bluuebunny/crossref_metadata_2025 huggingface dataset:
Plant evolution and diversity at the dry limit
Authors: Quandt Dietmar , Koch Marcus , Bechteler Julia , Stoll Alexandra
Published: March 2024

With 750 to 1000 plant species the Atacama Desert has a rich flora that evolved to its extreme and harsh arid environmental conditions. We focused on a variety of plant groups with different life history traits from the families Asteraceae, Bromeliaceae, Cactaceae, Loasaceae, Malvaceae and Zygophyllaceae to decipher their evolutionary history in the Atacama Desert and trace down colonization patterns in the past and the future, as well as the genetic basis of their adaptation to this (hyper-)arid desert. In an interdisciplinary setting we place our population genetic and genomic/transcriptomic analyses in the context of geological, geomorphological and climatic data. Our results point to an evolutionary young flora that originated mainly during the Paleogene and Neogene with accelerated diversification radiations taking place since the last 5-6 million years.
The onset of hyper‐aridity during the late Miocene as well the Quaternary climate oscillation have played a major role in the diversification of various plant groups. Population genetic analyses indicate that the dry core of the northern part of the Atacama acts as powerful barrier for floristic exchange and gene flow (e.g., Ophryosporus (Asteraceae), Huidobria, (Loasaceae)) which does not hold true for the southern part of the Atacama that is characterized by ravines and valleys connecting the coast to the Andean foothills. Observed genetic clusters are linked to ravines linking the coast with the Andes and are mirrored in gene expression patterns thus offering valuable insights into the genetic adaptation of desert plants (e.g., Huidobria chilensis). In addition, genetic isolation of coastal taxa is indicated due to recent climatic variability (e.g., Cristaria (Malvaceae)). Our results stemming from the Atacama flora is tested in the corresponding desert system of the Namib (e.g., Kissenia (Loasaceae), Zygophyllum (Zygophyllaceae)). in southern Africa and will enable us to find general patterns of plant evolution in arid environments.
How does the Red Sea Overflow Water reach the Southeastern Indian Ocean?
Authors: Menezes Viviane
Published: March 2024

This study is motivated by a relatively old and unsolved puzzle involving the spreading of the salty Red Sea Overflow Water (RSOW or Red Sea Water) at the Indian Ocean intermediate layer (500-1500 m). The RSOW spreads within the 27-27.6 kg/m3 (potential) density layer mainly along the Indian Ocean western boundary, a pathway that has received the most attention since the early 20th century. However, several studies report this salty water mass (or rather a diluted version) far away in the southeastern Indian Ocean between 10°S and 24°S. How does it arrive there? When we look at the mean intermediate-layer circulation maps, the advective pathway for the RSOW to the southeastern Indian Ocean is obscure.  As it moves southward, the RSOW mixes and interleaves with the fresher and colder Antarctic Intermediate Water (AAIW) and Indonesian Intermediate Water (IIW), becoming progressively less saline before the salinity maximum fades out. This makes it difficult to trace the RSOW pathways in the entire Indian Ocean based on its salinity fingerprint alone. Here, a different approach is used. The present study investigates the paths of the RSOW to the southeastern Indian Ocean using particle tracking Lagrangian simulations, a valuable tool to determine large-scale pathways and connectivity between oceanic regions. The simulations are based on the eddy-rich GLORYS12 (GLobal Ocean ReanalYses and Simulations 1/12° resolution) reanalysis that incorporates most satellite and in-situ observations in the altimeter era. Sets of virtual particles were released every five days between 1993 and 2014 in the westernmost part of the Gulf of Aden at three isopycnic levels within the RSOW layer and tracked for 300 years. We stopped seeding particles in 2014 because the cumulative number of released particles reached about 106, sufficiently large to infer pathways statistically. For performing the simulations, the GLORYS12 Eulerian velocity fields were repeated sequentially over the simulation period. Analysis of probability maps and pseudo-Eulerian velocity fields indicate that the equatorial area is the preferential pathway for the RSOW transport to the eastern Indian Ocean, which reveals the critical role of the Equatorial Intermediate Current in the western-eastern connectivity. A convoluted secondary eastward pathway is seen between 5S and 10S. After reaching the Java-Sumatra area, particles are transported southward along the southeastern boundary. However, most particles return to the western side around 12°S, and fewer particles flow further south offshore Western Australia.
Precipitation, temperature, and vegetation indices analysis for Saudi Arabia region: Feasibility of Google Earth Engine
Authors: Yaseen Zaher Mundher , Halder Bijay , Yassin Mohamed A. , Abba Sani I.
Published: March 2024

Climatic disaster is continuously triggering environmental degradation and thermal diversification over the earth's surface. Global warming and anthropogenic activities are the triggering factors for thermal variation and ecological diversification. Saudi Arabia has also recorded precipitation, temperature, and vegetation dynamics over the past decades. Therefore, monitoring past precipitation, temperature, and vegetation condition information can help to prepare future disaster management plans and awareness strategies. The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN-CDR) from the Center for Hydrometeorology and Remote Sensing (CHRS) data portal and Moderate Resolution Imaging Spectroradiometer (MODIS) are applied for precipitation, Land Surface Temperature (LST), Enhance Vegetation Index (EVI), and Normalized Difference Vegetation Index (NDVI) from 2003 to 2021 respectively. Yearly mean LST, EVI, NDVI, and precipitation values are calculated through the Google Earth Engine (GEE) cloud computing platform. MODIS-based LST datasets recorded the highest temperatures is 43.02 °C (2003), 45.56 °C (2009), 47.83 °C (2015), and 49.24 °C (2021) respectively. In between nineteen years, the average mean LST increased by 6.22 °C and the most affected areas are Riyadh, Jeddah, Abha, Dammam, and Al Bahah. The mean Precipitation is recorded around 776 mm, 842 mm, 1239 mm, and 1555 mm for the four study periods, while the high precipitation area is Jazan, Asir, Baha, and Makkah provinces. In between nineteen years, 779 mm of precipitation is increasing in Saudi Arabia.  Similarly, the NDVI vegetation indices observed 0.885 (2003), 0.871 (2009), 0.891 (2015), and 0.943 (2021), while EVI observed 0.775 (2003), 0.776 (2009), 0.744 (2015), and 0.847 (2021). The R2 values of the LST and EVI correlation is 0.0239 (2003), 0.0336 (2009), 0.0136 (2015) and 0.0175 (2021) similarly correlation between LST and NDVI is 0.0352 (2003), 0.0265 (2009), 0.0183 (2015) and 0.0161 (2021) respectively. The vegetation indices indicate that the green space is gradually increasing in Saudi Arabia and the highly vegetated lands are Meegowa, An Nibaj, Tabuk, Wadi Al Dawasir, Al Hofuf, and part of Qaryat Al Ulya. This analysis indicates that the temperature is increasing but precipitation and green spaces are increasing because of the groundwater recharge through dam construction, precision agriculture, and planned build-up is helps to prepare Saudi Arabia as a green country. Therefore, more attention to preparing the strategic agricultural plants as well as other vegetation and artificial groundwater recharge can improve the country as a green nation. This analysis might help to prepare future planning, awareness, and disaster management teams to prepare for future disasters and strategic steps for sustainable development.
Phenology Analysis of Cotton and Maize in Lake Karla Watershed under the mild climate scenario (RCP 4.5)
Authors: Tziatzios Georgios A. , Doro Luca , Tzabiras John , Mylopoulos Nikitas , Loukas Athanasios , Danalatos Nikolaos
Published: March 2024

In this paper, the effects of climate change on the phenology of cotton and maize are studied applying the Agricultural Policy/Environmental eXtender (APEX) simulation model. Cotton and maize are two dominant irrigated crops in Lake Karla Watershed (Central Greece). The phenology of maize and cotton is examined considering the mild climate scenario (RCP 4.5) with results from 5 climate models for the 2080 – 2100 period. The 5 climate models selected for this study are CNRM, HADLEY, ICHEC, IPSL and MPI. The scenario based on the HADLEY climate model predicts the highest values of average minimum and average maximum temperature while the ICHEC model predicts the lowest average minimum and average maximum temperature. In terms of precipitations, the MPI model predicts the lowest average precipitation while the  highest average precipitation is predicted by the CNRM climate model. The APEX model simulates plant development using the heat units approach and the heat units index (HUI), calculated as ratio between accumulated heat units and the total heat units needed to reach maturity, can be used as indicator of plant phenology. According to this approach, HUI = 1 indicates the physiological maturity. For all climate models the HUI shows that the cotton and maize reach maturity too early in the season as a result of which they also record lower yields, with the HADLEY climate scenario giving the lowest crop yield. According to the results provided by the APEX model for the two crops considered here, cotton will be affected the most by the predicted future climate.
Surface conditions and mean monthly temperatures in the Arctic
Authors: Ekrami Negar , Olafsson Haraldur
Published: March 2024

A large dataset of mean monthly temperatures in the circumpolar Arctic is explored for the winter and spring seasons, revealing locations with very high-temperature persistence.
The temperature persistence is related to the Earth´s surface in several ways.   A primary factor of persistence is the direct cooling effect of high snow cover or sea-ice extent in the spring, through its impact on albedo and surface fluxes.  A secondary effect is through modifications of regional-scale circulations, which can be detected in connection with variability in the sea-ice extent. 
The data reveals substantial persistence in the mean temperatures, leading to locally high correlation coefficients.  A remarkable negative correlation is found between the mid-winter and the spring.  This can be related to warm and snowy periods in the winter providing excessive snow into the spring.  
Advancements in Medicanes Tracking and Forecasting Using Artificial Intelligence
Authors: Martinez-Amaya Javier , Nieves Veronica , Muñoz-Marí Jordi
Published: March 2024

Medicanes, tropical-like cyclones in the Mediterranean Sea, pose unexpected challenges to unprepared areas due to their projected increases in intensity. To address these challenges, we proposed: 1) the development of an automatic tracking method in the absence of a comprehensive tracking database for Medicanes; 2) the implementation of a forecasting model for extreme cyclones utilizing artificial intelligence techniques. This is especially beneficial when traditional numerical models struggle to account for nonlinear interactions. We use a K-means algorithm and mean sea level pressure reanalysis data to track storm centers, determining maximum wind speed and position throughout each case’s lifetime. This information categorizes our dataset into storm-like and extreme Medicanes, and facilitates the extraction of spatiotemporal data from infrared satellite images. These features enable us to predict the final classification of Medicanes (whether they are storm-like or extreme) 6 to 36 h before peak wind speed, using an optimized combination of Convolutional Neural Network and Random Forest binary classification methods. By training and testing on Mediterranean data from 1984 to 2020, we successfully diagnosed between 72% and 87% of extreme Medicanes in the studied cases, depending on the lead-time. Our study is the first to employ artificial intelligences for both tracking and forecasting Medicanes, offering a foundational approach to enhance Medicanes preparedness and awareness.
Understanding fatal landslides on a global scale: insights from topographic, climatic, and anthropogenic perspectives
Authors: Fidan Seckin , Tanyas Hakan , Akbas Abdullah , Lombardo Luigi , Petley David N. , Gorum Tolga
Published: March 2024

Landslides are a common global geohazard that lead to substantial loss of life and socio-economic damage annually. Landslides are becoming more common due to climate change and anthropogenic disturbance, threatening sustainable development in vulnerable areas. Previous studies on fatal landslides have focussed on inventory development; spatial and temporal distributions; the role of precipitation and/or seismic forcing; and human impacts. However, their climatological, topographic, and anthropogenic characterization on a global scale has been neglected. Here, we present the association of natural and anthropogenically induced landslides in the Global Fatal Landslide Database (GFLD) with topographic, climatic, and anthropogenic factors, focusing on their persistent spatial patterns. The majority of natural (69.3%) and anthropogenic (44.1%) landslides occur in mountainous areas in tropical and temperate regions, which are also characterized by the highest casualty rates per group (66.7% and 43.0%, respectively). However, they significantly differ in terms of their morphometric footprint. Fatal landslides triggered by natural variables occur mostly in the highest portions of the topographic profile, where human disturbance is minimal. As for their anthropogenic counterpart, these failures cluster at much lower altitudes, where slopes are gentler, but human intervention is greater due to a higher population density. Our results demonstrate that fatal landslides have a heterogeneous distribution on different macro landforms characterized by different topographic, climatic, and population conditions. Our observations also point towards land cover changes being a critical factor in landscape dynamics, stressing human pressure as a discriminant cause/effect term for natural vs. human-induced landslide fatalities.
Dynamics of large-scale atmospheric circulation patterns in the wider Carpathian region (Europe) during the past 2000 years
Authors: Perşoiu Aurel
Published: March 2024

Increasing evidence suggests that accelerated warming leads to rapid changes in the dynamics of large-scale atmospheric circulation, with associated changes in the activity of storms and occurrence of extreme events, including extreme precipitation, severe drought, and extended periods of atmospheric blocking conditions. While in Western Europe the influence of the Atlantic Ocean dominates continental climate, in Eastern Europe, the overlap of Atlantic, Mediterranean and continental influences results in intricate circulation dynamics, with similarly complex climate variability. In this context, we present here a reconstruction of summer and winter climatic conditions and atmospheric circulation patterns across SE Europe during the Late Holocene. By combining various proxy-based climate reconstructions, we present here 1) time series and maps of the spatial patterns of winter and summer climate variability in SE Europe, covering the last ~2000 years; and 2) mechanisms linking large-scale atmospheric circulation patterns to external forcing and internal dynamic during periods of both slow and rapid climatic changes.
Different management strategies of disturbed forest areas in Central Germany: Effects on soil nutrient distribution, forest soil structure and microclimate
Authors: Koal Philipp , George Simon , Grieger Simon , Brock Marie , Profft Ingolf , Putzenlechner Birgitta
Published: March 2024

It has become increasingly challenging to maintain "regular" forest management, as the pace and magnitude of climate-related changes exceeds the response of many forest ecosystems. This has led to large-scale disturbances in recent years. To limit impacts on soil structure, the loss of soil organic matter and soil nutrients and to restore forest climate and functions, the development of suitable reforestation strategies on disturbed areas must be prioritised. Alternative management measures are needed to point out further options for the extensive clearing. To draw conclusions about the site-specific selection of suitable management options for disturbed areas, this study monitored mid- to long-term effects on soil structural and soil chemical parameters of the humus layer and topsoil as well as microclimatic properties.
Studies were carried out on large-scale Norway spruce (Picea abies (L.) Karst.) disturbance areas in low mountain regions in Thuringia. Different management variants were compared to vital spruce stands, ranging from standing deadwood to "high stumps", mulched and completely cleared areas. In addition to basic soil chemical and physical parameters, soil moisture and temperature of the topsoil and the organic layer as well as the surface temperature were recorded continuously over 30 months.
The results revealed significant differences in surface and soil temperature between the variants. Clear-cut areas showed higher soil temperatures and greater variability during the vegetation period. Standing deadwood lowered the average temperature and, in particular, mitigated high and low temperature peaks. Soil moisture showed temporal changes depending on the status of decline of the spruce forests. Even within the first few months, effects on the soil structure of the cleared disturbed areas can be detected, as macroaggregates degrade and the size fraction of microaggregates increases. With a narrowing C/N ratio in the mineral soil along with increasing thinning on the plots and intensity of management, mid-term (>6 months) losses in plant-available and total phosphorus content in the organic layer and the upper mineral soil were observed. While mulching led to an increase in soil organic matter (SOM) in the surface layer, a significant loss of SOM was determined over time in all other variants compared to vital spruce stands. Overall, we conclude that the aggregate stability and nutrient availability of the soil decreased faster with more intensive management intervention so that characteristics of the microclimate moved away from forest interior climate. Prolonged monitoring is required to verify whether the results are mid-term occasional effects or on the way to an equilibrium.
Advancements made to NOAA’s FENGSHA dust emission scheme within the Unified Forecast System with applications to regional air quality and subseasonal to seasonal forecasting
Authors: Baker Barry , Marvin Margaret , Hung Wei-Ting , Stajner Ivanka , McQueen Jeff , Montuoro Raffaele , Martin Cory , Huang Jianping , Campbell Patrick , Tang Youhua , Grell Georg , Zhang Li , Ahmadov Ravan , Bhattacharjee Partha
Published: March 2024

NOAA is developing the next generation air quality  prediction system for the United States  and global aerosol predictions within the Unified Forecast System (UFS) framework.  A major goal of this effort is to better represent and forecast impacts of extreme events like wildfires and dust storms on air quality  and impacts of aerosols globally on weather ranging from hourly  to seasonal scales. The FENSGHA (English analog of the Mandarin term for wind-blown dust)  emissions scheme developed at NOAA Air Resources Laboratory is adapted to the UFS for applications in the high resolution Rapid Refresh Forecast System with Smoke and Dust (RRFS-SD), the coupled online full chemistry air quality model (UFS-AQM), and the Global Ensemble Forecast System (GEFS) with prognostic aerosols.  One of the key parameters to model aeolian emissions within weather, climate, and air quality models is the threshold friction velocity (TFV). While in many models the TFV is determined by knowledge of soil size distributions and characteristics often assumed on a global scale, the FENGSHA dust emission model was originally constrained by observations following the works of Dale Gillette (1980, 1982, 1988). In this way, FENGSHA is a data-driven model, constrained by observations of saltation with respect to soil characteristics. In this study, a new way to determine the TFV is developed through a machine learning approach  constrained by observations and high resolution soil characteristics. We first use observed dust points detected by satellites compiled in Hennen et al. (2022), soil parameters from the SOILGRIDS version 2.0 or Beijing Normal University database, and ERA5 Land reanalysis data to train the machine learning model for  the TFV based solely on the soil inputs, including composition and physical characteristics. The machine learning  model results compare well with observations from Gillette and provide a robust and high resolution method to accurately describe the saltation velocity in both time and scale. Next, we apply this TFV within the  suite of UFS applications described above from regional to global scale. Retrospective simulations are compared with surface and satellite observations during dust events.
Estimating the causal effect of temperature on ozone air pollution
Authors: Hickman Sebastian , Griffiths Paul , Nowack Peer , Archibald Alex
Published: March 2024

Ground level ozone is an air pollutant which contributes to hundreds of thousands of premature deaths annually. Ground level ozone concentrations are controlled by physical and chemical processes, which can be sensitive to meteorological variables such as the local temperature. Understanding how ground level ozone concentrations are likely to change in future climates is important to understand the future impacts of ozone air pollution on human health. One factor that will influence how ground level ozone changes in the future is the sensitivity of ozone to changes in temperature, since temperature affects many of the processes controlling ozone.
One approach to determining the causal effect of changing temperatures on ozone is to perturb the temperature in simulations that model ozone concentrations. However, this approach relies on the simulations accurately representing observed physical processes. Here, we study another approach, estimating the effect of changing temperatures on ozone using causal inference methods and observed data. We show that double machine learning allows us to make estimates of the causal effect of temperature on ozone concentrations using large observational datasets. We estimate both average treatment effects and conditional average treatment effects, and compare our estimates with those of sensitivity studies using chemical box models. 
Abundance variations during a series of 3He-rich events observed by Solar Orbiter
Authors: Kouloumvakos Athanasios , Mason Glenn M. , Ho George C. , Allen Robert C.
Published: March 2024

On October 27 to 30, 2022, the Suprathermal Ion Spectrograph (SIS) on Solar Orbiter observed a series of 3He-rich solar energetic particle (SEP) events at a close radial distance from the Sun (0.42. AU). This period showed enhanced flux of 3He for a long time, a high abundance of heavy-ions, and multiple SEP injections with clear velocity dispersion in most cases. The spacecraft was magnetically connected close to a small active region (AR) that was likely the source of the series of 3He-rich events. The AR was close to a coronal hole that probably provided good access for the accelerated SEPs to the interplanetary space. During the separate SEP injections, we observe many jet-like eruptions and small-scale brightenings at the AR. I will present SIS observations that show interesting SEP spectrum characteristics and abundance variations. Interestingly, some of the injections exhibit very high 3He/4He and 3He/H ratios.
Io Source of Heavy Ions in Jupiter’s Equatorial Ionosphere
Authors: Bagenal Fran , Dols Vincent , Valek Philip , Waite Jack Hunter
Published: March 2024

The JADE instrument on Juno has measured cold (<1 eV) heavy ions (sulfur and oxygen) in the equatorial ionosphere of Jupiter as the spacecraft made its closest approach to the planet (~3,500 km above 1 bar level), as reported by Valek et al. (2020) for 17 passes (between perijoves 6 and 23). The source of these heavy ions in Jupiter’s proton-dominated ionosphere remains unclear. The presence of sulfur and oxygen suggests they ultimately came from Io. Inward transport of plasma from the Io torus is slow and the total flux very small. Moreover, adiabatic heating would produce energetic particles reaching the equatorial ionosphere rather than cold populations. An alternative possible source could be neutral atoms that are ejected by the plasma interaction with Io’s atmosphere. We take estimates of the neutral fluxes from models of the Io plasma-atmosphere interaction and explore how the flux of neutrals reaching Jupiter depends on the ejection speed and direction. We then consider typical equatorial atmospheric conditions at Jupiter and evaluate how the incoming neutrals become cold heavy ions mixed into the ionosphere. 
Unstable evolution of railways slope under the rainfall-vibration joint action
Authors: Haoyu Dong
Published: March 2024

Understanding the unstable evolution of railway slopes is the premise for preventing slope failure and ensuring the safe operation of trains. However, as two major factors affecting the stability of railway slopes, few scholars have explored the unstable evolution of railway slopes under the joint action of rainfall-vibration. Based on the model test of sandy soil slope, the unstable evolution process of slope under train vibration, rainfall, and rainfall-vibration joint action conditions is simulated in this paper. By comparing and analyzing the variation trends of soil pressure and water content of slope under these conditions, the change laws of soil pressure and water content under the influence of rainfall-vibration joint action are explored. The main control factors affecting the stability of slope structure under the joint action conditions are further defined. Combined with the slope failure phenomena under these three conditions, the causes of slope instability resulting from each leading factor are clarified. Finally, according to the above conclusions, the unstable evolution of the slope under the rainfall-vibration joint action is determined. The test results show that the unstable evolution process of sandy soil slope, under the rainfall-vibration joint action, can be divided into: rainfall erosion cracking, vibration promotion penetrating, and slope instability sliding three stages. If it is in a short period of time when the vibration starts or ends, the slope will also generate structural changes in vibration densification (vibration loosening). In the process of slope unstable evolution, rainfall and vibration play the roles of inducing and promoting slide respectively. In addition, the deep cracks, which are the premise for the formation of the sliding surface, and the violent irregular fluctuation of soil pressure, which reflects the near penetration of the sliding surface, constitute the instability characteristics of the railway slope together. This paper reveals the unstable evolution of sandy soil slopes under the joint action of rainfall-vibration, hoping to provide the theoretical basis for the early warning and prevention technology of railway slopes.
Mechanisms of seasonal variations of dissolved 137Cs concentrations in freshwaters: Fukushima and Chernobyl
Authors: Konoplev Aleksei , Kurosawa Honoka , Wakiyama Yoshifumi , Igarashi Yasunori , Nanba Kenji
Published: March 2024

Analysis of available monitoring data on seasonal variations of dissolved radiocesium concentrations in the water bodies of accidentally contaminated areas has revealed two basic mechanisms responsible for regular seasonal variations of dissolved 137Cs concentrations in water bodies (increase in summer and decrease in winter), namely temperature dependence of radiocesium desorption from sediments to solution, and ion-exchange remobilization of radiocesium by cations of ammonium generated as a result of organic matter decomposition in anoxic conditions. An equation has been derived describing seasonal variations of dissolved radiocesium in water bodies considering two basic factors: water temperature and combined concentration of basic competitive cations. In Fukushima rivers, which are mostly shallow and fast-flowing, ammonium concentration is usually negligible. For them, the predominant factor of dissolved 137Cs seasonality is the temperature dependence of 137Cs desorption. For stagnated stratified waters of ponds, lakes, and dam reservoirs in anoxic conditions, the role of ammonium in 137Cs mobilization can be comparable with that of water temperature or even be prevalent. Results of a field experimental study of dissolved 137Cs seasonality in three ponds of Okuma town in the near area of the Fukushima Daiichi nuclear power plant are presented.This research was supported by Environmental Radioactivity Research Center (ERAN) Projects I-23-11 and I-23-12.
The importance of soil structure data for soil erosion modelling and mapping
Authors: Gupta Surya , Alewell Christine
Published: March 2024

Soil structure is a crucial parameter for comprehending soil functioning, as it influences the impact of soil erosion and the behaviour of soil hydraulic properties. Simultaneously, soil structure is a crucial indicator of potential soil degradation or soil health status. Various proxies, including soil organic matter and soil texture, are employed to characterize soil structure in modeling. Nevertheless, the effectiveness of these proxies in determining soil erosion or soil hydraulic properties remains uncertain. To address this gap, we leverage available soil structure data along with diverse soil properties for Switzerland to investigate the relationship between proxies, soil structure data, and soil erosion rates. To achieve this, we initially developed a soil structure class map using approximately 42,000 samples and a random forest machine learning algorithm at various depths. The confusion matrices revealed accuracies ranging from 57% to 71% for different depths. Subsequently, we incorporated these soil structure maps into the soil erosion model and compared the results with those obtained using proxies. We anticipate that utilizing real measurements as opposed to proxies may lead to significant differences in erosion rates.
Beyond Traditional Metrics: Unravelling Hydrological Systems with a Response Time Evaluation Approach
Authors: Al-Yaari Amen , Longuevergne Laurent , Karami Ayoob , Schuite Jonathan
Published: March 2024

Hydrological, land surface, or climate models are commonly assessed using classical metrics (e.g., Nash-Sutcliffe Efficiency, Root Mean Square Error, etc.) to evaluate their performance in simulating total water storage (S) and streamflow (Q) either separately or jointly. However, these integrative metrics may provide limited insights into the descriptive capabilities of system dynamics, as they heavily rely on the quality of boundary conditions. In contrast to traditional hydrological modelling and approaches that predominantly operate in the time domain, this study introduces a novel approach based on the concept of hydrological ”response time”, physical information linked to system intrinsic properties, which is computed as the ratio S/Q in the frequency domain.
This approach explores how different components of the hydrological system respond to variations in input signals at different frequencies, offering reduced sensitivity to boundary conditions. An additional advantage of this approach is its ability to define dominant exchange processes between soil, rivers, and groundwater across various frequency ranges. This methodology contributes to a more robust and physics-based assessment of hydrological system behaviour, fostering a deeper understanding of water dynamics. To demonstrate the effectiveness of this approach, we evaluate Phase 6 of the Coupled Model Intercomparison Project (CMIP6) and the System Global Land Data Assimilation System (GLDAS)-driven Noah models against the Global Runoff Data Centre and the Gravity Recovery and Climate Experiment (GRACE) satellite time series of observed Q and S, respectively, across more than 50 large basins worldwide. The results will be presented and discussed.
Indian monsoon dynamics during the 8.2 ka event
Authors: Salman Mohd , Saraswat Rajeev
Published: March 2024

The 8.2 ka event refers to a prominent climate anomaly characterized by a sudden and significant global cooling. This event is believed to have been triggered by the release of large amounts of freshwater into the North Atlantic Ocean, disrupting the ocean thermohaline circulation and causing a temporary cooling episode, likely transmitted globally via atmospheric teleconnections. The global impact of this event is highly debated, mainly because of its short-lived nature. The signatures of this event are hard to find in usually centennially resolved marine records. We report a strong influence of 8.2 ka event on the monsoon in the Indian subcontinent, based on a decadal resolution marine sedimentary record recovered from the south-west Bay of Bengal. The abrupt decrease in coarse fraction (>63 µm), calcium carbonate (CaCO3), organic carbon (Corg), and Nitrogen (N) at 8.5 ka, points towards a collapse in productivity. The decrease in the Corg/N ratio at 8.5 ka, also suggests an abrupt weakening of the monsoon that continued till 8.0 ka. We report that this event affected the climate for 500 years in the Indian subcontinent and nearby oceans. Studying the impact of the 8.2 ka event in the Bay of Bengal provides valuable insights into the complex interactions between climate, oceanic systems, and local environments, highlighting the global and regional teleconnections.
 
Keywords: 8.2 ka event, Monsoon, Productivity, Circulation, Bay of Bengal.
Gravity waves and ice clouds – Interaction of dynamics and microphysics using a Lagrangian approach
Authors: Bergner Hannah , Spichtinger Peter
Published: March 2024

Ice clouds have a significant impact on the thermodynamic structure of their environment due to diabatic effects such as latent heat release in phase transitions. On the other hand, the ice clouds themselves are crucially affected by the local dynamics e.g. due to atmospheric gravity waves generated by frontal systems or the flow over a mountain. The interaction of the relevant dynamical processes and ice cloud microphysics on different length and time scales is not yet well understood. We investigate the influence of atmospheric gravity waves on ice cloud microphysics using a Lagrangian approach.The ice cloud properties are modelled by an ODE system where the variables are number and mass concentration as well as the supersaturation of water vapour over ice, while the vertical updraft is externally driving the system. The dynamical effects due to gravity waves are described by a Taylor-Goldstein type equation, which is then used to calculate trajectories of air parcels. We investigate the ice cloud microphysical properties along such trajectories. In this framework, we are able to run many simulations and thus study the setting for several different initial and environmental conditions.While the ice cloud system can be regarded as a non-linear oscillator for constant vertical motion, more complex behaviour emerges in the case of the non-constant updraft along trajectories. Due to the non-linearity of the ice cloud model and the overall complexity of the equations of the coupled systems, the feasibility of analytical calculations is limited and the investigation of the coupled system is largely based on numerical approaches.
Study of formaldehyde (HCHO) columns abundance from OMI satellite data in two agricultural regions in the south of Mexico
Authors: Mendoza Rodriguez Cristina Alejandra , Rivera Cardenas Claudia Ines , Espinosa Ponce Carlos Crispin
Published: March 2024

HCHO is one of the most abundant carbonyl compounds in the troposphere. At global scale, HCHO is mainly produced from the oxidation of volatile organic compounds (VOC) which come from biogenic (predominantly isoprene) emissions, biomass burning, and anthropogenic emissions. HCHO is produced in high amounts when both isoprene and nitrogen oxides (NOx, NO + NO2) are present. In order to determine the driver factors and the principal months of enhancement of HCHO over the Oaxaca and the Chiapas regions, important rain-fed maize agricultural areas located in the south of Mexico, HCHO columns from the Ozone Monitoring Instrument (OMI) were used in conjunction with isoprene emissions, NOx  emissions from biomass burning (NOx_bb), and NOx emissions from soils with their different sources (biomes: NOx_bio, fertilization and manure: NOx_fer, deposition of N: NOx_dep, pulses: NOx_pul, and total: NOx_tot) from January 2005 to December 2016. Based on scatterplots, Spearman rank correlations, and multiple regression models, we determined that isoprene and NOx_bb were important drivers of HCHO abundance in the Oaxaca region, especially in April and May. In the Chiapas region, important drivers were isoprene, NOx_bb, and NOx_fer, mainly from April to August. With the estimated regression coefficients, the contribution (in %) of the relevant emission fluxes for each region were calculated in order to know which source was the predominant one in the exacerbation of modeled HCHO (HCHOMOD). In the Oaxaca region, isoprene predominates over NOx_bb. In the Chiapas region, the emissions of NOx were more importantthan isoprene. NOx_bb and NOx_fer were enhanced principally due to the agricultural activity taking place in the Oaxaca and the Chiapas regions. Thus, this work demonstrates the impact of agricultural activity on HCHO columns observed by the OMI instrument.
An Observational Analysis of Environmental Effects on Tropical Cyclones Size Expansion
Authors: Chen Kexin
Published: March 2024

This study compares the wind fields and environmental conditions of Tropical cyclones (TCs) in rapid expansion (RE) and slow expansion (SE) events with similar internal features over the North Atlantic. The results indicate that the RE event occurs in an environment with stronger deep-layer vertical wind shear, higher upper-level divergence, and stronger lower-level vorticity. The analyses reveal a two-stage process in the RE event: 1) tilted vortex with downshear expansion and 2) realigned vortex with left-of-shear expansion. At 6 h after RE onset, the interaction between TCs and upper-level trough tilts the TCs and enhances upper-level divergence on the downshear side, favoring deep convection with significant inward vorticity transport there, thus causing pronounced downshear wind field expansion. By 12 h after RE onset, the TC-trough interaction shifts the maximum upper-level divergence from the downshear to left-of-shear and closer to the TC center, accompanied by the movement of precipitation towards the TC center and a reduction of vortex tilt. The vorticity transport in downshear-left and azimuthal advection of tangential wind in upshear-left jointly contribute to the left-of-shear wind field expansion. Additionally, the positive feedback among wind, surface latent heat flux, and convection facilitates the rapid size expansion in the RE event. In contrast, the weaker interaction between the TCs and upper-level westerly in the SE event accounts for a less pronounced tilt of the TCs and downshear convection, resulting in a slower expansion of the downshear wind field supported by the vorticity transport.
Inferring Ozone Production Regimes over the continental US
Authors: Singh Akanksha , Ring Allison M. , He Hao , Allen Dale J. , Dickerson Russell R. , Salawitch Ross J. , Canty Timothy P.
Published: March 2024

Surface ozone regulation policies depend heavily on Air Quality Models (AQMs) as vital tools, requiring validation through comparisons with observations. Identifying the factors influencing surface ozone formation is complicated because ozone photochemical production rates are non-linearly dependent on precursors such as nitrogen oxides (NOx) and volatile organic compounds (VOCs), with the best pollution reduction strategy usually dependent on targeting the precursor that exerts greatest control on surface ozone. Our study compares Ozone Production Regimes (OPRs) identified from both satellite observations and model simulations, using the ratio of tropospheric column formaldehyde to nitrogen dioxide (HCHO/NO2). We perform AQM simulations using CAMx for June-July-August 2016 over the Continental US (CONUS). We compare the model outputs against two versions of OMI NO2 data (KNMI's DOMINO QA4EVC and NASA-GSFC's MINDS retrievals) and two HCHO products (BIRA and NASA GSFC retrievals). Our analysis considers diurnal, rural-urban and altitudinal variations of OPRs, offering important insights for effective policy formulation. At the time of OMI overpass (~1:30 PM LT), ozone chemistry in most CONUS regions is NOx-limited, as indicated by HCHO/NO2 ratios of OMI and CAMx columns. Analysis of CAMx columns indicates that the HCHO/NO2 ratio varies with time of day and altitude with less NOx-limited conditions in the morning (10 AM LT) and in the planetary boundary layer (PBL). We highlight areas of the CONUS for which afternoon satellite measurements of HCHO/NO2 are not an accurate indicator of near-surface OPRs. Successful air quality regulations based on satellite observations targeting urban regions should consider the diurnal variations of surface OPRs and how well the satellites represent near-surface chemistry. Our results have implications for interpretation of TEMPO data, which will be available at nominally an hourly temporal resolution.
Indoor PM2.5 Exposure, Source Contribution and Related Health Risks During Haze and Non- haze Episodes in Dhaka Cantonment, Bangladesh: A Comparative Study
Authors: Nahian Samiha , Jeba Farah , Choudhury Tasrina Rabia , Begum Bilkis Ara , Salam Abdus
Published: March 2024

Haze is a common phenomenon during winter (December- February) in Dhaka, Bangladesh. Fine particulate matter or PM2.5 is considered the major component of haze. This study was conducted to evaluate the effect of haze on the concentration, chemical composition, source contribution and associated health risks of indoor PM2.5 in a residential home of Dhaka Cantonment, located at the center of Dhaka city. During haze, the 24- hour average indoor PM2.5 concentration was 139 ± 57.7 µgm-3, whereas that during non- haze period was 96.3 ± 17.7 µgm-3; both significantly exceeded the WHO guideline value (15 µgm-3). Despite the same indoor environment, haze- time PM2.5 concentration in Cantonment was 1.44 times higher than its non- haze counterpart. Mean I/O ratio (I/Ohaze= 0.92 and I/Onon- haze= 0.96) and strong positive correlation (R²haze= 0.89 and R2non- haze= 0.85) between indoor and outdoor PM2.5 suggested infiltration of polluted outdoor air into indoor environment. NOAA- HYSPLIT Backward Air Mass Trajectory Analysis indicated that north and northwestern air passing over the highly polluted Indo-Gangetic Plain (IGP) probably carried excessive air pollutants to Dhaka during winter, which might be responsible for creating haze and further increase of indoor PM2.5 level owing to infiltration. 24- hour gravimetric sampling of Indoor PM2.5 was carried out to quantify six heavy metals (Fe, Mn, Cu, Zn, Pb and Cr) by AAS analysis. Except Zn, haze- time concentration of all the heavy metals were 1.32 to 71.3 times higher than their non- haze concentrations. During haze, Pb (1022 ± 195 ngm-3) and Mn (693 ± 62.3 ngm-3) exceeded the WHO guideline values significantly. Enrichment factor analysis and source apportionment by Positive Matrix Factorization (PMF) revealed four sources of indoor PM2.5, namely- industrial emission (4.4%), crustal sources (17.6%), vehicular emission (44.6%) and fugitive lead (32.9%). Health risk assessment indicated that hazard index (HI) for children during haze period was 31.19, whereas that during non- haze period was 0.57 only. Moreover, haze- time HI for adults was 13.68, which was 29 times higher than its non- haze value (0.47). Hence, indoor PM2.5 exposure put children at much greater risk than the adults during haze, despite staying inside their home. Total cancer risk during haze and non- haze episodes exceeded the USEPA regulated target value (1 × 10-6). The total cancer risk during haze was 1.33 times higher than that during non- haze weather. Therefore, haze increased the probability of developing cancer from 1 in 2146 individuals to 1 in 1608 individuals. The hazard ratio (HR) during haze (9.25) and non- haze (6.42) period indicated severely compromised indoor air quality in the sampling household of Dhaka Cantonment, so effective measures should be adopted to control indoor air pollution.
Northern Peatland Vegetation Unfazed by Atmospheric Drought
Authors: Yuan Fenghui , Chen Ning , Wang Xianwei , Song Changchun , Xu Xiaofeng
Published: March 2024

While the prevailing narrative in most studies highlights global vegetation suppression due to increasing atmospheric drought, our investigation challenges this perspective, specifically in the case of northern peatlands. Through site-level manipulation experiments and a comprehensive multi-dataset synthesis, our study unveils the distinctive effects of increased vapor pressure deficit (VPD) on vegetation growth in northern peatlands, where the positive effects of VPD dominate. In northern peatlands under climate change, soil water availability and plant water use strategies emerge as key factors in these diverse impacts. Plants in these ecosystems thrive in moist soil-air environments, adopting an "open" water-use strategy characterized by relaxed stomatal regulation to optimize carbon uptake. Regional analysis confirms that the distinctive VPD effect is widespread in most northern peatlands, in contrast to global non-peatland areas where simultaneous warming and declining relative humidity result in vegetation suppression. This study contributes to reconcile the unique responses of northern peatlands to rising VPD, thereby enhancing our ability to accurately model and mitigate the impacts of climate change on these ecologically critical ecosystems.