Earth's Surface Research Articles

Machine Learning Techniques for Monitoring Water Quality in Water Resources

More than 66% of the Earth's total surface area is covered by water. Clean water is one of the basic needs of everyday life. Consistent pollution of water bodies can have far-reaching effects on the lives of living organisms. The World Health Organization has reported that the provision of safe drinking water for human consumption is a challenge that has reached alarming levels. This is because nearly 70% of the total water withdrawals worldwide are used in agriculture. To determine the water's suitability for human consumption, Tests are typically conducted by examining the properties of water in terms of physical, biological, and chemical conditions. There are various methods to measure water quality. Recently, an ongoing process has been shown to improve water quality. To solve this problem, this paper is using a machine learning model to Contribution for creation a smart model capable of classifying potable and non-potable water that is released to the water share by the competent authorities and the ability of Machine Learning models to monitor and predict water, especially Managing and Planning Water Resources. datasets were utilized in training and evaluating machine learning models, which includes (3276) samples with nine attributes and two labels indicating water usability According to the in our work the (Random Forest) algorithm have the best Through the results that appeared by accuracy (0.954084, 0. 882484, and 0. 931849 for three sizes of data.) and then (Decision Tree, K-Nearest Neighbor, Logistic Regression, SVC) sequentially. Index Terms—Machine Learning, potable water, Water Quality, water resources.

Assessment, identifying, and presenting a plan for the stabilization of loessic soils exposed to scouring in the path of gas pipelines, case study: Maraveh-Tappeh city

Dealing with collapsible soils consistently presents a crucial challenge for geological and geotechnical engineers. Loess soil is among the most widely recognized types of collapsible soils, covering approximately 10 % of the Earth's land surface. Loessic soil is a sedimentary deposit primarily composed of silt-size grains, loosely bound together by calcium carbonate. In Iran, approximately 17 % of Golestan province is covered by silty, clayey, and sandy loesses, primarily composed of loessic soil. Additionally, several energy transmission lines in this province traverse these loess-covered areas. Based on the reports from Golestan Gas Company experts, the scouring of gas pipeline channels in various regions, such as Dashli-Alum in Maraveh-Tappeh city, causes significant risks in the traffic roads and is one of the most critical issues facing this company. This research assessed the dispersion and collapse potentials of loess soil using a range of field exploration and laboratory testing methods. These methods included atomic absorption spectroscopy, the double hydrometer, scanning electron microscope photography, wavelength-dispersive X-ray fluorescence spectrometry, and consolidation tests. The results indicate that soil collapsibility was acquired as one of the components of the scouring phenomenon occurrences. To achieve an optimal solution, the effectiveness of the chemical stabilization method involving cement, bentonite, micro-silica, and synthesized nano‑titanium additives was evaluated through an oedometer, Atterberg limits, uniaxial compression, and direct shear tests. Additives dry mixing of cement and nano‑titanium were obtained as the optimal stabilization solutions against scouring compared to other additives. However, considering the environmental impacts of cement production and use, nano‑titanium presents a more environmentally sustainable option due to CO2 absorption and reduced damage potential to vegetation.

Surface temperature assimilation improving geostationary meteorological satellite surface-sensitive brightness temperature simulations over land

This study explores a possibility of improving Advanced Himawari Imager (AHI) surface-sensitive brightness temperature (TB) simulations over land by assimilating land surface temperature (LST) observations from the National Basic Meteorological Observing Stations of China. The Gridpoint Statistical Interpolation 3D-Var regional data assimilation (DA) system is modified to add LST as a new control variable and its background error variances, horizontal correlations and cross-correlations. The background covariances of LST with other control variables are calculated separately for daytime and nighttime samples in summer and winter seasons. A control experiment (ExpCTL) and three LST DA experiments with (ExpLST) and without (ExpLST_NBC) bias correction or with an average of LST within 2° × 2° grid boxes (ExpLST_SO) are conducted. Considering the fact that surface station observations are point measurements while the satellite TBs measure the total radiation effect of earth's surface within fields-of-view, a bias correction is found necessary for LST DA during daytimes (ExpLST). The biases are quantified by the differences from the Moderate-resolution Imaging Spectroradiometer LST retrievals to compensate for the representative differences. The analyzed fields are then used as input to the Community Radiative Transfer Model to simulate TBs of AHI surface-sensitive channels over land. A long-period statistics shows that ExpLST significantly reduces the observations minus simulations (OB) biases and standard deviations of surface-sensitive TBs in terms of reducing the diurnal variations and season dependences of TB biases over different surface types, which also outperforms ExpLST_NBC and ExpLST_SO at daytime. This study suggests a potential benefit of combining the use of LST observations for assimilating surface-sensitive infrared TBs.

How Do Schumann Resonance Frequency Changes in the Vertical Electric Field Component Reflect Global Lightning Dynamics at Different Time Scales?

AbstractThe electromagnetic waves in the Schumann resonance (SR) frequency range (<100 Hz) radiated by natural “lightning antennas” excite the Earth‐ionosphere cavity confined between the Earth's surface and the lower ionosphere. The peak frequencies of SR are known to vary with source‐observer distance (SOD), while the daily frequency range (DFR: fmax − fmin) is also indicative of the average size of thunderstorm regions. This paper provides observational evidence for these relationships based on SR frequency observations of the vertical electric (EZ) field component at Nagycenk (NCK), Hungary in Central Europe from the period 1994–2015. Variations of the peak frequencies are considered on the annual, seasonal and diurnal time scales as well as during a specific event when squall‐line formation of lightning activity in South America moves toward NCK. DFR is studied in relation to the El Niño Southern Oscillation (ENSO). Increasing area of lightning activity in mid‐high Northern hemisphere latitudes has been identified by DFR variations during the transition from warm to cold episodes of the ENSO in 1998 and 2010. The extension of the lightning area is considered as a consequence of energy released in the tropics and exported to higher latitudes with some months of delay from the end of the El Niño episodes. The frequency variations are interpreted via model calculations and supported with satellite‐based optical lightning observations (Optical Transient Detector, Geostationary Lightning Mapper). The described variations of SR peak frequencies and DFR yield information on the global/regional lightning dynamics and on this basis they have important application to climate issues as well.

Ca–Zn isotope fractionation during fluid–rock interaction in subduction zones and its implication for deep carbon cycle

Subducting slabs transport Earth's surface carbon into the deep mantle, with a portion of this carbon potentially recycled through volcanic eruptions at mid-ocean ridges or ocean islands. Non-traditional stable isotopes such as calcium (Ca) and zinc (Zn) are increasingly used to trace this deep carbon cycle. However, the potential for Ca and Zn isotope fractionation in the subduction zone, critical for the successful application of these tracers, remains insufficiently explored. In this study, we investigate high-pressure carbonated metamafic rocks and enclosed vein systems from a Paleo-oceanic subduction complex (SW Tianshan) to explore the possible fractionation of Ca and Zn isotope during subduction-related metamorphism and fluid–rock interaction. The δ44/40Ca (0.77 ‰–0.90 ‰) and δ66Zn isotope compositions (0.20 ‰–0.39 ‰) of greenschist-, blueschist- and eclogite-facies metabasites are consistent with their protoliths (OIBs and MORBs). We observe no systematic fractionation of either Ca and Zn isotopes across prograde metamorphism and associated dehydration. However, the precipitation of carbonate in surrounding rock along fluid pathways leads to an increase in the δ44/40Ca of residual fluids (>0.90 ‰). More significantly, we find detectable Zn isotope fractionation (ΔA-H = ẟ66Znaltered - ẟ66Znhost of 0.06–0.10 ‰) during fluid-mediated metasomatism of some blueschists/eclogites. Light Zn isotopes are preferentially released into the infiltrating fluid, resulting in an elevated δ66Zn isotope composition in the immediate carbonated eclogites along the vein. The modified slab fluids during migration are likely charactered by heavy δ44/40Ca and light δ66Zn compositions, which may play a crucial role in determining the low δ66Zn values found in some arc lavas. However, the MORB-like δ44/40Ca compositions observed in global arc magmatic rocks suggest that the slab-released Ca (possibly along with some carbon) is probably sequestered and stored along the migration path of the fluid, thereby hindering the slab–arc carbon recycling. Our study emphasizes that intraslab fluid–rock interaction results in similar δ44/40Ca and δ66Zn signature in carbonate-bearing eclogites compared to sedimentary carbonates. Consequently, deeply subducted carbonate-bearing eclogites –not necessarily sedimentary carbonates– might carry light δ44/40Ca and heavy δ66Zn signatures into the deep mantle, potentially influencing the corresponding Ca-Zn isotope compositions of some mantle-derived basalts.

Forest Fire Hazard Forecasting Based on Google Earth Engine Open Satellite Data

Introduction. Forest fires cause significant damage to both the natural fund and the national economy. In recent years, their harmful influence has increased due to global warming, and in Ukraine also due to the armed conflict. Thus, traditional methods of patrolling (ground and air) are not only costly, but also dangerous due to mines and possible shelling of border areas. Therefore, the role of surveillance using satellite systems is increasing. Space monitoring is more efficient and covers a larger area of ??the Earth's surface. Another important advantage is open access to information. The purpose of the paper is to build a mathematical model for determining fire danger based on climatic and biophysical satellite data for the forests of Ukraine, as well as a similar climatic zone with the possibility of further scaling to other climatic regions and types of vegetation cover. To adhere to the principles of open science, Google Earth Engine (GEE), a cloud-based platform that provides open access to dynamic collections of pre-processed Earth remote sensing results, was chosen. Results. Climatic and biophysical data for the forests of Ukraine for the years 2017-2020 were collected using the tools of the Python library for working with GEE data. Further, the obtained data were processed by two methods: linear (PCA) and non-linear (UMAP) in order to obtain statistically independent attributes. Both obtained datasets were subjected to statistical processing using the Bayesian method. Finally, for each point on the map for which information was collected, an indicator was calculated that predicted fire danger if the obtained value was greater than 1 and its absence in the opposite case. The resulting model showed its efficiency on training data. On the test dataset (data on Polish forests for the same period), the results turned out to be worse, in particular, the model using PCA did not predict absence of fire danger, and the model using UMAP generally showed lower performance. This can be due to both the imperfection of the model and the small size of the test dataset or factors unrelated to natural processes (in particular the human factor). Conclusions. An approach to forest fires forecasting based on satellite data is proposed. The obtained results indicate that the model is already effective at this stage, although machine learning methods have not yet been applied. However, it needs further improvement, so work on the model will be continued. Along with improving the quality of forecasts, attention will be paid to the geographic expansion and the creation of a web application. Keywords: fire danger in forests, satellite data, correlation, PCA, UMAP, hard-to-reach areas.

Solar Alpha Particle Radiation Increases Human Mortality – Examples from the Neoplasms Mortality in the Europe and Mediterranean

A dangerous phenomenon for humanity is described. In the joint analysis of data from satellites in orbit around the Earth and from the health statistics source EUROSTAT, it became clear that, by some mechanism, flows of positively charged particles with high energy entering the Earth's orbit increase mortality on the planet's surface. The increase in mortality is in a band of maximum risk in the Northern Hemisphere, parallel to the Equator and bounded by the parallels of 30° and 50° north latitude. Examples are given for the European Union mortality from neoplasms, confirming the described phenomenon. A hypothetical mechanism based on observational evidence has been proposed, according to which this dangerous phenomenon is due to solar alpha particles of high energy sufficient to overcome the atmosphere's resistance and reach the Earth's surface in a limited area of maximum death impact.

Evaluation of Cloud Masking Methods using Sentinel-2 Satellite Images on Google Earth Engine: A Case Study in Vietnam

The production of cloudless images from the optical satellite are critical in Earth surface monitoring. In 2015,Sentinel-2A was successfully launched into orbit by the European Space Agency. Sentinel-2 imagery is currently theprimary source of data for Earth monitoring. There are several ways to create cloudless images from multi-temporalSentinel-2 optical satellite imagery on the Google Earth Engine (GEE) platform. These include the Fmask (Function ofmask) method, the Fmask CDI (Cloud Displacement Index) method, and the Fmask CSP (Cloud Score Plus) method. Inthis paper, the authors build a program and evaluate the cloud masking methods on the GEE platform in Song Hinhdistrict, Phu Yen province, which is situated in the South-Central Coast region of Central Vietnam. The Song Hinh districtis a suitable study area for the evaluation of cloud masking methods on optical satellite images due to its diverse andcomplex terrain, which includes numerous peaks and valleys and a variety of climatic conditions. This article illustratesthe results of three cloud masking methods on Sentinel-2 images. In contrast to the Fmask method, the Fmask CDI andFmask CSP methods provide more benefits in detecting clouds and cloud shadows, resulting in more accurate outcomes

Trace element abundances in mineral phases and the groundmass of ocean island basalts

Incompatible trace elements are important tracers in igneous petrogenesis for determining processes acting: (i) prior to partial melting on magma sources; (ii) during partial melting, fractional crystallization or contamination of magmas, and (iii) after emplacement of lavas or intrusive rocks close to Earth's surface. Of particular interest are the high field strength elements (HFSE: Ti, Zr, Nb, Hf, Ta) which are incompatible elements with high valence states that are also relatively immobile in aqueous fluids. Abundances of Ti, Ta, and Nb (TITAN) in ocean island basalts (OIB) have been suggested to reflect recycled oceanic crust in mantle source regions, due to retention of these elements in subducted eclogitic rutile. Some of these elements have also been used to determine ‘canonical’ trace element ratios, such as Nb/U and Ta/U, that are considered invariant during petrogenetic processes. In this contribution, we present an extensive set of in situ trace element data for olivine, clinopyroxene, oxide minerals and groundmass for a suite of well-studied ocean island basalt (OIB) lavas from the Canary Islands, Azores, Samoa, Tubuai and La Réunion. The data were obtained using laser-ablation inductively coupled plasma mass spectrometry, and we also report a new open-source reduction routine for abundance determination using this method. Mineral-groundmass partitioning behavior is determined for olivine, clinopyroxene and oxides, showing that these are consistent with published partition coefficients for clinopyroxene and olivine, but are more variable for oxide phases. This variability is due to the wide variety of oxide phases possible in OIB (e.g., Cr-spinel, ilmenite, titanomagnetite) and their formation within the crystallization sequence. The new data shows that Nb and Ta budgets are dominated by fine-grained groundmass, as are most other incompatible trace elements, while the Ti budget is divided between clinopyroxene, oxide and groundmass. Modally reconstructed TITAN anomalies closely reproduce bulk rock compositions in samples with >40 % groundmass. Olivine and clinopyroxene fractional crystallization have negligible effects on TITAN anomalies, while oxide fractionation has more marked effects, with Ti anomalies being most affected. Variability in the HFSE in OIB and their association with other elements (e.g., Nb/U and Ta/U) can reflect source characteristics, although careful screening for petrogenetic effects should be done prior to ascribing significance to TITAN anomalies or canonical trace element ratios.

Effect of climate, crop, and management on soil phosphatase activity in croplands: A global investigation and relationships with crop yield

Agricultural and livestock production cover more than a third of the Earth's land surface and are crucial to food supply. Soil extracellular enzymes play an important role in the transformation of elements and compounds in soil, particularly acid (ACP) and alkaline (ALP) phosphatases (both, APases). These enzymes have a vital role in releasing phosphorus (P) from organic matter. However, the effect of climate variables and agro-ecosystem management on APase activity in croplands remains unclear, as does its eventual relationship with agricultural productivity. Therefore, we compiled a global database of APase activity in croplands (between 1977 and 2022) and we analysed 5876 observations across 474 papers to study climate variables, crop family, and management effects on ACP and ALP activity, and their relationship with yield. ACP activity is reduced by higher temperatures (p<0.001) and lower rainfall (p=0.002). There was an interaction effect of temperature and precipitation on ALP activity (p=0.046), with the negative effect of temperature being stronger with high precipitation, and low precipitation showing low ALP activity levels at any temperature. The crop family greatly influenced APase activity (p<0.001). Management practices affected ACP and ALP activity differently; ACP activity was positively influenced by organic fertilization combined with, crop rotation or irrigation by an average of 15.6 % and 30.7 %, respectively. ALP activity was mainly positively influenced by the interaction of two different factors: organic or inorganic-organic fertilization and reduced or zero tillage. Further understanding of soil enzyme mechanisms would aid global food security and yield. As ACP activity doubles from 100.0 to 200.0 mg pNP kg−1h−1, the crop yield increases by more than two-fold, an outcome not demonstrated in croplands until now. These results could enhance yield potential through the promotion of APase activity, and the consideration of climate variables and agro-ecosystem management, which could ultimately improve cost-benefit ratios for sustainable crop growth.

Historical landscape structures of the eastern part of upper Medzibodrožie region

Landscape represents a specific part of the earth's surface, while it has its own structure – primary, secondary and tertiary. The secondary landscape structure consists of elements of land use and material creations of man, which currently fill the earth's surface. The aim of the paper is to evaluate, based on the analysis of historical military and topographical maps, the changes in the secondary landscape structure in the area formed by the cadastral territories of selected municipalities in the eastern part of Upper Medzibodrožie Region. On four maps showing selected territories of Upper Medzibodrožie Region, we compare extensive changes that have occurred in the landscape structure mainly as a result of human intervention in the landscape structure. Historical maps show that the use of the Upper Medzibodrožie Region landscape has changed significantly over the past 150 years. River regulation, drainage works, deforestation and also the transformation of agriculture had a major impact on these changes. The results show that the largest decrease in area representation was recorded by forests and the largest increase by arable land.

Dissolved ammonia catalyzes proto-dolomite precipitation at Earth surface temperature

Marine carbonate rocks are the major reservoir of carbon through CaCO3 and CaMg(CO3)2 precipitation extracting CO2/HCO3- from the atmosphere/oceans; hence dolomite is one of the major sinks in the global carbon cycle. Most ancient dolomite has been considered as mainly precipitated under Earth surface conditions. Previous studies have demonstrated that microbes can mediate dolomite formation. However, the “microbial dolomite” model is not sufficient to explain the dolomite that shows no or little evidence of a microbial origin. Although attempted for decades, the synthesis of inorganically-produced dolomite at normal temperatures (<50 °C) has been relatively unsuccessful. Hence, this "dolomite enigma" has been one principal research focus this century. Here we demonstrate that NH3 catalyzes proto-dolomite precipitation inorganically with higher Mg/Ca molar ratios and CO32- activity at normal temperatures of 30 °C and 40 °C. NH3 dissolution increases the alkalinity of the solution and transformes into NH4+ ions, which prefer to bond with H2O on Mg[(H2O)6]2+ rather than free H2O, thus releasing Mg2+ to facilitate proto-dolomite nucleation. Furthermore, the low dielectric constant and low dipole moment allow NH4+ absorbed on crystal surfaces to lower the energy barrier of Mg[(H2O)6]2+ dehydration, promoting proto-dolomite nucleis growth. The system for proto-dolomite precipitation in our experiments closely simulates the natural aqueous environment. This study brings new insights to understanding the mechanisms of dolomite precipitation in natural waters.

SA-SatMVS: Slope Feature-Aware and Across-Scale Information Integration for Large-Scale Earth Terrain Multi-View Stereo

Satellite multi-view stereo (MVS) is a fundamental task in large-scale Earth surface reconstruction. Recently, learning-based multi-view stereo methods have shown promising results in this field. However, these methods are mainly developed by transferring the general learning-based MVS framework to satellite imagery, which lacks consideration of the specific terrain features of the Earth’s surface and results in inadequate accuracy. In addition, mainstream learning-based methods mainly use equal height interval partition, which insufficiently utilizes the height hypothesis surface, resulting in inaccurate height estimation. To address these challenges, we propose an end-to-end terrain feature-aware height estimation network named SA-SatMVS for large-scale Earth surface multi-view stereo, which integrates information across different scales. Firstly, we transform the Sobel operator into slope feature-aware kernels to extract terrain features, and a dual encoder–decoder architecture with residual blocks is applied to incorporate slope information and geometric structural characteristics to guide the reconstruction process. Secondly, we introduce a pixel-wise unequal interval partition method using a Laplacian distribution based on the probability volume obtained from other scales, resulting in more accurate height hypotheses for height estimation. Thirdly, we apply an adaptive spatial feature extraction network to search for the optimal fusion method for feature maps at different scales. Extensive experiments on the WHU-TLC dataset also demonstrate that our proposed model achieves the best MAE metric of 1.875 and an RMSE metric of 3.785, which constitutes a state-of-the-art performance.

Research progress on isotope tracing on the sources and transformations of reactive nitrogen in the earth-atmosphere system.

Since the Industrial Revolution, human activities have led to a rapid and sustained increase in reactive nitrogen production, resulting in nitrogen enrichment at the Earth's surface and triggering many ecological and environmental issues. Stable isotopes are effective tools for tracing the sources and mechanisms of environmental processes. The nitrogen isotope values in surface environments integrate the isotope signatures of different nitrogen sources and the isotope fractionation effects of transformation processes. The composition of nitrogen isotopes can thus be utilized to trace the sources and cycling of nitrogen at the surface, aiding the development of strategies to reduce reactive nitrogen emissions, and assess the ecological effects of nitrogen enrichment. We reviewed the research progress on nitrogen isotope in the sources of reactive nitrogen in atmospheric systems, plant nitrogen utilization, and tracking of nitrogen processes in forest ecosystems. We further discussed how to gain a more systematic and accurate understanding of nitrogen cycle within and between the various spheres of the surface environment.

Review on the research progress of earth pressure on slope retaining structure

The earth pressure of slope retaining structure is one of the problems that are often encountered in geotechnical engineering but have not yet been fully understood and well solved. At present, there are still a lot of problems that need to be solved. For complex conditions such as stratified soil or containing ground water, the distribution law of earth pressure and the displacement mode of retaining structure need to be further studied. This paper summarizes the existing research on earth pressure of slope retain structures. According to the research methods, it is divided into three categories: research on the theoretical calculation method of earth pressure, research on earth pressure by model test, and research on earth pressure by numerical simulation. Focused discussions are carried out respectively, and the previous research results are summarized. At present, there are still a lot of problems that need to be solved in the research of earth pressure of slope retaining structure, and the calculation formula of earth pressure and the assumed fracture surface of earth are lack of experimental verification and engineering measurement.

Zircon geochemistry from early evolved terranes records coeval stagnant- and mobile-lid tectonic regimes

Determining the mechanisms by which the earliest continental crust was generated and reworked is important for constraining the evolution of Earth's geodynamic, surface, and atmospheric conditions. However, the details of early plate tectonic settings often remain obscured by the intervening ~4 Ga of crustal recycling. Covariations of U, Nb, Sc, and Yb in zircon have been shown to faithfully reflect Phanerozoic whole-rock-based plate-tectonic discriminators and are therefore useful in distinguishing zircons crystallized in ridge, plume, and arc-like environments, both in the present and in deep time. However, application of these proxies to deciphering tectonic settings on the early Earth has thus far been limited to select portions of the detrital zircon record. Here, we present in situ trace-element and oxygen isotope compositions for magmatic zircons from crystalline crustal rocks of the Acasta Gneiss Complex and the Saglek-Hebron Complex, Canada. Integrated with information from whole-rock geochemistry and zircon U-Pb, Hf, and O isotopes, our zircon U-Nb-Sc-Yb results reveal that melting of hydrated basalt was not restricted to a single tectonomagmatic process during the Archean but was operative during the reworking of Hadean protocrust and the generation of juvenile crust within two cratons, as early as 3.9 Ga. We observe zircon trace-element compositions indicative of hydrous melting in settings that otherwise host seemingly differing whole-rock geochemistry, zircon Hf, and zircon O isotopes, suggesting contemporaneous operation of stagnant-lid (oceanic plateau) and mobile-lid (arc-like) regimes in the early Archean.

Impact of construction projects on sustainable landscape: a systematic review

Human activities related to land use, such as the transformation of natural landscapes into urban areas and agricultural fields, as well as changes in land management practices, have caused substantial modifications to the Earth's surface. These alterations have had significant consequences for climate, soil, hydrology, biodiversity, and ecosystem processes. The research presented in this study provides a comprehensive summary of previous investigations in the field of landscape research. The main aim of this paper is to make a comprehensive review about the effect of the construction projects on the sustainable landscape , the results found that the projects effect adversely on the landscape and the free re should be increased.

Using Pseudo-Color Maps and Machine Learning Methods to Estimate Long-Term Salinity of Soils

Soil salinity assessment methods based on remote sensing data are a common topic of scientific research. However, the developed methods, as a rule, estimate relatively small areas of the land surface at certain moments of the season, tied to the timing of ground surveys. Considerable variability of weather conditions and the state of the earth surface makes it difficult to assess the salinity level with the help of remote sensing data and to verify it within a year. At the same time, the assessment of salinity on the basis of multiyear data allows reducing the level of seasonal fluctuations to a considerable extent and revealing the statistically stable characteristics of cultivated areas of land surface. Such an approach allows, in our opinion, the processes of mapping the salinity of large areas of cultivated lands to be automated considerably. The authors propose an approach to assess the salinization of cultivated and non-cultivated soils of arid zones on the basis of long-term averaged values of vegetation indices and salinity indices. This approach allows revealing the consistent relationships between the characteristics of spectral indices and salinization parameters. Based on this approach, this paper presents a mapping method including the use of multiyear data and machine learning algorithms to classify soil salinity levels in one of the regions of South Kazakhstan. Verification of the method was carried out by comparing the obtained salinity assessment with the expert data and the results of laboratory tests of soil samples. The percentage of “gross” errors of the method, in other words, errors when the predicted salinity class differs by more than one position compared to the actual one, is 22–28% (accuracy is 0.78–0.72). The obtained results allow recommending the developed method for the assessment of long-term trends of secondary salinization of irrigated arable land in arid areas.

Dependence of tropical cyclone seeds and climate sensitivity on tropical cloud response.

Projections of future tropical cyclone frequency are uncertain, ranging from a slight increase to a considerable decrease according to climate models. Estimation of how much the Earth's surface temperature warms in response to greenhouse gas increase, quantified by effective climate sensitivity, is also uncertain. These two uncertainties have historically been studied independently as they concern different scales: One quantifies the extreme weather and the other the mean climate. Here, we show that these two uncertainties are not independent and are both influenced by the response of tropical clouds to warming. Across climate models, we show an anticorrelation between shortwave cloud radiative feedback and changes in the frequency of seed vortices, a prevalent type of tropical cyclone precursors. We further show an anticorrelation between effective climate sensitivity and tropical cyclone frequency changes, suggesting that global tropical cyclone frequency tends to decrease more substantially in models with larger temperature increase.

On atmospheric pressure and temperature correlation across various terrain types

Temperature (T), pressure (p), and density (ρ) are fundamental variables describing the atmospheric behavior. This study investigates the interdependence of these variables near Earth's surface in real-world conditions, by evaluating data from different European weather stations. It has been found that the correlation between pressure and temperature is strongly related to the dynamics of the PBL that facilitates a two-group classification. The first group includes all the stations in the plain or in the valley-floor and exhibits a weak correlation, R(p,T). 2D density plots representing hourly pressure against temperature have a distinctive triangular shape at these stations. Regardless of location, the upper boundary of this triangle consistently fits a linear equation with a constant slope and an intercept that scales with the average pressure of the station. This finding holds promising implications for enhancing the quality check of pressure and temperature data, enabling the identification of implausible measurements using a unified equation. In contrast, the second group includes stations with a strongly positive correlation R(p,T) and a more linear density plot; it includes all stations near a mountain-top. Their correlations exhibit identical features when compared to radiosounding data extracted at corresponding heights. The study concludes that: i) the first group of stations is significantly influenced by non-hydrostatic processes such as turbulence, friction and surface radiative heating/cooling in the PBL, resulting in weakly negative R(p,T) for shorter timescales that become null over longer durations; ii) the second group of stations has R(p,T) characteristics similar to the free atmosphere, predominantly regulated by hydrostatic balance and the advection of sensible heat.