bluuebunny/crossref_metadata_2025 huggingface dataset:
A “Parallel Evolution” of Flood Risk Management along the Rhine and the Sacramento Rivers
Authors: Daniels Ben , Roychowdhury Indumanti , Calderwood Andrew , Mezei Lidia , Rader Bethany , Schaefer Kathy , Tracy Erin , Webb Mariana , Pinter Nicholas , Lund Jay , Dahlke Helen , Yarnell Sarah
Published: March 2024

The Sacramento River in California, USA, and the Rhine River in Europe both have histories of major flooding events and great efforts to manage flood risk. We compare these two watersheds with an interdisciplinary lens to explore the goals, approaches, outcomes, and “parallel evolution” of differing flood risk management paradigms.The two basins share hydrologic similarities, but each approach to managing floods reflects the basin’s unique historical, environmental, and governance context. The Sacramento basin is entirely within the state of California, whereas the Rhine is a transnational river that drains nine European countries. The Rhine basin is larger and has a much larger population compared with the Sacramento basin.  The Sacramento basin has high interannual precipitation variability and receives most of its precipitation in the winter with significant mountain snowfall. The hydrology of the Rhine is also strongly influenced by mountain snowpack, but has precipitation that is more evenly distributed throughout the year. Flood-risk management on both the Sacramento and Rhine Rivers has evolved from ad hoc and local approaches, towards more systematic planning, culminating in significant state-level control in California, and state, federal, and transnational management on the Rhine. This transition was driven in recent years by the Central Valley Flood Protection Act and the European Floods Directive.Management of each basin has been shaped by an event-based evolution, in which disasters have driven management responses, tools, and approaches. Flood-risk paradigms in both basins include significant investment in engineering protection and, increasingly, soft-policy adaptations. Over time, flood management methods and objectives in each basin have become more diverse. For example, single-objective approaches have evolved towards multi-benefit projects. Both basins are expanding consideration of floodplain ecosystem importance and both now consider climate change to some in flood risk management.  Flood-protection levels are higher on the Rhine than on the Sacramento. Some areas of the Rhine have 1000-year or better protection whereas a  200-year-level protection for urban areas is now required in the Sacramento basin.The Sacramento River and the Rhine River are geographically and hydrologically similar in surprisingly many ways, including in the flood risk they pose.  But the flood-risk management paradigms in the two basins have evolved differently.  We argue that the differences are a form of “parallel evolution,” reflecting historical and political contrasts between the two systems.  Such contrasts present opportunities for alternative tools and lessons that can be explored and perhaps imported in both directions.
Future changes of Climate Suitability of Global Rainfed Food Crops under different CMIP6 scenarios
Authors: Mumo Lucia , Franzke Christian , Lee June-Yi
Published: March 2024

Achieving the second sustainable development goal, “Zero Hunger”, is challenging due to climate change, weather extremes and an unabated human population growth. The consequent increase in global food demand has put additional pressure on agricultural systems. Understanding spatial crop suitability alterations, yields and calories of the four major staple food crops around the globe is imperative for sustainable agricultural optimization, climate mitigation, and food security. This study uses three downscaled and bias-corrected shared socioeconomic scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) from the latest state-of-art climate models in Coupled Model Intercomparison Project phase 6 (CMIP6) courtesy of Worldclim: an ecological crop requirement model (Eco Crop) and a machine-learning extreme gradient boosting model (XGBoost) to estimate future crop suitability and yields. Our results elucidate a northward spatial shift in climate suitability and shrinkage of optimal crop-growing regions as the unsuitable and marginal areas expand. Notably, more reduction of suitable regions is observed for all the crops under the highest emission and in far-future climate (2061-2100) scenarios as compared to the SSP1-2.6 and during the near-future period (2021-2060). Nevertheless, gain in suitable areas for soybeans and wheat has been observed at high latitudes, while the tropics are projected to experience a significant loss of arable land. The optimal zone for maize is projected to significantly reduce by approximately 75% in all emission scenarios. This translates to a maize yield loss of 17.3%, and 8.5% in near and far-future climate periods respectively under SSP5-8.5 scenario. Spatial consistency shows that most of the suitable and optimal zones for soybeans are currently not been used. This study sheds light on crop production optimization as farmers are advised to shift to more suitable climate regions for a given crop rather than agricultural extensification that triggers desertification. Due to the considerable loss of climate-suitable regions for rainfed agricultural systems, global efforts should be directed to irrigation systems to ensure global food security and peace. Keywords: Eco crop, Climate suitability, CMIP6, Food security, Crop Yield, XGBoost
SuperDARN observation of ionospheric plasma flows associated with low-latitude auroras in Hokkaido, Japan
Authors: Nishitani Nozomu , Hori Tomoaki
Published: March 2024

During periods of severe geomagnetic activity, auroras can be observed at much lower geomagnetic latitudes than the average auroral oval, e.g., lower than 40 degrees. Although several papers discussed the possible generation mechanisms for these auroras, their relationship with the ionospheric plasma convection pattern or the electric field distribution is not well understood, mainly because there are few observation data available.The SuperDARN (SD) Hokkaido East and West radars, located at the lowest geomagnetic latitude among the SD radars at present, have been operating since 2006 and 2014, respectively, and observed ionospheric plasma convection patterns for three storm events in March 2015, November 2023, and December 2023, when low-latitude aurora was observed in Rikubetsu, Hokkaido, Japan (geomagnetic latitude: 37 degrees). Generally, the low-latitude auroral precipitation regions are accompanied by a shear of east-west ionospheric flows, although the detailed flow structure differs for each event. Some discussions and interpretations of these plasma flow patterns associated with the low-latitude auroras will be presented.
The Geometry and Thermal Fault Models of Flores Thrust
Authors: Andikagumi Harisma , Bradley Kyle
Published: March 2024

The 2018 Lombok earthquake demonstrated the hazard that the Flores Thrust possesses and highlighted our lack of knowledge on this crustal scale backarc thrust. The Flores Thrust extends from west to east, located at the backarc of the Lesser Sunda Islands, Indonesia. Here we construct the geometry model of the Flores Thrust by fitting the best surface on the relocated and filtered intraplate seismicity using simulated annealing and interpolating using the FastRBFTM algorithm. The thrust has a flat and a ramp component where the flat is generally constant, inclined ~5° southward, but limited between eastern Bali and western Sumbawa due to the sediment-filled North Bali-Lombok Basin. The ramp of the thrust is dipping southward with a 38° average dip, where the dip increases eastward from Bali (27°-37°) to Lombok (28°-38°), Sumbawa (30°-50°), and western Flores (40°-58°), but then shallower in central Flores (29°-39°). The segmented geometry of the Flores Thrust with varying dips from west to east might be related to the complex geological history and the heterogeneity of both the upper and lower plates in the Lesser Sunda region. Based on our analysis of the volcano distribution, the seismogenic zone of Flores Thrust is constrained by arc volcano distribution; bounded by volcanoes at the western tip (Raung, Ijen, and Baluran in Java) and the eastern tip (Lereboleng and Lewotobi in Flores) while the deeper part is terminated by the along-arc distribution of volcanoes or where the temperature exceeds the brittle-ductile transition zone (>450°C). The proximity between the Flores Thrust and the volcanism might also suggest its interplay during the thrust development. The presence of high-K backarc volcanoes, Tambora and Sangeang Api, to the north of the low-K basaltic-andesitic dominated volcanoes in Sumbawa (e.g., Sangenges and Sorumundi) suggest a possible northward arc migration, closer to the thrust, and a complex interaction between arc volcanism and thrust development. Therefore, the complexity of the Flores Thrust geometry and its interplay with the volcanism should be investigated further, to mitigate the greater effects of any geological hazards in the region.
Nitrous oxide emissions and stable isotopic composition in urban sources and ambient air in Seoul, South Korea
Authors: Kim JeongEun , Ahn Jinho , Toyoda Sakae
Published: March 2024

 Nitrous oxide (N2O), known for its ozone-depleting potential and characterized by a long residence time of 120 years in the atmosphere, is the third most significant anthropogenic greenhouse gas after CO2 and CH4. Primary sources of N2O include nitrification and denitrification processes in soils and aquatic systems, as well as from direct anthropogenic sources such as fossil fuel combustion and wastewater treatment plants. The increase in N2O emissions due to agricultural activities and urbanization is complex, given the high variability of these emissions. To characterize anthropogenic N2O sources, we collected air samples from tunnels and wastewater treatment plants. Additionally, to establish the background levels for Seoul, a megacity in South Korea, we collected ambient air from three sites (Mt Gwanak, Mt Nam, and Olympic Park) monthly throughout the year 2023. These air samples were measured for greenhouse gas concentrations (CO2, CH4, and N2O), and the stable isotopic compositions of N2O (δ15Nbulk, δ18O, and SP values) were analyzed using IRMS. The stable isotopic ratios of N2O emitted from the vehicles were determined as 6.0 ± 1.2 ‰ for δ15Nbulk, 34.4 ± 11.7 ‰ for δ18O, and 6.0 ± 4.2 ‰ for SP values. Furthermore, N2O from wastewater treatment plant water tank air exhibited variations dependent on dissolved oxygen levels. Notably, the stable isotopic compositions of N2O from anthropogenic sources were consistently depleted compared to the ambient air of Seoul (δ15Nbulk: 5.9± 0.2 ‰, δ18O: 43.8 ± 0.1 ‰, SP: 18.6 ± 0.3 ‰ (S.E.)). Intriguingly, while δ15Nbulk and δ18O values of ambient air were depleted relative to the global average, SP values exhibited a wide range and significant variability. This suggests the presence of pronounced spatial and temporal variabilities in N2O emissions, underscoring the need for further research to understand the extent of anthropogenic impacts.
Turn up the heat to locate and quantify groundwater flow in fractured rock aquifers in coastal zones of the tropical island of Curaçao
Authors: Kruijssen Titus , Wit Mike , Akkermans Sandra , Leusink Joshua , van Breukelen Boris , van der Ploeg Martine , Bense Victor
Published: March 2024

Dual porosity flow is an important mechanism for groundwater transport in fractured rock aquifers. However, quantification and characterization of fracture flow systems remains challenging, as it often involves complex procedures such as the injection of tracers. In this study we conducted single-well pumping tests in 11 uncased wells in a coastal fractured rock aquifer while monitoring in-well salinity and temperature gradients through downhole casts using a Conductivity-Temperature-Depth (CTD) logger. In this way, we aimed to observe how naturally occurring salinity gradients in the well become disturbed by induced groundwater flow to the well, and if these gradients may serve as natural tracers for fracture flow. Since natural temperature gradients in the wells are minimal, we applied point electrical heating at the bottom of the well to create a plume of slightly warmer water to migrate up the wellbore during pumping from the top. During the pumping tests in this set-up, repeated CTD casts suggest that groundwater flow to these wells is strongly focused along narrow zones and is occurring at various rates over a range of salinities and temperatures. Hence, the observed patterns in both salinity and temperature presumably reflect the presence of fracture zones, which could indeed be confirmed by downhole camera observations for some wells. Further data analysis resulted in detailed hydrogeological characterization of the 11 wells, comprising an assessment of the fracture density and hydraulic conductivity of the aquifers, as well as the origin of the inflowing water being meteoric mostly fresh water or deeper saline groundwater.
Fundamental shift of ice temperature in the Third Pole under global warming
Authors: Yang Wei
Published: March 2024

The Tibetan Plateau and its surroundings, sometimes referred to as High Mountain Asia or the Third Pole, have the largest mid-latitude glaciers and act as Asia's water tower. Previous studies based on remote sensing and ground-based measurements have revealed the magnitude and the accelerated trend of surface ice loss in this region over the past two decades. However, little is known about the englacial temperature and its response to climate change. Here we present a compilation of ice temperature profiles from 21 deep cores drilled in the accumulation zone of different glaciers covering the Third Pole. By combining these ice-core records with other climate datasets and thermal modelling, we have found that the thermal statues in the extreme high-altitude regions have undergone fundamental changes against the background of climate warming, particularly in the surrounding of Third Pole. The spatial pattern of the ice temperature structure shows clear contrasting patterns. Due to the intense latent heat generated by the refreezing of surface meltwater, the englacial temperature of boreholes in the vicinity of the Third Pole is far from a steady state, reflecting an increasing atmospheric temperature over the past decades and non-stationary climatic conditions. The repeated measurements in the same boreholes on different glaciers also showed that the englacial temperature profile can either increase or decrease, mainly depending on the effects of meltwater production and firn thickness. Such a dramatic shift in ice temperature in the Antarctic region have profound implications for glacier response to climate change and glacier-related disasters in this high-altitude regime.
A Positive-Definite Moist EDMF Parameterization Scheme for Turbulent Mixing in the PBL
Authors: Grell Evelyn , Bao Jian-Wen
Published: March 2024

Planetary boundary layer (PBL) parameterizations using the eddy diffusivity - mass flux (EDMF) technique for turbulent mixing in the convective PBL have been popularly used in weather and climate models.  When including moist adjustment processes, some numerical implementations of the EDMF parameterization may result in unphysical solutions of cloud condensate, for example, negative cloud water quantities.  To solve this problem, a procedure to obtain a positive definite solution is proposed to solve the moist EDMF equations.  In this presentation, we will demonstrate the formulation of the solution procedure and show examples of its impact on the PBL mixing simulation using a single-column model.
Research on Sea Ice Freeboard Retrieval from CryoSat-2 Based on Artificial Intelligence
Authors: Yang Xinran
Published: March 2024

The Arctic is one of the important drivers of global climate and environmental change. Its atmosphere, oceans, and sea ice movements have direct or indirect impacts on global atmosphere and ocean circulation as well as climate variability. Sea ice plays a crucial role in maintaining climate balance in the Arctic region, preventing more solar radiation from entering the sea through its high reflectivity and limiting air sea heat exchange, reducing sea surface temperature and sea ice melting rate. Sea ice thickness is an important parameter that describes the properties of sea ice. Obtaining the freeboard of sea ice through satellite altimetry measurements is of critical importance for sea ice thickness retrieval and understanding changes in Arctic sea ice. So far, research on satellite observations of pan-Arctic sea ice thickness has been limited to winter months. The key to measuring the freeboard using altimetry lies in distinguishing sea surface types and correctly identifying adjacent inter ice waterways. However, there are a large number of melting pools on the surface of summer floating ice, which make traditional waveform classification schemes unable to accurately distinguish sea surface types and become the main obstacle to retrieval freeboard of summer sea ice. In this study, a one-dimensional convolutional neural network classification model is built using CryoSat-2 summer sea ice classification training and testing dataset to improve summer sea ice freeboard retrieval. The model uses three parameters as input sources, i.e., elevation, pulse peakness, and backscatter coefficient. It achieves an overall accuracy of 84.3%. The sea ice freeboard is calculated from the elevation difference between the ice-covered waterways and its surrounding floating ice, resulting in distributions of 15-day individual sea ice freeboard and sea ice freeboard on an 80-km resolution grid. The results show that although there are many missing data due to noise and other issues, effective sea ice freeboard can be obtained in all months in summer. It demonstrates the feasibility of this method.
Assessing the Variability of Radiation, Water and Energy in the Deep Tropics Over the Last 3 Decades
Authors: Stackhouse Paul , Cox Stephen , Mikovitz J. Colleen , Zhang Taiping , Leitmann-Niimi Nicolas
Published: March 2024

Global surface energy closure and its variability depends heavily upon the surface radiative energy budget in the deep tropics.  A key process observed is the change in convection regimes from disorganized convection to organized deep convection.  During these periods an imbalance is observed between energy and water fluxes in terms of energy closure in some atmospheric reanalysis systems, implying that processes are not simulated well.  A recent paper by Hsaio et al (2023, pre-published version) found that the transition process has wind shear and longwave cloud radiative feedback signatures.  In this presentation, we assess the surface radiative budget in the deep tropics by comparing multiple data products (GEWEX SRB Rel4IP, CERES Ed4.1, ISSCP FH, etc.) and describing the variability across the deep tropics for the period from 1988 to near present.  We assess this variability of the radiative flux anomalies (including the net TOA, surface and the atmospheric divergence fluxes) against water vapor divergence, cloud properties (include ISCCP “Weather States, Tselioudis et al. 2021) and larger scale wind shear.  We include further analysis contrasting 6 key tropical oceanic regions (Indian Ocean east and west, tropical western, central and eastern Pacific Ocean, and Tropical Atlantic Ocean) and the sensitivity of the fluxes as a function of fluctuations in cloud types in response to various larger scale atmospheric processes (e.g. El Niño, Indian Ocean Dipole).  These are contrasted against the modeled radiative fluxes from ERA-5 and MERRA-2.  Ocean buoy measurements of radiative fluxes are utilized to help assess data radiative flux uncertainty over the nearly 40 year period.  In general, the variability for overlap periods of these various data products agrees well, but there are significant differences in the net fluxes that vary according to the rendering of surface, atmospheric, aerosol and cloud properties.  We conclude with recommendations for continuing work.
Pan-regional characterization of the variability in the Indonesian Seas
Authors: Wang Yuan , Xue Huijie
Published: March 2024

The Indonesian Seas feature a wide-spectrum of variations in hydrography and circulation. This study applies a simple frequency-based time series decomposition method on the 20-year model outputs without data-assimilation, and demonstrates the spatial distribution of the variations in intra-seasonal, semi-annual, annual, and inter-annual bands, respectively. The four bands of variations are further used in K-mean clustering to investigate the inherent dynamical similarities/dissimilarities for a pan-regional characterization. The clusters based on the variations of the sea-level/thermocline emphasize the competing impacts of the annual and inter-annual variations in the Indonesian Seas, which lays on a "cross-road" of the inter-annual variation dominated NE-SW oriented deep-ocean regime and the annual variation dominated NW-SE oriented marginal sea regime. The annual variation is primarily driven by the regional monsoon wind. Moreover, profiles of annual current variations show a significant difference between the main and east branch of the Indonesian Throughflow (ITF), where annual variations play a major role above (below) the thermocline in the main (east) branch. In general, the ITF variability is mainly influenced by the remotely generated inter-annual variability, regional annual forcings by monsoon, and local flow instability and fluctuations, with the semi-annual variation being minor but non-trivial.
Impact of cascade reservoirs on nutrients transported downstream and regulation method based on hydraulic retention time
Authors: Zeng Qinghui
Published: March 2024

 Cascade reservoirs construction has modified the nutrients dynamics and biogeochemical cycles, consequently affecting the composition and productivity of river ecosystems. Cascade reservoirs in different rivers typically exhibit distinct variabilities in the retention characteristics of different nutrients. The Jinsha River, as the predominant contributor to runoff, suspended sediment (SS), and nutrients production within the Yangtze River, is a typical cascade reservoir region with unclear transport patterns and retention mechanisms of nutrients (nitrogen and phosphorus). Therefore, we monitored monthly variations in nitrogen and phosphorus concentrations from November 2021 to October 2022. The results demonstrated that the concentrations and fluxes of total phosphorus (TP) and particulate phosphorus (PP) significantly decreased as they moved downstream along the cascade of reservoirs, primarily due to PP deposited with SS, while total nitrogen (TN) and dissolved total nitrogen exhibited opposing trends. Moreover, the positive average annual retention rates for TP and PP were 9.64% and 15.64%, respectively, in contrast to the negative averages of -8.38% for TN and -10.51% for particulate nitrogen. A higher proportion of TP and PP was retained by the reservoirs in the flood season compared to the non-flood season. Additionally, the variability in runoff-sediment and hydraulic retention time (HRT) of cascade reservoirs played crucial roles in the retention of TP and PP. A stronger relationship between HRT and TP retention rate during the flood season suggested that the cascade reservoirs could effectively transport or intercept TP downstream when HRT was either less than or greater than 5.3 days. Consequently, the HRT of these reservoirs could be managed to control nutrients delivery, which was of particular significance for watershed government institutions. This study enhances our comprehension of how cascade reservoirs influence the distribution and transport patterns of nutrients, offering a fresh perspective on nutrients delivery regulation. 
The lithosphere-asthenosphere boundary unveiled through trans-dimensional Bayesian inversion of geomagnetic satellite data
Authors: Yang Cong , Ren Zhengyong , Chen Chaojian , Yao Hongbo , Gu Yu , Tang Jingtian , Zhang Keke
Published: March 2024

The lithosphere-asthenosphere boundary, distinguishing the rigid lid from the weak mantle, intricately regulates the exchange of energy and materials between the overlaying moving plates and the convecting asthenosphere across geological timescales. This pivotal boundary not only controls the formation of mountains and deep oceans but also governs natural hazards such as volcanic eruptions and earthquakes. Moreover, it plays a fundamental role in exerting influence over global climate changes and creating the hydrosphere that sustains life on Earth. Recognizing its paramount significance in cultivating a habitable environment, extensive seismic, magnetotelluric, heat flow, and viscosity measurements have been employed to scrutinize its depth variations and transitions in chemical and physical properties. Nevertheless, the precise location of the transition between the strong lid and the weak mantle, as well as the exact mechanism controlling the thickening of the lithosphere and the weakening of the upper mantle, remains a subject of ongoing debate. Tidally-induced magnetic field data, measured by geomagnetic satellites and generated through galvanic coupling between ocean sedimentary layers and the underlying conductive rocks, provide a unique opportunity to remotely sense the lithosphere-asthenosphere boundary. This study develops a new inversion algorithm to image the globally averaged conductivity profile beneath the Earth’s surface and utilizes extracted tidally-induced magnetic field data from geomagnetic satellites to focus on the lithosphere-asthenosphere boundary. Employing the trans-dimensional Bayesian concept and a three-dimensional integral equation solver that accounts for heterogeneous surface continents and oceans, this approach holds the potential to provide a significant statistical probability of the imaged lithosphere-asthenosphere boundary and other sub-lithosphere discontinuities, along with associated conductivity values. These conductivity discontinuities and values are then used to infer potential water content and partial melt in the weak mantle, crucial for unraveling the hidden mechanism behind lithosphere thickening.
Keywords: lithosphere-asthenosphere boundary; tidally-induced magnetic field; trans-dimensional Bayesian; Geomagnetic satellites
Development of a spectrum-based scheme for flocculation processes in estuaries
Authors: Xu Fanghua , Fang Zheng
Published: March 2024

Flocculation processes of cohesive sediments in estuaries play a critical role on sediment transport and biogeochemical cycles in estuaries. Due to convergence of marine saltwater and freshwater runoff, coupled with periodic tidal cycles, cohesive sediment exhibits intricate flocculation processes that are challenging to simulate. It has been found that the size bin-based schemes are effective to simulate these processes, especially under highly variable conditions. However, the application of this kind of scheme is limited due to expensive computational cost. In the study, we develop a new spectrum scheme based on the spectral pattern of floc size distribution from a size bin-based scheme to expedite modeling execution. The newly-developed scheme is implemented into the Princeton Ocean Model (POM) and applied to simulate cohesive sediment transport in the Hudson River Estuary. The effectiveness of this spectrum scheme is evaluated by comparing simulation results with in-situ observations and results from a size bin-based scheme. The results indicate that the newly-developed scheme can well simulate the time evolution of floc concentrations. Compared to the original size bin-based scheme with 15 bin number, the average percentage error is about 1.86%, with an average acceleration of 4.60 times for cohesive sediment advection. Additionally, as the parallel core numbers and bin numbers increase, the acceleration effect of this bin-spectrum scheme gets better. In summary, the newly-developed spectrum scheme for flocculation processes provides significant acceleration benefits for size bin-based schemes, and has a potential to be widely used for simulating flocculation processes in estuaries.
Irrigated crop migration severely accelerated global groundwater depletion
Authors: Liu Zitong , Zhu Yuyao , Gu Weiyi , Mueller Nathaniel , Qin Yue
Published: March 2024

As the primary global freshwater consumer, the migration of irrigated agriculture plays a critical role in driving alarming groundwater depletion and hence threatens sustainable water management and food security. Yet, little is known regarding the dynamic changes of historical irrigated agriculture migration, and therein the associated threatening impacts on groundwater depletion. Here, we couple a state-of-art global crop water model, global hydrological models, and long time-series of statistic data to provide one of the first attempts to map the spatial-temporal heterogeneities in irrigated agriculture migration patterns across the globe during the past thirty-five years (1985-2019), and unravel the dynamic impacts of irrigation migration on groundwater depletion across global key food-producing regions. We find that a global average 6.29 degree eastward crop migration results in 37% increases in global groundwater depletion intensity and 46% of global total groundwater depletion increases (68.5 km3) over this period, particularly across global major breadbaskets such as India, China, which together contribute 83%, 83% and 87% of global food crop, fruit and vegetable production. Generally, crop migration significantly exacerbates groundwater depletion intensity in developing Asia (particularly reverses the otherwise decreasing trend in India and Pakistan), while alleviating groundwater depletion in developed North America and Europe. Our study highlights the previously overlooked unsustainable crop migration trend in severely accelerating groundwater depletion over the past four decades and calls for cautious irrigation migration planning, particularly across global breadbaskets.
Evaluating Landslide Susceptibility on the Big Sur Coast, California, USA using Complex Network Theory
Authors: Desai Vrinda D. , Handwerger Alexander L. , Daniels Karen E.
Published: March 2024

As a result of extreme weather conditions such as heavy precipitation, natural slopes can fail dramatically. While the pre-failure deformation is sometimes apparent in retrospect, it remains challenging to predict the sudden transition from gradual deformation to runaway acceleration. Recent advancements in remote sensing techniques, like satellite radar interferometry (InSAR), enable high spatial and temporal resolution measurements of deformation and topographic information, providing valuable insights into landslide detection and activity. Landslides are common on the Big Sur coast, Central California, USA due to active tectonics, mechanically weak rocks, and high seasonal precipitation. We use satellite InSAR data from Copernicus Sentinel-1A/B to identify 23 active landslides within our 175 km2 study site; one is Mud Creek, a slow-moving, deep-seated landslide that catastrophically failed in May 2017 and another is Paul’s Slide, which has experienced nearly constant motion for decades. We use multilayer networks to investigate the spatiotemporal patterns of slow deformation on the 23 active landslides. In our analysis, we transform observations of the study site — ground surface displacement (InSAR) and topographic slope (digital elevation model) — into a spatially-embedded multilayer network in which each layer represents a sequential data acquisition period. We use community detection, which identifies strongly-correlated clusters of nodes, to identify patterns of instability. We have previously shown [Desai et al., Physical Review E, 2023] that using high-quality data containing information about the fluidity (via velocity as a proxy) and susceptibility (slope) of the area successfully forecasts the transition of the Mud Creek landslide — the only formally slow-moving landslide in this collection to have catastrophically collapsed — from stable to unstable. Using multivariate analysis, we compare the traits of the active landslides, such as precipitation, vegetation, deformation, topography, NDVI, and radar coherence, against the results of the community detection. A strong indicator of instability is a combination of poor InSAR coherence and high displacement. Combined with community detection, we are able to differentiate between creeping landslides that are stable and landslides that display concerning trends that may warn of catastrophic failure.
Ontogeny and brooding strategy of the early Cambrian arthropod Isoxys minor from the Qingjiang biota
Authors: Ma Jiaxin , Pates Stephen , Wu Yu , Lin Weiliang , Liu Cong , Wu Yuheng , Zhang Mingjing , Fu Dongjing
Published: March 2024

lsoxys is a worldwide distributed bivalved arthropod known almost exclusively from Cambrian Burgess Shale-type Lagerstätten. Outline analyses using 34 specimens of the iconic large bivalved arthropod Isoxys minor from the Cambrian Stage 3 (~518Ma) Qingjiang biota and the Cambrian Stage 4 Guanshan biota, interpret that they are the same species and there is a very slight difference in the shape of the outlines of the carapaces between the two biotas. This suggests that environment might be driving intraspecific variation. Quantitative analysis of shape changes during growth using 51 specimens of l. minor from the Qingjiang biota, reveals that its valves gradually elongate and the ratio of cardinal spines and spherical eyes relative to the valve length significantly decreases during postembryonic development. I. minor has proportionally large cardinal spines and eyes in the earliest stages, and this allometric growth is beneficial for self-protection and foraging, which may have improved the survival rate of individuals with these characters. In addition, two of the specimens document the evidence of brood care in l. minor, and the egg cluster occupies almost the entire dorsal region under the carapace. Compared to other early Paleozoic egg-carrying arthropods, l. minor broods have the highest number (~300 per clutch) of small (0, ~0.5mm) eggs. Since the ovigerous individuals are almost half the size of the adults, l. minor may have possessed reproductive ability during the early life stage. The results indicate that spines played an antipredatory role for l. minor, and that it followed a r-strategy of reproducing with many individuals at an early stage. l. minor also represents the earliest diverging arthropod from which brood care has been documented.
Development of Global Integrated Turbulence Forecast System for the Republic Of Korea Air Force
Authors: Lee Dan-Bi , Kim Jung-Hoon , Hwang Jaedon , Song Jae-Ik , Jung Hyejeong
Published: March 2024

Unexpected encounters with aviation turbulence, a hazardous weather phenomenon affecting aircraft operations, can cause casualties and aircraft damage. The Republic Of Korea Air Force (ROKAF) currently provides turbulence forecast information for the East Asia/Korean Peninsula area based on the Korea Air Force-Weather and Research Forecasting (KAF-WRF) model-derived turbulence diagnostics. However, because the turbulence forecast information is not provided for the global area, operational weather forecasting support to overseas areas, whose importance is increasing under modern warfare, is limited. Accordingly, in this study, we developed the global integrated turbulence forecast system considering various turbulence generation mechanisms, called the KAF-Global Turbulence Forecast (KAF-GTF) system, based on the two global numerical weather prediction (NWP) models being currently used in operation by the weather group of the ROKAF. The ROKAF’s global NWP models are the Global Forecast System (GFS) and European Centre for Medium-Range Weather Forecasts (ECMWF), which have horizontal resolutions of 0.5°x0.5° and 0.25°x0.25°, respectively. The two global NWP model-based KAF-GTF systems are developed based on the methodology of version 3 of the Graphical Turbulence Guidance (GTG) system of Sharman and Pearson (2017) and consist of the following three steps: i) individual clear-air turbulence and mountain wave turbulence diagnostics representing various turbulence generation mechanisms are calculated using the global NWP model output, ii) the raw values of those turbulence diagnostics are converted into eddy dissipation rate (EDR), which represents the intensity of atmospheric turbulence, using the simple EDR conversion equation, and iii) KAF-GTF forecast is derived by combining the EDR-scaled turbulence diagnostics through ensemble averaging. The combination set of individual turbulence diagnostics and the EDR conversion equations used in the KAF-GTF system are applied as in GTG 3, considering that the combination set of turbulence diagnostics and their EDR conversion equations optimized for the global turbulence forecast were already constructed in the GTG3. In this study, the performance of two KAF-GTFs based on GFS and ECMWF are compared using turbulence cases reported from aircraft turbulence observation data for the evaluation, and the evaluation results will be represented in the conference.Acknowledgment: This research was funded by the Republic Of Korea Air Force Weather Group Research Program (2023UMM0343), and was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2023-00250021).
Understanding of the Wintertime Atmospheric Aerosol Properties with Explainable Machine Learning
Authors: Hu Qihua , Kim Hwajin
Published: March 2024

Winter atmospheric aerosols, marked by formation under dynamic and complex conditions due to distinct environments, haze events and regional transportation, is greatly challenging to investigate. To address this, we employed XGBoost models integrated with SHapley Additive exPlanations (SHAP) to explore the meteorological and chemical drivers, as well as the impact of transportation, on aerosol characteristics.We conducted measurements using a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) during the 2018 winter (Jan 17th to Feb 22nd) in urban Seoul, Korea. Our analysis included various PM components (nitrate, sulfate, chloride, ammonium, and organics) and sources of organic aerosols (OA), such as more-oxidized oxygenated OA (MO-OOA), less-oxidized OOA (LO-OOA), cooking OA (COA), hydrocarbon-like OA (HOA), and biomass burning OA (BBOA), using positive matrix factorization (PMF). The models demonstrated high predictive accuracy (R>0.90) for all species and sources.Notably, nitrate formation was found to be significantly influenced by CO concentration and relative humidity (RH), highlighting the role of local sources and aqueous-phase formation. For sulfate, RH was identified as the dominant factor. Organic components, constituting 42.4% of total PM mass, were analyzed for their diverse sources. Temperature and RH were the major drivers for MO-OOA (O/C=0.94) formation, with a critical temperature threshold near 0 °C identified for differentiating formation conditions. Specifically, temperature above the ice point and high RH significantly enhanced MO-OOA formation, and it is likely related to the availability of liquid water for aqueous-phase oxidations to occur. LO-OOA (O/C=0.77) was controlled by CO concentration, suggesting its local formed feature being the same line with nitrate.Primary OAs, HOA (O/C=0.09) and BBOA (O/C=0.39) were dominated combustion sources (CO concentration), while BBOA (O/C=0.39) was closely linked to temperature. Interestingly, BLH showed a greater impact on COA (O/C=0.20) ,likely due to accumulation during early shrinkage of the boundary layer in winter.This novel approach effectively identified distinct drivers of aerosol formation and emission features in winter, offering new insights compared to traditional methods. However, the models showed limitation in defining the strong influence of transportation impacts from upwind areas, as found in various research, possibly due to constraints in cluster ID input, which could not distinguish high and low loading clusters. The limitation indicates an area for further investigation.
Sea surface pCO2 variability on different time scales in the East China Sea based on high-frequency time-series observations
Authors: Luo Yaohua , Zhang Zhirong , Chen Jinshun , Xu Yi , Cao Fuqing , Huang Tao , Guo Xianghui , Dai Minhan
Published: March 2024

We examined the sub-seasonal to interannual variability and multi-year trend of sea surface CO2 partial pressure (pCO2) and air-sea CO2 flux at a coastal site of the East China Sea (31⁰N, 122.8⁰E) based on high-frequency time-series data collected by a buoy since 2013. Seasonal average sea surface pCO2 was highest in autumn, but the lowest value can appear in winter or spring, depending on the biological productivity in spring. The seasonal amplitude of pCO2 was up to 123 μatm. Based on property-property relationships and a simple mass budget model, we found that temperature change, biological activity, water mixing and air-sea CO2 exchange all made significant contributions to the seasonal variation of pCO2. From winter to summer, seasonal warming and atmospheric CO2 uptake elevated the pCO2, while net biological production, weakened vertical mixing and the retreat of the Yellow Sea Coastal Water (YSCW) lowered the pCO2. Conversely, from summer to winter, seasonal cooling and CO2 emission lowered the pCO2, while respiration, enhanced vertical mixing and the YSCW intrusion raised them up. Over short-term timescale, biological production and respiration frequently drew down or elevated the pCO2 by 150-400 μatm within 5-10 days during warm months. When biological activity was suppressed during cold months, such short-term variations were dominated by water mixing with a smaller pCO2 amplitude of 5-60 μatm within 2-6 days. This site was a sink of atmospheric CO2 in winter and spring, but a CO2 source in summer and autumn. Annually, it was a moderate CO2 source in 2014 (air-sea CO2 flux was 2.88 ± 11.02 mmol m−2 d−1), a weak CO2 sink in 2016 (-0.21 ± 12.23 mmol m−2 d−1), and a weak CO2 source in the combined year of the first half of 2017 and the second half of 2018 (0.40 ± 9.11 mmol m−2 d−1). The relatively high CO2 source in 2014 was likely due to the weaker biological production in spring and more typhoon passage in autumn. From 2013 to 2019, the wintertime sea surface pCO2 didn’t follow the increasing trend of the atmospheric pCO2, leading to an enhancing carbon sink in winter.
Thirty-two years of high precision data on the stable isotopes of carbon dioxide from a successful collaboration between NOAA and INSTAAR 
Authors: Michel Sylvia Englund , Tans Pieter , Miller John , Ortega John , Braun Kerstin , Leon Taline , Vaughn Bruce , Clark Reid , Li Jianghanyang , White James
Published: March 2024

Monitoring the long-term changes in the stable carbon isotope ratio of carbon dioxide (expressed as δ13C-CO2) is a useful tool to track the fate of atmospheric CO2 and variations in the global carbon cycle. Due to the small but significant change in global mean atmospheric δ13C-CO2 of approximately -0.75‰ over the last three decades, a robust and traceable method is required to track the long-term change in δ13C-CO2 globally. The Stable Isotope Lab at the INSTAAR of the University of Colorado Boulder has been partnering with NOAA’s Global Monitoring Laboratory since 1990 to measure CO2 stable isotopes within the Global Greenhouse Gas Reference Network. Here, we present our latest data product, globally distributed observations of δ13C-CO2 in the past 32 years. We have improved our traceability by moving our data onto the CO2 -in-air JRAS-06 isotopic scale (a representation of V-PDB). We also have established robust quality management systems and have improved our methods of quantifying uncertainty.  Our data demonstrate how the interactions among the atmosphere, the biosphere and anthropogenic activities had been recorded in δ13C-CO2 from more than 70 sites worldwide. The data reveal distinct seasonal variations of δ13C-CO2 that change with latitude, highlighting spatial differences in the influence of anthropogenic activities, net photosynthesis, and ocean-atmosphere CO2 exchange. Long-term observations also show that the spatiotemporal patterns of δ13C-CO2 vary interannually, which is mainly related to the impact of climate variability on the terrestrial biosphere. We are actively engaged in using these data in complex modeling frameworks to better understand the inter-relationships between climate and the global carbon cycle.
Integrating Deep Learning and the Google Earth Engine Could Computing Platforms for Fast and Accurate Cloud Masking
Authors: Zhang Chengkang , Wang Yueming , Nie Wen , Qi Yunliang , Zhang Lei , Ren Lei
Published: March 2024

In dealing with optical satellite images, accurate and efficient cloud positioning and masking are often the prerequisites for the subsequent tasks. However, the current cloud masking algorithms have difficulty in achieving these two goals at the same time. On the one hand, though many physically based models such as the Fmask algorithms have been proposed and widely applied, the performance of these methods still has some limitations including manually adjusted parameters in selecting the proper index and poor performance in thin cloud detection. This situation is much worse when applying the built-in Fmask in cloud-computing platforms such as the Google Earth Engine (GEE). On the other hand, an increasing number of sophisticated algorithms based on Deep Learning such as Convolutional Neural Networks (CNN) and Transformers have been proposed, they are, in most cases, deployed in local environments and require huge amounts of computational capacity to accomplish the tasks, which is inefficient and cannot be quickly utilized in large-scale and long-term studies, especially shows limitations with the trial of transferring the model into the GEE platforms. To solve the aforementioned dilemmas, the present study proposes a novel method for cloud masking by integrating deep learning and cloud-computing GEE. First, we construct a cloud dataset that is composed of globally selected cloud-contaminated pixels with the Fmask algorithm. Then, we use this cloud dataset to train a lightweight and flexible deep learning model based on LeNet. Last to screen out cloud pixels. Last, the developed model is transferred into the cloud-computing GEE platform and used to conduct cloud masking for each optical satellite image. The results show that in comparison to the conventional Fmask algorithm, the performance of the proposed exists superior in both detecting thick and thin clouds. More importantly, cloud masking can be achieved without bureaucratic procedures such as first downloading images and uploading the cloud masking, which is often required by locally developed deep learning models. By utilizing the proposed method, accurate and fast cloud detection can be achieved on the GEE platform that can be used in subsequent tasks like image compositing. For example, the generated monthly mean composting images show much better performance in visualizing ground objects when compared to those images based on the Fmask method, as the remaining cloud pixels that cannot be detected by the built-in Fmask algorithms can be more accurately examined. Through the usage of the proposed cloud mask methods, the merits of the powerful strength in data fitting and model optimization of deep learning algorithms and high efficiency in dealing with big data of GEE are naturally integrated, which is expected to shed light on cloud masking and other remote sensing modeling tasks.