Extreme Variability Research Articles

Development and evaluation of the modified and standardized rainfall anomaly indices for extreme variability analysis.

This study introduces two refined rainfall anomaly indices-the Modified Rainfall Anomaly Index (MRAI) and the Standardized Rainfall Anomaly Index (SRAI)-to address limitations in the traditional Rainfall Anomaly Index (RAI). The existing RAI struggles to effectively capture extreme wet and dry rainfall conditions and relies on a simplistic formulation. To evaluate these indices on a continental scale, data from the Integrated Multi-Satellite Retrievals for GPM (IMERG) was used for the Conterminous United States (CONUS), enabling scalability to ungaged locations and beyond. Additionally, daily annual maximum series (AMS) from 2,360 NOAA stations provided reference data to enhance the robustness of the analysis. IMERG data informed the MRAI and SRAI, while station data validated the RAI. Findings showed MRAI's kurtosis ranged from 0 to +0.9, consistently higher than SRAI and RAI, while SRAI exhibited a kurtosis range from -0.9 to -0.1. Median index ranges were -2 to 0 for SRAI, 0 to +2 for MRAI, and -1 to +1 for RAI. Comparing MRAI and RAI, performance metrics revealed average PRB of -23.5, RMSE of 0.93, MBR of 0.74, NSE of 0.82, and KGE of 0.53. For SRAI versus RAI, metrics showed PRB of -14.5, RMSE of 1.7, MBR of 0.8, NSE of 0.41, and KGE of 0.46. Spatially, MRAI effectively captured positive anomalies leaning toward wet extremes, while SRAI identified negative anomalies indicating dry extremes. These indices demonstrate significant potential for climate change studies, especially when applied together.

Modeling Return Levels of Non-Stationary Rainfall Extremes Due to Climate Change

Global warming increases evaporation and atmospheric water vapor, leading to more extreme events in both spatial and temporal domains. This study conducts a non-stationary extreme value analysis of the annual daily maximum at 36 meteorological stations over Iran from 1960 to 2021. We applied stationary and non-stationary Generalized Extreme Value (GEV) models within a Bayesian framework to estimate return levels for rainfall extremes, along with 90% confidence intervals. Our findings indicate that non-stationary models are not prominently evident based on AIC at most stations; however, non-stationary Generalized Extreme Value (GEV) models outperform stationary models based on RMSE and NSE evaluation criteria that sufficiently capture variations in extremes. Furthermore, most observed changes in extreme events exhibit a non-stationary pattern. Non-stationary analysis indicates that the frequency and severity of rainfall extremes have shown both increasing and decreasing trends, characterized by inconsistent spatial patterns.

Extreme Scale Height Variations and Nozzle Shocks in Warped Disks

Extreme Scale Height Variations and Nozzle Shocks in Warped Disks

Analysis of The Energy Impact of Electric Vehicle Integration in Uruguay

Objective: The objective of this study is to investigate the integration of EVs in Uruguay between 2025 and 2040, based on data from the National Energy Balance (BEN) and the 2005–2030 Energy Policies (PE0530) document, aiming to analyze the impacts of the increasing adoption of EVs on the country's electrical system.. Theoretical Framework: The methodology of this research is based on the development of scenarios derived from indicators of the electric sector, transport sector, population, and vehicle fleet. It is structured around new indicators that allow the comparison of energy demand increases under three EV adoption rates in Uruguay: natural (1%), moderate (3%), and accelerated (10%). Python programming was used to evaluate the extrapolations of these indicators through Simple Linear Regression (RLS) and Simple Exponential Smoothing (SES), determining the most appropriate methodology using Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) metrics. Data were collected from governmental websites in Uruguay and other publicly accessible domains. Method: The methodology adopted for this research comprises [concisely describe the study design, including approach, participants, instruments, procedures, etc.]. Data collection was carried out through [explain the specific methods used, such as interviews, questionnaires, observations, among others]. Results and Discussion: The results revealed that EV adoption generates increasing impacts on electrical demand, with 1% and 3% scenarios showing controlled impacts, while the 10% scenario demonstrates a significant increase, requiring strategic adaptations to avoid overloading the electrical system. Despite the usefulness of RLS and SES projection methodologies, their limitations lie in their sensitivity to extreme variations and reliance on historical data, which may hinder accuracy in contexts of rapid changes or unforeseen factors, such as future policies or technological advancements. Research Implications: This study presents practical and theoretical implications, highlighting Uruguay's need to invest in the expansion of the SIN and renewable sources to meet potential future EV demand, as well as to implement integrated policies for electric mobility. Theoretically, it reinforces the use of methodologies like RLS and SES for robust projections, influencing sectors such as the automotive industry, adapting to electrification, and the environmental sector, through emissions reductions, showcasing the impact of interdisciplinary approaches. Originality/Value: This study adds value by highlighting how different scenarios affect the SIN infrastructure of a country, especially one powered by 97% renewable energy sources. The approach can guide the formulation of future energy policies, assisting in infrastructure planning, setting renewable generation targets, and promoting electric mobility. By quantifying demands and benefits, this study provides input for strategic decisions, supporting sustainable energy transition and aligning public policies.

Ellagic Acid: A Green Multi-Target Weapon That Reduces Oxidative Stress and Inflammation to Prevent and Improve the Condition of Alzheimer's Disease.

Oxidative stress (OS), generated by the overrun of reactive species of oxygen and nitrogen (RONS), is the key cause of several human diseases. With inflammation, OS is responsible for the onset and development of clinical signs and the pathological hallmarks of Alzheimer's disease (AD). AD is a multifactorial chronic neurodegenerative syndrome indicated by a form of progressive dementia associated with aging. While one-target drugs only soften its symptoms while generating drug resistance, multi-target polyphenols from fruits and vegetables, such as ellagitannins (ETs), ellagic acid (EA), and urolithins (UROs), having potent antioxidant and radical scavenging effects capable of counteracting OS, could be new green options to treat human degenerative diseases, thus representing hopeful alternatives and/or adjuvants to one-target drugs to ameliorate AD. Unfortunately, in vivo ETs are not absorbed, while providing mainly ellagic acid (EA), which, due to its trivial water-solubility and first-pass effect, metabolizes in the intestine to yield UROs, or irreversible binding to cellular DNA and proteins, which have very low bioavailability, thus failing as a therapeutic in vivo. Currently, only UROs have confirmed the beneficial effect demonstrated in vitro by reaching tissues to the extent necessary for therapeutic outcomes. Unfortunately, upon the administration of food rich in ETs or ETs and EA, URO formation is affected by extreme interindividual variability that renders them unreliable as novel clinically usable drugs. Significant attention has therefore been paid specifically to multitarget EA, which is incessantly investigated as such or nanotechnologically manipulated to be a potential "lead compound" with protective action toward AD. An overview of the multi-factorial and multi-target aspects that characterize AD and polyphenol activity, respectively, as well as the traditional and/or innovative clinical treatments available to treat AD, constitutes the opening of this work. Upon focus on the pathophysiology of OS and on EA's chemical features and mechanisms leading to its antioxidant activity, an all-around updated analysis of the current EA-rich foods and EA involvement in the field of AD is provided. The possible clinical usage of EA to treat AD is discussed, reporting results of its applications in vitro, in vivo, and during clinical trials. A critical view of the need for more extensive use of the most rapid diagnostic methods to detect AD from its early symptoms is also included in this work.

Population genomics reveals strong impacts of genetic drift without purging and guides conservation of bull and giant kelp.

Kelp forests are declining in many parts of the northeast Pacific.1,2,3,4 In small populations, genetic drift can reduce adaptive variation and increase fixation of recessive deleterious alleles,5,6,7 but natural selection may purge harmful variants.8,9,10 To understand evolutionary dynamics and inform restoration strategies, we investigated genetic structure and the outcomes of genetic drift and purging by sequencing the genomes of 429 bull kelp (Nereocystis luetkeana) and 211 giant kelp (Macrocystis sp.) from the coastlines of British Columbia and Washington. We identified 6 to 7 geographically and genetically distinct clusters in each species. Low effective population size was associated with low genetic diversity and high inbreeding coefficients (including increased selfing rates), with extreme variation in these genetic health indices among bull kelp populations but more moderate variation in giant kelp. We found no evidence that natural selection is purging putative recessive deleterious alleles in either species. Instead, genetic drift has fixed many such alleles in small populations of bull kelp, leading us to predict (1) reduced within-population inbreeding depression in small populations, which may be associated with an observed shift toward increased selfing rate, and (2) hybrid vigor in crosses between small populations. Our genomic findings imply several strategies for optimal sourcing and crossing of populations for restoration and aquaculture, but these require experimental validation. Overall, our work reveals strong genetic structure and suggests that conservation strategies should consider the multiple health risks faced by small populations whose evolutionary dynamics are dominated by genetic drift.

Pervasive glacier retreats across Svalbard from 1985 to 2023.

A major uncertainty in predicting the behaviour of marine-terminating glaciers is ice dynamics driven by non-linear calving front retreat, which is poorly understood and modelled. Using 124919 calving front positions for 149 marine-terminating glaciers in Svalbard from 1985 to 2023, generated with deep learning, we identify pervasive calving front retreats for non-surging glaciers over the past 38 years. We observe widespread seasonal cycles in calving front position for over half of the glaciers. At the seasonal timescale, peak retreat rates exhibit a several-month phaselag, with changes on the west coast occurring before those on the east coast, coincident with regional ocean warming. This spatial variability in seasonal patterns is linked to different timings of warm ocean water inflow from the West Spitsbergen Current, demonstrating the dominant role of ice-ocean interaction in seasonal front changes. The interannual variability of calving front retreat shows a strong sensitivity to both atmospheric and oceanic warming, with immediate responses to large air and ocean temperature anomalies in 2016 and 2019, likely driven by atmospheric blocking that can influence extreme temperature variability. With more frequent blocking occurring and continued regional warming, future calving front retreats will likely intensify, leading to more significant glacier mass loss.

Interdecadal Variation of Springtime Compound Temperature‐Precipitation Extreme Events in China and Its Association With Atlantic Multidecadal Oscillation and Interdecadal Pacific Oscillation

AbstractThe concurrent occurrence of temperature and precipitation extremes, known as compound temperature‐precipitation extreme events (CTPEEs), leads to more pronounced consequences for human society and ecosystems than when these extremes occur separately. However, such compound extremes have not been sufficiently studied, especially during boreal spring. Spring is an important transition season, during which the CTPEEs plays a pivotal role in plant growth and revival of terrestrial ecosystems. This study investigates the spatio‐temporal variation characteristics of spring CTPEEs in China, including warm‐dry, warm‐wet, cold‐dry, and cold‐wet combinations. The compound cold‐wet extreme events occur most frequently, followed by warm‐dry, warm‐wet, and cold‐dry events. The frequency of CTPEEs associated with warm (cold) extremes shows a marked interdecadal increase (decrease) around the mid‐to‐late 1990s. It is found that the interdecadal change in CTPEEs is primarily determined by the variation in temperature extremes. This interdecadal shift coincides with the phase transitions of the Atlantic Multidecadal Oscillation (AMO) and the Interdecadal Pacific Oscillation (IPO). After the mid‐to‐late 1990s, the configuration of a positive AMO and a negative IPO excited atmospheric wave trains over mid‐high latitudes, causing high‐pressure and anticyclonic anomalies over East Asia. This leads to less cloudiness, allowing an increase in downward solar radiation, which enhances surface warming and contributes to an increase (decrease) in warm‐dry and warm‐wet extremes. The above observations are confirmed by the Pacemaker experiments. The results of this study highlight a significant contribution of internal climate variability to interdecadal changes in CTPEEs at the regional scale.

Spatio-temporal Variations of Heat Extremes across the Yangtze River Delta during 2001-2023 Based on Remotely Sensed Seamless Air Temperature.

Heat extremes become increasingly frequent and severe, posing adverse risks to public health and environment. Previous research on extreme heat mostly used meteorological observations or reanalysis data, which cannot well capture detailed spatial patterns. This study developed a seamless air temperature (Ta) dataset from remote sensing data to characterize the spatio-temporal variations of heat extremes in the Yangtze River Delta (YRD) from 2001 to 2023. First, the daily maximum Ta of cloud-free pixels was estimated through machine learning algorithms from MODIS land surface temperature (LST) and other remote sensing data. Then, gaps in the estimated Ta caused by cloud cover were filled using the Temporal Fourier Analysis (TFA) method, generating a seamless daily maximum Ta dataset. The remotely sensed Ta achieved an overall MAE of 1.11°C. Based on the remotely sensed Ta, six heat indices were calculated to characterize heat extremes, including heat days (HTD), effective accumulated high temperature (EAHT), heatwave frequency (HWF), cumulative heatwave days (HWD), maximum heatwave duration (HWMD) and average heatwave duration (HWAD). Heat extremes occurred frequently in the YRD, with obvious spatial variability. Southern basins experienced intense heat with high frequency and duration, while southern mountains and northern areas experienced weaker heat extremes. Urban areas have substantially more intense heat events than suburbs, attributed to urban heat island effect. 2022 recorded the most severe heat, with notable events also in 2013 and 2003. This study provides valuable insights into heat events in the YRD and serves as a reference for remote sensing research on heat events.

Improving Medication-Related Safety for Residents in Nursing Homes: A Qualitative Study.

To gain a better understanding of the perceptions of RNs on medication safety concerns and potential solutions for nursing home (NH) residents. This prospective, qualitative study used semi-structured phone interviews with a description approach. We used purposeful sampling to recruit 12 RNs employed at two NHs in the northeastern region of the United States. The Systems Engineering Initiative for Patient Safety constructs informed the interview guide, coding, and qualitative theme identification. We categorized non-user-friendly charting systems and gained insights into more experience with paper-based charting under the technology component. For the organization component, participants identified the importance of teamwork, communication, and leadership. Participants also mentioned how education and nationality of training impact medication administration (MA) safety. Task-related concerns revealed how different care approaches, extreme workload variation, and task prioritization during the day are perceived as critical issues that need to be addressed. Staff shortages were also expressed as an environment-related concern. Findings highlight the importance of appropriate nurse-to-patient ratio, the significance of user-friendly charting systems, and customizing the interface of MA in the charting system. [Journal of Gerontological Nursing, xx(xx), xx-xx.].

Capacity Planning (Capital, Staff and Costs) of Inpatient Maternity Services: Pitfalls for the Unwary.

This study investigates the process of planning for future inpatient resources (beds, staff and costs) for maternity (pregnancy and childbirth) services. The process of planning is approached from a patient-centered philosophy; hence, how do we discharge a suitably rested healthy mother who is fully capable of caring for the newborn baby back into the community? This demonstrates some of the difficulties in predicting future births and investigates trends in the average length of stay. While it is relatively easy to document longer-term (past) trends in births and the conditions relating to pregnancy and birth, it is exceedingly difficult to predict the future nature of such trends. The issue of optimum average bed occupancy is addressed via the Erlang B equation which links number of beds, average bed occupancy and turn-away. Turn-away is the proportion of times that there is not an immediately available bed for the next arriving inpatient. Data for maternity units show extreme and unexplained variation in turn-away. Economy of scale implied by queuing theory (and the implied role of population density) explains why many well intended community-based schemes fail to gain traction. The paper also addresses some of the erroneous ideas around the dogma that reducing length of stay 'saves' money. Maternity departments are encouraged to understand how their costs are calculated to avoid the trap where it is suggested by others that in reducing the length of stay, they will reduce costs and increase 'efficiency'. Indeed, up to 60% of calculated maternity 'costs' are apportioned from (shared) hospital overheads from supporting departments such as finance, personnel, buildings and grounds, IT, information, etc., along with depreciation charges on the hospital-wide buildings and equipment. These costs, known as 'the fixed costs dilemma', are totally beyond the control of the maternity department and will vary by hospital depending on how these costs are apportioned to the maternity unit. Premature discharge, one of the unfortunate outcomes of turn-away, is demonstrated to shift maternity costs into the pediatric and neonatal departments as 'boomerang babies', and then require the cost of avoidable inpatient care. Examples are given from the English NHS of how misdirected government policy can create unforeseen problems.

Quantifying Metagenomic Strain Associations from Microbiomes with Anpan.

Genetic and genomic variation among microbial strains can dramatically influence their phenotypes and environmental impact, including on human health. However, inferential methods for quantifying these differences have been lacking. Strain-level metagenomic profiling data has several features that make traditional statistical methods challenging to use, including high dimensionality, extreme variation among samples, and complex phylogenetic relatedness. We present Anpan, a set of quantitative methods addressing three key challenges in microbiome strain epidemiology. First, adaptive filtering designed to interrogate microbial strain gene carriage is combined with linear models to identify strain-specific genetic elements associated with host health outcomes and other phenotypes. Second, phylogenetic generalized linear mixed models are used to characterize the association of sub-species lineages with such phenotypes. Finally, random effects models are used to identify pathways more likely to be retained or lost by outcome-associated strains. We validated our methods by simulation, showing that we achieve more accurate effect size estimation and a lower false positive rate compared to alternative methodologies. We then applied our methods to a dataset of 1,262 colorectal cancer patients, identifying functionally adaptive genes and strong phylogenetic effects associated with CRC status, sometimes complementing and sometimes extending known species-level microbiome CRC biomarkers. Anpan's methods have been implemented as a publicly available R library to support microbial community strain and genetic epidemiology in a variety of contexts, environments, and phenotypes.

First acquiring articles in a second language: A new approach to the study of language and social cognition

Pragmatic phenomena are characterized by extreme variability, which makes it difficult to draw sound generalizations about the role of social cognition in pragmatic language by and large. I introduce cultural evolutionary pragmatics as a new framework for the study of the interdependence between language and social cognition, and point at the study of common-ground management across languages and ages as a way to test the reliance of pragmatic language on social cognition. I illustrate this new research line with three experiments on article use by second language speakers, whose mother tongue lacks articles. These L2 speakers are known to find article use challenging and it is often argued that their difficulties stem from articles being pragmatically redundant. Contrary to this view, the results of this exploratory study support the view that proficient article use requires automatizing basic socio-cognitive processes, offering a window into the interdependence between language and social cognition.

Concurrent Heat Extremes in Relation to Global Warming, High Atmospheric Pressure and Low Soil Moisture in the Northern Hemisphere

AbstractSummer heat extremes increasingly co‐occur worldwide, posing disastrous impacts on our society and the environment. However, the spatial pattern and underlying mechanisms of concurrent heat extremes remain unclear. We used a statistical framework to estimate the spatial concurrence strength of heat extremes in the Northern Hemisphere and identified their relationships to global warming, atmospheric circulation, and land‐atmosphere feedbacks. Concurrent heat extremes over different regions have significantly increased in the Northern Hemisphere from 1950 to 2023. Moreover, heat extremes show strong spatial concurrence strength, and the driving factors vary geographically. Global warming is responsible for long‐term increases in the frequency and strength of concurrent heat extremes, with most pronounced impact in tropical regions. In the absence of warming trends, the temporal and spatial variations in concurrent heat extremes are mainly caused by simultaneous high atmospheric pressure controlled by large‐scale circulations, particularly in mid‐latitude regions. While low soil moisture enhances regional heat extremes through land‐atmosphere feedbacks, it plays a minor role in driving concurrent heat extremes alone but can contribute in combination with high‐pressure anomalies. Given the ever‐increasing risks of heat extremes, our study underscores the importance of identifying the mechanisms of spatially concurrent heat extremes to improve prediction and mitigation of widespread heatwaves and their adverse impacts on socio‐economic sustainability and human well‐being.

Scale effects on suspended sediment and their response to extreme precipitation in karst basins.

Extreme precipitation is a crucial trigger for soil erosion events in karst regions. However, the existence of a scale effect in suspended sediment characteristics of karst basins and which extreme precipitation variables control this effect remain unclear. To investigate this, we analyzed the scale effect on suspended sediment characteristics using monthly hydrological data from five karst basins of varying scales, consistently monitored from 2012 to 2019. We aimed to clarify the contribution of extreme precipitation to suspended sediment and identify the dominant influencing factors. The results showed a significant negative exponential correlation between basin scale and sediment transport rate (STR). The phenomenon occurs due to two main reasons, first, the increased sediment transit distances with growing basin dimensions, leading to higher sedimentation; second, the unique dual hydrological structure of karst landscapes, which enhances subterranean leakage and further sedimentation. Furthermore, extreme precipitation was found played a crucial role in explaining STR variability, explaining approximately 56% to 78% of the observed variance in the five karst basins. Simultaneously, the dominant extreme precipitation factors affecting suspended sediment variability varied with basin scale. Specifically, heavy precipitation days, consecutive wet days, the rainstorm amounts and rainstorm days were identified as the main determinants. These variations are mainly attributed to the watershed's sensitivity to extreme precipitation events and its intrinsic attributes, including dual pathways, land use patterns, and geomorphological types, etc. This study provides theoretical insights into the increasing soil erosion caused by extreme precipitation in karst basins with different scales.

Novel KCNQ2 Variants Related to a Variable Phenotypic Spectrum Ranging from Epilepsy with Auditory Features to Severe Developmental and Epileptic Encephalopathies.

Pathogenic KCNQ2 variants are associated with neonatal epilepsies, ranging from self-limited neonatal epilepsy to KCNQ2-developmental and epileptic encephalopathy (DEE). In this study, next-generation sequencing was performed, applying a panel of 142 epilepsy genes on three unrelated individuals and affected family members, showing a wide variability in the epileptic spectrum. The genetic analysis revealed two likely pathogenic missense variants (c.1378G>A and c.2251T>G) and the already-reported pathogenic splice site (c.1631+1G>A) in KCNQ2 (HGNC:6296). The phenotypes observed in the affected members of family 1, which shared the c.2251T>G variant, were epilepsy with auditory features (EAFs), focal epilepsy, and generalized epilepsy, and none of them suffered from neonatal seizures. The gene panel contained further genes related to EAFs (LGI1, RELN, SCN1A, and DEPDC5), which were tested with negative results. The phenotypes observed in family 2 members, sharing the splice site variant, were neonatal seizures and focal epilepsy in childhood. The last unrelated proband, harboring the de novo missense c.1378G>A, presented a clinical phenotype consistent with DEE. In conclusion, we identified two unreported KCNQ2 variants, and report a proband with EAFs and individuals without typical KCNQ2 neonatal seizures. Our study underscores the extreme variability in the phenotypic spectrum of KCNQ2-related epilepsies and unveils the prospect of its inclusion in screening panels for EAFs.

Elliptical Fourier analysis of molar outlines in Late Pliocene Parapapio whitei from Makapansgat Limeworks, South Africa

Introduction: Alongside Australopithecus africanus at Makapansgat South Africa, dated to nearly 3 million years before present, are remnants of Parapapio (Cercopithecinae). The extreme variability of this fossil assemblage has stymied efforts to specify the taxon parameters for Parapapio, which are attributed to at least three species. Study aims: The first maxillary molar occlusal outlines of the two most complete fossils attributed to Parapapio whitei are compared. The degree of group cohesion in Parapapio whitei is evaluated using three extant cercopithecoid taxa. Methods and Materials: The fossil crania from Makapangsat Members 3–4, MP 221 and MP 223, both referred to Parapapio whitei, are compared to three extant cercopithecoid taxa including Cercocebus agilis (n=8), Colobus angolensis (n=8) and Papio anubis (n=8). Molar shape is captured using elliptical Fourier analysis of occlusal outlines and molar size dimensions are estimated from measuring software. Results: MP 223 is larger than MP 221 in occlusal area and the minimum buccolingual length of M1 although the variability between the two Parapapio whitei fossils is commensurate with that observed in Papio anubis. MP 221 and MP 223 are more similar to one another in occlusal outline shape than to any other taxon. However, MP 223 falls consistently closer to Papio anubis whereas MP 221 resembles Papio anubis in some respects and Cercocebus agilis in others. Conclusion: MP 221 and MP 223 likely belong to a single species with no clear affinity to any of the extant taxa examined. The differences in molar size characterizing Parapapio whitei, a terrestrial forager, is potentially indicative of male bimaturatism or ecological variability which may also characterize Australopithecus africanus at Makapansgat.

Discovering Climate Change during the Early 21st Century via Wasserstein Stability Analysis

Climate change is an essential topic in climate science, and the accessibility of accurate, high-resolution datasets in recent years has facilitated the extraction of more insights from big-data resources. Nonetheless, current research predominantly focuses on mean-value changes and largely overlooks changes in the probability distribution. In this study, a novel method called Wasserstein Stability Analysis (WSA) is developed to identify probability density function (PDF) changes, especially the extreme event shift and nonlinear physical value constraint variation in climate change. WSA is applied to the early 21st century and compared with traditional mean-value trend analysis. The results indicate that despite no significant trend, the equatorial eastern Pacific experienced a decline in hot extremes and an increase in cold extremes, indicating a La Niña-like temperature shift. Further analysis at two Arctic locations suggests sea ice severely restricts the hot extremes of surface air temperature. This impact is diminishing as the sea ice melts. By revealing PDF shifts, WSA emerges as a powerful tool to re-examine climate change dynamics, providing enhanced data-driven insights for understanding climate evolution.

Soil microbiome interventions for carbon sequestration and climate mitigation.

Mitigating climate change in soil ecosystems involves complex plant and microbial processes regulating carbon pools and flows. Here, we advocate for the use of soil microbiome interventions to help increase soil carbon stocks and curb greenhouse gas emissions from managed soils. Direct interventions include the introduction of microbial strains, consortia, phage, and soil transplants, whereas indirect interventions include managing soil conditions or additives to modulate community composition or its activities. Approaches to increase soil carbon stocks using microbially catalyzed processes include increasing carbon inputs from plants, promoting soil organic matter (SOM) formation, and reducing SOM turnover and production of diverse greenhouse gases. Marginal or degraded soils may provide the greatest opportunities for enhancing global soil carbon stocks. Among the many knowledge gaps in this field, crucial gaps include the processes influencing the transformation of plant-derived soil carbon inputs into SOM and the identity of the microbes and microbial activities impacting this transformation. As a critical step forward, we encourage broadening the current widespread screening of potentially beneficial soil microorganisms to encompass functions relevant to stimulating soil carbon stocks. Moreover, in developing these interventions, we must consider the potential ecological ramifications and uncertainties, such as incurred by the widespread introduction of homogenous inoculants and consortia, and the need for site-specificity given the extreme variation among soil habitats. Incentivization and implementation at large spatial scales could effectively harness increases in soil carbon stocks, helping to mitigate the impacts of climate change.

Contribution of the GRACE Satellite Mission to Mapping Water Mass Variations in River Basins

Abstract. In the context of climate change, there is a need to understand the dynamics and temporal fluctuations of continental water. Such knowledge is essential for the development of more effective and sustainable management strategies for this indispensable resource. The Earth's gravitational field is not constant but varies over time due to factors such as mass redistribution during the hydrological cycle. The GRACE satellite mission (Gravity Recovery and Climate Experiment) provides valuable information about the geodynamic behaviour of our planet by estimating variations in the continental water storage from the temporal changes in the Earth’s gravity field.The aim of this work is to demonstrate the contribution of satellite gravimetry to identify patterns of variation in continental water masses within large river basins. For this purpose, a regional study of the TWS (Total Water Storage) derived from GRACE was carried out, focusing on the spatial and temporal changes detected in the La Plata Basin in South America. The periods with the most extreme variations between 2019 and 2023 were analyzed, and the TWS was compared with satellite precipitation data, to subsequently relate them to ENSO events that occurred in the region. The results show that GRACE detected the significant changes in water storage, highlighting in particular the severe drought that occurred in this basin in 2022.