands were identified by remote sensing and fieldwork analysis and characterized by 13 geoindicators elements (e.g., near-surface lithology, flat valley bottom, spring presence, perennial surface water, hydromorphic soils, TWI, curvature, slope). Geomorphological and hydrological conditional factors define the wetland classification. The eleven wetlands identified are distributed on narrow valleys with slopes under 0.2m/m. The rainfall accumulation patterns directly link the surface flow temporality; only two areas show perennial surface flow. The perennial/intermittent hydrological regime seems to be directly linked to land use intensity. The intense deforestation is linked to the agricultural potentiality due to higher water disponibility. Valley bottom morphology was one of the critical elements to wetland classification, and curvature and slope values characterized it. Also, as a hydro-geomorphological feature, vertical incision and incised channels define the flow concentration/diffusion grade. The plan wetlands were defined by curvature values between 0.03-0.07 and slope values under 0.08m/m. Concave wetland show curvature from 0.1 to 0.19 and slope values between 0,08-0.2m/m. Considering these parameters, four classes were delineated for Wetlands in Chapada do Araripe: (1) flat with channelled valley floor;  (2) flat with unchanneled valley bottoms;   (3) Concave with channelled valley floor; and  (4) concave with unchanneled valley bottoms. Vegetated wetlands show the predominance of vertical incision processes and the presence of continuous channels (types 1 and 3). In contrast, deforested wetlands are controlled by valley floor sedimentation/silting process and absence/discontinuity of vertical incision. The vegetation presence was more significant than the curvature characteristics of valley floor vertical incisions. The association of vegetation presence with near surface low-permeable limestone layer controlled perennial hydrological regime. In this sense, it can be concluded that the geomorphological and hydrological parameters are essential for the characterization and classification of Wetlands. Becoming critical to elaborate specific legislation that aims to protect these environments, especially those found in dry lands.
Complex laboratory earthquake sequences show asperity interactions through creep fronts and illuminate the mechanics of delayed earthquake triggering
Authors: Cebry Sara Beth , Ke Chun-Yu , Shreedharan Srisharan , Marone Chris , Kammer David , McLaskey Gregory
Published: February 2023

Natural earthquakes occur in clusters or sequences that arise from complex triggering mechanisms, but direct measurement of the mechanisms responsible for complex temporal sequences and delayed triggering is rarely possible. A central question involved whether delayed triggering is due to slow slip and stress transfer or local weakening/fatigue processes such as stress corrosion. We investigate the origins of this complexity and its relationship to fault heterogeneity using a biaxial loading apparatus with an experimental fault that has two dominant seismic asperities. The fault is composed of a 5 mm layer of quartz powder, a velocity weakening material common to natural faults, sandwiched between 760 mm long polymer blocks that deform similar to the way 10 meters of rock would behave. Due to the higher local normal stress and the free surface boundary condition on the sample ends, the sample behaves like two asperities, one at each end, that can fail independently. As the quartz powder was continuously sheared, the friction properties changed, and we observed a transition from steady sliding to periodic repeating earthquakes that transitioned into aperiodic and complex sequences of fast and slow events. There is also reason to believe that friction properties evolved differently on the higher normal stress asperities and made them more unstable than the center part of the laboratory sample. Sequential ruptures on the two different asperities were linked via migrating slow slip which resembles creep fronts observed in numerical simulations and on tectonic faults. The propagation velocity of the creep fronts ranged from 0.1 to 10 m/s, which is broadly consistent with the velocity of slow slip fronts inferred from migrating tectonic tremor sources. Utilizing both local stress measurements and numerical simulations, we observe that the speed and strength of creep fronts are highly sensitive to fault stress levels left behind by previous earthquakes and may serve as on-fault stress meters.
Characterizing Isotropic Source Component of DPRK Nuclear Tests by Affine-invariant Bayesian Samplers with Uncertainty Estimate for Data Noise and Theory Error
Authors: Hu Jinyin , Phạm Thanh-Son , Tkalčić Hrvoje
Published: February 2023

A seismic moment tensor (MT, a 3x3 matrix) is a general source representation of various seismic events under the point source assumption, which is generally valid for small-to-medium size earthquakes. A full MT can be decomposed into isotropic (ISO), compensated linear vector dipole (CLVD), and double-couple (DC) components. The ISO represents the explosion/collapse source process that involves volumetric changes. Therefore, the relative significance of the ISO component, which can be learned from inverting seismic waveforms, is an essential indicator to discriminate between earthquakes and explosive events. However, an intrinsic ISO-CLVD tradeoff impedes resolving shallow explosive sources due to the high similarity of long-period waveforms at regional distances. Even though this tradeoff can be mitigated by extra constraints such as teleseismic P-waves, there is still an urgent need for advanced inversion algorithms to explore the solution space thoroughly. Apart from that, a rigorous uncertainty estimate is required to constrain the source better. Firstly, the inversion should consider the data noise. Secondly, the theory error primarily due to imperfect knowledge of Earth's structure is also significant but proven difficult to treat. Here, we propose a new Bayesian MT inversion scheme with affine-invariant ensemble samplers to explore the MT parameter space accounting for data and theory errors. Carefully designed synthetic experiments indicate the advantage of the newly developed method in resolving the isotropic components of a shallow seismic source. Our application to DPRK tests reveals a similar source mechanism dominated by a high ISO and significant CLVD components, including a small DC component. This study aims to characterize shallow explosive sources' physics better, thus helping verify compliance with the CTBT.  
Assessing the separate contribution of the domain, RCM, and GCM to the uncertainty in CORDEX simulations over the overlapped regions that include Jordan
Authors: Alkhasoneh Hebah , Rowe Clinton
Published: February 2023

Jordan is a Middle Eastern, developing country at significant risk for the adverse effects of human-induced climate change, including drought incidents. The region is highly vulnerable to drought due to being a water-scarce nation that shares limited water resources, the arid and semi-arid climate conditions, and the population explosion owing to the surrounding conflicts. Using regional climate model simulations from the Coordinated Regional Downscaling Experiment (CORDEX) project, a robust study has been developed to analyze current and future drought conditions in Jordan. The country is included in more than one CORDEX domain. This poses the question, as how sensitive is downscaling to the choice of domain? The regional climate models (RCMs) and the global climate models (GCMs) are two other sources of uncertainty. The goal of this first step study is to address the separate contributions of domain selection, downscaling regional models, and forcing global models to simulation uncertainty. This information will direct the best use of CORDEX to produce climate change signals by combining the results from the various CORDEX domains and enhancing the drought analysis.  Legasa et al. (2020) and Diez-Sierra et al. (2022) assessed the uncertainty related to the choice of domain as opposed to that of models combining the uncertainty related to RCMs and GCMs. Legasa et al.'s work was conducted over the Mediterranean region. They concluded that the domain selection effect is negligible. In this study, seasonal and monthly climatology data of temperature and precipitation variables from MENA (Middle East and North Africa) and Africa CORDEX domains were considered to construct Taylor diagrams and apply the analysis of variance method over Jordan’s region. The results of the two variables show that the domain contributes the least to the variance and is negligible, whereas the GCMs-related uncertainty contributes the most. This result supports the procedure of building a grand ensemble of various model simulations relating to overlapping domains, which will be used to enhance the drought analysis and assist policymakers with planning mitigation and adaptation procedures. References:Legasa, M.N., et al. (2020) Assessing multidomain overlaps and grand ensemble generation in CORDEX regional projections. Geophys. Res. Lett. 47, https://doi.org/10.1029/2019GL086799Diez-Sierra, J., Iturbide, M., Gutiérrez, J. M., Fernandez, J., Milovac, J., Cofiño, A. S., and Cimadevilla, E.: Assessing the consistency of CORDEX multidomain projections in overlapping regions worldwide, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6059, https://doi.org/10.5194/egusphere-egu22-6059, 2022 