Atmospheric Moisture Research Articles

Drought and radiation explain fluctuations in Amazon rainforest greenness during the 2015–2016 drought

Abstract. The 2015–2016 Amazon drought was characterized by below-average regional precipitation for an entire year, which distinguishes it from the dry-season-only droughts in 2005 and 2010. Studies of vegetation indices (VIs) derived from optical remote sensing over the Amazonian forests indicated three stages in canopy response during the 2015–2016 drought, with below-average greenness during the onset and end of the drought, and above-average greenness during the intervening months. To date, a satisfactory explanation for this broad temporal pattern has not been found. A better understanding of rainforest behaviors during this unusually long drought should help predict their response to future droughts. We hypothesized that negative VI anomalies could be caused by water and heat stress exceeding the tolerance ranges of the rainforest. To test our hypothesis, based on monthly observations of terrestrial water storage (TWS), land surface temperature (LST), and vapor pressure deficit (VPD) for January 2003 to December 2016, we proposed an approach to categorize regions into two groups: (1) those exceeding normal hydrological and thermal ranges and (2) those within normal ranges. Accordingly, regions exceeding normal ranges during different stages of the 2015–2016 event were delineated. The results showed a gradual southward shift in these regions: from the northeastern Amazon during August to October 2015 to the north–central part during November 2015 to February 2016 and finally to the southern Amazon in July 2016. Over these regions exceeding normal ranges during droughts, negative VI anomalies were expected, irrespective of radiation anomalies. Over the regions within normal ranges, VI anomalies were assumed to respond positively to radiation anomalies, as is expected under normal conditions. We found that our proposed approach can explain more than 70 % of the observed spatiotemporal patterns in VI anomalies during the 2015–2016 drought. These results suggest that our “exceeding normal ranges”-based approach combining (i) water storage, (ii) temperature, and (iii) atmospheric moisture demand drivers can reasonably identify the most likely drought-affected regions at monthly to seasonal timescales. Using observation-based hydrological and thermal condition thresholds can help with interpreting the response of the Amazon rainforest to future drought events.

Reversible wettability of thermally treated Hanji decorated with supersonically sprayed ZnO nanoparticles

In this study, we aimed at transforming naturally superhydrophilic Hanji, a traditional Korean Han paper into its superhydrophobic version. This change is crucial for applications requiring water damage resistance, such as mold growth, abrasion, and degradation. The resulting superhydrophobic Hanji shows potential for diverse applications, including fabricating wallpaper, traditional window covers, and high-end wrapping paper. To achieve this, ZnO nanoparticles (NPs) were deposited on the surface of Hanji via supersonic spraying, resulting in morphological curvatures capable of accommodating nanoscale air pockets. Additionally, supersonic spraying facilitated the robust adhesion of ZnO NPs to the Hanji cellulose fibers. Notably, the hydroxyl groups from both ZnO and Hanji were removed through subsequent annealing, resulting in superhydrophobic ZnO-Hanji. The annealing-induced shrinkage and densification of Hanji enhanced its superhydrophobicity, a property not achieved using regular A4 paper. This substantiated the unique benefits of using Hanji to realize superhydrophobicity. The superhydrophobicity reverted to superhydrophilicity upon exposure to ultra-violet irradiation, initiating reactions of the –OH group from atmospheric moisture with electron–hole pairs on the ZnO surfaces. Consequently, tunable/reversible wettability of ZnO-decorated Hanji was achieved via simple supersonic spraying and annealing, without any chemical modifications.

Changes in Mesoscale Convective System Precipitation Structures in Response to a Warming Climate

AbstractMesoscale convective systems (MCSs) are crucial components of the hydrological cycle and often produce flash floods. Given their impact, it is important to understand how they will change under a warming climate. This study uses a satellite‐ and radar‐based MCS tracking algorithm on convection‐permitting climate model simulations and examines changes in MCS properties and precipitation structures between historical and future simulations. An underestimation in MCS total precipitation is evident in historical simulation compared to observations, due to model's depiction of MCS precipitation area and summertime occurrence frequency. Under pseudo‐global warming, increases in MCS frequency and total warm season precipitation are observed, most notably in the southern U.S. The precipitation intensity and precipitating area generated by future MCSs also rises and results in an increase in precipitation volume. MCS precipitation structures are further classified into convective core and stratiform regions to understand how change in these structures contributes to future rainfall changes. In a warmer climate, the stratiform region demonstrates minimal change in size, but increases in mean precipitation rate and mean maximum precipitation rate by 15% and 29% are noted, respectively. A more robust future response is observed in the convective core region, with its size, mean precipitation rate and mean maximum precipitation rate increasing significantly by 24%, 37% and 42%, respectively. Finally, by examining the environmental properties of MCS initial condition, future intensification of convective rain may be attributed to a combined effect of substantial increases in atmospheric instability and moisture availability.

Global Climatology of Low‐Level‐Jets: Occurrence, Characteristics, and Meteorological Drivers

AbstractLow‐level jets (LLJs), vertical profiles with a wind speed maxima in the lowest hundred meters of the troposphere, have multiple impacts in the Earth system, but a global present‐day climatology based on contemporary data does not exist. We use the spatially and temporally complete data set from ERA5 reanalysis to compile a global climatology of LLJs for studying the formation mechanisms, characteristics, and trends during the period of 1992–2021. In the global mean, LLJs are detected 21% of the time with more cases over land (32%) than over the ocean (15%). We classified the LLJs into three categories: non‐polar land (LLLJ), polar land (PLLJ), and coastal (CLLJ) LLJs. For LLLJ, the averaged frequency of occurrence is 20% and 75% of them are associated with a near‐surface temperature inversion as a prerequisite for an inertial oscillation. PLLJs are also associated with a temperature inversion and occur even more frequently with 59% of the time. These are also the lowest and the strongest LLJs among the three categories. CLLJs are particularly frequent in some marine hotspots, situated along the west coast of continents, with neutral to unstable stratification close to the surfaces and a stably stratified layer aloft. We found distinct regional trends in both the frequency and intensity of LLJs over the past decades, which can have implications for the emission and transport of aerosols, and the transport of atmospheric moisture. Future studies could address changes in LLJs and the associated implications in more detail, based on the here released ERA5‐based LLJ data.

Charge Transfer and Ion Occupation Induced Ultra‐Durable and All‐Weather Energy Generation from Ambient Air for Over 200 Days

AbstractThe notion of spontaneous and persistent energy generation from omnipresent atmospheric moisture presents an alluring prospect in the realm of next‐generation energy sources. Here, an ultra‐durable and all‐weather energy generator (UAEG) predicated on interface‐induced proton migration derived from enhanced proton dissociation by charge transfer and ion occupation is reported, which reduces the diffusion barrier of protons in chromatogram‐like mass transfer by avoiding the rebinding of dissociated protons with charged polyelectrolyte chains, thus leading to efficient and continuous proton migration through heterogeneously hygroscopic interface and delivering ultra‐durable direct‐current output. Deep insight into underlying mechanisms is demonstrated by theoretical calculations and in situ investigations toward molecular interactions and charge distribution. A UAEG unit with 4 cm2 in size can generate an impressive electric output (0.88 V and 37.58 µA) across extensive relative humidity (10–90%) and ambient temperature (−30–50 ˚C), capable of generating energy in all‐weather conditions (e.g., sunny, cloudy, overcast, and rainy) regardless of day and night. Importantly, it is the first time that a commercial electronic is continuously driven for over 200 days in all‐weather conditions just depending on ambient moisture. This work provides a novel perspective for the development of ultra‐durable and all‐weather moisture‐enabled energy generators.

Experimental methods in chemical engineering: Karl Fischer titration

AbstractKarl Fischer titration (KF) measures the water content in organic and inorganic compounds. Water reacts with a titrant solution containing iodine and a sulphurous monoalkyl ester to produce a monoalkyl sulphate ester and HI. In volumetric titrators, a burette injects the titrant directly into a cell while coulometric titrators generate titrant in situ. Regardless of the volume of the sample, volumetric titration is limited to 100 mg, while coulometric titration is best suited for . KF is fast (), considered accurate (), and precise (). However, factors such as humidity, non‐standard analytes (hexane, isopropanol, ethylene glycol), tritrant composition, and temperature compromise its repeatability: the % sample standard deviation, (), varied from 2% to 60% (). This high variability is, in part, due to the experimental design that included samples and conditions ill‐suited for the technique. However, even for the tests for which KF is suitable, . Certain compounds react with the titrant, which increases the variability. The main sources of error affecting the analysis are ambient moisture, pH, solvent, sample handling, and titration speed. As of 2023, the Web of Science has indexed 1332 articles with Karl Fischer as a key word (Topic), but more than 3600 mentioning the technique (All fields). A bibliometric analysis classifies these contributions into five clusters: spectroscopy, stability, temperature, solubility, and mixtures.

Exploring vertical gradients of radio refractivity and their significance for radio wave propagation in Abuja, Jos and Makurdi of North-Central Nigeria

Vertical radio refractivity gradients are essential for monitoring propagation conditions when designing and planning terrestrial radio links for communications in the lower atmosphere. Average data gathered from meteorological factors such as temperature, pressure, and relative humidity was used from 1980 to 2020 n this study. This study focuses on the vertical gradient of radio refractivity within the lower atmospheric layer, investigating its influence on factors like signal propagation, route clearance, and line-of-sight communication. The analysis encompasses three cities - Abuja, Makurdi, and Jos. In Figure 2 monthly average changes in the refractivity gradient are presented for Abuja. In addition, the seasonal radio refractivity gradient shows mean values of -110.000N/km for Abuja which shows that the refractivity condition is Super-Refraction, -77.553N/km for Jos which shows that the refractivity condition is Normal-Refraction and -97.209N/km for Makurdi which shows that the refractivity condition is Normal-Refraction respectively. Higher gradient values, G1, G2, and G3 were observed during the dry season (December-February) which could be attributed to dry air and steeper refractivity gradients. In contrast, lower gradient values were observed during the wet season (June-October) due to increased atmospheric moisture. Similarly, measured vertical radio refractivity gradient data, G1 N/km, G2 N/km, and G3 N/km for Jos displayed consistent fluctuations throughout the year. Similarly, measured vertical radio refractivity gradient data, G1 N/km, G2 N/km, and G3 N/km for Jos displayed consistent fluctuations throughout the year. Notably, wetter months exhibit higher refractivity gradient values, while drier months show lower values. G2 consistently records the highest gradient values, and despite varying magnitudes, the trends remain consistent. Finally, measured vertical radio refractivity gradient data, G1 N/km, G2 N/km, and G3 N/km for Makurdi indicate distinct fluctuations with the most negative values observed in November and December. The Dry Season witnesses relatively lower gradient values, while the Transition and Wet Seasons experience rising values, influenced by atmospheric shifts. The Higher negative values during the wet season suggest pronounced variations in the refractive index, affecting radio wave propagation. These findings emphasize the significance of refractivity gradient variations and their implications for radio wave behaviour particularly during different seasons.

The Role of Atmospheric Stabilities and Moisture Convergence in the Enhanced Dry Season Precipitation over Land from 1979 to 2021

Abstract Between 1979 and 2021, global ocean regions experienced a decrease in dry season precipitation, while the trend over land areas varied considerably. Some regions, such as southeastern China, the Maritime Continent, eastern Europe, and eastern North America, showed a slight increasing trend in dry season precipitation. This study analyzes the potential mechanisms behind this trend by using the fifth major global reanalysis produced by ECMWF (ERA5) data. The analysis shows that the weakening of downward atmospheric motions played a critical role in enhancing dry season precipitation over land. An atmospheric moisture budget analysis revealed that larger convergent moisture fluxes lead to an increase in water vapor content below 400 hPa. This, in turn, induced an unstable tendency in the moist static energy profile, leading to a more unstable atmosphere and weakening downward motions, which drove the trend toward increasing dry season precipitation over land. More water vapor in the low troposphere is because of higher moisture convergence and moisture transport from ocean to land regions. In summary, this study demonstrates the intricate elements involved in altering dry season rainfall trends over land, which also emphasizes the importance of comprehending the spatial distribution of the wet-get-wetter and dry-get-drier paradigm. Significance Statement This study found that global land precipitation during the dry season slightly increased from 1979 to 2021, while precipitation over oceans declined. Moist static energy analysis showed a trend toward less stability in areas with increased dry season precipitation and the opposite trend in regions with declining precipitation. Water vapor content trends and dynamic components were the primary controlling mechanism for precipitation trends. Furthermore, the hotspots with pronounced increases or decreases in dry season precipitation reflect local circulation changes influenced by anthropogenic or natural factors.

Fungal Hyphae on the Assimilation Branches Are Beneficial for Haloxylon ammodendron to Absorb Atmospheric Water Vapor: Adapting to an Extreme Drought Environment.

Research on endophytic fungi in desert plants, particularly the epiphytic or endophytic fungi of leaves, remains limited. In the extremely arid regions of northwest China, the ultra-xerophytic desert plant Haloxylon ammodendron harbors white fungi on its assimilating branches during autumn. The hyphae of these fungi intertwine, both internally and externally, comprising superficial, bridging, and endophytic types. The superficial hyphae attach to the surface of the assimilating branches and continuously grow and intersect, forming a thick layer of felt-like hyphae. This thick, felt-like layer of hyphae facilitates the adsorption of atmospheric water vapor on the surface of the hyphae or the assimilating branches, allowing H. ammodendron to capture atmospheric moisture, even under low humidity. Some superficial hyphae penetrate the cuticle into the epidermis, becoming bridging hyphae, which can rapidly transport water from the outside of the epidermis to the inside. The endophytic hyphae shuttle within the epidermis, achieving rapid water transfer within the epidermis of the assimilating branches. The presence of these three types of hyphae not only enables the assimilating branches of H. ammodendron to achieve rapid water absorption and transmission, but also facilitates the uptake of atmospheric water vapor under low humidity conditions. We discuss the mechanism by which the hyphae promote water absorption from the perspectives of hyphal composition, the formation of felt-like structures, and environmental conditions. We consider the presence of fungal hyphae on the surface of the H. ammodendron assimilating branches as an inevitable ecological process in arid environments. This study provides important theoretical insights into the mechanisms underlying the strong drought resistance of desert plants in extremely arid regions and offers strategies for desertification control.

Determination of Transport Pathways and Mutual Exchanges of Atmospheric Moisture between Source Regions of Yangtze and Yellow River Basins

Knowledge of the quantitative importance of the moisture transport pathways and mutual moisture exchange of the source regions of the Yangtze (SYZR) and Yellow (SYR) rivers’ basins, the adjacent origins of China’s two longest rivers, can provide insights into the regional atmospheric branch of the hydrological cycle over the source regions. The method with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and a Lagrangian moisture source diagnostic to identify the major moisture transport pathways quantifies their importance to two types of daily precipitation events—daily precipitation more than 10 mm (PM) events and daily precipitation less than 10 mm (PL) events—for the two rivers’ regions during the summer (June–August, 1986–2015) and finds the characteristics of mutual moisture exchange. The results indicated that both the Bay of Bengal group pathway and the northwest China group pathway play significant roles in PM and PL events over the SYZR, contributing 41.87% and 39.12% to PM events and 41.33% and 33.16% to PL events, respectively. The SYR has five main moisture path groups; the Bay of Bengal group pathway, the northwest China group pathway, and the southeast China group pathway play significant roles in PM and PL events over the SYR, contributing 32.34%, 23.28%, and 34.36% to PM events and 34.84%, 36.18%, and 19.83% to PL events, respectively. The volume of moisture passing from the SYZR to the SYR is approximately 60 times that of the reverse, constituting about 6.9% of the total moisture released in SYR precipitation. It is worth noting that the moisture release was concentrated in the nearer west group pathway, and the main moisture uptake locations were beyond the source region of the two rivers (remote sources) in the PM events. The aggregate moisture release high-frequency moisture transport path groups are found in the southeastern parts of Zhiduo County and the southeast of Zaduo County.

HiMIC-Monthly: A 1 km high-resolution atmospheric moisture index collection over China, 2003–2020

Near-surface atmospheric moisture is a key environmental and hydro-climatic variable that has significant implications for the natural and human systems. However, high-resolution moisture data are severely lacking for fine-scale studies. Here, we develop the first 1 km high spatial resolution dataset of monthly moisture index collection in China (HiMIC-Monthly) over a long period of 2003~2020. HiMIC-Monthly is generated by the light gradient boosting machine algorithm (LightGBM) based on observations at 2,419 weather stations and multiple covariates, including land surface temperature, vapor pressure, land cover, impervious surface proportion, population density, and topography. This collection includes six commonly used moisture indices, enabling fine-scale assessment of moisture conditions from different perspectives. Results show that the HiMIC-Monthly dataset has a good performance, with R2 values for all six moisture indices exceeding 0.96 and root mean square error and mean absolute error values within a reasonable range. The dataset exhibits high consistency with in situ observations over various spatial and temporal regimes, demonstrating broad applicability and strong reliability.

Potential valorization and transformation of plastic biomass waste into useful fertilizers in agricultural Mediterranean soils under extreme climate conditions

Plastics are widely used in agricultural practices, although recently they have been recognized as a new emerging risk in soils. Polyethylene (PE), is commonly used by farmers to cover agricultural practices; geotextile, is used mainly for ground and crop covering; and polyvinyl chloride (PVC) is considered the main material contained in irrigation hoses. The present study aimed to assess the effects of three plastics (polyethylene, geotextile, polyvinyl chloride) on the soils’ fertility. Several pot experiments were conducted in soil samples from the study area (Thessaly) contaminated with adequate amounts of each plastic type (PE, geotextile: 2% v/v and PVC: 5% v/v). Water was added in two quantities: one to maintain typical soil moisture levels according to the crops’ requirements and an elevated amount to form supersaturating soil conditions similar to those following a flood event. Furthermore, temperature effect was also investigated to assess its impact on plastics’ behavior and soil fertility. The levels of all nitrogen forms and the microbial activity were determined at 10, 30, and 60 days. Significant changes were observed in the concentrations of nitrate, nitrite, and ammonium ions under ambient soil moisture conditions especially when the microplastics were incubated for a longer period. PE addition resulted in greater changes, followed by geotextile, although PVC addition did not induce significant changes in the nitrification process during the experimental time. PE and geotextile microplastics appeared to enhance microbial colonization and total microbial activity. In addition, soil characteristics were notably altered when moisture stress conditions were reached (85%) and when soils were flooded for two months, leading to a severe decrease in the availability of all nitrogen forms. The results showed that alterations in soil nitrogen forms in the presence of plastics study are crucial for maintaining the health and improving the productivity of Mediterranean soils.

In situ microbial bioremediation of obsolete pesticides at their disposal sites

Soil pollution by pesticides is a global problem in many countries, including Kyrgyzstan. Currently, 50 storage facilities for obsolete banned pesticides exist, severely threatening the surrounding populations and environment. In this study, in situ bioremediation technology was used to remove pesticide contamination from soil around the storage facilities. Three conditions were tested: application of fertile soil and bioproduct, application of fertile soil and no bioproduct (Control 1), and application of fertile soil and no bioproduct (Control 2). An aerobic bioremediation approach was used: the treatment was applied directly to the contaminated soil. For the bioaugmentation, three selected active degrading bacterial species were used: Stenotrophomonas sp. (Ps-B strain), L. fusiformis (SA-4 strain) and E. cloacae (SB-2 strain). Regular aeration, loosening and watering were performed during the subsequent months to create the conditions required to activate the local microflora and the degrading activity of the bacterial species in the bioproduct. The bioproduct of three active bacteria species has demonstrated a high pesticide decomposition effect. The pesticides were degraded from 85.6 to 99.0 ± 0.05% within six months of initiating the bioremediation process. The efficiency of the degradation process depended on optimum atmospheric conditions, that is, temperature, pH, and moisture content of the soil. Our study recommends using the agrotechnical and biotechnological approach for moderately pesticide-polluted soils and pesticide storage areas.

Optimal utilization of waste wool: Preparation of bionic moisture-absorbing keratin membrane with hierarchical porous structure to harvest atmospheric moisture

In addressing the challenge of water scarcity, solar-assisted atmospheric water harvesting (SAWH) has emerged as a promising strategy. Here, we have designed a hierarchical regenerated wool keratin membrane (LiCl@CNMC) that mimics the natural Murray network. Carbon nano tube, serving as solar absorbers, are uniformly deposited on the hierarchical keratin membrane. Hygroscopic salt LiCl is impregnated into the keratin membrane to achieve exceptional water uptake capacity. Under simulated sunlight exposure, the surface temperature can reach 83.5 °C. Furthermore, the LiCl@CNMC membrane exhibits outstanding water absorption (0.79–2.67 g g−1) and desorption performance at 30–80 % RH. The bionic water-collecting membrane can carry out 12 adsorption–desorption cycles every day under outdoor conditions, and yielding 11.92 g g−1 day−1 of clean water. The design of regenerated keratin membrane not only provides a direct way for the regeneration and utilization of keratin materials, but also provides valuable guidance and inspiration for the preparation and application of natural polymers found.

Changes in moisture sources contributed to the onset and development of the 2017-2019 southeast Australian drought

In 2017-2019 southeast Australia experienced one of its most severe droughts since 1900. Rainfall over the region encompassing the Murray-Darling Basin was consistently below average for three consecutive cool seasons, an unprecedented event on record. A strong positive Indian Ocean Dipole event has been previously suggested to have intensified the conditions of the drought in 2019, however the state of the climate drivers cannot fully explain the onset and development of this drought. In this study, we adopt a different approach to investigate processes other than remote climate drivers that may have triggered the drought. Using a Lagrangian model to identify moisture sources to the Murray Darling Basin, we show that local processes were crucial in explaining the onset and development of the drought. We identify the oceanic and terrestrial sources of atmospheric moisture over the Murray Darling Basin and show for the first time a significant decline in rainfall moisture supply from the Tasman Sea in 2017 and 2018. We further show that anomalous atmospheric circulation transported the expected moisture northward toward the Maritime Continent. Our results provide an explanation for the moisture and rainfall deficit that caused the 2017-19 southeast Australian drought. Understanding the processes that led to the 2017-2019 drought is an important step towards improved predictions and planning for future multi-year droughts in Australia.

Bayesian Non-Parametric Inference for Multivariate Peaks-over-Threshold Models.

We consider a constructive definition of the multivariate Pareto that factorizes the random vector into a radial component and an independent angular component. The former follows a univariate Pareto distribution, and the latter is defined on the surface of the positive orthant of the infinity norm unit hypercube. We propose a method for inferring the distribution of the angular component by identifying its support as the limit of the positive orthant of the unit p-norm spheres and introduce a projected gamma family of distributions defined through the normalization of a vector of independent random gammas to the space. This serves to construct a flexible family of distributions obtained as a Dirichlet process mixture of projected gammas. For model assessment, we discuss scoring methods appropriate to distributions on the unit hypercube. In particular, working with the energy score criterion, we develop a kernel metric that produces a proper scoring rule and presents a simulation study to compare different modeling choices using the proposed metric. Using our approach, we describe the dependence structure of extreme values in the integrated vapor transport (IVT), data describing the flow of atmospheric moisture along the coast of California. We find clear but heterogeneous geographical dependence.

Detecting Nonadditive Biotic Interactions and Assessing Their Biological Relevance among Temperate Rainforest Trees.

AbstractInteractions between and within abiotic and biotic processes generate nonadditive density-dependent effects on species performance that can vary in strength or direction across environments. If ignored, nonadditivities can lead to inaccurate predictions of species responses to environmental and compositional changes. While there are increasing empirical efforts to test the constancy of pairwise biotic interactions along environmental and compositional gradients, few assess both simultaneously. Using a nationwide forest inventory that spans broad ambient temperature and moisture gradients throughout New Zealand, we address this gap by analyzing the diameter growth of six focal tree species as a function of neighbor densities and climate, as well as neighbor × climate and neighbor × neighbor statistical interactions. The most complex model featuring all interaction terms had the highest predictive accuracy. Compared with climate variables, biotic interactions typically had stronger effects on diameter growth, especially when subjected to nonadditivities from local climatic conditions and the density of intermediary species. Furthermore, statistically strong (or weak) nonadditivities could be biologically irrelevant (or significant) depending on whether a species pair typically interacted under average or more extreme conditions. Our study highlights the importance of considering both the statistical potential and the biological relevance of nonadditive biotic interactions when assessing species performance under global change.

Monitoring and Detecting Plant Diseases Using Cloud-Based Internet of Things

The farming field is currently going through an upheaval as a consequence of the Internet of Things (IoT), which is offering farmers a respectable spectrum of tackles that include precision and sustainable agriculture for confronting problems within the industry. IoT technology is used to obtain data on ambient conditions which include soil moisture, air temperature, and atmospheric moisture that are advantageous to the enhancement of the various microorganisms and the propagation of farm-related problems. Farmers' ambition to connect through their farms from any location around the globe at any time is fostered by IoT. Wirelessly connected devices record the situation of the farm, and microcontrollers are implemented to automate and regulate farm operations so that conditions may be observed remotely. Farmers can leverage IoT on their mobile devices to be warned about the ongoing state of their cultivated land at any time and at nearly any point across the world. IoT technology can help traditional farming become more profitable while lowering the hurdles it faces. Farmers possess real-time access to the details, which allows them to determine a health condition that originates from favorable ambient conditions. Farmers subsequently become professionals at sustaining the ecosystems of their crops. Furthermore, farming industries necessitate greater numbers of workers and more staff people. Unfortunately, a rising number of human beings are departing the agriculture industry, which has rendered the lack of employees severe. As an outcome, intelligent agricultural technologies are essential in agriculture to shrink the amount of workforce demanded while providing the rising requirements imposed by rising populations.

Extremes of summer Arctic sea ice reduction investigated with a rare event algorithm

Various studies identified possible drivers of extremes of Arctic sea ice reduction, such as observed in the summers of 2007 and 2012, including preconditioning, local feedback mechanisms, oceanic heat transport and the synoptic- and large-scale atmospheric circulations. However, a robust quantitative statistical analysis of extremes of sea ice reduction is hindered by the small number of events that can be sampled in observations and numerical simulations with computationally expensive climate models. Recent studies tackled the problem of sampling climate extremes by using rare event algorithms, i.e., computational techniques developed in statistical physics to reduce the computational cost required to sample rare events in numerical simulations. Here we apply a rare event algorithm to ensemble simulations with the intermediate complexity coupled climate model PlaSim-LSG to investigate extreme negative summer pan-Arctic sea ice area anomalies under pre-industrial greenhouse gas conditions. Owing to the algorithm, we estimate return times of extremes orders of magnitude larger than feasible with direct sampling, and we compute statistically significant composite maps of dynamical quantities conditional on the occurrence of these extremes. We find that extremely low sea ice summers in PlaSim-LSG are associated with preconditioning through the winter sea ice-ocean state, with enhanced downward longwave radiation due to an anomalously moist and warm spring Arctic atmosphere and with enhanced downward sensible heat fluxes during the spring-summer transition. As a consequence of these three processes, the sea ice-albedo feedback becomes active in spring and leads to an amplification of pre-existing sea ice area anomalies during summer.

Towards highly dense electrolytes at lower sintering temperature (∼1200 °C): Optimization strategies for BaCe0.7Zr0.1CuxY0.2-xO3-δ in SOFCs

High-conducting and long-term stable proton-conducting electrolytes are of utmost importance. This study investigates the synthesis and characterization of BaCe0.7Zr0.1CuxY0.2-xO3-δ (BCZCuxY; x = 0, 0.005, 0.01, 0.02, 0.05, and 0.1) electrolytes tailored for proton-conducting solid oxide fuel cells (SOFCs). Through Cu2+ doping at the B-site of BaCe0.7Zr0.1Y0.2O3-δ (BCZY), a successful reduction of the sintering temperature to 1200 °C was achieved. BCZCu0.02Y exhibited a high relative density of approx. 98.1% at this temperature, but beyond 2 mol% Cu doping, the appearance of a BaCuO2 secondary phase adversely impacted conductivity. The electronic properties of BCZY and BCZCuxY are elucidated via partial density of states (PDOS) analysis, revealing optimized crystal structures and band gap reductions (from approx. 1.9 eV–1.1 eV) upon Cu doping. Notably, BCZCu0.02Y demonstrated a commendable conductivity, with values of 3.5 × 10−2 S. cm−1 in air and 4.8 × 10−2 S. cm−1 in a moist atmosphere at 750 °C. Remarkably, excellent electrochemical stability was observed in a moist hydrogen atmosphere for up to 450 h at 600 °C. Single cells incorporating BCZCu0.02Y electrolytes exhibited peak power densities of 380 mW/cm2 at 750 °C. The incorporation of 2 mol% Cu2+ in the BCZY lattice holds promise for achieving low-temperature sintering and high-performance proton-conducting SOFCs.