bluuebunny/crossref_metadata_2025 huggingface dataset:
Indirect and direct aerosol feedback in the global and regional scale NOAA UFS Weather Model
Authors: Li Haiqin , Grell Georg , Ahmadov Ravan , Romero-Alvarez Johana , Zhang Li , James Eric , Baker Barry , Olson Joseph , Sun Shan , Schnell Jordan , Wang Ning
Published: February 2023

Aerosols play a significant role in the radiation and atmospheric precipitation physics of microphysics and convection, and have a significant impact on air quality, visibility, public health, aviation, and climate. A physics suite, which includes the aerosol-aware double momentum Thompson-Eidhammer microphysics scheme (TH-E MP), the scale-aware and aerosol-aware Grell-Freitas (GF) convection scheme, and the MYNN-EDMF boundary layer and shallow cloud scheme, was developed at NOAA Global System Laboratory (GSL). The GSL physics suite is applied in the FV3GFS global model and the Rapid Refresh Forecast System (RRFS) regional model. We also developed the RRFS – Smoke and Dust model (RRFS-SD) at NOAA GSL with the Common Community Physics Package (CCPP), which is designed to facilitate a host-model agnostic implementation of physics parameterizations. Because of the interactive and strongly coupled nature of chemistry and physics, it is natural to allow for the smoke, dust and other chemical modules to be called directly from the physics suite. Here we embedded the plume rise modules for wildfire, sea-salt, dust, and anthropogenic emission modules into the regional model of RRFS and global UFS model using CCPP as subroutines of physics. The prognostic emissions of sea-salt, and organic carbon are combined to represent the “water friendly” aerosol emission, while the prognostic emission of dust is used to represent “ice friendly” aerosol emission for TH-E MP. With this implementation, we examined the aerosol indirect feedback when using the TH-E scheme in the global FV3GFS forecast with C768 (~13km) horizontal resolution and 127 vertical levels. There are significant cloud-radiation responses to the aerosol differences, and the severely positive precipitation bias over Europe and North America is significantly alleviated when applying this aerosol emission method for indirect feedback. We also examined the smoke direct feedback to the radiation in the RRFS-SD with 3km horizontal resolution and 64 vertical layers for September, 2020 during which the western US experienced extreme wildfires. The aerosol direct feedback run significantly improves the forecast of aerosol optical depth, surface 2m air temperature, 10m wind speed, and radiation fluxes.
Measured mechanical, optical and electrical properties of dust partciles collected in the coma of comet 67/P
Authors: Hilchenbach Martin , Stenzel Oliver , Hornung Klaus
Published: February 2023

During the ESA ROSETTA science mission to comet 67P/Churyumov-Gerasimenko, the dust particle analysing instrument COSIMA sampled dust in the size range from a few um to mm equivalent diameter in the inner coma of the comet.  The particles were analysed in-situ with an optical microscope and a secondary ion mass spectrometer. The dust particles were collected on porous gold black surfaces with relative low impact velocity and the break up or fragmentation due to impact as well as by mechanical and/or electrical means have been studied. We summarize the results and conclusions on the measured mechanical, optical and electrical parameters such as porosity, material strength, reflectance, electrical conductivity and relative permittivity of the dust particles.
Does carbonly-water exchange of oxygen occur during phloem loading of sucrose? An exploratory study involving vapor 18O labelling techniques.
Authors: Song Xin
Published: February 2023

Stable oxygen isotope composition of tree ring cellulose (d18Ocell) has been increasingly used as a tool for reconstruction of environmental conditions (e.g. air temperature, precipitation, relative humidity) and ecophysiological variables (e.g. leaf temperature, stomatal conductance) that prevail during the period of tree growth. The current tree-ring d18Ocell mechanistic model assumes no oxygen exchange/biochemical fractionation effect during sucrose loading from the source leaf to the phloem, but is has been debated as to whether or not such an assumption is valid. Here, we performed an experimental study to quantify the possible extent of carbonyl-water exchange of oxygen during phloem loading. Towards this goal, we used a custom-made multiple-channel water vapor isotope signal labeling system to expose experimental plants to a range of water vapor d18O compositions under physiologically stable conditions; this in turn allowed the creation of a large gradient in d18O of leaf water, leaf sucrose, and phloem sucrose without disrupting plant physiology. We will present data collected from this experiment to examine the d18O relationships among the various water and sucrose pools, which may provide some insights into the possible isotope effects associated with sucrose translocation from leaf to the phloem. 
Reproducible Open Source Carbon Cycle Models Biogeochemical Model Database bgc_md2
Authors: Müller Markus , Metzler Holger , Ceballos Núñez Verónika , Viatkin Kostiantyn , Lotze Thomas , Wells Jon , Zhou Yu , Liao Cuijuan , Chandel Aneesh , Tao Feng , Huang Yuanyuan , Bennett Alison , Bian Chenyu , Jiang Lifen , Wang Song , Gang Chengcheng , Sierra Carlos , Luo Yiqi
Published: February 2023

How to formulate and run an element cycling model within a day?How to compare many models with respect to many different diagnostics reliably? How to allow models to be formulated in different ways?How to make runnable models transparent without implementation details obscuring the scientific content?bgc_md2 is an open source python library, available on github and binder. It provides an extendable set of datatypes that capture the essential properties compartmental models have in common and enables the formulation of a model with a few lines of regular python code. The structure of the model is captured in symbolic math (using sympy) and can be checked during the creation of the model e.g. by drawing a carbon flow diagram or printing the flux equations using the same mathematical symbols used in the publication describing the model. This can be done long before a complete parameter set for the model is added and the model can be run e.g. for a benchmark.The computation of diagnostic variables both symbolic or numeric is based on the common building blocks which avoids the effort, obscurity and possible inconsistency resulting from a model specific implementation. The difference in available data for different models is addressed by computational graphs.Instead of an inflexible schema for a relational database records can have different entries reflecting the available data.Using the computability graphs the comparable is extended to the computable data. This allows for instance comparing a model described by a collection of fluxes with one described by matrices.bgc_md2 is an extendable library that provides complex and well tested tools for model comparison but does not force the user into a rigid framework.Rather than full automation it aims at flexibility of use within the python universe and can be used interactively in a jupyter notebook as well as in parallel computations on a supercomputer for global data assimilation as we do in a current model inter comparison.Example jupyter notebooks can be explored interactively on binder without installation. 
Nitrogen input alleviates the priming effect of biochar addition on soil organic carbon decomposition
Authors: He Yanghui , Zhou Xuhui
Published: February 2023

The combination of biochar and nitrogen (N) addition has been proposed as a potential strategy to mitigate climate change by sequestering carbon (C), while simultaneously boosting crop yields. However, our current knowledge about how biochar and N addition alter mineralization of native soil organic C, which is referred to priming effects (PEs), is largely limited. To address these uncertainties, three C3 biochar (pyrolyzing rice straw at 300, 550, and 800 ℃) and its combination with N fertilizer (urea) were incubated in a C4-derived soils at 25 ℃ in the laboratory. Our results showed that all these 3 types of biochar with different addition rate caused positive priming of native soil organic C decomposition (up to +58.4%), but negative or no priming occurred in biochar bound N treatments. The maximum negative PEs (-14.5%) were observed in 300 ℃ biochar with 1% addition rate bound N (B1300N) treatment. We find a negative correlation between the priming intensity and soil inorganic N content across all treatments. Furthermore, the biochar-induced PEs regulated by microbial biomass, fungi/bacteria ratio, and microbial metabolic efficiency. These findings indicated that eligible biochar used for blending traditional mineral fertilizer has a larger climate-change mitigation potential than biochar and fertilizer alone, while sustain relatively high crop yields.
Plant-microbial interactions for nitrogen absorption converge between arbuscular- and ectomycorrhizal-dominated ecosystems at high nitrogen availability
Authors: Du Zhenggang , Zhou Xuhui
Published: February 2023

Nitrogen (N) availability is one of the critical limiting factors regulating plant growth, microbial activity, and the interactions between plants and soil microorganisms. The competition between plants and microorganisms, represented by the ratio of microbial N immobilization and plant N uptake (measured as Nim: PNU ratio), generally reflects the degree of N limitation in a terrestrial ecosystem. However, the key factors driving the pattern of Nim: PNU ratio across global ecosystems remain little understood. Here, using a global data set of 1022 observations from 184 studies, we examined the relative importance of mycorrhizal associations, N availability, climate, plant, and soil properties on the Nim: PNU ratio. Our results show that mycorrhizal fungi type (arbuscular mycorrhizal (AM) vs. ectomycorrhizal (EM) fungi) in combination with soil N availability explain the variation in the Nim: PNU across terrestrial ecosystems. In AM fungi-associated ecosystems, the relation between Nim and PNU displayed a weaker negative correlation (r =-0.06, p < 0.001), whereas there was a stronger positive correlation (r = 0.25, p < 0.001) in EM fungi-associated ecosystems. Those results indicated that the AM-associated plants display a weak interaction with soil microorganisms for N absorption, while EM-associated plants cooperate with soil microorganisms. Further, we found that the Nim: PNU ratio for both AM- and EM-associated ecosystems gradually converge at a stable value (14.7 vs. 13.5, p > 0.05) with greater N availability. Our study thus highlights that plant-microbial interaction for N absorption both equalize and stabilize at increased N supply, and both these mechanisms primarily depend on the mycorrhizal association of plants in terrestrial ecosystems.
Isotopic fingerprinting as an effective tool for polluter apportionment in environmental crimes involving groundwater
Authors: Gargini Alessandro , Filippini Maria
Published: February 2023

One pillar of the protection of groundwater established by the EU legislation is the “polluter pays principle”. Following this principle, the costs for the remediation of contaminated sites must be in charge of the responsible of the environmental crime. Compound Specific Isotope Analysis (CSIA), also known as “isotopic fingerprinting”, is a robust tool to apportion the source of groundwater contamination and eventually the polluter. The isotopic composition of the contaminant molecule may reflect the production process of a compound or the origin of the raw materials used in the production. Here we present the effective and decisive application of isotopic fingerprinting of carbon stable isotopes in the molecule of chlorinated hydrocarbons (chlorinated ethenes PCE-Perchloroethylene and TCE-Trichloroethylene) for the source apportionment in two contaminated sites in Italy, namely Ferrara (Emilia-Romagna region, Northern Italy) and Bussi sul Tirino (Abruzzo region, Central Italy). In both cases, industrial wastes from a production of chloromethanes, using methane and chlorine, were disposed illegally in unlined dumps resulting in a severe contamination of groundwater. The companies responsible for the contamination are different in the two sites but the production process is the same, resulting in a similar isotopic signature of the wastes. In both cases, the isotopic fingerprinting was critical to identify the chlorometane production as the source of contamination among other possible sources, despite two different hydrogeological settings (a large alluvial plain in the Ferrara site and a narrow valley with macroclastic alluvial deposits and travertines in the Bussi site). In both cases, PCE and TCE showed strongly depleted values of δ13C (isotopic ratio of the fraction of 13C respect to 12C isotopes of carbon) ranging between  -87 and -65‰ for PCE and between -79 and -64‰ for TCE. The very depleted isotopic values are related to the use of methane in the production process instead of coal, this last one being commonly adopted in the synthesis of PCE and TCE for commercial use (e.g. for laundry of textiles or metal degreasing). The groundwater contamination in the two sites had serious implications in terms of sanitary risk due to vapour intrusion into residential buildings (Ferrara site) or water ingestion by local citizens (Bussi site) from a public water supply well field site serving about 300.000 inhabitants and affected for more than 20 years by the contamination (from the opening in 1984 to the decomissioning in 2007). In both cases, complex legal issues arose either below penal or civil jurisdiction and the isotopic fingerprinting was used as the most relevant proof in order to identify the polluters.
A Dynamical Framework to Understand and Predict the Indian Summer Monsoon Low Pressure Systems
Authors: Srujan K. S. S. Sai , Sandeep Sukumaran , Kodamana Hariprasad
Published: February 2023

About 60% of the rainfall during the Indian Summer Monsoon (ISM) is manifested by the synoptic-scale storms form over North Bay of Bengal (BoB) and the adjacent land area known as “Low-Pressure Systems” (LPS). Unlike tropical cyclones, the storms during this season (LPSs) are embedded in the background monsoon flow, which makes them difficult to predict, considering the chaotic nature of the monsoon. Nearly one-third of these synoptic-scale storms are formed due to the amplification of disturbance which is propagating from the Western North Pacific (WNP) (categorized as “downstream LPS”). We observed an association of tropical cyclones (TCs) originating over WNP with the genesis mechanisms of downstream LPS over the BoB. The TCs over the WNP are classified into different clusters based on different features like length, genesis location, landfall, etc., using the gaussian mixture models. We found that four major clusters of WNP TCs are responsible for triggering 83% of the downstream LPS genesis. We established a causality using the transfer entropy analysis between the fluctuations in mean sea-level pressure over BoB and the Rossby wave activity over the WNP prior to the initiation of an LPS.Our results suggest a plausible prediction of downstream LPS at least a week ahead. The current generation of climate models has low skill in simulating the LPS; understanding the dynamics behind the genesis of LPS is the way to improve the LPS-related precipitation in climate models. The recent advancement in using AI/ML in predicting various weather and climate phenomena, including our recent study in predicting the synoptic-scale sea-level pressure using the ConvLSTM model explains the importance of dynamics-based data-driven ML models to predict complex weather patterns. Understanding the dynamics of such physical phenomena will help in identifying the appropriate predictors for the data-driven ML models.
Simulation of the Mediterranean Cyclone ‘IANOS’ using non-hydrostatic Weather Research and Forecasting model: Sensitivity to Convection Parameterizations and Microphysics
Authors: Mishra Alok Kumar , Jangir Babita , Strobach Ehud
Published: February 2023

The Mediterranean Sea’s distinctive and complicated terrain and the surrounding high mountain systems create a favorable environment for cyclogenesis. Despite Mediterranean cyclones being relatively weaker in intensities, smaller sizes, shorter lifetimes, and rarer than mid-latitude cyclones that develop over open oceans, they strongly influence the Mediterranean climate, including extremes. Despite notable improvements in the fine-scale processes, regional models still have considerable uncertainty. They are related to various constraints such as physical parameterization (convection schemes and microphysics), boundary conditions, and horizontal/vertical resolution. This study is focused on the sensitivity to microphysics schemes and convective parametrization using the non-hydrostatic Weather Research and Forecasting (WRF) numerical weather prediction model for a recent intense Medicane, ‘IANOS’, which was formed over the central Mediterranean Sea during 15-21 September. IANOS attained its mature stage on days 17–18 September and landed over the coast of Greece on 18 September. The horizontal grid spacing of 3 km × 3 km and 39 sigma levels up to 25 hPa were taken on one single domain covering most of the Mediterranean Sea, part of Europe, northern Africa, and part of the eastern North Atlantic Ocean. The simulation of IANOS shows strong sensitivity to the initial conditions, and the simulations initialized on 15 September or later show reasonable skill. All the microphysics schemes, ‘with and without’ enabling the convection scheme, reproduce the IANOS characteristics reasonably well with notable inter-simulation differences in magnitude and location. The large discrepancy and inter-simulation difference is noticed in the track and intensity on 18 September before hitting the coast.

Keywords: IANOS, WRF, convection parametrization, microphysics
On bedload particle deposition and hop statistics
Authors: Wu Zi , Jiang Weiquan , Zeng Li , Fu Xudong
Published: February 2023

Understanding the statistics of bedload particle motions is of great importance. To model the hop events defined as trajectories of particles moving successively from the start to the end of their motions, recently, Wu et al. (Water Resour Res, 2020) have successfully performed individual-based simulations according to the Fokker–Planck equation for particle velocities. However, analytical solutions are still not available due to (i) difficulties in treating the velocity-dependent diffusivity, and (ii) a knowledge gap in incorporating the termination of particle motions for the equation. In the latest work (Wu et al., J Fluid Mech, 2023), we have specified a Robin boundary condition representing the deposition of particles; and devised a variable transformation to deal with the velocity-dependent diffusivity. The original bedload transport problem is thus found to be governed by the classic equation for the solute transport in tube flows with a constant diffusivity after the transformation. By solving the spatial and temporal moments of the governing equation, we have investigated the influence of the deposition rate on three key characteristics of particle hops. Importantly, we have related the deposition rate to the mean travel times and hop distances, enabling a direct determination of this physical parameter based on measured particle motion statistics. The analytical solutions are validated by experimental observations with different bedload particle diameters and transport conditions.
Towards compatible finite element discretizations of stochastic rotating shallow water equations
Authors: Bauer Werner , Li Long
Published: February 2023

We introduce a stochastic representation of the rotating shallow water equations and a corresponding structure preserving finite element discretization in Firedrake. The stochastic flow model follows from using a stochastic transport principle and a decomposition of the fluid flow into a large-scale component and a noise term that models the unresolved flow components. Similarly to the deterministic case, this stochastic model (denoted as modeling under location uncertainty (LU)) conserves the global energy of any realization. Consequently, it permits us to generate an ensemble of physically relevant random simulations with a good trade-off between the representation of the model error and the ensemble's spread. Applying a compatible finite element discretisation of the deterministic part of the equations combined with a standard weak finite element discretization of the stochastic terms, the resulting stochastic scheme preserves (spatially) the total energy. To address the enstrophy accumulation at the grid scale, we applied an anticipated potential vorticity method (APVM) to stabilize the stochastic scheme. Using this setup, we compare different realizations of noise parametrizations in the context of geophysical flow phenomena and study potential pathways to fully energy preserving stochastic discretizations.
Exploring the physical state of Colombian lithosphere using body wave attenuation using ML
Authors: Kumar Rohtash , Singh Utkarsh Pratap , Rai Amritansh , Singh Ankit , Maurya Satya Prakash , Singh Raghav
Published: February 2023

The present study explores the P waves and S-wave attenuation characteristics to reveal the crustal physical state of entire Colombia region. A quality data set of 190 records of local events occurred during 2017-2021 has been analyzed. The epicentral distance of the events upto 200 km with magnitude greater than 4.5. The data is provided by IRIS_DMC from Global Seismographic Network (GSN). The extended coda normalization method of Yoshimoto et al. (1993) is employed for estimation of P-wave quality factor (Qα) and S-wave quality factor (Qβ). For 5 second windows, the S, P, and coda-wave spectra are examined at nine center frequencies viz. 1, 1.5, 3, 6, 9, 12, 15, 18 and 24 Hz. With increase in frequency, both Qα and Qβ values rise. The Qα values increases from 50.88 at 1.0 HZ to 806.36 at 24 Hz and Qβ varies from 44.89 at 1.0 Hz to 1595.55 at 24 Hz. Therefore, both Qα and Qβ are reliant on frequency with frequency dependent relationships Qα = 40.152f0.8425and Qβ = 35.301f1.2479. The average Qα and Qβ results reported in this study are in good agreement with results from previous studies, with low Q0 values less than 200, which are indicative of seismically and tectonically active area. We found that Colombia region Qα and Qβ values are comparable to those of other seismically active regions throughout the world. The observed ratio of Qβ / Qα is greater than unity over the whole examined frequency range shows that the earth medium of the study region has a significant degree of heterogeneities. The obtained relations in the study will be quite useful in simulation of earthquake ground motion as well as seismic hazard assessment which will be quite helpful in minimizing the loss of life and damage to property in the area.
Stochastic models for earthquake occurrence
Authors: Papadimitriou Eleftheria
Published: February 2023

The complexity of seismogenesis requires the development of stochastic models, the application of which aims to improve our understanding on the seismic process and the associated underlying process. Semi Markov models are introduced for estimating the expected number of earthquake occurrences with the classification of the model states based on earthquake magnitudes. The instantaneous earthquake occurrence rate between the model states as well as the total earthquake occurrence rate can be calculated. Seismotectonic characteristic of the study area, incorporated in the model as important component of the model, increase the consistency between the model and the process of earthquake generation and support a classification that integrates magnitudes and style of faulting, thus being more effective for the seismic hazard assessment. For revealing the stress field underlying the earthquake generation, which is not accessible to direct observation, the hidden Markov models (HMMs) are engaged. The HMMs consider that the states correspond to levels of the stress field and its application aim to reveal these states. Different number of states may be examined, dependent upon the organization of observations, and the HMMs are capable to reveal the number of stress levels as well as the way in which these levels are associated with the occurrence of certain earthquakes. Even better results are obtained via the application of hidden semi–Markov models (HSMMs) considering that the stress field constitutes the hidden process and which, compared with HMMs, allow any arbitrary distribution for the sojourn times. The investigation of the interactions between adjacent areas is accomplished by means of the linked stress release model (LSRM), based upon the consideration that spatio–temporal stress changes and interactions between adjacent fault segments constitute the most important component in seismic hazard assessment, as they can alter the occurrence probability of strong earthquakes onto these segments. The LSRM comprises the gradual increase of the strain energy due to continuous tectonic loading and its sudden release during the earthquake occurrence. The modeling is based on the theory of stochastic point process, and it is determined by the conditional intensity function. In an attempt to identify the most appropriate parameterization that better fits the data and describes the earthquake generation process, a constrained “m–memory” point process is introduced, the Constrained–Memory Stress Release Model (CM–SRM) implying that only the m most recent arrival times are taken into account in the conditional intensity function, for some suitable mÎN, instead of the entire history of the process. The performance of the above mentioned models application are evaluated and compared in terms of information criteria and residual analysis.
Recognizing distinct climate effects of combustion energies from different sectors
Authors: Jiang Ke , Shen Guofeng
Published: February 2023

Fuel combustion provides basic energies for the society but also significantly affect environmental quality and the global issue of climate change. The sustainable energy transition should systematically evaluate impacts of current and future combustion energies on climate by taking multi-forcers into the consideration. A variety of fuels burned in different facilities expectedly has distinct impacts on climate by different climate forcers, which remains to be quantitatively assessed. This work studied climate effects of different fuel combustion processes, taking both greenhouse gases (GHGs) and short-lived climate forcers (SLCFs) into the consideration, and analyzed their spatiotemporal characteristics. By using updated emission inventories and an Earth System Model, we evaluated absolute and relative contributions in energy and climate forcing and the nexus for the combustion emissions by fuels, sectors, and regions. We found that, from 1970 to 2014, biomass burning contributed 11.6% to the accumulative anthropogenic energy consumption, but only 7.6% to the radiative forcing. However, fossil fuel combustion showed short-term cooling effect compared to biomass. Within fossil fuels, coals burned in the energy sector and oil used in the transportation sector contributed comparable energies consumed (24% and 20% of the total) but had distinct climate forcing (1% and 40%, respectively). Globally, coals burned in the energy production had negative impacts on climate forcing, but positive effects in the residential sector. Coals burnt in the energy sector in developing regions had lower climate forcing effect per unit energy (RF/E) compared to that in developing regions like Asian countries, but they had higher RF/E in oil used in the transportation section. Distinct climate efficiencies of energies and the spatial heterogeneity call for differentiated energy utilization strategies and pollution control technologies and policies. The short-term but strong climate impacts due to relative cooling SLCFs control are expected to be considered in the tipping point study of the planet boundary.
On the effectiveness of green infrastructure to reduce stormflow at catchment scale
Authors: Klaus Julian , Busch Paulina , McHale Michael
Published: February 2023

Population growth and climate change alter the urban water cycle resulting in increasing frequency and magnitude of urban floods. In this study, we compared stormwater response in an urban drainage system between two adjacent urban sewersheds in Buffalo, NY, USA. At the first site (DEL), comprehensive installations of green infrastructure (GI) (i.e. bioretention cells) were carried out, while the second site (SQ) was minimally influenced by GI practices. Stormflow was monitored as pipeflow at both sites for an observation period of five years, three pre-construction and two post-construction years. We identified storm events and calculated event runoff, as excess flow above baseflow. Additionally, we evaluated annual total flow and peakflow (annual and seasonal) between the sites and between pre- and post-construction. Our analyses were confined to snow-free seasons because storage of precipitation in the snowpack confounds the evaluation of the precipitation-runoff relation. The analysis showed that the GI implementation was highly effective in reducing stormflow. Total annual flow was reduced at DEL between pre- and post-construction, while no trend was observable at the minimally influenced by GI SQ. Also, event-based stormflow was reduced through GI implementation across all snow-free seasons. Last, median event peakflow was clearly reduced through GI, especially in spring and summer, whereas results during fall were less clear. Through this hydrometric analysis, this study is among the first that provided evidence for the efficiency of GI in reducing stormflow beyond the plot-scale and thus provides future guidance on flood mitigation in urban environments.       
SHAFTS – A deep-learning-based Python package for Simultaneous extraction of building Height And Footprint from Sentinel Imagery
Authors: Li Ruidong , Sun Ting , Tian Fuqiang , Ni Guangheng
Published: February 2023

Buildings are common components in the urban environment whose 3D information is fundamental for urban hydrometeorological modeling and planning applications. In order to monitor building footprint and height across large areas on a regular basis, recent earth observation research has witnessed promising progress in mapping such information from publicly available satellite imagery by statistical methods using regression between multi-source remotely sensed data and target variables. However, most of them often involve tedious feature preprocessing, which constrains their capability to establish a comprehensive representation of an ever-changing and multi-scale urban system efficiently.Considering this bottleneck, this work develops a deep-learning-based (DL) Python package-SHAFTS (Simultaneous building Height And FootprinT extraction from Sentinel Imagery) to estimate 3D building information at various scales. SHAFTS provides Convolutional Neural Networks (CNN) with the Multi-Branch Multi-Head (MBMH) structure to automatically learn representative features shared by building height and footprint mapping tasks from multi-modal Sentinel imagery and additional background DEM information. Besides, to leverage the power of big data infrastructures, SHAFTS offers essential functionality including automatically collecting potential reference datasets by web scraping and filtering appropriate input imagery from Google Earth Engine, which can effectively ease model upgrading and deployment for large-scale mapping.To evaluate the patch-level prediction skills and city-level spatial transferability of developed models, this work performs diagnostic performance comparisons in 46 cities worldwide by using conventional machine-learning-based (ML) models and CNN with the Multi-Branch Single-Head (MBSH) structure as benchmarks. Patch-level results show that DL models successfully produce more discriminative feature representation and improve the coefficient of determination of building height and footprint prediction over ML models by 0.27-0.63, 0.11-0.49, respectively. Moreover, stratified error assessment reveals that DL models effectively mitigate severe systematic underestimation of ML models in the high-value domain. Additionally, within the DL family, comparison in spatial transferability demonstrates that the MBMH structure improves the accuracy of CNN and reduces the uncertainty of building height predictions in the high-value domain at the refined scale. Therefore, multi-task learning can be considered as a possible solution for improving the generalization ability of models for 3D building information mapping.
Evaluation of remotely sensed and reanalyzed irrigation maps over China
Authors: Tian Xin , Dong Jianzhi , Wei Lingna , Kang Xiaoqi , Zhang Huiwen , Sun Xiaosong , Li Shuaikun , Zhao Dexing , Li Yuxi
Published: February 2023

The uncertainty of the irrigated area is a key error source of irrigation modeling. Existing irrigation maps, produced by either remote sensing or reanalyzed dataset, are known to contain substantial inter-product differences. However, relatively little work has been done to comprehensively compare and evaluate these irrigation maps. This study uses censored data collected from the National Bureau of Statistics (NBS) of China to evaluate irrigated areas derived eight commonly used irrigation maps at county levels. The spatial distribution and the temporal variability these products are evaluated using more than 1651 country-level data record during the period of 2000 to 2020. Based on our analysis, we seek to provide insights into the reliability of using current available irrigation maps for large scale modeling analysis and future developments of the large-scale irrigated area mapping.
Optical Dating of Agricultural Terrace Deposits
Authors: Lang Andreas , Bahl Chiara , Snape Lisa , Mauz Barbara , Brown Anthony
Published: February 2023

Agricultural terraces are common features of cultivated hillsides across the world and have recently attracted increasing attention as archives of land-use practices and as soil carbon depositories. Such terraces originate from various soil translocation processes and throughout usage are subject of frequent reworking. Establishing chronologies for agricultural terraces usage is, thus, notoriously difficult. Here, we report results from optically-stimulated luminescence dating of terrace sediments that (i) originate from a wide range of locations across Europe stretching from the Polar circle to the Mediterranean; (ii) are derived from various host lithologies including igneous rocks, Triassic sedimentary rocks, Neogene marine deposits, and Pleistocene glacial and periglacial sediments; (iii) represent a range of cultivation styles including labour intensive manual techniques as well as mechanised tillage; and, (iv) cover a wide span of time periods from the Early Bronze Age through to modern times. Reliable chronologies of optical ages, consistent internally and in agreement with independent age information, were established on silt-sized quartz extracts from loess derived terrace deposits and on sand-sized quartz grains derived mostly from sedimentary host rocks. OSL signals of quartz extracted from deposits with igneous and turbiditic host rocks are often not of sufficient quality for optical dating purposes.
Large-scale perspective on the extreme near-surface winds in the central North Atlantic
Authors: Stanković Aleksa , Caballero Rodrigo , Messori Gabriele
Published: February 2023

This study investigates winter cyclones that cause extreme 10 m winds in the central North Atlantic region (30o to 60o latitude, -50o to -10o longitude) in the ERA5 dataset. We employ a bottom-up approach consisting of selection of the extreme 10 m wind events and analysis of the cyclones that caused the extremes.The 10 m wind extremes were ranked using the Klawa and Ulbrich (2003) destructiveness index, which takes into account wind exceedances over the local 98th percentiles. The top 1% of destructive events were chosen for further analysis. Cyclones were associated with the extreme winds by finding the closest sea-level pressure lows at the times of maximum wind speeds.By analyzing various meteorological fields associated with the temporal evolution of the selected cyclones, we find an important role of interactions with other pre-existing cyclones that create suitable conditions for the development of the subsequent extreme windstorms.  
Variations in the amplitude of El Niño–Southern Oscillation in the past 250 million years
Authors: Li Xiang , Hu Shineng , Hu Yongyun , Guo Jiaqi , Lan Jiawenjing , Lin Qifan , Yuan Shuai
Published: February 2023

The El Niño–Southern Oscillation (ENSO), originating in the central and eastern equatorial Pacific, is a defining mode of interannual climate variability with profound impact on global climate and ecosystems. Although ongoing coordinated community efforts have offered insights into how ENSO will change in the future under anthropogenic warming, the geological history of ENSO remains intricate. In particular, there is a clear lack of systematic study on how ENSO has evolved in response to vast variations in land-sea distributions and climate mean states over geological timescales. To unravel this, we analyze a series of time-slice coupled climate simulations forced by changes of paleogeography, atmospheric CO2 concentrations, and solar radiation in the past 250 million years (Myr). Our simulations for the first time demonstrate that ENSO is the leading mode of tropical Pacific sea surface temperature (SST) in the past 250 Myr. Further, the amplitude of ENSO is predominantly captured by the zonal advective feedback and thermocline feedback, both of which are primarily regulated by eastern equatorial Pacific climatological SST. These findings highlight the significance of climate mean states in interpretation of the amplitude of ENSO during the deep past, and provide enlightening implications for constraining future climate change.
Enhanced solar radiation pressure modeling for LEO precise orbit determination: result validation and improvement
Authors: Li Min , Wang Youncun , Jiang Kecai , Li Wenwen , Zhao Qile , Fang Rongxin , Wei Na , Mu Renhai
Published: February 2023

Precise orbit knowledge is a fundamental requirement for low Earth orbit (LEO) satellites. Accurate non-gravitational force modeling directly improves the overall quality of LEO precise orbit determination (POD). Time-dependent radiation data and modeled physical effects are considered to address the potential approximation errors in solar radiation pressure (SRP) modeling. We develop an advanced thermal reradiation model for satellite solar panels. A set of improved non-gravitational force models is performed for LEO POD, and we discuss the benefits of the enhanced dynamic models on orbit quality and dependence on empirical parameters. The Gravity Recovery and Climate Experiment Follow-On (GRACE-FO), Jason-3, and Haiyang-2B missions are selected for the POD process. Estimated empirical acceleration and scale parameters and independent satellite laser ranging (SLR) are used to validate the final orbit solutions. The magnitude of empirical acceleration estimated in POD is reduced by 19% with the enhanced dynamic modeling, and the estimated scale factor for the SRP converges to stable and reasonable level. Furthermore, the steady-state temperature model used in thermal reradiation can effectively reduce mismodeled effects in the SRP, and the systematic linear dependency revealed by the SLR residuals is significantly reduced for the GRACE-C and Jason-3 satellites, with improvements of approximately 61% and 49%, respectively. With the enhanced non-gravitational force models, the SLR validation shows the best orbit solutions with RMS values of 10.4, 10.1, 12.4, and 13.2 mm for the GRACE-C, GRACE-D, HY-2B, and Jason-3 satellites, respectively. Overall, advances are made in the explicit modeling of non-gravitational forces to pursue superior satellite orbits, suggesting a more dynamic orbit solution.
On the attribution of annual maximum discharge across the conterminous United States
Authors: Villarini Gabriele , Kim Hanbeen
Published: February 2023

Floods affect many aspects of our lives, and our improved understanding of the processes driving the historical changes in this natural hazard can provide basic information to enhance our preparation and mitigation efforts. Here we analyze 3,885 streamgages across the conterminous United States and attribute the inter-annual variability in annual maximum discharge to precipitation and temperature. This is accomplished by first developing gamma regression models to describe the seasonal maximum discharge in terms of basin-averaged precipitation, temperature, and antecedent wetness (i.e., the basin-averaged precipitation for the season prior to the one of interest, and used as a proxy for antecedent soil moisture conditions). These seasonal models are then mixed through a Monte Carlo approach to obtain the annual maximum discharge distribution. Despite its simplicity, our results show that the developed statistical attribution approach can describe very well the inter-annual variability in annual maximum discharge across the conterminous United States.
Generalized Image Segmentation Model for Multi-annual Retrogressive Thaw Slumps Mapping
Authors: Lin Yiling , Mirzadeh Sayyed Mohammad Javad , Hu Xie , Liu Jifu
Published: February 2023

The railways and highways along the Qinghai Tibet Engineering Corridor (QTEC) were established on the frozen ground. Intensive engineering construction and human activities have significantly disturbed the permafrost environment. The melting of ice-rich permafrost closely relates to the carbon release. Beyond that, elevated pore fluid pressures may initiate or enlarge retrogressive thaw slumps (RTSs), which may further damage the foundation of critical transportation lifelines. However, the precise locations and margins of hundreds of RTSs around QTEC have not been systematically identified and delineated due to their remote locations and divergent surface features. The development of deep learning makes it possible to automatically and accurately identify and delineate the margins of RTSs. However, inventorying multi-temporal and large-scale RTS is challenged by the low generalization of deep learning model. Here we will apply the DeepLabv3+ segmentation algorithm to decipher 3-meter resolution PlanetScope optical images for a RTSs detection model. Fine-tuning, CycleGAN, and domain adversarial training will be used to improve the model's generalization ability. The time-dependent metric changes of RTSs will be investigated based on 2018-2022 multi-temporal RTS inventories. We will further extract the ground displacements over the mapped RTS using European Space Agency’s Copernicus Sentinel-1 satellite images and time-series Interferometric Synthetic Aperture Radar (InSAR) analysis. Our study leverages remote sensing big data and deep learning methods for hazard mitigation over the frozen ground in high environmental vulnerability.
Wave impact force and dynamic pressure on a monopile under different scenarios of focused breaking waves
Authors: Cui Ting , Yuan Lihao , Han Duanfeng , He Guanghua , Wang Weizhi , Bihs Hans
Published: February 2023

Cylindrical slender members are typical compositions of many offshore and harbor structures. Extreme wave impact loading on such monopile structure is a very important problem as the slamming force acts for a very short period of time and the magnitude of the load is high. This study aims to estimate the breaking impact dynamic force on a monopile based on the numerical simulational results to analyze the loading characteristics in finite water depth. The simulation of the interaction between the focused breaking waves and monopile is carried out in a numerical wave tank established based on the two-phase flow model in REEF3D, the open-source computational fluid dynamics program. The fluid field is governed by the Reynolds-averaged Navier-Stokes equation. Two equation k-w turbulence models are adopted to model the turbulence structures during the complicated chaotic interaction process between the focused breaking wave and a single vertical cylinder. Four different locations of typical breaking scenarios are chosen to investigate the breaking loading variation during the breaking process. The situation when the wave breaks after the structure is selected in a wave-breaking process to evaluate the quasi-static force. Based on this method, the dynamic loading due to wave breaking can be evaluated. The harmonic structure of the dynamic force is analyzed using the FFT method. The slamming force on the cylinder is different as wave-breaking intensities change during the breaking process. The dynamic pressure and wave run-up on the cylinder are also investigated under four typical breaking situation.
Dayside neutral wind vertical shear at low F region altitude observed by the ICON satellite
Authors: Huang yuyang , Xiong Chao
Published: February 2023

The Michelson Interferometer for Global High-Resolution Thermospheric Imaging (MIGHTI) onboard the Ionospheric Connection Explorer (ICON) mission measures the neutral winds from 88 km to 310 km altitudes, which provides a good opportunity to investigate the vertical distribution of neutral winds, especially their vertical shears. Based on over two years data from MIGHTI/ICON, we focused on the wind vertical shears at the low F region (from 88 km to 245 km) in this study. As the green line of MIGHTI works only on the dayside, only the dayside from 0600 to 1800 local time (LT) has been considered. As a result, there were 206 and 96 orbits were identified with clear vertical shears for the meridian and zonal wind components, respectively. Interestingly, such wind vertical shears occurred not only during magnetically disturbed periods, as there were 75.73% and 78.12% orbits with vertical shears identified in the meridional and zonal wind with Kp less than 2. Dependences of the wind vertical shears on local time (LT), geographic latitude (Glat) and longitude (Glon) have been further checked, and we found that the wind vertical shears have different trends for the LT dependence, e.g., the mean altitude of meridional (zonal) wind reversed from southward to northward (westward to eastward)  is higher at dawn, and then slowly decreases toward dusk; or the mean altitude of wind reversal is higher at dusk and slowly increases towards dusk. Such two kinds of altitude trends of the wind vertical shears were also found for the dependence on Glat, but not on Glon. The mean altitudes of wind reversal are around 160 km for most of the Glon sectors, with only a slight decrease or increase at the sector where the magnetic equator is far away from the geographic equator, indicating that the ion drag should also play a role in causing the wind vertical shears. The relation between the wind vertical shears at E (England et al., 2022) and low F region altitudes have been further investigated. From the orbits with wind vertical shears at low F region identified, there were about 90% orbits with also wind vertical shears simultaneously observed at the E region, but the altitude trends can be the same or opposite for the vertical shears at the two regions, even for the same orbit. Such a relation suggests that the causes for wind vertical shears at the E and low F region altitudes could be different.