Wind Intensity Research Articles

Anomalous thermal and winds condition drove low surface chlorophyll-a in La Paz Bay during the 2015–2016 El Niño event

La Paz Bay (LPB) considered one of the most highly productive bays in the southwestern Gulf of California, Mexico, recently established as Priority Marine Region, supports many species of ecological importance. In this context, daily composites of surface chlorophyll a (Chl-aSAT), sea surface temperature (SST) satellite images derived from the MODIS-Aqua sensor, and a wind intensity index (WI) calculated with data recorded simultaneously at four points along the coast, were used to describe the strong 2015–2016 El Niño impact over the surface chlorophyll pigments in LPB, relative to its average for 2003–2013. Significant relationships between SST, WI (used as environmental factors) and Chl-aSAT (RSST = −0.74, RWI = −0.40, P < 0.01) were found using exponential models for the entire study period, with moderate correlation during El Niño winter condition (December 2015 to March 2016) between SST and Chl-aSAT (RSST = 0.45, P < 0.02). The Chl-aSAT showed unexpectedly low values (∼0.5–1.2 mg m−3) with one month-lag of the winter bloom period jointly with the presence of warmer-than-usual water (∼1.0 °C) and episodes of strong northwesterly winds (speed 8.0–10.0 m s−1) that began in autumn that drove a ∼2 month-lag in its winter peak. The Chl-aSAT and SST winter spatial patterns, showed low Chl-aSAT values (∼−0.5 to −1.0 mg m−3) along the bay and higher-than-usual SST by ∼ 0.5–1.0 °C relative to a year under the La Niña winter condition (2017–2018). This triggered the possible thermocline deepening and the lowest levels of nutrient supply to the photic layer during the El Niño winter episode. Hovmöller diagrams of Chl-aSAT and SST anomalies along the coast revealed a sharp drop to negative anomaly values (∼− 0.7 to −1.2 mg m−3), in-phase but negatively correlated with the SST coastal anomalies (R = − 0.88, P < 0.01). This biophysical coupling played a crucial role in the exceptional drop to the lowest winter Chl-aSAT levels seen in LPB since the MODIS satellite sensor began taking measurements in 2002 (Chl-aSAT values were lower than usual by ∼ 0.9–1.2 mg m −3). Besides the lowest winter levels observed, this research reflected the El Niño signal-driven changes over the basic seasonal average of the LPB climate system The non-significant negative trend observed in the winter average Chl-aSAT values, indicates that LPB may be less resilient to future environmental disturbances.

The strongest winds in tornadoes are very near the ground

Tornadoes contain some of the strongest winds on earth, causing death and damage when impacting man-made and natural objects, such as buildings and trees. Quantifying tornado winds near the surface is critical to characterizing tornado hazards. Direct measurements of tornado winds are rare and are usually obtained at least >100 m above the ground, well above building height, by proximate mobile radars. The representativeness of these mobile radar-obtained measurements to wind speeds closer to the surface is unknown. Here we analyze rare, low-level mobile radar observations of 73 different tornadoes to demonstrate that the strongest winds in tornadoes generally occur very near the ground. Therefore, even proximate radar measurements at >100 m above the ground usually substantially underestimate actual tornado wind intensity.

A novel approach for reservoir sedimentation analysis of Khadakwasla dam catchment, Maharashtra, India – A field data base model

The phenomenon of sediment yield occurred in the reservoir had been studied in the research. Khadakwasla reservoir is a major water source for domestic, industry and agriculture to Pune district in Maharashtra India located on Mutha river. The erosion is the natural and geological process. The rate of erosion is increased due to human influence. Erosion is the action of removes soil, rock from one position from land surface and its transfer to another position. Land use land cover, drainage pattern and soil strata are the primary factors of the soil erosion. Rainfall, runoff, temperature, solar radiation, humidity and wind intensity are the weather parameters mostly influenced on the sediment depositions. The sedimentation is the critical issue for utilization of reservoir. Buckingham&apos;s Pi theorem considering with dimensional analysis of sixteen primary and weather parameters are used to estimate the amount of sedimententering and deposition in the Khadakwasla reservoir for the period (2000- 2020). The calibration process was performed using field measurement data. The result obtained by using hydrological model that the annual sediment discharged to Khadakwasla reservoir. This paper impends to an endeavor for development of a hydrological model which studies the relation between sediment analysis and dimensional analysis parameters together to establish the foremost sensitive parameter for soil erosion.

Using LASSO regularization to project recruitment under CMIP6 climate scenarios in a coastal fishery with spatial oceanographic gradients

As climate change disrupts fisheries, scientists are interested in fisheries projections under climate change scenarios. However, projections that account for spatial oceanographic gradients use increased variable selection power and output high spatial resolution climate data are needed to improve strategic fisheries management. This study uses the least absolute squares and selection operator, a regularization technique, and improved, climate change projections from phase 6 of the Couple Model Intercomparison Project to relate Atlantic surfclam, Spisula solidissima solidissima, recruitment to climate variables. Results show a longitudinal gradient in New York State waters where western recruitment displays a negative relationship with sea surface temperature and eastern recruitment displays a negative relationship with eastward spring wind intensity. Models project that recruitment in 2050 will decrease 100% in western waters and remain sporadic, but high, in eastern waters. This study provides insight regarding surfclam responses to climate change and considerations (methodological and statistical) for improved climate-based fisheries projections.

System modelling and performance assessment of green hydrogen production by integrating proton exchange membrane electrolyser with wind turbine

This investigation delves into the production of green hydrogen with the aid of a polymer electrolyte membrane electrolyzer with its source of energy harnessed from wind using a vertical axis wind turbine (VAWT). The integrated numerical approach was adopted in the simulation environment of MATLAB, Simulink, and Simscape™ to develop the comprehensive mathematical model of the system. The component-level models are linked to the electrolyser, and wind turbines are modelled distinctively considering their efficiencies. The study first explores current types of electrolysers, from their operational characteristics to their merits and demerits. The Proton Exchange Membrane Electrolysers were recommended as the best electrolysis alternative due to their fast start-up time, and the technology being matured. Various power electronics required in connecting the energy from the wind turbine to the electrolyser was equally discussed. Some of these notable power electronics include the Permanent Magnet Synchronous Generators (PMSG), Full Bridge Diode Rectifier, as well as DC–DC Buck Boost Converter. The study was conducted at Warwickshire area as the location for the installation of the Proton Exchange Membrane Electrolyser System. It was however deduced that the performance of the electrolyser was predominant at higher temperatures but lower pressures. The intensity of wind also had a direct correlation to the overall performance of the electrolyser. In summary, for the wind turbine under investigation, at 1 bar pressure and operating temperature of 20 °C, 65,770 L of hydrogen was produced and this is equivalent to 4656.3 kg of hydrogen or 156.4 kWh of energy.

The Response of the Subtropical Front to Changes in the Southern Hemisphere Westerly Winds—Evidence From Models and Observations

AbstractThe location of the Subtropical Front (STF), the boundary between Subtropical and Subantarctic Water in the Southern Ocean is proposed to be influenced by the strength and location of the Southern Hemisphere westerly winds. We use a hydrodynamic hindcast model and recent observations to test if changes in the westerly winds can cause meridional shifts in the STF over interannual to decadal timescales by modulating local Ekman transport. We find that increased, or northward, shifted westerly winds lead to an enhanced northward Ekman transport over large parts of the Southern Ocean, resulting in a northward shift in the STF. Conversely for weaker or southward shifted westerly winds where the STF migrates south. However, this relationship breaks down in regions with strong eddy variability and western boundary current systems. In these regions an increase in westerly winds lead to a southward shift in the STF. Observation data from 2004 to 2019 display a southward shift of STF associated with the positive Southern Annular Mode. However, the shift is smaller than the latitudinal shifts in the location of the zero wind stress curl and maximum westerly winds (−0.4° latitude/decade). This discrepancy is due to positive Ekman trends resulting from the intensification of the westerly winds, which oppose the southward migration. Changes in the Ekman transport and the overall southward shift of the STF have also resulted in an observed positive trend in chlorophyll‐a concentrations south of the STF, which could have ramifications for marine ecosystems and the biological pump in the Southern Ocean.

WIND FACTOR IN SPATIAL AND TEMPORAL DYNAMICS OF WIND EROSION WITHIN VOLYN REGION

The analysis of the wind factor as a factor of wind erosion of Polissia soils is highlighted. The highest intensity of wind erosion in the Polissya zone is observed in the spring and autumn periods, when the density of vegetation cover is the lowest during the year and there is no snow cover. The temporal dynamics of the wind regime forms certain patterns, which determines the formation of the corresponding clusters of months of the year as indicators of the temporal regularity of the wind regime and clusters of administrative districts as indicators of the spatial regularity of the wind regime. The early spring period is the least long (two months), which allows it to be interpreted as transitional. This interpretation explains the inclusion in this cluster by the dynamic features of August as also the transition period from the summer wind regime to the autumn one. The winter period is characterized by an extremely strong wind regime, the lowest wind intensity is observed in the summer-autumn period. The transitional early spring period is characterized by an intermediate level of wind load, but the greatest variability of indicators, which also emphasizes the transitional nature of this time stage of the year. It was established that the maximum value of the wind factor for these areas is observed in winter and is 3,57 m3 s−3, and the minimum is observed in August and is 2,3 3,57 m3 s−3. The central and eastern regions (Manevytskyi, Kovelskyi and Rozhishchenskyi) also form a homogeneous subzone, the peculiarity of which is that the duration of strong winds in the winter period is somewhat shorter compared to the northwestern regions. The highest wind load is observed in the winter months, and the lowest at the end of summer. Geographically, the north-western and south-eastern regions of the region experience the greatest wind load. In terms of time, three consecutive periods can be distinguished: winter, early spring, and summer-autumn.

Time-Series Prediction of Intense Wind Shear Using Machine Learning Algorithms: A Case Study of Hong Kong International Airport

Machine learning algorithms are applied to predict intense wind shear from the Doppler LiDAR data located at the Hong Kong International Airport. Forecasting intense wind shear in the vicinity of airport runways is vital in order to make intelligent management and timely flight operation decisions. To predict the time series of intense wind shear, Bayesian optimized machine learning models such as adaptive boosting, light gradient boosting machine, categorical boosting, extreme gradient boosting, random forest, and natural gradient boosting are developed in this study. The time-series prediction describes a model that predicts future values based on past values. Based on the testing set, the Bayesian optimized-Extreme Gradient Boosting (XGBoost) model outperformed the other models in terms of mean absolute error (1.764), mean squared error (5.611), root mean squared error (2.368), and R-Square (0.859). Afterwards, the XGBoost model is interpreted using the SHapley Additive exPlanations (SHAP) method. The XGBoost-based importance and SHAP method reveal that the month of the year and the encounter location of the most intense wind shear were the most influential features. August is more likely to have a high number of intense wind-shear events. The majority of the intense wind-shear events occurred on the runway and within one nautical mile of the departure end of the runway.

Wind Defiant Morphing Drones

Intense winds are a challenge for vertical take‐off and landing drones with wings. In particular, in the hovering regime, wings are sensitive to wind currents that can be detrimental to their operational and energetic performances. Tail‐sitters are particularly prone to those wind currents because their wings are perpendicular to the incoming wind during hovering. This wind generates a large amount of drag and can displace and destabilize the vehicle, possibly leading to catastrophic failures. Herein, our morphing strategy demonstrates in a custom‐built 1.8 kg tail‐sitter with morphing wings that can actively resist winds and leverage them to increase its aerodynamic efficiency. It is shown that adaptive wing morphing during hovering in adverse wind conditions can reduce normalized energy consumption up to 85%, increase attitude and positional stability, and leverage wind energy to increase its yaw angular rate up to 200% while decreasing motor saturation levels.

Does Increasing Climate Model Horizontal Resolution Be Beneficial for the Mediterranean Region?: Multimodel Evaluation Framework for High‐Resolution Model Intercomparison Project

AbstractThe Mediterranean region (MR) is one of the climate change hot spots, posing serious threats to society. The insufficient resolution of the global climate models limits their capability to resolve the complex topography over MR, resulting in a large bias in climate variables. This study examines the performance of four Coupled Model Intercomparison Project phase six models from the High‐Resolution Model Intercomparison Project (HighResMIP) in reproducing the Mediterranean climate. A special focus is put on the role of oceanic and atmospheric model horizontal resolution and spread among the models. Various aspects, relevant to air‐sea interactions and precipitation are examined, including the mean, extremes, and associated mechanisms. All HighResMIP models reasonably well capture the large‐scale oceanic and atmospheric characteristics, but there is a sizable model‐to‐model difference. The Hadley Centre Global Environment Model and European Centre for Medium‐Range Weather Forecasts generally perform better than the other models at comparable atmospheric and oceanic horizontal resolutions. A finer oceanic resolution improves the representation not only of oceanic characteristics (i.e., sea surface temperature, SST) but also of the atmospheric processes (wind and precipitation). Likewise, increasing atmospheric model resolution benefits various atmospheric and ocean characteristics. Over some sub‐basins of the Mediterranean Sea, the intensification of surface wind speed results in the deepening of the ocean's mixed layer leading to cooling, indicating negative feedback in Wind‐SST. In contrast, in other regions, the warmer SST results in the intensification of wind (positive feedback in Wind‐SST).

Estimating the tropical cyclone wind structure using physics-incorporated networks

Satellite-based remote sensing technology plays a significant role in identifying tropical cyclones (TCs), and most of the current research focuses on intensity estimation. However, analyzing the wind structure of TCs, which is directly related to the danger they bring, remains a challenge. By adding prior knowledge of TCs into the model, we propose a physics-incorporated network based on multi-task learning to estimate wind radii and intensity, whose layers can automatically extract rotation-invariant features related to the TC core from multichannel satellite imageries. In addition, we build a more comprehensive dataset, including global Statistical Hurricane Intensity Prediction Scheme (SHIPS) predictors, to tackle the structure task. We compare our model with existing methods, and it shows that our model gets better results in estimating 50-knot and 64-knot wind radii and achieves a 4.87-knot root-mean-squared error (RMSE) of intensity. By predicting probability density functions, our model quantifies the uncertainty of the result. The experimental results show that the incorporation of rotation equivariance into the layers can enhance TC structure estimation. By considering the feature importance of multi-source predictors, we find that our model pays attention to key predictors related to the TC structure. Specifically, the tangential wind speed at 500 km from the TC center and the radius of the 5-knot wind both greatly reduce the error of the estimated parameters. Finally, two case studies show that the proposed model performs well most of the time during TCs’ rapid intensification. However, when TCs’ system is not well organized, estimating the wind structure is challenging.

Transition probability and gale intensity assessments of tropical cyclones based on warning signals

Typhoons may damage wind power equipment as they pass through wind farms, so the intensity analysis and prediction of the strong winds near the wind farm are helpful for the safety protection and effective utilization of offshore wind power facilities. Based on the warning signals and duration of tropical cyclones affecting Hong Kong from 1946 to 2020, the transition probability of the warning signals with a certain duration range is calculated, and the variation rules of tropical cyclones' gale intensity is analyzed, which can provide reference for wind turbines to resist typhoons. The intensity of strong winds in the nearby sea area caused by tropical cyclones is classified using cluster analysis. Then the variation trend of the number, intensity and skewness coefficient of tropical cyclones belonging to each category every year is analyzed. The results show that a warning signal's residence time will affect the transition probability, thus affecting the operations of the wind turbines. Most of the signal processes in part categories include the signals with a relatively higher severity, so adequate preventive measures should be taken for these categories of signal processes.

The intensification of coastal hypoxia off central Chile: Long term and high frequency variability

Hypoxia is a phenomenon where dissolved oxygen (DO) is reduced to levels that are low enough to strongly affect ecological and biogeochemical processes. This occurs within the continental shelf off central Chile (36°S), influenced by seasonal coastal upwelling (Spring-Summer). Monthly measurements of DO and other oceanographic variables in the water column (1997−2021) over the 92 m isobath along with high-resolution and near-surface observations (POSAR buoy), are analyzed to examine incidences of hypoxia and understand the physical and biogeochemical processes modulating DO vertical distribution and its temporal variability. On average, the percentage of the water column with DO levels below 89 (hypoxia) and 22 (severe hypoxia) μmol L−1 reaches 68% (i.e., hypoxic waters are found below 30 m) and 44% (below 50 m depth), respectively, but during the upwelling season, as much as 87% (below 12 m depth) and 81% (below 17 m depth) of the water column exhibits these levels. On the sub-seasonal scale during upwelling season six hypoxic events lasting at least 2 days occur at 10 m depth. There is a strong seasonal correlation between the volume of the seawater presenting hypoxia and upwelling favorable winds. Furthermore, there is a high DO interannual variability partially related to the El Niño Southern Oscillation (ENSO). Over 2 decades, it is estimated that DO concentration in surface and subsurface layers decreases (up to 21 μmol L−1 decade−1) as waters get colder (up to 0.29°C decade−1). Remarkably, the volume of hypoxic and severe hypoxic waters over the shelf has increased more than 2 times since 1997 and shows a significant positive correlation with the upwelling index. These preliminary findings indicate that the increase in local DO consumption is partially associated with upwelling intensification. Given the clear evidence of wind intensification in coastal upwelling ecosystems and thus the increase in hypoxic events, the coastal zone may be highly vulnerable to hypoxia, impacting biological resources and biogeochemical cycles.

Roles of Surface Forcing in the Southern Ocean Temperature and Salinity Changes under Increasing CO2: Perspectives from Model Perturbation Experiments and a Theoretical Framework

Abstract A rapid warming and freshening of the Southern Ocean have been observed over the past several decades and are attributed to anthropogenic climate change. In this study, ocean model perturbation experiments are conducted to separate roles of individual surface forcing in the Southern Ocean temperature and salinity changes. Model-based findings are compared with results from a theoretical framework including three idealized processes defined on the θ–S diagram. Under the future scenario of CO2 doubling, the heat flux forcing dominates the large-scale warming, deepening of isopycnals, and spiciness changes along isopycnals, which can be captured by an idealized pure warming process to represent the subduction of surface heat uptake. The poleward-intensifying westerly winds account for 24% of the enhanced warming between 35° and 50°S and would have comparable contribution as the heat flux forcing after removing the global ocean warming effect. In contrast, the widespread freshening in the Southern Ocean driven by increased surface freshwater input is largely compensated by the wind-driven saltening. The response to freshwater forcing could not be approximated as a similar pure freshening process as the induced cooling and freshening have comparable effects on density. The wind-driven changes are primarily through the local heave of isopycnals, thus resembling an idealized pure heave process, but contain considerable spiciness signals especially in the midlatitude Southern Ocean, resulting from anomalous northward transport and subduction of heat and salt that are largely density-compensating. These distinct signatures of individual surface forcing help us to better understand observed and projected changes in the Southern Ocean. Significance Statement Considerable changes including a rapid warming and freshening have been observed in the Southern Ocean as it absorbs most of the extra heat from the anthropogenic climate change, receives increased surface freshwater input, and experiences a poleward shift and intensification of the westerly winds. The purpose of this study is to distinguish different contributions from surface heat flux, freshwater flux, and wind forcing to the Southern Ocean temperature and salinity changes, based on ocean model experiments and three idealized processes from a theoretical framework. Our study reveals distinct signatures of individual surface forcing that help us to understand linkages between changes seen at the surface and in the interior Southern Ocean.

Random Forest Approach for Improving Nonconvective High Wind Forecasting across Southeast Wyoming

Abstract High winds are one of the key forecast challenges across southeast Wyoming. The complex mountainous terrain across the region frequently results in strong gap winds in localized areas, as well as more widespread bora and chinook winds in the winter season (October–March). The predictors and general weather patterns that result in strong winds across the region are well understood by local forecasters. However, no single predictor provides notable skill by itself in separating warning-level events from others. Random forest (RF) classifier models were developed to improve upon high wind prediction using a training dataset constructed of archived observations and model parameters from the North American Regional Reanalysis (NARR). Three locations were selected for initial RF model development, including the city of Cheyenne, Wyoming, and two gap regions along Interstate 80 (Arlington) and Interstate 25 (Bordeaux). Verification scores over two winters suggested the RF models were beneficial relative to current operational tools when predicting warning-criteria high wind events. Three case studies of high wind events provide examples of the RF models’ effectiveness to forecast operations over current forecast tools. The first case explores a classic, widespread high wind scenario, which was well anticipated by local forecasters. A more marginal scenario is explored in the second case, which presented greater forecast challenges relating to timing and intensity of the strongest winds. The final case study carefully uses Global Forecast System (GFS) data as input into the RF models, further supporting real-time implementation into forecast operations.

Variability of plankton production during the spring bloom in NW Iberia

A coupled physical (Regional Ocean Modeling System, ROMS)-biogeochemical model (N2PZD2) at a horizontal resolution of 3.5 km was implemented for N and NW Iberia, an area of high productivity associated with upwelling. The physical model has been the object of previous studies and has proven its capability to perform well in reproducing the main oceanographic features in the area (upwelling, river plumes, slope currents, fronts, filaments), which is fundamental to properly representing the variability and distribution of the biogeochemical variables. The biogeochemical model was set up to account for the main nutrient inputs in the area: upwelling and rivers. Upwelling input required proper characterization of the nutrient content variability of the Eastern North Atlantic Central Water, which was achieved by using a temperature-nitrate relationship obtained from observations to impose nitrate at the open boundaries. The resulting biophysical model accurately reproduced the timing and interannual variability of the spring bloom compared with satellite chlorophyll (chl a) observations. A comparison with the Instituto Español de Oceanografía’s in situ spring-monitoring Pelacus cruises (which include plankton) revealed that the model was able to reproduce the variability at shorter scales (days) and demonstrated its ability to complement the observational data and reveal the variability in the area around the spring transition. In this respect, both the model and observations showed that productivity on this narrow shelf is affected by seasonal upwelling that results from the interplay of wind, river plumes and light intensity, all varying at interannual, seasonal and event scales.

Štabovi za vanredne situacije kao elementi sistema upravljanja rizikom kod velikih šumskih požara

In recent years, forest fires are becoming more frequent, which is partly a consequence of global warming and the appearance of extremely hot summers, more frequent occurrences of drought, as well as increased wind intensity, but primarily as a consequence of great human carelessness and sometimes evil intentions. Large forest fires are a serious danger and their occurrence and spread directly endangers people, buildings, material goods and the environment. Emergency situation during this type of fires can be declared when a large area of quality forest is affected, when there is an immediate danger to people, material goods or the environment. When declaring an emergency situation, emergency headquarters and expert operational teams are activated whose task is to manage the risk in forest fire protection and to take measures to reduce the risk and protect people and material goods. The functioning of the operations centers and the effective implementation of measures have a direct impact on the efficiency of extinguishing large forest fires and the degree of efficiency in protecting people, buildings and property. The main goal of this paper was the analysis of the work and significance of the headquarters for emergency situation as a risk management factor in forest fire protection.

Comparison of the efficiency of wind power plants from renewable energy types to reduce atmosphere pollution in Marmara region

Our need for energy is increasing every day with the advancement of technology. Energy plays a major role in the social and economic sphere of life. The need for RES is increasing day by day although the need for energy is produced from fossil fuels in many countries. In addition to this, while the harmful gases emitted to the environment as a result of using fossil fuel for energy production harm the nature, this is not possible in renewable wind energy. Renewable wind energy is an endless source of energy obtained from natural processes. Therefore, wind power stations get attention of many countries. The wind industry is the world's fastest-growing energy source. However, the main problem of the renewable wind energy sector is that the desired wind intensity cannot be sustained at the same rate and the installation costs are high. Many countries are aware of the importance of wind energy and make certain investments in renewable wind energy in the long term. Wind turbines can be in different shapes according to their location and intended use. One of the most important reasons for their different designs is the wind types in their geographies. In this study, wind power plants in five different regions in Marmara region were discussed. These plants were com-pared among themselves, the results were evaluated and the efficiency of the plants compared.

비행청소년의 분노 표현과 지각된 스트레스에 따른 빗속의 사람(PITR)그림 반응특성 연구

This study aimed to find out whether the PITR test can be used as a psychological test tool to evaluate the anger expression and perceived stress response of delinquent adolescents. The subjects of the study were 223 vocational training youths located in G city, and the study tools were a person in the rain (PITR) picture test, anger expression checklist, and perceived stress checklist. For data analysis, independent sample t-test was performed by using SPSS 25.0. The research results are as follows. First, in the response characteristics of the person in the rain (PITR) picture test for the anger expression of delinquent youths, significant differences are confirmed in the amount and intensity of rain, the intensity of wind, and the number of lightning. And in the response of coping resources, significant differences were found in the number of direct protection, adequacy of indirect protection, facial expression, and overall figure. Second, in the response characteristics of the person in the rain (PITR) picture test for the perceived stress of delinquent youths, meaningful differences resulted from the amount of rain, the strength of wind, the relationship between lightning and people, and the relationship between people and puddles. In response to coping resources, there are significant differences in the appropriateness of direct protection, the appropriateness of indirect protection, facial expression, and stroke. Based on the above research results, we could verify that the person in the rain (PITR) picture test is useful as a tool to evaluate anger expression and perceived stress in juvenile delinquents.

Spatial and Temporal Variability of Soil Erosion in Northeast China from 2000 to 2020

Northeast China is a prominent base for commercial grain production nationwide. Soil erosion, a primary cause of land degradation and grain yield decrease, has become an imminent issue and is still not well documented in Northeast China. Thus, a comprehensive assessment of soil erosion in Northeast China is essential for deepening our understanding of various geological and agricultural issues, such as control of regional water and soil losses, anti-degeneration attempts on black soil, preservation of land fertility, and safeguarding of national food security. Based on the Revised Universal Soil Loss Equation (RUSLE) and the Revised Wind Erosion Equation (RWEQ) models, this paper comprehensively assessed the water and wind erosion in Northeast China from 2000 to 2020 and analyzed the current situation, as well as the spatial and temporal evolution of soil erosion. The results suggest the following: (1) The degree of soil erosion in Northeast China was mainly slight, and water erosion was more severe than wind erosion. Water and wind erosion in bare land and grassland were more intensive than in cropland and forests. The Liao River Plain (LRP) has undergone relatively intensive water erosion, while the wind erosion in the Greater Kinggan Mountains Region (GKMR) was more intensive than in other sub-regions. (2) A slight intensifying trend of water erosion could be observed in Northeast China from 2000 to 2020, where the area of slight water erosion decreased and that of light and intensive water erosion increased. The water erosion in the Changbai Mountain Region (CBMR), the Sanjiang Plain (SJP), and the Songnen Plain (SNP) intensified, while the LRP has undergone slower water erosion than before. The water erosion in bare land and cropland intensified, while the water erosion in grassland and forests slowed down. Compared to the first decade (2000–2010), the second decade (2010–2020) in the timespan of study had a reversed trend of water erosion from intensifying to moderating, which means water erosion was alleviated. (3) A moderating trend in wind erosion could be found in Northeast China from 2000 to 2020, where the area of slight wind erosion increased and that of light, moderate, and intensive wind erosion decreased. The wind erosion in the LRP showed a pronounced decrease, and the wind erosion in bare land and cropland also considerably decreased. Compared to the first decade, the amount of wind erosion in the second decade decreased by 18.2%, but the rate in the second decade decreased slowly or even increased. These two facts indicate that wind erosion in Northeast China has alleviated, but this trend is gradually slowing down. Soil erosion is caused by multiple factors, such as climate, topography, soil, and human activities. This study provides important implications for our understanding of soil erosion control and management in Northeast China. In sub-regions with severe erosion, such as the LRP and the GKMR, we can adopt methods such as zero tillage, cross ridge tillage, and straw mulching according to the local characteristics of soil erosion to slow down the process.