bluuebunny/crossref_metadata_2025 huggingface dataset:
A Revisionist View of the Mid-Pleistocene Transition
Authors: Clark Peter U. , Shakun Jeremy , Rosenthal Yair , Pollard David , Köhler Peter , Hostetler Steven , Bartlein Patrick , Liu Zhengyu , Zhu Chenyu , Schrag Daniel , Pisias Nicklas
Published: March 2024

The Mid-Pleistocene Transition (MPT) is commonly characterized as a change in both temperature and ice volume from smaller amplitude, 41-kyr variability to higher amplitude, ~100-kyr variability in the absence of any significant change in orbital forcing. Here we reassess these characteristics based on our new reconstructions of changes in global mean surface temperature (DGMST) and global mean sea level over the last 2.5 Myr. Our reconstruction of DGMST includes an initial phase of long-term cooling through the early Pleistocene followed by a second phase of accelerated cooling during the MPT (1.5-0.9 Ma) that was accompanied by a transition from dominant 41-kyr low-amplitude periodicity to dominant ~100-kyr high-amplitude periodicity. Changes in rates of long-term cooling and variability are consistent with changes in the carbon cycle driven initially by geologic processes followed by additional changes during the MPT in the Southern Ocean carbon cycle. The spectrum of our sea-level reconstruction is dominated by 41-kyr variance until ~1.2 Ma with subsequent emergence of a ~100-kyr signal that, unlike global temperature, has nearly the same concentration of variance as the 41-kyr signal during this time. Moreover, our sea-level reconstruction is significantly different than all other reconstructions in showing fluctuations of large ice sheets throughout the Pleistocene as compared to a change from fluctuations in smaller to larger ice sheets during the MPT. We attribute their longer period variations after the MPT to modulation of obliquity forcing by the newly established low-frequency CO2 variability. Specifically, prior to reaching their maximum size at the end of each ~100-kyr interval, ice-sheet response to periods of lower CO2 was modulated by higher obliquity, and vice versa, with the times of maximum ice-sheet growth only occurring when low CO2 combined with the next obliquity low. Ice sheets then began to melt in response to the next increase in obliquity, with the subsequent sequence of events and feedbacks leading to a termination. High-resolution ice-core CO2 records that extend beyond 0.8 Ma are needed to test this hypothesis. Otherwise, large ice sheets shared a common size threshold throughout the Pleistocene equivalent to sea level below -80 m that, when exceeded, resulted in a termination that was paced by the next increase in obliquity.
Strongly Coupled Land-Atmosphere Data Assimilation and Its Impact on Near-surface Weather Forecasting
Authors: Pu Zhaoxia , Huang Kian
Published: March 2024

Near-surface weather forecasts are critical for protecting life and human activities. However, they remain a challenging problem in modern numerical weather prediction (NWP) due to difficulties in representing complicated land–atmosphere interactions in numerical models. This talk will outline recent advancements made by the first author's research team in understanding and developing coupled land-atmosphere data assimilation methods that improve near-surface weather forecasts. The association between near-surface variables and soil moisture was evaluated with observations, coupled land–atmosphere model, and data assimilation. Results indicated a strong coupling between soil moisture and the low-level atmosphere, especially the atmospheric boundary layer. Then, the weakly and strongly coupled land–atmosphere data assimilation methods were compared regarding their impact on the prediction of near-surface atmospheric conditions. Results showed that strongly coupled land–atmosphere data assimilation, with simultaneous corrections to the land and atmospheric conditions, outperformed weakly coupled data assimilation.  More importantly, the recent efforts in developing strongly coupled land–atmosphere data assimilation with NOAA Unified Forecast System (UFS) model and Joint Efforts for Data Assimilation Integration (JEDI) system, as well as the progress with NASA Unified Weather Research and Forecasting (NU-WRF) model and GSI data assimilation system will be reported. The impacts of coupled land-atmosphere data assimilation systems on short- and medium-range weather forecasting will also be discussed.
Irreversibility of Extreme Precipitation in East Asia under Multi-Scenario to Carbon Neutrality
Authors: Lee Min-Uk , Park Jong-Yeon , Kim Han-Kyong , Byun Young-Hwa , Sung Hyun-Min , Park Ji-Sook , Jeon Woo-Jin
Published: March 2024

Extreme precipitation refers to a bipolar climate phenomenon in which a high amount of precipitation occurs in a short period or a drought persists for a long period. In a future climate with increased CO2 concentrations, the characteristics of extreme precipitation can undergo significant variations. This study focuses on East Asia (110°-150°E, 20°-50°N) and employs six indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) to assess the reversibility of extreme precipitation events. The Carbon Dioxide Removal (CDR) experiment, simulated by the National Institute of Meteorological Sciences and the Korea Meteorological Administration (NIMS-KMA) climate model, involves increasing the CO2 concentration by 1% per year from the Pre-Industrial (PI) level and decreasing it from four different carbon-neutral points: A (44 years), B (51 years), C (70 years), and D (140 years) from the initial year. The NIMS-KMA simulation proves most effective among eight models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Results indicate that extreme precipitation indices respond nonlinearly to CO2 concentration, with intensity and frequency indices showing hysteresis. Reversibility is limited, and delayed carbon neutrality leads to increased irreversibility. Notably, the R99 frequency index exhibits the highest irreversibility, ranging from 10.61% to 29.50% from point A to point D. This suggests that postponing carbon neutrality may strengthen the central Pacific warming pattern, intensify subtropical high pressure in the northwest Pacific, and increase water vapor flow into East Asia. 
Did monsoon govern the Asian rainy season in the early Eocene? An ensemble paleoclimate simulation perspective.
Authors: Santra Abhik , Capitanio Fabio A. , Dommenget Dietmar , Goswami Bhupendranath , Farnsworth Alex , Hutchinson David K. , Arblaster Julie M. , Lunt Daniel J. , Steinig Sebastian
Published: March 2024

The Asian summer monsoon (ASM) is a seasonal response of the coupled land-ocean-atmospheric system, which influences more than 60% of the world’s population. Although progress has been made in understanding the ASM variability and its prediction, the timing and governing factors for the ASM initiation are still debatable as recent proxy evidence and modeling studies suggested the initiation of a wet-dry monsoonal climate from the Cretaceous period (145 million years ago, Ma) to the early Miocene or late Oligocene epoch, ∼25-22 Ma. Capitalizing on an ensemble of paleoclimate simulations for the early Eocene (56-48 Ma), we show that the Asian wet season was considerably weaker and shorter than present in the absence of an elevated heat source like the Tibetan Plateau in the early Eocene. The deficient upper tropospheric meridional temperature gradient couldn’t drive the seasonal northward migration of the precipitation band over South Asia. Additionally, the weaker cross-equatorial moisture flow was mechanically blocked by the Gangdese mountain along the southern edge of Asia, leading to significantly dry conditions in South Asia. The enhanced atmospheric greenhouse gases were inadequate to strengthen the seasonal circulation and precipitation variability to the present level. We argue that an altered wet and dry seasonality over South Asia was not necessarily qualified as the Eocene ‘monsoon’.
Drought Forecasting with ML-based Regionalized Climate Indices
Authors: Lee Taesam , Kong Yejin , Hwang Sunghyun , Lee Sejeong
Published: March 2024

Drought forecasting in South Korea has become imperative due to the increased frequency of occurrence leading various damages such as property loss and casualties. Precipitation in South Korea is distributed with high deviation, substantially concentrated in summer. Other seasons have a comparatively low amount of precipitation resulting unbalanced water resources of each season. To overcome the skewed seasonal precipitation, numerous dams and reservoirs have been constructed and operated. The management of those water-related structures should be carried out carefully to meet seasonal requests of water resources, and the precipitation prediction for each season has become critical. However, the seasonal precipitation forecasting has been a challenging task due to complex weather systems and climate patterns. The current study proposes a novel procedure for forecasting seasonal precipitation as: (1) regionalization of climate variables; (2) extraction of features with PCA, ICA and Autoencoder; and (3) finally regression model applications. Two globally gridded climate variables, Mean Sea Level Pressure (MSLP) and Sea Surface Temperature (SST) were teleconnected with the Accumulated Seasonal Precipitation (ASP) of South Korea. The results indicate that the k-means clustering successfully regionalizes the highly correlated climate variables with the ASP and all three feature selection algorithms, PCA, ICA, and Autoencoder present their superiority in different seasons combining GLM and SVM models. Especially, the PCA performs better with the linear GLM model and the Autoencoder shows better performance with the nonlinear SVM model. Overall, it can be concluded that the proposed seasonal precipitation forecasting procedure combining ML-based algorithms can be a good alternative.
Evaluating the potential source of contamination from sulfide minerals in major rocks in South Korea
Authors: Yim Gil-Jae , Youm Seung-Jun , Han Hyeop-Jo , Lee Seon-Yong , Lee Jin-Young
Published: March 2024

The utilization of surrounding rocks is required in human living areas, and these development activities create large cut slopes and generate large amounts of cut rocks as construction materials. If these development areas are strata containing sulfide minerals (pyrite, etc.), contamination may occur, causing environmental pollution problems in the development site and surrounding areas. Several methods have been studied for the preliminary identification of potentially contaminated rocks, including Acid Base Accounting (ABA), Modified ABA procedures, Carbonate Neutralization Potential determinations, Humidity cell tests, Column tests, Batch reactor (Shake flask) tests, and Field tests (Orava, 1997; USEPA and Hardrock Mining, 2003). Studies on rock samples have resulted in most of the samples being classified as Non-Acid Forming (NAF), with some samples containing sulfide minerals (such as pyrite) being classified as Potentially Acid Forming (PAF). It can be expected that future development of these rocky areas may affect the surrounding environment or rock utilization. Therefore, these rock areas are considered to be in need of management. It would be desirable to investigate the occurrence of pollution sources caused by mineral sulfides in advance and take appropriate countermeasures. It is expected to reduce the economic losses that may occur in the future, and it is judged that the pollution problem of the surrounding environment can be further reduced.
Open path cavity-enhanced absorption spectroscopy for detecting ambient nitrate radicals
Authors: Wang Haichao , Wang Yiming , Wang Jie
Published: March 2024

Nitrate radical is an important nocturnal oxidant in the atmosphere, regulates the fate of volatile organic compounds and nitrogen oxide, and affects the air quality. While the concentration of NO3 in the ambient is low to several to tens of parts per trillion by volume in general on the surface. During the past decades, people attempted to detect ambient NO3 by developing several techniques including Differential optical absorption spectroscopy (DOAS), Laser-induced fluorescence (LIF), Cavity Ring-Down Spectroscopy (CRDS), and Cavity-enhanced absorption Spectroscopy (CEAS). The latter two are widely used in NO3 measurement but suffer from the sampling loss change due to its high reactivity. Here we try to develop an open CEAS system to measure NO3 in the ambient air. This method is free of sampling loss but has its technical challenges, that as the interferences of water absorptions during the NO3 absorption window near 662 nm. Different from previous studies, we applied a small cavity cage (~40 cm high reflectivity mirror distance) during the hardware design, which features good stability. In addition, we used a sensor to measure ambient temperature and relative humidity, which helped us to calculate the real-time water vapor cross-section to retrieve the water vapor concentration with high accuracy. At last, we will report the instrumental performance in the laboratory tests and field applications.
Thirty-year dryland crop rotation improves soil multifunctionality and shifts soil fungal community
Authors: Wang Ying
Published: March 2024

Crop rotation plays an important role in changing soil microbial communities, which is critical to maintaining soil multifunctionality. However, limited data exist on the long term impact of crop rotations on soil multifunctionality and its link with soil fungal community in drylands. In a dryland field experiment with 30-year legume- and non-legume-based winter wheat rotations and winter wheat-fallow system, we investigated the soil multifunctionality (via cycling and pools of soil carbon and nitrogen) and the overall community and functional groups of soil fungi. The links between soil multifunctionality and fungal communities were also explored. We found that long-term crop rotation increased soil multifunctionality index and that of carbon cycle. Crop rotation shifted soil fungal community composition, and reduced the proportion of putative pathotrophs. The overall fungal community was almost equally explained by soil and plant variables, while fungal functional groups (i.e., saprotrophs and pathotrophs) were more affected by soil variables. The indicator taxa in the non-legume-winter wheat rotation were distinctly different from those in the legume-based winter wheat rotation soils, indicating that the non-legume-winter wheat rotation selects different fungal taxa from the legume-based winter wheat rotation. Moreover, the changes in community composition of soil fungi, putative saprotrophs and pathotrophs were related to soil multifunctionality and that of carbon and nitrogen cycles. Our results highlight that long-term crop rotations shape the soil fungal communities; the changes in soil fungi and fungal functional groups have potential to improve soil multifunctionality in the crop rotation systems in drylands.
Experimental Investigation of Thermal Dispersion Within Porous Media Under Natural Groundwater Flow Conditions
Authors: Park Byeong-Hak , Baek Ji-Young , Rau Gabriel C. , Lee Kang-Kun
Published: March 2024

Recent studies in the field of shallow geothermal applications emphasize the crucial role played by mechanical thermal dispersion as a fundamental heat transport mechanism within saturated porous media. However, Previous studies have overlooked or underestimated mechanical thermal dispersion, leading to a scarcity of information on thermal dispersivity in the literature. This study experimentally and numerically investigates the validity of general assumptions concerning mechanical thermal dispersion within a porous medium. For this purpose, comprehensive laboratory experiments were conducted using heat and solute tracers across various porous materials at different background flow velocities (Re < 0.52). The analysis results suggest that water injection induces substantial mechanical dispersion, even at low flow velocities. Additionally, the thermal dispersivity ratio may deviate from the assumed value, underscoring its importance in the environmental impact assessment of the thermal use of shallow aquifers. Our experimental findings also suggest that thermal dispersion is affected by both local thermal non-equilibrium and small-scale heterogeneity.Keywords: Thermal dispersion; Water injection; Thermal dispersivity ratio; Local thermal non-equilibrium; Small-scale heterogeneity AcknowledgementsThis work was supported by the Nuclear Research  and  Development  Program  of  the  National  Research  Foundation  of  Korea  (NRF-2021M2E1A1085200). This work was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2022R1A2C1006696).
Different AMOC Stabilization between Past Interglacials and Future
Authors: Liu Wei , Shi Feng , Zhang Xiao , Yin Qiuzhen
Published: March 2024

The excess freshwater in the Arctic due to global warming is causing a weakening the Atlantic Meridional Overturning Circulation (AMOC). The question of how the climate change will impact the stability of the AMOC, however, remains unclear. We address this uncertainty through a series of ensemble simulations (100 members) using freshwater hysteresis experiments, aiming to elucidate potential changes in AMOC stability across different interglacials. Our findings suggest that future increases in anthropogenic CO2 emissions will bolster the AMOC's resistance to excess freshwater, though it exhibits less resilience compared to past interglacials. In future climate scenarios, warmer conditions lead to a notable delay in sea ice expansion, which aids in the preservation of deep water formation and AMOC strength. Concurrently, an intensification of freshwater convergence in the North Atlantic acts as a dampening factor during AMOC recovery under warmer climate background. The influence of orbital parameters on AMOC stability across different interglacials is found to be relatively minor. These results underscore the importance of considering background climate conditions, particularly CO2 concentrations, when investigating future AMOC changes and making comparisons to past AMOC dynamics.
Individual versus combined effects of drought, warming and eCO2 on grassland water uptake and fine roots
Authors: Tissink Maud , Radolinski Jesse , Reinthaler David , Venier Sarah , Pötsch Erich M. , Schaumberger Andreas , Bahn Michael
Published: March 2024

In a changing climate, grasslands are expected to experience major shifts in water supply and demand. To date, little is known about how projected future conditions of severe drought, climate warming, and rising CO2 affect grassland water uptake, and whether adaptations of fine roots affect the capacity to extract water from soil. Using a multifactor global-change experiment in a managed montane C3 grassland, we studied the individual and combined effects of drought, warming (+3 ℃), and elevated CO2 (eCO2; +300 ppm) on root water uptake (RWU) over three growing seasons. RWU was assessed across different layers of the main rooting horizon using diel soil moisture dynamics during non-rain periods. We also investigated treatment effects on fine roots (production, traits), fine-root-to-shoot ratios, and consequences for RWU capacity. By increasing vapour pressure deficit (VPD) and its effect on RWU rates normalized to soil water content (RWUSWC), warming reduced RWU during hot periods. Under sustained warming, grassland decreased specific root length, and increased root diameters and fine-root-to-shoot ratios. Conversely, eCO2 slowed RWUSWC at high VPD, though fine-root adaptations were negligible. Compared to warming alone, future conditions (warming, eCO2) increased RWUSWC to a lesser extent and induced no fine-root adaptations, but reduced RWU to a similar degree. Drought reduced RWU (-66–75%) and increased water sourcing from deeper soil layers; however, a hot season amplified any RWU reductions under future conditions by 20%. Altogether, our study demonstrates that (i) RWU in C3 grasslands declines in a warmer, drier future, though (ii) eCO2 will mitigate the need for fine-root adaptations, maintaining RWU capacity. However, (iii) rising temperatures will exacerbate RWU reductions under drought. Therefore, hot droughts should have significant repercussions for water dynamics in C3 grasslands.
Designing a GIS-based Decision Support System to protect environmental and human health by integrating spatial data, environmental information, and health data for informed decision-making.
Authors: Yoon Hoonjoo , Son Sujin , Choi Inho , Jo Jungmin , Kwon Jiyoon
Published: March 2024

Pathogens are a factor that determines emergency responses for both the public and the safety of first responders due to their life-threatening properties. At the same time, pathogen contamination is difficult to detect, and specialized skills, tools, and procedures are needed to deal with it. Waterborne pathogen contamination accidents can occur anywhere and for a variety of reasons. Earthquakes can cause disruptions to the urban drinking water and wastewater networks, and can also be contaminated by accidents, malicious attacks, and illegal activities.This study developed a decision support system for pathogen contamination management in disaster situations by utilizing GIS technology. The system will not only enhance the operational capability of early responders (FRs) and strengthen overall management, but also reduce errors when setting up new technologies.The system integrates various technical means, such as collecting and analyzing satellite and drone-based water quality data and evaluating the severity of water pollution using social media data. This enables rapid and accurate detection and re-response of environmental risks. The system is interconnected with various sources through REST and open APIs, and effectively manages data by utilizing MongoDB and geo-server.The study is expected to make a significant contribution to protecting the environment and human safety by providing an accurate risk assessment and providing the necessary technical means to respond to pathogen pollution in disaster situations. Industrial accidents can be reduced by increasing the capacity to respond to risks that have not been specifically identified and strengthening the ability to respond to disasters. The study will also provide essential data for policy-making and regulatory development aimed at protecting the environment. This research was supported by Korea Institute for Advancement of Technology(KIAT) grant funded by the Korea Government(MOTIE)  (P163300014, 2021 Industrial Technology International Cooperation Project - Horizon2020 Program)  
Nature-based solutions for improving food security: A systematic globalreview
Authors: Ho Loc , Nguyen Minh , Babel Mukand Singh , Park Edward
Published: March 2024

Nature-based solutions (NBSs) have been promoted as a holistic way to solve a variety of societal issues while benefiting biodiversity at the same time. To date, applications of NBS approaches that help ensure food security have yet been systematically reviewed. In this paper, we critically review the specific NBSs for food security, highlighting their limitations, to provide recommendations that promote their applications for improving global food security. Our systematic review of nearly 700 peer-reviewed articles indicated that many NBS approaches can be applied to enhance food security dimensions individually or together. However, there is a strong bias towards food availability and not enough research has been done to link NBSs withimprovements in food access and utilization. Over 80% of the reviewed papers were of short-term studies or without specific timeframes, and 25% offered no information on economic effectiveness of NBSs. Environmental benefits of NBSs were explicitly described in about 60% of these papers, and biodiversity enhancement was measured in only about 10%. We, therefore, recommend future applications of NBSs to safeguard food security be shifted to food access and utilization with careful consultation with local communities to address their specific context, using indicators that are easily measured and managed. Systematic monitoring regime and robust and diversified financial support system are also equally important in efforts to successfully implement NBSs. Moreover, environmental and societal benefits, especially water productivity and biodiversity, must be incorporated into the planning and design of NBSs.
Formation and reaction mechanisms of Criegee intermediates in the atmosphere
Authors: Tong Shengrui , Chen Meifang , Yu Shanshan , Ge Maofa
Published: March 2024

Criegee intermediates (CIs) can be generated by the ozonolysis of alkenes, and few amounts can come from radical-radical reactions. CIs are found to be the important oxidants, and can react with many gases in the atmosphere. The reaction rate of CIs with HCOOH is about 10-10 cm3molcule-1s-1, and the reaction rate of SO2 with CIs is much faster than with OH radical. A Matrix-isolate Vacuum FTIR method was constructed to capture CIs during the reaction of O3 with alkenes. Different kinds of Primary ozonides (POZs), CIs, and Secondary ozonides (SOZs) were detected, and the reaction processes were deduced. Combining of the experimental and quantum chemistry methods, the reactivity of different structure CIs were investigated. The contribution of these CIs to the formation of OH radicals and SOA were further discussed. Fundamental understanding on the structures and reactivity of CIs is crucial to deepen the understanding of Criegee chemistry and its impact on the atmospheric chemistry.
Deep-Learning Based Seasonal Chlorophyll Forecasting in the Tropical Atlantic 
Authors: Martinez Balbontin Gabriela , Jouanno Julien , Benshila Rachid
Published: March 2024

Accurate biogeochemical forecasting of the oceans is crucial for ecosystem and fisheries management. In this study, we propose a methodology for chlorophyll forecasting at a seasonal scale by leveraging physical ocean forecasts and autoencoders, a type of convolutional neural network. Chlorophyll-a is a key indicator of phytoplankton biomass, and it offers the advantage of being relatively easy to measure at a large scale using satellite-based color sensors. Specifically, this approach focuses on estimating surface chlorophyll concentrations in the Tropical Atlantic from forecasted physical properties of the ocean: sea surface temperature and salinity, sea surface height, and mixed layer depth. The proposed method is trained on the GlobColour dataset, a cloud-free, merged chlorophyll concentration output from various sensors, from 1998 to 2009. Seven-month forecasts are performed for the period 2010–2020, with monthly initialization. We show that we can skillfully integrate data from the ECMWF’s long-range forecasting system, SEAS5, to predict multiannual and seasonal chlorophyll levels. Evaluation against 2010–2020 GlobColour data demonstrates the autoencoder’s skill in capturing spatial and temporal patterns. Seasonal performance was assessed for regions of interest, including the Equatorial and Senegal-Mauritania upwelling regions, the Inter-Tropical Convergence Zone (ITCZ), and the Northern Atlantic. The neural network consistently outperforms the biogeochemical reanalysis of reference in measured skill and has the additional advantage of being less resource-intensive than traditional models. These results further confirm the potential of deep-learning techniques in operational oceanographic applications. Future work will focus on expanding this approach to generating global-scale, multi-nutrient forecasts in the context of the European Digital Ocean Twin (EDITO) project, which aims to provide an environment to exploit this type of machine-learning based simulation algorithms. 
Influence of contrasting sea surface temperature warming patterns on atmospheric circulation and cloud feedbacks
Authors: Mackie Anna , Byrne Michael P. , Williams Andrew I.L.
Published: March 2024

Climate sensitivity, defined as the global-mean surface temperature change due to a doubling of atmospheric CO2, is a key metric for quantifying the Earth system response to increasing greenhouse gases. Estimates of climate sensitivity vary widely, making it difficult for societies to prepare for the impacts of climate change. Uncertainty in climate sensitivity is driven primarily by uncertainty in how clouds will respond to warming. But how clouds respond to climate change depends strongly on the geographic pattern of warming: the so-called ‘pattern effect’. This recently-discovered phenomenon is crucial to narrowing uncertainty in climate projections, yet fundamental understanding of the processes underpinning the pattern effect is underdeveloped. In particular, the potential role of changes in atmospheric circulation as a crucial link between warming patterns and cloud feedbacks remains unclear. 

Here we use a series of idealised GCM simulations and a moist static energy (MSE) framework to investigate the coupling between tropical sea surface temperature (SST) warming, circulation changes and cloud feedbacks. In the simulations the SST of different ‘patches’ of the tropical ocean are perturbed, resulting in strongly non-linear cloud responses. We demonstrate that the circulation response is also non-linear and closely coupled to the cloud response. Specifically, SST warming in the west Pacific leads to a reduction in ascent fraction – the proportion of the atmosphere that is ascending at 500 hPa – over the tropical ocean, associated with an increased top-of-atmosphere shortwave cloud radiative effect.  In contrast, SST warming in the east Pacific has little effect on ascent fraction. We develop a framework for estimating ascent fraction as a function of near-surface MSE, inclusive of an entraining-plume model to account for dry-air mixing into moist ascending air. We demonstrate how this framework can provide insight into both the circulation changes associated with patterned SST warming and the resulting cloud feedbacks. 
Fast analysis of urban meteorological observations with the user-friendly MetObs-toolkit
Authors: Vergauwen Thomas , Top Sara , Jacobs Amber , Covaci Andrei , Dewettinck Wout , Vandelanotte Kobe , Hellebosch Ian , Caluwaerts Steven
Published: March 2024

Working with and analysing data from non-traditional measurement networks, such as urban climate networks, can be challenging and time consuming. After undertaking an observational campaign, researchers often face the issue of missing data due to technical problems such as power cuts or data communication issues. Additionally, data from low-cost networks or crowdsourced data need quality control to avoid the inclusion of measurement errors and biases, which often leads to additional gaps in the time series. Moreover, data storage formats and temporal measurement frequencies are often not consistent or synchronised when comparing data of different measurement networks. MetObs, an open-source Python toolkit, was developed to overcome these issues and fully exploits such valuable datasets. MetObs aims to provide a framework for the entire flow from raw sensor data to a dedicated analysis, with the possibility to apply it to various types of non-traditional networks without any formatting issues. To obtain a clean dataset, the time resolution is firstly resampled to the desired resolution, followed by identifying erroneous and missing records. Finally, missing records are filled in with the most suitable or preferred gap-filling method. Dedicated software for quality control, such as TITAN and CrowdQC+, already existed prior to the development of MetObs and are therefore implemented in the toolkit instead of being reinvented. The toolkit makes it moreover possible to generate analytics with the possibility to incorporate geographical data and create various graphics for the analysis of the meteorological measurements. MetObs was developed in such a way that people without a coding background can utilise it to get insight into their own meteorological measurements by following examples and using tutorials. At the same time, it allows more experienced data scientists to tweak the functionalities in such a way that the toolkit provides a pipeline for their dedicated use case.
The energy and water exchange and its effect on the weather and climate over the Tibetan Plateau and surrounding regions
Authors: Ma Yaoming
Published: March 2024

Containing elevated topography, the Tibetan Plateau (TP) has significant thermodynamic effects for regional weather and climate change, where understanding energy and water exchange process (EWEP) is an important prerequisite. However, estimation of the exact spatiotemporal variability of the land-atmosphere energy and water exchange over heterogeneous landscape of the TP remains a big challenge for scientific community. Focused on the above scientific question, a series of atmospheric scientific experiments and research programs have been conducted since the 1960s, quantitatively evaluating both the spatial distribution and the multi-timescale variation of EWEP via observation, remote sensing, and numerical simulation. Based on the three main approaches, the major advances on EWEP over the past 30 years are systematically summarized in this work. All these results advanced the understanding of different aspects of EWEP over the TP by using in situ measurements, multisource satellite data and numerical modeling. Future studies are recommended to focus on the optimization of the current three-dimensional comprehensive observation system, the development of advanced parameterization schemes and the investigation of EWEP on weather and climate changes over the TP and surrounding regions.
Cost and health benefits of clean heating in rural China
Authors: Tao Shu
Published: March 2024

Residential sector contributes significantly to emissions of various air pollutants and adverse health impacts in rural China. One of the major activities leading to the emissions is space heating using solid fuels in rural households. Although cooking energy has switched rapidly towards clean one in the past several decades, solid fuels still dominate the heating activity in rural areas, primarily due to high cost of using electricity or natural gas. A recent government intervention in North China Plain to replace coal with clean energy for rural residential heating has resulted in great success. Here we show that the clean heating is feasible for a large rural population in entire heating zone at reasonable cost. Electricity is preferred over natural gas for cost, save, and energy security reasons. The scheme of promoting clean heating can be optimized based on population density. If per capita investment can reach 1,700 RMB, 75% of rural population in the heating zone can be covered, resulting in avoidance of 42,000 premature deaths associated with exposure to PM2.5 from solid fuels.
Comparison of gravity waves detected in the lower ionosphere by narrowband VLF measurements and in the F layer by a continuous Doppler sounding system
Authors: Bozóki Tamás , Chum Jaroslav
Published: March 2024

Gravity waves (GWs) are an important class of atmospheric waves that can propagate from the troposphere up to the upper atmosphere, where they can contribute significantly to the dynamical changes in the ionosphere. The aim of the present contribution is to gain a deeper understanding of the coupling between the lower and the middle ionosphere via gravity waves by the concurrent analysis of narrowband VLF measurements (characterizing GWs in the E layer) carried out at the Tihany Geophysical Observatory (TGO), Hungary and the multi-point and multi-frequency continuous Doppler sounding system (characterizing GWs in the F layer) operated by the Institute of Atmospheric Physics, CAS in the Czech Republic. The signal from the German VLF transmitter (call sign: DHO, frequency: 23.4 kHz) detected at the TGO have been considered for the present study, since the Doppler system located in the western part of the Czech Republic is close to the midpoint of the DHO-TGO wave propagation path. The inferred gravity wave activities have also been compared with the lightning locations provided by the World Wide Lightning Location Network (WWLLN) in order to identify the possible source areas of the upward propagating gravity waves. The preliminary analysis was carried out for the summer months of 2021. From the narrowband VLF measurements, the day-to-day variation of the average GW activity for each night was determined using the Wavelet transform. In the case of the Doppler system, the estimated Doppler shifts and the spreadF proxy were used to characterize the nighttime GW activity. Our results show low correlation (~0.04) between GW activity inferred from the VLF and Doppler measurements. On the other hand, for both the VLF and Doppler measurements, we could identify certain areas where the large number of lightning strokes was associated with enhanced GW activity in the corresponding ionospheric measurement. However, the areas found for the two measurements do not overlap, which may indicate that the VLF measurement is sensitive to a different area where the Doppler system is located. This work has been supported by the PITHIA-NRF Trans-National Access (TNA) programme.
Decomposition of Monsoon Dynamics: Reconciling Data and Model Comparison for Geological Time Periods
Authors: Sun Yong , Wu Haibin , Ding Lin , Ramstein Gilles
Published: March 2024

Understanding past climate informs our future scenarios. Proxy data and climate models are vital for studying past climate change, but discrepancies often arise between these approaches. This study introduces an innovative approach that reconciles proxy data with models by decomposing the physical processes driving monsoon precipitation changes. Focusing on East Asian Summer Monsoon (EASM) precipitation across significant periods in the PMIP, our analysis highlights: 1) the dominance of dynamic effects over thermodynamic effects during the mid-Holocene, 2) contrasting impacts of thermodynamic and dynamical processes during the Last Glacial Maximum, and 3) distinct regional controls of thermodynamic and dynamical processes in the mid-Piacenzian warm period, reflecting diverse water vapor sources. The study concludes that decomposing the physical processes of precipitation aids in reconciling records and simulations. It asserts that simulations consistently yield a decomposed process that spatially aligns with the records. The mismatch between records and simulations primarily arises from simulation biases in the relative contributions of the decomposed physical processes to precipitation changes, suggesting a need for improvement in simulations.
Long-term gravity field changes from SLR data and the combination with GRACE  for improving low-degree coefficients
Authors: Gałdyn Filip , Sośnica Krzysztof , Zajdel Radosław
Published: March 2024

In recent two decades, monitoring of changes in the Earth’s gravity field has been carried out mainly by the Gravity Recovery And Climate Experiment (GRACE) and its successor GRACE Follow-On. However, before the GRACE era,  very little information is available on the temporal evolution of the Earth's gravity field prior to that date. Moreover, through these missions, we have many gaps between 2010 and 2019. Fortunately, GRACE and GRACE Follow-On are not the only missions that can be used to recover variations in the Earth's gravity field. For the recovery of the mass redistribution processes on a large scale, we may employ precise Satellite Laser Ranging (SLR) observations.We propose a set of long-term, continuous solutions based on SLR data. In our solutions, we use observations from spherical geodetic satellites. The gravity field is expanded up to a degree and order 10 with a monthly resolution from 1/1995 to 10/2021. The main solution has been decomposed into solutions expanded to degree and order 4, 6, 8, and 10 and stacked, taking advantage of the stability of the low-degree expansion and the better resolution of the high-degree expansion. The results show the reduction of the correlations between obtained parameters, stabilization of the ice mass estimates in polar regions – in Greenland and Antarctica, and a reduction of the noise over oceans by a factor of four.In the GRACE and GRACE Follow-On datasets, the replacement of the spherical harmonics C20 and C30 with SLR-derived data is necessitated by suboptimal quality resulting from thermal effects impacting satellites and accelerometer malfunctions. In both SLR and GRACE solutions, coefficients of the same order and parity exhibit strong correlations. Merely replacing two specific coefficients could introduce bias into the solution. Therefore, we propose a comprehensive approach, combining GRACE with SLR solutions up to a degree and order of 10x10. This strategy ensures a proper consideration of the sensitivity of each technique to gravity field coefficients. The combined solution exhibits reduced noise compared to standard GRACE COST-G solution and effectively address the distinct sensitivities of SLR and GRACE techniques to low-degree time-variable gravity field coefficients.
Image-based small body shape modeling using the neural implicit method
Authors: Chen Hao , Oberst Jürgen , Willner Konrad , Hu Xuanyu , Damme Friedrich , Ziese Ramona , Gläser Philipp
Published: March 2024

One of the objectives of cameras on spacecraft for exploration of asteroids and comets is to perform shape modeling of the small bodies. Stereo-photogrammetry (SPG) and stereo-photoclinometry (SPC) stand out as the two main image-based methods for shape modeling, used in both previous and ongoing missions. In recent years, machine learning technology has experienced rapid development and demonstrated great promise for planetary topographic modeling. However, applications to small bodies have been limited so far. In this work, we present a neural implicit shape modeling method designed specifically for small body images characterized by rapid model convergence. We select 25143 Itokawa, explored by the Hayabusa mission, as a demonstration.  The method uses a sparse set of 52 images captured by the Asteroid Multi-band Imaging Camera (AMICA). The results are consistent with models previously produced using the SPC method in terms of overall size and shape. Also, our method can effectively capture fine-scale terrain features on the surface of Itokawa. This suggests that the neural implicit method can provide a new option and insight for the 3D reconstruction of small bodies.
Early days of carbon isotope geochemistry in paleoceanography and limnogeology - tales from Judy’s ETH Lab 
Authors: Weissert Helmut
Published: March 2024

 Fundamentals of C-isotope geochemistry were established in the mid-1950s. Its use as a proxy in paleoceanography and paleoclimatology was long underestimated. While oxygen isotope geochemistry was identified early as a powerful tool in Ice Age history, carbon isotope geochemistry evolved only in the 1970s into a valuable instrument in paleoceanography and paleolimnology.  In 1976, Judy McKenzie was offered the chance to build the first stable isotope lab at ETH Zürich. Judy was, together with her team, among the first geoscientists searching for applications of C-isotope geochemistry in paleoceanography and limnogeology. Seasonal fluctuations in lake productivity were monitored in C-isotope composition of lake sediments and C-isotope records measured in pelagic carbonates served as a tracer of circulation and productivity in Cenozoic and Mesozoic oceans. In the eighties C-isotope geochemistry was recognized as a proxy of the global carbon cycle and its history was traced in C-isotope records measured in pelagic carbonates. The ETH Lab contributed with the several publications on C-isotopes and the carbon cycle to the seminal Chapman conference on “The Carbon Cycle and Atmospheric CO₂: Natural Variations Archean to Present” (Florida, 1984). An improved understanding of marine carbon fractionation processes allowed to use paired carbonate and organic carbon isotope analyses as a proxy for past atmospheric carbon dioxide concentrations. Today C-isotope geochemistry is established as a most valuable tool in paleoclimatology and paleoceanography, in sedimentology and geomicrobiology.
Laboratory Experiments on the Transport of Microplastic Particles in Gravel and Sand Sediments
Authors: Ding Jiaxing , Grischek Thomas
Published: March 2024

Column experiments are used to study infiltration and transport behavior of microplastics (MP) in aquifers. The transport behavior of various MP polymer types, including PET, POM, PMMA, and PS, which differ in size (0.8 – 3 mm), density (1.03 – 1.42 g/cm3), and shape, has been examined. The MP particles were added to the inflow of columns containing different gravel compositions, having both unimodal (d50 = 12, 6.5, 2.5, 1.2 mm) and bimodal distribution (d50 = 10, 6, 3.5 mm), and also of columns filled with sand (d50 = 0.031 and 0.065 mm). To introduce MP particles into the sediment, a novel approach involving melting frozen MP particles embedded in ice layers was employed. This method naturally replicated the infiltration process while minimizing blockages or particle losses in the circuit's pipes and connectors. After infiltration at defined flow rates for three days, MP particles have been separated from sediment layers of 3 cm thickness manually or using density separation. The depth where they were identified is defined as infiltration depth. Micro computed tomography (Micro-CT) was applied to visualize sediment pores and throats where MP passed through. Results for infiltration in different gravel textures showed as expected that smaller MP are transported to a greater depth. Lighter MP were also found in deeper layers due to its shape. Concerning shape effects, flat circular discs showed a higher potential to be found at greater infiltration depth, compared to spheres, fibers and pellets. Concerning the size ratio between MP and sediment grains bimodal sediment reveals to hinder the infiltration of MP due to its lower pore size, which is consistent with results from the Micro-CT pore measurement. Initial results from sand column experiments will be analyzed to explore the size ratio range between sediments and MP under saturated conditions, highlighting the differences in MP behavior between sand and gravel. The findings enhance our understanding of MP transport mechanisms in aquifer sediments and infiltration basins and offer insights for groundwater and sediment MP contamination mitigation.
Does a soil drying-rewetting cycle decrease the effectiveness of nitrification inhibitors?
Authors: Ribeiro Pablo , Mühling Karl
Published: March 2024

Changes in soil moisture content can be an important factor influencing the effectiveness of nitrification inhibitors (NIs). Therefore, we hypothesized that a soil drying-rewetting cycle enhances biodegradation and decreases the effectiveness of NIs. This study evaluated the effectiveness of DMPP and MP+TZ (3-Methylpyrazol and Triazol) under a drying and rewetting cycle relative to low and high soil moisture conditions under two soil textures. NIs performance was assessed through measuring (i) daily and cumulative N2O-N emissions, (ii) soil NH4+-N and NO3−-N concentrations, and (iii) the composition of bacterial soil communities over the experimental period in an incubation study. NIs application reduced the overall N2O-N emissions under drying-rewetting (-45%), 40% water-holding capacity (WHC) (-39%), and 80% WHC (-25%). In general, the relative abundance of nitrifying bacteria Nitrospira spp., Nitrosomonas, Nitrobacter, and Nitrosococcus was reduced by DMPP and MP+TZ application, explaining the observed results. Unexpectedly, between days 30 and 60, DMPP and MP+TZ inhibitory effect on nitrification was weakened, and the N2O-N emissions from NI-treated soils increased by 5 to 6-fold relative to the control treatment in the silt loam soil at 80% WHC. These results indicated that DMPP and MP+TZ application can cause late increased N2O-N release due to short-term effects on the relative abundance of nitrifying bacteria and subsequent NO3−-N accumulation. Thus, our study provided new insights into how the interaction between time and soil water content can decrease the effectiveness of NIs.