Decrease In Precipitation Research Articles

Storage mycotoxin producing fungi in Hungarian sorghum (Sorghum bicolor L. Moench) samples—molecular approach of Fusarium spp.

AbstractThe last few years have been a huge challenge for every farmer in Europe and Hungary because of the increase in hot days and the decrease in precipitation. These facts induced the farmer’s interest in sorghum because it has better stress tolerance than many other cereales, but little is known about mycotoxin-producing fungi, which can infect this crop. Mycotoxins are secondary metabolites of filamentous fungi, and they are not only phytotoxic but also harmful to humans and animals. This study aimed to determine the internal infection caused by Alternaria spp., Fusarium spp., and Aspergillus spp., which are known as mycotoxin-producing fungi in food raw material. In our study in the case of sorghum, the presence of various mycotoxin-producing fungi was detected on Fusarium selective media (Nash and Snyder media), and the results indicate that these genera are present in sorghum grains as potential mycotoxin producers. To determine which Fusarium species is occurring in our sorghum grain samples, a molecular genetic study was performed on isolated fungi using the TEF region primer pairs to identify the occurring Fusarium species. We mainly identified Fusarium proliferatum in our conventional sorghum samples. The results show that the mentioned mycotoxin-producing fungi are in the sorghum grains and may pose a risk to the safety of feed and food because they may produce mycotoxins in the field or while being stored.

Fire–precipitation interactions amplify the quasi-biennial variability in fires over southern Mexico and Central America

Abstract. Fires have great ecological, social, and economic impact. However, fire prediction and management remain challenges due to a limited understanding of their roles in the Earth system. Fires over southern Mexico and Central America (SMCA) are a good example of this, greatly impacting local air quality and regional climate. Here we report that the spring peak (April–May) of fire activities in this region has a distinct quasi-biennial signal based on multiple satellite datasets measuring different fire characteristics. The variability is initially driven by quasi-biennial variations in precipitation. Composite analysis indicates that strong fire years correspond to suppressed ascending motion and weakened precipitation over the SMCA. The anomalous precipitation over the SMCA is further found to be mostly related to the East Pacific–North Pacific (EP-NP) pattern 2 months prior to the fire season. The positive phase of the EP-NP leads to enhanced precipitation over the eastern US but suppressed precipitation over the SMCA, similar to the spatial pattern of precipitation differences between strong and weak fire years. Meanwhile, the quasi-biennial signals in precipitation and fires appear to be amplified by their interactions through a positive feedback loop at short timescales. Model simulations show that in strong fire years, more aerosol particles are released and transported downstream over the Gulf of Mexico and the eastern US, where suspended light-absorbing aerosols warm the atmosphere and cause the ascending motion of the air aloft. Subsequently, a compensating downward motion is formed over the region of the fire source and ultimately suppresses precipitation and intensifies fires. Statistical analysis shows the different durations of the two-way interaction, where the fire suppression effect of precipitation lasts for more than 20 d, while fire leads to a decrease in precipitation at shorter timescales (3–5 d). This study demonstrates the importance of fire–climate interactions in shaping the fire activities on an interannual scale and highlights how precipitation–fire interactions at short timescales contribute to the interannual variability in both fire and precipitation.

The Spatio-Temporal Dynamics of Water Resources (Rainfall and Snow) in the Sierra Nevada Mountain Range (Southern Spain)

This paper describes the use of a unique spatio-temporally resolved precipitation and temperature dataset to assess the spatio-temporal dynamics of water resources over a period of almost seven decades across the Sierra Nevada mountain range, which is the most southern Alpine environment in Europe. The altitude and geographical location of this isolated alpine environment makes it a good detector of climate change. The data were generated by applying geostatistical co-kriging to significant instrumental precipitation and temperature (minimum, maximum and mean) datasets. The correlation between precipitation and altitude was not particularly high and the statistical analysis yielded some surprising results in the form of mean annual precipitation maps and yearly precipitation time series. These results confirm the importance of orographic precipitation in the Sierra Nevada mountain range and show a decrease in mean annual precipitation of 33 mm per decade. Seasonality, however, has remained constant throughout the period of the study. The results show that previous studies have overestimated the altitudinal precipitation gradient in the Sierra Nevada and reveal its complex spatial variability. In addition, the results show a clear correspondence between the mean annual precipitation and the NAO index and, to a much lesser extent, the WeMO index. With respect to temperature, there is a high correlation between minimum temperature and altitude (coefficient of correlation = −0.84) and between maximum temperature and altitude (coefficient of correlation = −0.9). Thus, our spatial temperature maps were very similar to topographic maps, but the temporal trend was complex, with negative (decreasing) and positive (increasing) trends. A dynamic model of snowfall can be obtained by using the degree-day methodology. These results should be considered when checking the local performance of climatological models.

Analysis of the Jumping Characteristics and Influencing Factors of Ozone Pollution in Beijing

Based on environmental monitoring data and meteorological observation data from 2016 to 2022 in Beijing, combined with backward trajectory clustering and potential source area contribution analysis, the characteristics, meteorological impacts, and potential source areas of ozone (O3) pollution were analyzed. The results showed that there was a total of 41 O3 pollution processes with jumping characteristics in Beijing from 2016 to 2022, with an average of 5.9 times a year. The occurrence time was concentrated in May to July, and the day of the jump (OJD2) was higher than the day before the jump (OJD1). The average value of ρ(O3-8h) was 78.3% higher, and the peak concentration was 78.9% higher. The high O3 concentration zone in the OJD2 region exhibited a characteristic of advancing from south to north. The main reasons for the occurrence of jumped O3 pollution in Beijing could be summarized as local accumulation caused by unfavorable meteorological conditions and regional transmission impact. The occurrence of jump-type ozone pollution was characterized by an increase in southerly wind frequency, temperature rise, pressure decrease, and precipitation decrease. The increase in southerly wind frequency provided conditions for the transport of O3 and its precursors, and rapid photochemical reactions occurred under local high temperatures, with less superimposed precipitation, comprehensively pushing up the ozone concentration level of OJD2. Six air mass transporting pathways were identified through clustering analysis; the air mass from the direction north of OJD2 decreased by 11.2%, whereas the air mass from the south and east directions increased by 6.7% and 4.4%, respectively, with the air masses mainly transmitting over short distances. The ozone concentration corresponding to the south and east directions was relatively high, making a significant contribution to Beijing's pollution. The analysis of potential source areas revealed that the main potential source areas of OJD2 ozone pollution were the central, southern, and eastern parts of Beijing-Tianjin-Hebei, which contributed 82.6% to the pollution trajectory. There was a significant contribution of regional transport during jump-type ozone pollution, and it is necessary to strengthen joint prevention and control in the Beijing-Tianjin-Hebei Region.

Trend analysis of MODIS NDVI time series and its relationship to temperature and precipitation in Northeastern of Iran.

Vegetation plays a crucial role in providing organic matter and regulating energy exchange on the Earth's surface. This study investigates the changes in vegetation cover, temperature, and precipitation in northeastern Iran during 2001-2020. MODIS-NDVI time series data and climatic data from 11 synoptic stations were utilized. The nonparametric Mann-Kendall method was employed to detect trends in vegetation cover and climatic variables. Additionally, the correlation between climatic parameters and vegetation was examined. Trend analysis revealed significant increases/decreases in vegetation cover in 32%/26% of the region, respectively. The increasing trend in vegetation cover was predominantly observed in highlands, suggesting that a warmer climate has enhanced the living conditions for plants in these regions. The vegetation trend map indicates an expansion of vegetation cover in the northern and central parts of Iran during the past 20years, whereas the southern and eastern portions experienced declines. The relationship between vegetation and elevation revealed that vegetation increased above 1,850m and decreased below 850m. Trend analysis showed no significant trend in precipitation data since the beginning of the twenty-first century, but an increasing trend in temperature was observed in 82% of the region's area, excluding the western strip. Correlation coefficients between temperature, precipitation, and vegetation indicated that declining temperatures are the limiting factors for vegetation in the highlands, while in lowland areas, the decrease in precipitation significantly diminishes vegetation growth.

Effect of climate change on the seasonal variation in photosynthetic and non-photosynthetic vegetation coverage in desert areas, Northwest China

Efficient prediction of the response of vegetation to future climate change requires an in depth understanding of the effect of climate change on the land cover by photosynthetic (fPV) and non-photosynthetic vegetation (fNPV) and its driving mechanism. Here, we aimed to estimate fPV and fNPV, and analyze the impacts of climate factors on their seasonal variability in the arid desert of northwestern China. First, optimal vegetation indices (VIs) were selected to estimate fPV and fNPV based on measured spectral reflectance, and the accuracy of estimated fPV and fNPV using Sentinel-2 images was evaluated with data from an unmannedaerialvehicle (UAV). Then, partial correlation, multi-correlation and time‐lag effect analyses were used to obtain the correlation coefficients and lag times between fPV, fNPV and climate change. The results showed that Normalized Difference Vegetation Index (NDVI) and Dead Fuel Index (DFI) were the optimal VIs to estimate fPV and fNPV in the desert, with the accuracy of 67 and 52 % for fPV and fNPV, respectively. The average fPV and fNPV were 8.15 and 9.26 % from March to November, their seasonal variability was consistent with plant phenology, and there was a decrease in fPV and fNPV from east to west with a decrease in precipitation. The variability in fPV was driven by precipitation while that of fNPV was dominated bytemperature. The time-lag of temperature and precipitation effect on fPV was 1.28 ± 1.28 and 1.61 ± 1.16 months, respectively, and on fNPV was 1.28 ± 1.2 and 1.19 ± 1.24 months, respectively. The time-lag of temperature-precipitation interaction on fPV and fNPV were 1.4 ± 1.22 and 1.2 ± 1.28 months, respectively. Accumulated precipitation had a positive effect on fPV and a negative effect on fNPV, while the impact of accumulated temperature was the opposite. We conclude that there were time-lag and cumulative effects of climate change on fPV and fNPV variability in desert areas. This study helps us better understand the climate-vegetation interactions and provides a scientific basis for desert vegetation management under climate change.

Causes of the severe drought in Southwest China during the summer of 2022

In summer 2022, Southwest China (SWC) suffered its worst drought since 1980, with a rainfall deficit and an extremely high temperature anomaly. This had a severely harmful effect on agricultural production, water resources, and hydroelectric supply over SWC. Both a less-than-normal water vapor supply and warmer-than-normal temperature contribute to the precipitation decrease associated with drought. Using the observed station data from the China Meteorological Administration and the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis (ERA5) data, our results show that the 2022 summer drought over SWC was caused by both the less-than-normal water vapor supply and warmer-than-normal temperature, and the warmer temperature played a more important role, unlike in previous droughts. The warmer air temperature for the 2022 summer induced record-breaking potential evapotranspiration (PET) over SWC, reducing surface water and drying out soils. Meanwhile, the warmer air temperature made it difficult for water vapor to reach saturation, resulting in a decrease in precipitation over the whole of SWC. We found that such anomalous water vapor supply and temperature were closely related to the South Asian high (SAH) during summer 2022. The SAH was stronger and covered a larger area than during other summer SWC droughts since 1980. The anomalous 2022 summer SAH inhibited the water vapor transport from the tropical Indian Ocean to SWC and further caused a significant warming temperature anomaly by regulating the thickness of the layer between isobaric surfaces, which contributed to the record-breaking summer drought over SWC. Our study highlights the vital role played by warmer temperatures in the 2022 summer drought. Considering that the warming air temperature under greenhouse-gas forcing may cause more droughts like that in 2022 in the future, the 2022 drought may yield useful information that will provide insight into future droughts and raise awareness of the impact of temperature on extreme climate events.

Widespread reduction in gross primary productivity caused by the compound heat and drought in Yangtze River Basin in 2022

Abstract Terrestrial ecosystems play a pivotal role in the global carbon sequestration process, and their photosynthetic capacity is highly susceptible to fluctuations in climate conditions. In 2022, the Yangtze River Basin (YRB) in China experienced an extensive and severe compounded heat and drought event. Compared with the past two decades, our results revealed that the temperature increased by approximately 0.78 ± 0.45 °C and precipitation decreased by about 45.20 ± 30.10 mm from July to October 2022 over the whole YRB. Region I (west from the Sichuan Basin and east to the easternmost of the basin) experienced a more severe temperature increase (0.98 ± 0.35 °C) and precipitation decrease (−60.27 ± 23.75 mm) compared to the other regions in the YRB. Changes in temperature and precipitation resulted in an increase of 0.14 ± 0.06 kPa in vapor pressure deficit (VPD) and a decrease of 5.28 ± 2.09 m3 m−3 in soil moisture, ultimately leading to a total loss of 26.12 ± 16.09 Tg C (about −6.08% compared to the 2001–2021 mean) in gross primary productivity (GPP) of July to October in 2022. It is noteworthy that broadleaf forests, which comprise 12.03% of the natural vegetation in region I, contributed only 6.46% of the GPP loss between July and October compared to other vegetation types, showing greater resistance to this climate event. Our findings from multiple linear regressions highlight that high temperatures and reduced soil moisture together contribute up to 94% photosynthesis loss in July–October in natural vegetation in region I, while the contribution of reduced VPD is minimal. In the future, we will further explore the impacts of compound heat and drought events on the coupled carbon and water cycles across different ecosystems, in order to better understand the ecosystem response mechanisms to extreme climates.

EVALUATION OF THE HYDROLOGICAL RESPONSE TO CLIMATE AND LAND USE CHANGE IN A WATERSHED

Climate change and land-use change influence hydrological processes in a basin, thereby affecting water production. The Cañar River basin originates in the Andean moors and flows into the Pacific Ocean, covering areas of great importance for conservation and agriculture. The basin exhibits a high degree of climatic and ecosystem variability. Two scenarios were proposed and studied using a semi-distributed hydrological model: a) a future climate scenario based on the projection of historical precipitation and temperature trends observed from 1985 to 2010 at 9 stations distributed throughout the basin, and b) a future soil use scenario derived from a multi-temporal analysis of land use, explanatory variables, and transition models. The analysis revealed an increase in precipitation during the rainy season and a decrease in precipitation during the dry season, resulting in a slight reduction in annual precipitation. During the study period, an increase in temperatures is observed in the low and high zones, while in the middle zone, there is a slight reduction in temperatures. The most significant land use changes were observed in natural vegetation, which experienced a significant reduction in area. If the observed climatic trends persist, precipitation would be expected to be concentrated mainly in the rainy season, leading to increased water availability during that period and a significant decrease during the dry season.

Trend analysis of hydro-climatic variables in the Great Lakes Depression region of Mongolia

Abstract Arid and semi-arid regions are the first to be affected by hydro-climatic changes. The Great Lakes Depression Basin in western Mongolia is the most notable example of such a region. Therefore, analyzing hydro-climatic changes in the Great Lakes Depression region is essential for future climate, hydrological, eco-hydrological processes, and ecosystem studies in similar areas and basins. In this study, Mann–Kendall (MK), innovative trend analysis method (ITAM), and Sen's slope estimator test (SSET) were used to determine the interrelationship between climate and river discharge changes and lake water level changes through statistical analysis. During the last 30 years, the air temperature has increased by 1.2 °C (Z = 1.16). Total annual precipitation decreased by 23.44 mm, resulting in 134.16 mm (Z = −0.79). The river discharge of the major rivers, such as Khovd River (Z = −3.51) and Zavkhan River (Z = −6.01), has significantly decreased. In Uvs (Z = 0.30) and Khyargas (Z = 2.03) lakes, the water level has also dropped. This study confirms that the increase in air temperature in the depression area of the Great Lakes reduces the amount of precipitation, and the decrease in precipitation affects the decrease in river discharge, which further affects the water level of the inflowing lakes.

The Circumglobal Transport of Massive African Dust and Its Impacts on the Regional Circulation in Remote Atmosphere

Abstract Atmospheric dust from North Africa, the largest and most persistently active dust source over the world, spreads widely in the Northern Hemisphere and plays essential roles in the Earth environment evolution. During 7–24 June 2020, an extremely strong dust event occurred with its westward spreading modulated by the North Atlantic Oscillation (NAO) and its eastward spreading regulated by European blocking, ultimately resulting in the circumglobal transport of African dust. The Mediterranean low pressure linked to the European blocking dipole was the key to facilitating the eastward transport of dust. This record-breaking African dust episode caused a notable diurnal precipitation decrease of 0.98 mm day−1 over northeastern India and a decrease of 1.55 mm day−1 over central North America, which was ascribed to the effect of dust-induced radiative heating on large-scale circulation. It triggered a Rossby wave train and caused anomalous high pressure over northeastern India, which weakened the India summer monsoon and consequently inhibited the occurrence of precipitation. Dust-induced radiative heating also supported the stability in the anomalous warm high over North America, further repressing import of moisture from Atlantic. Ambient moisture and atmospheric instability also presented consistent variation over North America and India characterized as strengthen descending motion and sharply reduced moist convection. This study reports, for the first time, the strong modulation of regional circulation by circumglobally transported African dust, especially in Asia and North America. The new aspects on the unexpected consequences on moisture convection indicate broader roles that the dust may play in the global climate change.

Evaluation of atmospheric indicators in the Adriatic coastal areas: a multi-hazards approach for a better awareness of the current and future climate

Increasing climate resilience to global warming is one of the main challenges of the last few decades. Effective local measures have to be adopted to provide concrete solutions to the current and expected impacts of climate change. This is the goal of the AdriaClim Italia-Croatia Interreg Project (https://www.italy-croatia.eu/web/adriaclim), aimed at supporting the development of regional and local climate change adaptation plans for the Adriatic coastal regions. For this purpose, an exhaustive number of atmospheric climate indicators have been identified and evaluated across nine pilot areas to assess the current and expected main climate hazards affecting these regions, considering the worst-case emissions scenario (Representative Concentration Pathway RCP 8.5). The proposed analyses are provided by the results of the regional climate atmospheric model developed within the AdriaClim Project. The selected climate indicators are used to assess the possible evolution of the climate hazard across the pilot areas, covering different hazards, such as thermal discomfort, drought, and hydrological instability. A site-dependent investigation of the atmospheric climate indicators is proposed to emphasize which regions are more affected than others by the investigated climate hazards, thus warranting more attention in defining and proposing new adaptation strategies. The results highlight increasing temperatures (up to +3°C) across the Adriatic coastal regions, with more emphasis on the Northern Adriatic, where the combined effect with the relevant decrease in precipitation (down to −2 mm/day) may lead to severe drought conditions in the coming decades. In contrast, precipitation-related diseases may hit more Central and South Italy than the Northern Adriatic, except for the Emilia-Romagna region, which is found to be highly sensitive to both hazard categories. Finally, it is relevant to emphasize that these analyses have to be carefully considered in supporting adaptation strategies due to the lack of uncertainty estimates representing a fundamental element for decision-makers.

Synoptic weather patterns during fire spread events in Siberia

Several recent studies have indicated a strong relationship between extensive wildfires in Siberia and synoptic-scale weather processes. In this study, we used the concept of fire spread events to investigate the relationships between synoptic and surface-level weather conditions and extensive wildfires in Siberia during 2001–2022 using the MODIS and ERA5 reanalysis products. We analyzed the spatio-temporal features and seasonality of fire spread events in the region and found that most of them occurred in the central part of Eastern Siberia (ES) during the summer months, following the wildfire season in the region. A significant positive trend in the annual count of fire spread events was found in ES, coinciding with non-significant negative trends in cloud cover and precipitation and non-significant positive trends in air temperature and the fire weather index. Results show that in the ES region, which accounts for 46 % of the total number of considered events, the main driver of fire spread events is the formation of a positive geopotential height anomaly, which, based on the pattern of the meridional wind component, indicates the presence of an anticyclone above the area of fire spread events. The presence of a high-pressure zone causes a decrease in cloud cover over regions with fires, leading to increases in the amount of incoming solar radiation and surface air temperature and a decrease in precipitation. These conditions contribute to the drying of fuel and an increase in the overall fire hazard level, which in turn leads to an intensification of the combustion process, as evidenced by an increase in the radiative power of fires.

Diurnal Patterns in the Observed Cloud Liquid Water Path Response to Droplet Number Perturbations

AbstractA key uncertainty in Aerosol‐cloud interactions is the cloud liquid water path (LWP) response to increased aerosols (λ). LWP can either increase due to precipitation suppression or decrease due to entrainment‐drying. Previous research suggests that precipitation suppression dominates in thick clouds, while entrainment‐drying prevails in thin clouds. The time scales of the two competing effects are vastly different, requiring temporally resolved observations. We analyze 3‐day Lagrangian trajectories of stratocumulus clouds over the southeast Pacific using 2019–2021 geostationary data. We find that clouds with a LWP exceeding 200 g m−2 exhibit a positive response, while clouds with lower LWP show a negative response. We observe a significant diurnal cycle in λ, indicating a more strongly negative daytime adjustment driven by entrainment‐drying. In contrast, at night, precipitation suppression can occasionally fully counteract the entrainment‐drying mechanism. Overall, λ appears weaker than previously suggested in studies that do not account for the diurnal cycle.

Analysis of Meteorological Element Variation Characteristics in the Heilongjiang (Amur) River Basin

Located in the Heilongjiang (Amur) River in north-east Asia, spanning four countries, plays a crucial role as an international border river, and its meteorological changes significantly impact the variation in water resources in the basin. This study utilizes daily average temperature and precipitation data from 282 meteorological stations in the Heilongjiang (Amur) River Basin and its surrounding areas for the period 1980–2022. The analysis employs spatial interpolation, change point testing, and model construction prediction methods. The results indicate a significant increasing trend in both overall temperature and precipitation changes within the Heilongjiang (Amur) River Basin. At the spatial scale, the annual warming rate increases gradually from the southeastern coastal region to the northwestern plateau region, while the rate of precipitation increase decreases from the southern area towards its surroundings. Temporally, the warming amplitude during the growing season decreases gradually from east to west, and the trend in precipitation changes during the growing season aligns with the overall annual precipitation trend. During the non-growing season, the warming trend shows a decrease in the plains and an increase in the plateau, while precipitation increase concentrates in the central and southern plains, and precipitation decrease predominantly occurs in the northwestern plateau region. Temperature and precipitation change points occurred in the years 2001 and 2012, respectively. In precipitation prediction, the Long Short-Term Memory (LSTM) model exhibits higher accuracy, with R (Pearson correlation coefficient) and NSE (Nash-Sutcliffe efficiency coefficient) values approaching 1 and lower NRSME values. This study provides a research foundation for the rational development and utilization of water resources in the Heilongjiang (Amur) River Basin and offers valuable insights for research on climate change characteristics in large transboundary river systems.

A global assessment of environmental and climate influences on wetland macroinvertebrate community structure and function

AbstractEstimating organisms' responses to environmental variables and taxon associations across broad spatial scales is vital for predicting their responses to climate change. Macroinvertebrates play a major role in wetland processes, but studies simultaneously exploring both community structure and community trait responses to environmental gradients are still lacking. We compiled a global dataset (six continents) from 756 depressional wetlands, including the occurrence of 96 macroinvertebrate families, their phylogenetic tree, and 19 biological traits. Using Bayesian hierarchical joint species distribution models (JSDMs), we estimated macroinvertebrate associations and compared the influences of local and climatic predictors on both individual macroinvertebrate families and their traits. While macroinvertebrate families were mainly related to broad‐scale factors (maximum temperature and precipitation seasonality), macroinvertebrate traits were strongly related to local wetland hydroperiod. Interestingly, macroinvertebrate families and traits both showed positive and negative associations to the same environmental variables. As expected, many macroinvertebrate family occurrences were positively associated with temperature, but a few showed the opposite pattern and were found in cooler or montane regions. We also found that wetland macroinvertebrate communities would likely be affected by changing climates through alterations in traits related to precipitation seasonality, temperature seasonality, and wetland area. Temperature increases may negatively affect collector and shredder functional groups. A decrease in precipitation could lead to reductions in wetland area benefiting drought‐tolerant macroinvertebrates, but it may negatively affect macroinvertebrates lacking those adaptations. Wetland processes may be compromised through broad‐scale environmental changes altering macroinvertebrate family distributions and local hydroperiod shifts altering organism traits. Our complementary family‐based and trait‐based approaches elucidate the complex effects that climate change may produce on wetland ecosystems.

Multi-objective optimization and evolution of dissimilar welding process between Cr-Mo steel and austenitic stainless steel for power plant application

In this study, response surface methodology (RSM) was employed to optimize the welding parameters’ effects on mechanical properties of dissimilar welds between Cr-Mo steel grade (P11) and austenitic stainless steel (AISI 316LN). To determine the best welding parameters, variance analysis (ANOVA), desirability function, and perturbation analysis were used to create regression models and identify the significant parameters influencing tensile strength and hardness gaps in the weld joints. The results indicated that welding speed is the most significant parameter affecting both the austenitic hardness gap and tensile strength, while gas flow has the most significant impact on the hardness gap of Cr-Mo steel. Furthermore, welding speed positively influences the mechanical properties of dissimilar weld, whereas welding current has a slight negative effect on tensile strength. The optimum welding parameters were found to be 130 A for welding current, 70 mm min−1 for welding speed, and 13 l min−1 for welding gas flow, resulting in hardness gap values of 18.10 HV (Stainless steel side), 27.38 HV (Cr-Mo steel side), and a tensile strength of 453.90 MPa. The optimum parameter effect is concentrated at the weld interfaces between the fusion zone and the heat-affected zone. This effect led to limitations in grain coarsening, a reduction in the martensite and delta ferrite phase percentages, a slight increase in the bainite ratio, and a decrease in carbide precipitations. As a result, a homogenization of strain distribution in the optimum weld was achieved, leading to ductile fracture in Cr-Mo steel.

Dominance of soil moisture over aridity in explaining vegetation greenness across global drylands

Drylands are one of the most sensitive areas to climate change. Despite being characterized by water scarcity and low precipitation, drylands support a wide range of green biodiversity and nearly 40 % of the global population. However, the climate change impacts on dryland characteristics and vegetation dynamics are debatable as the reasons remain poorly understood. Here, we use hydro-meteorological variables from ERA5 reanalysis and GIMMS-NDVI to analyze the changes in dryland aridity and vegetation greenness in the eight selected global dryland regions. The total dryland area (excluding hyperarid) has increased by 12 %, while arid, semiarid, and dry sub-humid areas have increased by 10.5 %, 8 %, and 25 %, respectively. We find a significant increase in aridity in drylands across the globe, except for South Asia. A decrease (increase) in precipitation is the major driver for a significant increase (decrease) in dryland aridity, with a notable contribution from climate warming. Despite decreasing trends in precipitation, vegetation greenness has significantly increased in most dryland regions due to increased soil moisture. Cropland expansion in Europe, Asia, and Australia resulted in the maximum increase in NDVI (Normalized Difference Vegetation Index) in dryland regions. The highest increase, with a ΔNDVI of 0.075, was observed in South Asia. The enhanced vegetation greenness observed is attributed to the expansion of croplands in recent decades, which has increased soil moisture. Overall, we show that monitoring soil moisture variability can provide a more robust explanation for vegetation greenness in the global drylands than aridity change. Moreover, human interventions of climatic alteration through land use change practices, such as cropland expansion, cannot be ignored while explaining the ecosystem dynamics of the drylands.

A Geodetic-Data-Calibrated Ice Flow Model to Simulate Historical and Future Response of Glaciers in Southeastern Tibetan Plateau

Glaciers play a vital role in the Asian mountain water towers and have significant downstream impacts on domestic, agricultural, and industrial water usage. The rate of glacier mass loss in the Southeastern Tibetan Plateau (SETP) is among the highest in Asia and has intensified in recent decades. However, a comprehensive quantification that considers both spatial and temporal aspects of glacier mass loss across the entire SETP is still insufficient. This study aimed to address this gap by utilizing geodetic datasets specific to each glacier by calibrating the Open Global Glacier Model (OGGM) driven by HAR v2 and reconstructing the glacier mass balance of 7756 glaciers in the SETP from 1980 to 2019 while examining their spatial variability. The findings reveal that the average mass balance during this period was −0.50 ± 0.28 m w.e. a−1, with an accelerated loss observed in the 2000s (average: 0.62 ± 0.24 m w.e. a−1). Notably, central glaciers in the SETP exhibited relatively smaller mass loss, indicating a gradient effect of increased loss from the central region toward the eastern and western sides. By the end of this century, the area, length, and volume of glaciers in the entire SETP region are projected to decrease by 83.57 ± 4.91%, 90.25 ± 4.23%, and 88.04 ± 4.52%, respectively. Moreover, the SETP glacier melt runoff is estimated to decrease by 62.63 ± 6.16% toward the end of the century, with the “peak water” point of glacier melt runoff predicted to occur in 2023 under the SSP585 scenario. Sensitivity experiments demonstrated that the SETP glaciers are more than three times more sensitive to temperature changes than to precipitation variations, and the observed decrease in monsoon precipitation indicates the weakening magnitude of the Indian summer monsoon in recent years. The spatially refined and high-temporal-resolution characteristics of glacier mass loss presented in this study contribute to a better understanding of specific glacier changes in the SETP. Additionally, the prediction results provide valuable references for future water resources management and policy formulation in the SETP region.

Impact of urban dynamics and climate change on forest areas the Maamora forest in the city of Kenitra, Morocco

Studies have focused on the issue of drought on one hand, and urban dynamics on the other, as prominent topics in physical geography for the former, which specializes in climate change, and human geography for the latter, which concerns field sciences. This research is part of a series of studies and specifically relates to a wetland area in the western plain, specifically Maamora Forest in the city of Kenitra. This research addresses three main axes: the first axis relates to human factors contributing to the reduction and deterioration of Maamora Forest over the past three decades and analyzes their impact on the forest. This is done by determining the development and dynamics of cork oak through remote sensing data, manifested in the analysis of aerial images from three different periods (1975, 1995, and 2022), complemented by field research throughout the period between 2022 and 2023. The second axis focuses on studying climatic data for the studied area, extending from 1987 to 2019. It highlights the manifestations of climate change, such as a decrease in annual precipitation and an increase in temperatures, and their impacts on the overall forest and specifically on cork oak trees. This is done using the LANG equation. The results indicate that the region has experienced four dry periods, accounting for 87.5% of the total 28 years, which range from 1987/1988 to 1995/1994, 1997/1998 to 2010/2011, 2012/2013 to 2014/2015, and 2016/2017 to 2018/2019. In contrast, the percentage of semi-humid and extremely dry years only accounted for 6.25% each, with an average duration of two years. The third axis relates to monitoring the effects of climate change on the forestry sector, specifically the Maamora Forest, through the use of modern techniques such as remote sensing and spectral plant and water indicators. It aims to understand the role of these technologies in spatial monitoring of factors and phenomena that negatively impact forest areas in general, and the Maamora Forest in particular.