bluuebunny/crossref_metadata_2025 huggingface dataset:
Status and plan of ensemble forecast system in Korea Meteorological Administration (KMA)
Authors: Kim Eun-Jung , Shin Hyun-Cheol , Park Jong Im , Ha Jong-Chul , Kwon Young-Cheol
Published: February 2023

The ensemble forecast system based on the Korea Integrated Model (KIM), which is developed for Korea’s own numerical weather prediction (NWP) model, has been in operation at Korean Meteorological Administration (KMA) since October 2021. KMA ensemble forecast system consists of 50 perturbation members (25 members for long-range forecast) and 1 control simulation. Four-dimensional LETKF (Local Ensemble Transform Kalman Filter) with additive and RTPS inflation scheme is used to make initial perturbation. Evaluation of forecast scores shows that our operational ensemble forecast system is generally more skillful compared to the deterministic simulation as forecast time is longer. Also, forecast with increased ensemble size produces better representation of atmospheric fields especially in higher latitudes. Details of results from operational ensemble system and impacts of increased ensemble size will be discussed with introducing a brief overview of our ensemble forecast system and development plan in future. 
GAN-based forecasting model via self-adaptive clustering approach
Authors: An Sojung , Oh Tae-Jin , Na Inchae , Jang Jiyeon , Park Wooyeon , Kim Junghan
Published: February 2023

Deep learning has been rapidly adopted in short-term precipitation prediction, such as simulating precipitation movement and predicting extreme weather events. Recently, generative adversarial neural networks (GANs) have been shown to be effective at dealing with field smoothing with increasing lead time. Several studies (Jing et al., 2019; Ravuri et al., 2021) demonstrated the potential of GAN by solving spatial smoothing problems and demonstrating reliable predictive performance. However, despite promising results from GANs, unbalanced datasets and human annotations can limit the predictive ability of deep learning and induce biased results. In addition, precipitation is a complex process that depends on various factors. Thus, approximating the model into a single latent space is a challenge, and furthermore, there is a risk of mode collapse. This study introduces an algorithm for predicting precipitation by clustering precipitation types using self-supervised learning (SSL) and estimating rainfall distribution according to precipitation types. First, we derive precipitation-type labels by self-clustering a generator that is a multi-layer ConvGRU. And then, we predict six-hour precipitation based on the gaussian distribution of each type. SSL improves the performance of precipitation forecasting based on type-specific representation learning through adaptive sampling in latent space. The proposed methodology was verified using hybrid surface rainfall (HSR) dataset at a spatial resolution of 500m with a resolution of 2,305 (longitude) × 2,881 (latitude) and a temporal resolution of 5 min. The images consist of 256×256 pixels from scaling down to a resolution of 4 km and are extracted at 30-minute intervals. Experimental results show that our method outperforms a state-of-the-art method on a six-hour prediction basis with a mean squared error and critical success index on unseen datasets. Also, the proposed algorithm can predict various precipitation types without spatial smoothing.
Increasing destructive potential of extratropical transition events in response to higher CO2 concentration in global climate model
Authors: Cheung Hung Ming , Chu Jung-Eun
Published: February 2023

When tropical cyclones (TCs) move to the mid-latitudes, they encounter the baroclinic environment where many of them experience extratropical transition (ET) by which they lose the symmetric and warm-core characteristics and transform into extratropical cyclones (ETCs). ETCs are usually faster than TCs and oftentimes destructive to coastal cities with strong wind and heavy precipitation. Climate models predict that the mean intensity of TCs would become stronger fundamentally due to the increase in atmospheric moisture contents in response to global warming. However, whether the destructiveness of ETCs originated from TCs will change in the future has not been explored with a high-resolution fully-coupled model. To understand the future changes in ET events and the destructive potential of these ETCs, we analyzed the high-resolution Community Earth System Model (CESM) simulations (0.25 degrees for the atmosphere and 0.1 degrees for the ocean) with present-day, doubling, and quadrupling CO2 concentrations.The high-resolution model well captures the frequency and annual cycle of the ET events compared to observation with underestimated frequency in the North Atlantic and West Pacific while overestimating them in the East Pacific, South Indian, and South Pacific. Our results show that the frequency and ratio of ET events do not change significantly in both CO2 doubling and quadrupling experiments. An increase in 10-m wind speed at ET completion is observed mainly in North Atlantic and South Indian. We used the total integrated kinetic energy, which depends on the wind speed and the area covered by the high wind region of a storm, to represent the destructive potential of a storm upon ET completion. It is found that the relative ratio of the strongly destructive ETCs to weaker ETCs increase in response to greenhouse warming.Our study highlights the destructive potential of transitioned TCs. Since ETCs usually have greater spatial coverage than TCs, the former can impact a larger population and region, albeit with lower intensity. Therefore, accurate prediction of future changes in ET events can have significant socio-economic implications.
Geophysical evidence of large-scale silica-rich fluid flow above the continental subduction interface
Authors: Mao Yuantong , Zhao Liang , Malusà Marco , Solarino Stefano , Pondrelli Silvia , Sun Baolu , Aubert Coralie , Salimbeni Simone , Eva Elena , Guillot Stéphane
Published: February 2023

Continental subduction zones are crucial tectonic settings where subducted slabs exchange crustal materials with the mantle, and geochemical changes occur with the participation of fluids at increasing temperatures and pressures. The occurrence of pervasive networks of quartz veins in exhumed sections of the Alpine subduction wedge provides evidence for major silica-rich fluid circulation in the shallowest levels of the subduction zone. However, the occurrence of silica-rich fluids at greater depths above the subduction interface remains speculative.Rocks involved in the subduction zone experience variable temperature and pressure conditions and show a wide range of densities and seismic velocities that are not necessarily correlated. An integrated analysis of seismic velocities, Vp/Vs ratios and rock densities may provide a viable tool to detect compositional variations in the Earth’s interiors and infer the impact of large-scale fluid flows on the intrinsic physical properties of subducted rocks. We tackle this issue from a geophysical perspective, by applying H-κ stacking, receiver function analysis, and waveform and gravity modelling. We found a belt of high Vp/Vs ratios >1.9 in the rear part of the Alpine subduction wedge, consistent with a partly serpentinized upper-plate mantle, and a belt of unusually low Vp/Vs ratios <1.7 in the frontal part of the subduction wedge that we interpret as the effect of a pervasive network of silica-rich veins above the subduction interface. Laboratory experiment shows that Vp/Vs ratios are generally higher for serpentinite (2.0-2.2), and much lower for quartz (1.46-1.48).Our results suggest a dominant role of silica-rich fluids in the subduction wedge. These silica-rich fluids rose within the subduction wedge until the change in ambient conditions precipitated the formation of a widespread network of quartz veins, as observed in the field. And this pervasive quartz-vein network changes the physical properties of the subduction-wedge rocks, implying a major impact on rheology favoring crustal deformation during continental subduction.
Impact of the Indo-Pacific Warm Pool on the Tropical Circulations and Changes in Saturation Threshold SST
Authors: Kim Hye-Ryeom , Ha Kyung-Ja
Published: February 2023

The Indo-Pacific warm pool (IPWP) is enclosed by a 28 ◦C isotherm and plays a vital role in controlling tropical circulations. However, the effects of changes in regional warm pool sea surface temperatures (SSTs) on the circulations remain unexplored. To do this, we divided the IPWP into the Indian and Pacific sectors and distinguished their responses to natural variability and global warming. And then, we examined the impacts of the interannual variability (IAV) in warm pool SST on the tropical Hadley, Walker, and monsoon circulations. The Hadley circulation was affected by warm pool SST warming, i.e., warmer SSTs over the warm pool strengthened the upward branch of Hadley circulation, whereas the downward branch was weakened and strengthened in the Northern and Southern Hemispheres. Walker circulation was strengthened (weakened) in the warming (natural) mode. Consequently, the Walker circulation is weakened since the natural variability of warm pool SST plays a more dominant role than the warming trend of SSTs over the warm pool. It is notable that warm pool warming has little impact on monsoon circulation. Our findings highlight the different roles of the IAV of warm pool regions in each tropical circulation as part of the warming trend and natural variability. Furthermore, an increase in precipitation is limited up to a specific SST, although SST becomes warmer. We defined this specific SST as Saturation Threshold SST (STT). Under a warming climate, future changes in STT over the IPWP and its mechanism will be shortly shown in this presentation.
Pb isotope heterogeneities in the mantle and links to the supercontinent cycle
Authors: Armistead Sheree , Eglington Bruce , Pehrsson Sally , Huston David
Published: February 2023

Isotopic proxies such as Hf, Nd and Pb are widely used to understand the evolution of Earth’s crust and mantle. Of these, Pb isotopes are particularly sensitive to crustal influences, and the extraction of mantle melts. We present a global compilation of Pb isotope data from syngenetic Volcanogenic Massive Sulphide (VMS) deposits, which allow us to track the evolution of Pb isotopes in deposits that are associated with dominantly back-arc and extensional oceanic settings through time.Unradiogenic Pb isotope signatures, specifically low model source µ (238U/204Pb) values, in some Archean cratons have long been recognised, yet their origin remains elusive. For example, sulphides from the c. 2.7 Ga Abitibi Belt in the Superior Province of Canada require long-lived (> 500 my) evolution of a source component to generate the Pb isotope signatures observed. Other isotope systems, such as Lu-Hf and Sm-Nd, show relatively juvenile signatures for the Abitibi Belt, suggesting decoupling of the different systems. Low µ values are evident in ore deposits and rocks from the Archean to modern settings but are most prominent in Archean settings because of their associated low 207Pb/204Pb values, unlike for younger times.Pb isotope data at a global and broad temporal scale show that periods with distinct low µ values have a marked cyclicity that coincides with the supercontinent cycle. We propose that during supercontinent assembly, portions of older unradiogenic, Pb-rich mantle are tapped and incorporated into VMS deposits. Pb, possibly enriched in sulphides, can explain the apparent decoupling of Pb from silicate-controlled isotope systems like Hf and Nd. We suggest that the source of this unradiogenic mantle component formed during the previous supercontinent cycle when large volumes are extracted from the mantle to form (radiogenic) crust and an unradiogenic residue, which most likely resides in the lithospheric mantle although some may also be present as discrete ‘pods’ in the circulating mantle. This process provides a mechanism to explain isolation of source regions for several hundred million years, as required to generate the low µ values, until later tapping during a subsequent supercontinent amalgamation cycle.The low µ values in the c. 2.7 Ga Abitibi Belt represent the best-known Archean occurrence of this signature, indicating that their unradiogenic source relates to a major mantle extraction event that would have occurred at least 500 my earlier, i.e. at about 3.2 Ga.
Stalagmite-inferred hydroclimate changes in northern Italy during Allerød/Younger Dryas transition
Authors: Hsieh Chieh-Ju , Hu Hsun-Ming , Shen Chuan-Chou , Michel Véronique , Valensi Patricia , Starnini Elisabetta , Zunino Marta
Published: February 2023

The Younger Dryas (YD), a 1200-year-long cooling event interrupting the warm Bølling-Allerød period, started from 12,870 ± 30 yr BP (2σ, before 1950 C.E.). Here we present decadal-resolved stalagmite BA18-2 multi-proxy records from Bàsura cave, northern Italy. The StalAge age-depth model with 8 U-Th dates with 2-sigma errors of ± 26-193 yrs shows that BA18-2 encompasses Allerød/YD transition, from 14,038 ± 92 to 12,090 ± 54 yr BP. Oxygen isotope data fluctuate between -7.16‰ and -3.68‰, with a clear 2.4‰ increase during the YD onset at 12,870 ± 30 yr BP. Stalagmite BA18-2 Sr/Ca and Ba/Ca linger from 0.060-0.085 mmol/mol and 6.4-9.1 µmol/mol, respectively, from 14,038 ± 92 to 12,681 ± 55 yr BP, ~ 2 centuries after the beginning of YD. A clear 160-year-long two-step increase in both Sr/Ca and Ba/Ca records started from 12,681 ± 55 yr BP, which is a 200-yr lag relative to the timing of BA18-2 oxygen isotope increasing trend. We argue that the oxygen isotope could be governed by temperature, moisture source, and/or rainfall amount; while, the Sr/Ca and Ba/Ca ratios predominantly reflect precipitation change. Our results might suggest asynchronous thermal and hydrological changes in northern Italy during the Allerøod/YD transition.
Muon tomography optimization for dry cask spent nuclear fuel storage imaging
Authors: Valencia Jesus , Hecht Adam
Published: February 2023

Dry cask spent fuel storage containers currently house much of the world’s spent nuclear fuel stores outside of spent fuel cooling pools. In order to maintain, continuity of knowledge of these containers, seals are applied. When these seals are broken, the containers must be relocated to spent fuel pools for visual inspection.  Large amounts of steel shielding, required for radiation safety, significantly attenuates both radiation emitted from the fuel itself and incoming radiographic probes such as x-ray and neutrons. As a result, the effectiveness of these more traditional radiographic probes is greatly diminished, and no other passive, in situ verification methods are currently in use. While promising results have been demonstrated, long measurement times limit the attractiveness of cosmic-ray muon radiography as a passive verification method. The work presented here compares performance of differing reconstruction techniques to draw recommendations for the optimization of future cosmic-ray muon tomography measurements. For tomographic imaging, the results show that using a plenoptic depth of field reconstruction method, rather than traditional backprojections, results in better imaging resolution for a limited number of views. The depth of field reconstruction method also requires a smaller number of views to reconstruct images useful in the verification of dry cask spent fuel storage containers.
Discovery of Neoproterozoic glaciogenic diamictites and cap carbonate couplet in the Alxa Block, NW China: Evidence from stratigraphic, sedimentologic and geochemical studies
Authors: Shao Dong , Han Yigui , Li Meng , Lu Lihui , Cao Xuyang , Ju Pengcheng
Published: February 2023

The global-scale glacial events recorded by diamictite and cap carbonate couplets occurred in the late Neoproterozoic and has been recognized on at least 15 paleo-continents. Diamictite and cap carbonate couplets play a pivotal role in establishing regional stratigraphic correlations and understanding the extreme climatic conditions and glacial-interglacial cycles of the Neoproterozoic glaciation. Here we report newly discovered Neoproterozoic glaciogenic diamictite and cap carbonate couplet in the Longshoushan area at the southwestern margin of the Alxa Block, NW China. Based on detailed stratigraphic and sedimentologic studies, we identified massive and stratified diamictites at the bottom of the Hanmushan Group, both with poorly sorted and rounded gravels. The presence of glacial striations and ice-rafted dropstones in stratified diamictites supports a glaciogenic origin. The upward transition from massive diamictites to stratified diamictites indicates the process of glacier retreat. The occurrence of thin-bedded phyllites in the stratified diamictites suggests a short-term deglaciation during the glaciation. The 2- to 2.6-m-thick cap carbonates cover the stratified diamictites and consist of thinly laminated microcrystalline dolomites. The basal cap carbonates contain closely linked sheet cracks, cemented breccias, tepee-like structures and cavities. The cap carbonates show high-resolution 13CPDB chemostratigraphy and negative δ13C values (ca. −2.9 to −4.1‰), typical of the Marinoan cap carbonates. Regional sedimentary characteristics and the C-O isotope values suggest that the diamictites and cap carbonate couplet in the Alxa Block likely correspond to the Marinoan glaciation and subsequent deglaciation (ca. 635 Ma), not the previously assumed Ediacaran glaciation. Thus, the diamictite and cap carbonate sequence marks the Cryogenian-Ediacaran boundary in the Alxa Block and provides evidence for further stratigraphic correlation and investigation. This work was financially supported by NSFC projects (grants 42072264, 41730213, 41902229, 41972237) and Hong Kong RGC GRF (17307918).
Arrival Picking for Distributed Acoustic Sensing seismic based on fractional lower order statistics
Authors: Wang Xiang , Wang Honghui , Wang Yuhang , Zeng Shangkun , Wang Yiru
Published: February 2023

In recent years, fiber-optic distributed acoustic sensing (DAS) has been gradually applied to seismology because of its long-distance and dense observation capability. It is a great challenge to effectively process the massive seismic data recorded by DAS. At present, the seismic data processing methods based on deep learning have achieved great success, especially in the tasks of seismic detection and arrival-time picking. However, due to the differences between DAS and geophone, such as sensing principles, spatial and temporal sampling rates, and noise intensity. The seismic arrival time picking model based on deep learning, which is trained by geophone seismic data with low spatial and temporal sampling rates and low noise intensity, severely degrades in performance on DAS seismic data with high spatial and temporal sampling rates and high noise intensity. In addition, a new seismic arrival time picking model is trained by fully supervised learning, which usually requires a large number of seismic data with accurate labels. However, the huge cost of manual picking and the lack of effective automatic picking models make it very difficult to build large-scale DAS seismic data sets with accurate labels. Therefore, it is very difficult to build an arrival time picking model based on fully supervised learning for DAS seismic data.In this study, we propose a DAS seismic arrival time picking method based on fractional lower order statistics. Based on the difference of probability density function between noise and seismic signal, the proposed method uses alpha-stable distribution modeling noise (generally follow a Gaussian distribution) and seismic signal (generally follow a non-Gaussian distribution), and uses fractional lower order statistics under the assumption of alpha-stable distribution as the characteristic function to pick the arrival time.Synthetic and actual DAS data tests show that the proposed method has better performance and robustness to random noise than other methods based on characteristic functions, such as STA/LTA, AR-AIC and kurtosis. Since the actual DAS seismic data has no ground truth of arrival time, we have further the performance of the proposed method on the geophone seismic data set. The proposed method provides better results on geophone seismic data and the data after up-sampling them to the typical time sampling rate of DAS.
Forest management scenarios using Korean dynamic stand growth model considering the new climate change regime
Authors: Hong Mina , Kim Moonil , Ko Youngjin , Lee Woo-Kyun
Published: February 2023

Climate change is a global issue affecting our lives, surrounding environments, and socioeconomic sectors. Accordingly, the recently published IPCC sixth assessment report emphasizes the role of forests as a source of greenhouse gas sink and shows the importance of climate resilient development pathways (CRDPs). South Korea is also putting forth policies such as the ‘2030 NDC’ and ‘2050 LED’ and is trying to find sustainable forest management measures to respond to the new climate change regime. Therefore, this study sought strategic measures to solve problems such as age class imbalance and mortality increase due to climate change in forests using the Korean dynamic stand growth model. Furthermore, CRDP was selected through recently announced SSP climate data and policy-based forest management scenarios to respond to the new climate change regime. As a result, the climate scenario is SSP1, the forest management scenario is when clear-cut harvest according to the legal final cutting age and thinning is implemented about 200,000 ha, reforestation of appropriate species to respond to climate change, and access to the forest road is within 1km, it was found that the overall growth of the forest increased. Although the current growth of 4.3m3 ha-1 decreases to 2.39m3 ha-1 in 2050, it is predicted to increase to 3.16m3 ha-1 in 2100 through the growth of species suitable for the climate and balance of age classes. In addition, it was analyzed to contribute to the increase in sequestration and carbon storage in logs due to harvest. In conclusion, this study is meaningful in that it presents a future strategy for responding to the new climate regime by reflecting the environmental and ecological characteristics of South Korea. 
Long-term changes in biogeochemical environments and their effects on dissolved oxygen concentrations in the East Sea
Authors: Kim ﻿Haejin , Kim Hanna , Kim Kyeong Ok , Hirose Naoki
Published: February 2023

The East Sea (ES, or East/Japan Sea) is a semi-enclosed marginal sea where deep convection occurs and is therefore appropriate to identify the signals of climate changes. The substantial decrease in dissolved oxygen (DO) concentration has been observed in the deep layers of the ES compared to the globally averaged condition. In addition, in-situ and satellite-based measurement datasets as well as model results showed the enhancement of biological production in the upper layers. As such, changes in biogeochemical environments have been recorded in the ES due to the climate change, which also has a clear impact on long-term changes in the DO concentration.This study investigates the alternations of biogeochemical environments, from the surface to the deep layer of the ES, using a coupled physical-biogeochemical model. This modelling study also allowed a quantitative estimation of the biological effect on the DO concentration.
New ca.1150 Ma paleomagnetic results of North China Craton (NCC) its paleogeographic and tectonic implications
Authors: Ding Jikai , Zhang Shihong , Evans David , Zhao Hanqing , Li Haiyan , Yang Tianshui , Wu Huaichun , Shi Meinan
Published: February 2023

A new paleomagnetic study is carried out on the ca. 1150 Ma mafic dykes from the North China Craton (NCC). After stepwise thermal demagnetization, most samples yielded two components. The low-temperature component directs north and down with intermediate inclination, which is interpreted as a viscous remanent magnetization of the present magnetic field. The high-temperature component (HC) directs east and down with steep inclination. Positive baked-contact tests and a reversal test suggest the HC is primary. Combined with the relevant paleomagnetic data previously published (Hou et al., 2009; Wang et al., 2020), a new pole is calculated from more than thirty high-quality virtual geomagnetic poles. The pole has averaged out the paleo-secular variation and is different from any younger paleomagnetic poles of the NCC. The pole places the NCC in a mid-latitude region. Combined with the reported 1230-780 Ma paleomagnetic poles from NCC and Laurentia, the new results suggest the two continents assembled during ca. 1150–1110 Ma at high-latitude region. They then together moved to low-latitude region and merged with Amazonia, Baltica, Kalahari to become a part of Rodinia.
Marine redox fluctuation during the Marinoan Snowball Earth: evidence from red beds of the Nantuo Formation in South China
Authors: Meng Zekun , Zhou Xiqiang , Wang Zhenfei , Ju Pengcheng , Huang Kangjun
Published: February 2023

The Marinoan Snowball Earth event marks a critical time in Earth’s history, with significant climate change characterized by low-latitude glaciation. The ocean is hypothesized to be anoxic during the Marinoan glaciation (ca. 649 to 635 Ma). However, this hypothesis is contradicted with global marine red beds (MRB) deposited in the Marinoan glaciation and diversification of complex eukaryotes after the termination of the Marinoan. To better comprehend the redox conditions of the late Cryogenian seawater, we present systematic sedimentological, mineralogical (SEM), and Fe geochemical analyses (Fe isotope and Fe speciation) of the MRB from the Nantuo Formation in South China.Two continuous ice advance-retreat cycles in the Nantuo Formation are separated by a MRB sequence, indicating an interglacial period with limited influence from glaciation. The results of Fe speciation show that the predominant phase of FeHR (highly reactive Fe) is Fe-oxide with extremely low content of Fe-pyrite and Fe-carbonate of the Nantuo Formation. Furthermore, well-preserved and nanometer-sized hematite (Fe-oxide) particles randomly dispersed in the matrix, suggesting that Fe(II) oxidation occurred in the water column rather than in the sediments. High FeHR/FeT ratios and near-zero δ56FeHR values of the MRB suggest scavenging of dissolved Fe(II) by quantitative oxidation at the basal of the Nantuo Formation. A positive δ56FeHR shift above the MRB further reflects the partial oxidation of Fe(II) to Fe(III) in the water column. These suggest sufficient oxygen derived from meltwater and/or atmosphere during the inter-glacial episode, facilitating the deposition of MRB. The oceanic redox conditions switch to anoxic in response to the re-appearance of the second glacial episode. Our findings suggest that the dynamic redox state of seawater was likely controlled by ice-sheet advancing-retreating cycles and provide new insight into redox conditions during the end-Cryogenian Marinoan glaciation.
Temperature sensitivity of soil organic carbon decomposition responses to warming and elevated CO2 in the tidal marsh ecosystem
Authors: Lee Jaehyun , Yang Yerang , Kang Hojeong , Noyce Genevieve , Megonigal Patrick
Published: February 2023

Tidal marsh is a large reservoir of soil organic carbon (SOC), considered one of the most efficient natural carbon sinks. However, the future carbon pool of this ecosystem has large variability and uncertainty due to climate change such as temperature rise and elevated atmospheric CO2 concentration. Microbial-mediated SOC decomposition is a key process that regulates the carbon cycle of tidal marsh. This process is largely temperature-dependent, thus understanding the response of temperature sensitivity (Q10) of SOC decomposition to climate change is critical to improving our prediction capability of the tidal marsh carbon cycle and the climate feedback. However, the response of Q10 of SOC decomposition on climate change in tidal marsh ecosystem is yet to be revealed, hampering our prediction capability of the future tidal marsh carbon cycle. Here, we elucidate the effect of warming and elevated CO2 concentration on the Q10 of SOC decomposition at a Salt Marsh Accretion Response to Temperature eXperiment (SMARTX). Surface sediments were collected in 2022 (6 years after manipulation started) from ambient, +5.1℃ (W), elevated CO2 (750ppm, eCO2), and +5.1℃+elevated CO2 (W+eCO2) plots and the Q10 of SOC decomposition was determined. W significantly decreased aerobic SOC decomposition rate most likely due to the labile carbon depletion and thermal adaptation, whereas eCO2 and W+eCO2 increased the aerobic decomposition rate at high temperatures (25 and 30℃). Anaerobic SOC decomposition rate was not affected by W whereas eCO2 and W+eCO2 significantly increased anaerobic decomposition rate at all temperatures. Q10 of aerobic SOC decomposition was not affected by W whereas eCO2 and W+eCO2 significantly increased. Q10 of anaerobic SOC decomposition was not affected by climate change. Overall, our finding demonstrates that elevated CO2 concentration increases the vulnerability of soil carbon stock to warming in tidal marshes, with implications for modeling the future carbon cycle of the ecosystem.
Modelliing evaporation from soil profiles
Authors: Kamai Tamir , Assouline Shmuel
Published: February 2023

Evaporation is a significant part of the water cycle and the main process for water vapor exchange between Earth's surface and atmosphere. Evaporation from bare soil consists of two main stages: stage 1, with a relatively high and often steady evaporation rate that is controlled mainly by atmospheric conditions, and stage 2, with lower and exponentially decreasing evaporation rates that are limited by the diffusive nature of the vapor flow and the hydraulic properties of the drying medium. In dry or drought conditions that are characterized with long dry spells, stage 1 is short and during stage 2 water is depleted from the top near-surface soil, forming a dry soil layer (DSL), where water flows in vapor phase only. Measuring bare soil evaporation over larger areas is challenging due to the natural heterogeneity. These measurements become even more challenging under dry conditions, due to the equipment needed for capturing low fluxes under extremely high liquid water potentials and equivalent vapor pressures. Therefore, predictive tools are essential for estimation of soil evaporation. To date, modeling of this transient evaporation process is limited, mainly because it either requires sophisticated numerical models that account for its complexities or relies on analytical solutions that are too simplistic to capture its dynamics.We present an analytical model that accounts for the main mechanisms of the evaporation process, but is relatively simple in its construction. The governing mechanisms during this dynamic process are captured by accounting for the hydraulic properties of the drying medium, the characteristic features of the medium that control water flow, the atmospheric forcing, and the partitioning between the liquid and vapor phases of the water within the drying profile. We validate this simplified approach using data from a numerical model and from evaporation experiments in different soil types, under various ambient conditions. In addition to depicting evaporation rates and the cumulative loss of water over time, we demonstrate the effect of soil hydraulic properties and their heterogeneity on the evaporation process. Additionally, we show how the model predicts the spatiotemporal partitioning between water (liquid and vapor) phases, with specific attention to the DSL that develops during longer periods of evaporation, with the corresponding downward migration of the evaporative front.
Machine learning based estimation of urban on-road CO2 concentration in Seoul
Authors: Park Chaerin , Jeong Sujong
Published: February 2023

As it is predicted that the amount of urban on-road CO2 emissions will continue to increase, it is essential to manage urban on-road CO2 concentration for effective urban CO2 mitigation. However, limited observation of on-road CO2 concentration prevents the full understanding of the variation of urban on-road CO2 concentration. Therefore, in this study, a machine learning based model that predicts on-road CO2 concentration (CO2traffic) was developed for Seoul, South Korea. This model predicts hourly CO2traffic with high precision (R2 = 0.8 and RMSE = 22.9 ppm) by utilizing CO2 observation, traffic volume, traffic speed, and wind speed data as main factors. Analyzing the CO2traffic data predicted by the model, the high spatiotemporal inhomogeneity of CO2traffic over Seoul with 14.3 ppm by time and 345.1 ppm by road was found. The large spatiotemporal variability of CO2traffic is related to different road types (major arterial road, minor arterial road, and urban highway) and land-use types (residential, commercial, bare ground, and urban vegetation) where the road belongs. The cause of the increase in CO2traffic was different by its road type, and the diurnal variation of CO2traffic was different by its land-use type. Our results demonstrate that high spatiotemporal on-road CO2 monitoring is needed to manage the urban on-road CO2 concentration showing high inhomogeneity. In addition, it suggests that a model using machine learning techniques can be an alternative for monitoring CO2 concentrations on all roads without conducting the observation.This work was supported by Korea Environment Industry &Technology Institute(KEITI) through "Climate Change R&D Project for New ClimateRegime.", funded by Korea Ministry of Environment(MOE) (2022003560006).
A Numerical Study on Estimation of the Trees’ Effects on the Distributions of Fine Particles (PM2.5) in an Urban area
Authors: Han Sang Cheol , González-Pérez Alejandra , Kang Jung-Eun , Kang Geon , Kim Jae-Jin
Published: February 2023

In this study, we investigated the effects of trees planted in an urban area on PM2.5 reduction using a computational fluid dynamics (CFD) model. For realistic numerical simulations, the Local Data Assimilation and Prediction System (LDAPS) operated by the Korea Meteorological Administration was used to provide the initial and boundary conditions to the CFD model. The CFD model was validated against the PM2.5 concentrations measured by the sensor networks in the area. We conducted the numerical simulations for three configurations of the trees: 1) no tree (NT) case, 2) a case considering only trees’ drag effect (TD), and 3) a case considering trees’ drag and dry deposition effects (DD). Comparison of the average concentrations showed that the trees in the area reduced the PM2.5 concentrations during the simulation period. The results showed that trees’ dry deposition can offset the concentration increase caused by trees’ drag effect and, resultantly reduce the PM2.5 concentrations in the tree-plated area.
Step-ahead forecasting of GRACE-derived terrestrial water storage spatial downscaling in Saudi Arabia using Elman recurrent learning and support vector regression
Authors: Abba Sani , Yassin Mohamed , Usman Abdullahi , Aljundi Isam
Published: February 2023

The growth and sustainability of human development rely on water availability. Proper management of Groundwater as the main source of one-third of freshwater resources is compulsory because of its renewable sources and to safeguard food sanctuary and water security. The steps ahead modeling of GRACE Terrestrial Water Storage (TWS) was employed in this study using the GRACE TWS data from 2007 to 2017 and TWS spherical harmonic solution obtained from the University of Texas (UT) center for space research.  The data was used to create the artificial intelligence-based models viz: Elman neural network (ENN) and Support vector regression (SVR) based on several input variables, including t-12, t-24, t-36, t-48, and TWS as the output variable. The models were evaluated using mean absolute error (MAE), root means square error (RMSE), mean absolute percentage error (MAPE), correlation coefficient (CC), and Nash–Sutcliffe efficiency (NSE). The estimation outcomes depicted that only SVR-M1 (NSE=0.993, MAE0.0346) generated promising results, with ENN-M3 (NSE=0.6586, MAE=0.6895) as the second-best model. All other models’ combinations were within the range of good to marginal accuracies, which are unreliable for decision-making. 
Intense atmospheric frontogenesis by air-sea interaction captured at Ieodo Ocean Research Station during Typhoon Lingling (2019)
Authors: Yang Sinil , Moon Il-Ju , Bae Hyo-Jun , Kim Baek-Min , Byun Do-Seong , Lee Hwa-Young
Published: February 2023

The Ieodo Ocean Research Station (Ieodo ORS) is a fixed marine observation platform at the boundary of the Yellow and East China Seas. In 2019, a Category 4 Typhoon Lingling passed by the Ieodo ORS very closely. At that time, the Ieodo ORS observed Sea Surface Temperature (SST) cooling of 4.5°C by vertical mixing and negative turbulent heat flux (i.e., the sum of sensible and latent heat fluxes) due to the SST cooling. In this study, uncoupled and coupled simulations were conducted to examine the role of air-sea interactions in changes in atmospheric frontogenesis around the typhoon passage. In the coupled simulation, SST cooling up to 6°C occurred over the dangerous semicircle due to vertical mixing induced by wind stress. Strong wind stress also enhanced the SST gradient and, therefore, contributed to the formation of a steeper atmospheric frontal zone. Moreover, the comparison with reliable datasets supports the physical linkage between SST cooling and atmospheric frontogenesis by utilizing the meridional theta-e gradient and moisture convergence zone. Therefore, we hope to improve our understanding of atmospheric frontogenesis by air-sea coupling processes in developing a coupled atmosphere-ocean modeling system from the simulation results.
Improving Streamflow Predictions over Indian Catchments using Long Short Term Memory Networks
Authors: Magotra Bhanu , Saharia Manabendra , Dhanya Chandrika Thulaseedharan
Published: February 2023

Streamflow modelling plays a critical role in water resource management activities. The “physically based" models require high computation resources and large amounts of input meteorological data which results in high operating costs and longer running times. On the other hand, with advancements in deep-learning techniques, data-driven models such as long short-term memory (LSTM) networks have been shown to successfully model non-linear rainfall-runoff relationships through historically observed data at a fraction of computation cost. Moreover, using physics-informed machine learning techniques, the physical consistency of data-driven models can be further improved. In this study, one such method is applied where we trained a physics-informed LSTM network model over 278 Indian catchments to simulate streamflow at a daily timestep using historically observed precipitation and streamflow data. The ancillary data included meteorological forcings, static catchment attributes, and Noah-MP simulated land surface states and fluxes such as soil moisture, latent heat, and total evapotranspiration. The LSTM model's performance was evaluated using error metrics such as Nash-Sutcliffe Efficiency (NSE), Kling-Gupta Efficiency (KGE) and its components, along with skill scores based on 2x2 contingency matrix for hydrological extremes. The trained LSTM model shows improved performance in simulating streamflow over the catchments compared to the physically based model. This will be the first study over India to generate reliable streamflow simulations using a hybrid state-of-the-art approach, which will be beneficial to policy makers for effective water resource management in India. 
The journey towards FAIR: A story from the marine domain
Authors: Thijsse Peter , Carval Thierry , Kokkinaki Alexandra , Buck Justin , Moncoiffe Gwenaelle , Quimbert Erwann , Alviset Guillaume , Schaap Dick
Published: February 2023

The marine subdomain consists of a diverse data landscape, with several Research Infrastructures (RIs) involved. In the ENVRI-FAIR project the marine domain is represented by Euro-ARGO, ICOS (Marine), EMSO, and LifeWatch (Marine) as RIs as listed on the ESFRI roadmap, and SeaDataNet as European marine data management infrastructure. The overarching goal of ENVRI-FAIR is that all participating research infrastructures (RIs) will improve their level of FAIRness and become ready for connecting their data repositories and services to the European Open Science Cloud (EOSC).To achieve this goal, the marine domain partners have first analysed and assessed the FAIRNess level of each participating RI and identified the necessary actions to improve their individual FAIRness. They then created a roadmap and implementation plan that led to the development of an Essential Ocean Variable (EOV) demonstrator, highlighting the FAIRness achievements.   In this presentation we will discuss in more detail the RI FAIR assessment and analysis process and show how it evolved alongside the evolution of the FAIR assessment tools themselves and the harmonisation required to be meaningful and useful. We will then walk you through the analysis of this assessment that led to a list of strengths and weaknesses per RI, and the solutions to overcome the weaknesses for each individual of the FAIR principle. Finally, we will present the outcomes of the required upgrades, adoptions of standards, improvements, developments and services that were developed as part of the implementation plan and led to the construction of the EOV demonstrator product.
Effects of Wetting and Drying Cycles on Strength of Latrobe Valley Brown Coal
Authors: Baghbani Abolfazl , Baumgartl Thomas , Filipovic Vilim
Published: February 2023

Water penetration, changes in the groundwater level and moisture content changes can affect the physical and chemical properties of coal in an open pit mine. Water levels in open coal pit mines can vary throughout the year, resulting in a number of wet and dry cycles for brown coal. Wet and dry cycles occurring throughout the year can affect the mechanical strength of the stone's microstructure and macroscopic structure. Loss of strength can have severe negative impacts if such rock is integral component in landform design. Until now, no research has been conducted on the effects of wet and dry loading cycles on brown coal. This study investigates the effect of wet and dry cycles on brown coal's strength by conducting a series of unconfined compressive strength (UCS) laboratory tests. For this purpose, nine laboratory samples with dimensions of 38 x 76 cm were prepared. Samples were placed inside distilled water chambers in a temperature-controlled environment. Afterwards, the samples were subjected to unconfined compressive strength (UCS) tests following 0, and 3 cycles of wet and dry conditions. The results of the UCS test show that as the number of wetting and drying cycles increased, the UCS of the samples decreased from 2150 to 330 kPa after three cycles of wetting and drying. In addition, the results indicate that the elastic modulus of brown coal has decreased from 10500 to 1200 kPa. Also, the Poisson ratio decreased from 0.34 to 0.27. This study confirms the importance of paying attention to the wet and dry cycles in brown coal mines.
Thermal-nonthermal energy partition in weak flares observed by STIX, XSM, and SDO
Authors: Awasthi Arun Kumar , Mrozek Tomasz , Litwicka Michalina , Steslicki Marek , Kolomanski Sylwester , Kulaga Karol
Published: February 2023

The disparate nature of thermal-nonthermal energy partition during weak flares compared to that during the large flares is still an open issue and quantifying the relative productivity of multi-wavelength emission during weak flares can enable inferring the underlying energy release mechanism. Therefore, we analyze multi-wavelength emission from ∼150 flares during September 20-25, 2021, commonly observed from Spectrometer Telescope for Imaging X-rays (STIX) (at ∼0.6 AU), STEREO-A, GOES, and SDO observatories (significant overlap of observing field-of-view). The ratio (Qf ) of HXR (>12 keV) fluence (Fhxr ) and SXR (4-10 keV) flux (Fsxr), at the maximum of Fsxr (tp), is derived to quantify the relative productivity of HXR and SXR emission during flares. The variation of Qf with Fsxr enabled us to quantitatively identify the cases of strongly non-thermal (cold) and highly thermal (hot) flares. The identification of the source active region using the EUV images (from AIA) revealed the uniform behavior of different active regions in producing cold and hot flares. Besides, thermal-nonthermal plasma parameters as estimated by spectral-fit of STIX and XSM observations indicate a possible role of pre-flare density in flare loops to be resulting in disparate thermal-nonthermal emission partition. Therefore, we conduct case studies of flares of the aforementioned types by – synthesizing the X-ray images from STIX observations – analyzing the E/UV images, and magnetograms, and — performing the hydrodynamical simulations using the 1D Palermo-Harvard code. With such a multi-wavelength analysis of an ensemble of weak flares, we probe the energy release mechanism and evaluate the same in the framework of the standard model of energy release during large flares.
Lithospheric imaging beneath North India using surface wave tomography
Authors: Kumar Deepak , Gaddale Suresh , Maurya Satish , Gupta Subhash Chandra
Published: February 2023

We provide a shear wave velocity model of the Indo-Gangetic plain (IGP) that extends down to a depth of 100 km.  Using vertical component seismograms of 108 broadband (BB) stations (50 and 58) of IRIS-DMC and National Centre for Seismological (NCS) respectively, located in and around the Northern Indian plate. The group velocity dispersion of the Rayleigh wave has been picked along  ~3000 paths across the study region over a period range of 8 to 80s. To construct the 3D shear wave velocity structure, we employ a two-step surface wave tomography procedure. In the first step, regionalized dispersion maps are prepared for each period of correlation length of 60km, and subsequently, we employ the Markov chain Monte Carlo (McMC) trans-dimensional Bayesian inversion algorithm to obtain the shear wave velocity structure. In regionalized dispersion maps, at short periods (~8s) we see slow velocity in northern IGP and region reported thick basement (~6km) from previous studies. For moving towards increasing periods map indicate slow velocity anomalies in the Himalayan and Tibetan plateau region are associated with a thick crust (>50) in contrast to the typical crust (~40km) of IGP. The fast and slow velocities areas are identified which are associated with the Indian shield and thick crust in the Himalayas. Further, we inverted regionalized geographical locations to get shear wave velocity at each point to make a 3D lithospheric model. We have used 20 chains with 600k burn-in phase and 300k in the main phase for sampling the posterior distribution and from the final posterior distribution best 500k models with of 5% deviation has been selected after removing those model that has outlier chains with unrealistic models.Keywords:  Surface waves, Bayesian inversion, Seismic tomography, Northwestern Himalayas.