August Temperature Research Articles

Xylotrophic Agaricomycetes Monitoring in Some Types of Spruce and Birch Forests (Subzone of the Southern Taiga, Perm Territory, Russia)

We have summarized the results of xylotrophic agaricoid basidiomycetes long-term monitoring in some types of indigenous and derived forests in the southern taiga subzone of Perm Krai. We carried out the research by a stationary method on the test 50×20 m areas, one in each type of forest: spruce forest at the brook, sorrel spruce forest and birch forest. We did the work in three periods: I – 1975–1977, II – 1994–1996, III – 2010–2012. The collection of material was carried out annually: in August 3 times with an interval of 10 days (the species composition, number and air-dry biomass of basidiomes were taken into account), and in September once (only the species composition of fungi was taken into account). To date, we have established that the number of xylotrophic agaricoid fungi in the studied forest types varies from 60 (sorrel spruce forest) to 66 (birch forest). Most of the identified species belong to the Tricholomataceae family (37.7–43.3% of the total number of xylotrophic fungi species in each of the biogeocoenoses). There was an annual accumulation of detectable fungal species, with the largest number of species (67–75%) detected from 2 to 9 times, and 2–3% of them were permanent, occurring annually. There was relative stability of the species composition of higher vascular plants (Jaccard generality coefficient: J = 56–88) over time and more significant changes in the species composition of xylotrophic fungi (J = 36–50). The spruce forests had the most similarity of fungi species composition between the cenoses by periods (J = 44–52), and for the entire observation period, the sorrel spruce forest and birch forest had the maximum Jaccard index between cenoses (J = 56). The yield of xylotrophic agaricoid fungi in the studied cenoses varies by years of observation. The birch forest had the largest number and biomass of basidiomata for all the three periods of the research. A decrease in the number of basidiomes of xylotrophic fungi in the sorrel spruce forest was established with an increase in the average monthly air temperature in August (Spearman correlation coefficient: rs = −0.70). The sorrel spruce forest was the most favorable for the biota of xylotrophic agaricoid basidiomycetes, both in number (Shannon index: H = 1.23) and in biomass (H = 1.20), during all the research, since the biota of xylotrophes of the specified cenosis was more diverse and its components were most aligned.

A Circulation Study Based on the 2022 Sino–Vietnamese Joint Survey Data from the Beibu Gulf

This study analyzed the horizontal and vertical distribution characteristics of temperature and salinity in the central and eastern regions of the Beibu Gulf, based on conductivity measurements in summer 2022, temperature, and depth (CTD) measurement data from the Sino–Vietnamese cooperative project “Demonstration Study on Ecological Protection and Management in Typical Bays: Seasonal Survey of the Beibu Gulf”. Furthermore, the study utilized the computational results from the numerical Finite-Volume Coastal Ocean Model (FVCOM) to elucidate the intrinsic patterns that formed the temperature and salinity distribution characteristics in August 2022 from both thermodynamic and dynamic perspectives. The circulation in the Beibu Gulf drives external seawater to move northward from the bay mouth. During this movement, numerous upwelling areas are created by lateral Ekman transport. The formation of different scales of cyclonic and anticyclonic vortices and current convergence zones is influenced by topography, runoff, and the water flux from the Qiongzhou Strait, which are key factors in the formation of upwelling and downwelling. The surface circulation in August 2022 significantly differed from the 20-year average surface circulation, with an influx of 1.15 × 104 m3/s more water entering the Beibu Gulf compared to the multi-year average. The water flux from the Qiongzhou Strait is a critical factor affecting the circulation patterns in the Beibu Gulf. The northeastern waters of the Beibu Gulf are characterized by current convergence zones, where extensive upwelling occurs. The rich nutrient salts in these areas promote the reproduction and growth of phytoplankton and zooplankton, making this the most favorable ecological environment in the Beibu Gulf and serving as a natural reserve for fisheries, coral reefs, dugongs, and Bryde’s whales.

Comparative analysis of changes in bioecological indicators of Thaumetopoea pityocampa (Den. & Schiff.) (Lepidoptera: Notodontidae) for a 28-31 year period

In 2022, a study was conducted with experimental material from the area of Marikostinovo village, covering various aspects of species bioecology. The stability or changes that have occurred in these bioecological parameters after a 28-31 year period were analysed, with research data from this area conducted in the period 1991-1994. The fecundity of pine processionary moths in the 5 generations compared had a stable level of average values above 214 eggs. The long-term observations and reporting of this indicator gave reason to draw the conclusion that in this region of Bulgaria, the species develops stably, successfully overcoming possible occurrences of extremely high temperatures in July and August. In the egg stage, the most significant factor in reducing the number of T. pityocampa is the impact of parasitoids. Its effect is not a constant value but varies widely, being the difference nearly twice. The relative share of eggs destroyed by predators is insignificant. A distinctive feature of the Marikostinovo site is the high relative proportion of dead caterpillars, sterile and empty eggs, with values significantly higher than those in other areas of the species’ global range. This is the warmest and driest region of Bulgaria. The high values of this indicator are also formed by the large number of unfertilised, sterile eggs, reaching in 1994 up to 1/5 of the eggs in the sample. The dominant species, with constant presence in all samples, is Ooencyrtus pityocampae.

Formation and evolution of thermokarst landslides in the Qinghai-Tibet Plateau, China

Thermokarst landslide (TL) activity in the Qinghai-Tibet Plateau (QTP) is intensifying due to climate warming-induced permafrost degradation. However, the mechanisms driving landslide formation and evolution remain poorly understood. This study investigates the spatial distribution, annual frequency, and monthly dynamics of TLs along the Qinghai-Tibet engineering corridor (QTEC), in conjunction with in-situ temperature and rainfall observations, to elucidate the interplay between warming, permafrost degradation, and landslide activity. Through the analysis of high-resolution satellite imagery and field surveys, we identified 1298 landslides along the QTEC between 2016 and 2022, with an additional 386 landslides recorded in a typical landslide-prone sub-area. In 2016, 621 new active-layer detachments (ALDs) were identified, 1.3 times the total historical record. This surge aligned with unprecedented mean annual and August temperatures. The ALDs emerged primarily between late August and early September, coinciding with maximum thaw depth. From 2016 to 2022, 97.8 % of these ALDs evolved into retrogressive thaw slumps (RTSs), identified as active landslides. Landslides typically occur in alpine meadows at moderate altitudes and on gentle northward slopes. The thick ice layer near the permafrost table serves as the material basis for ALD occurrence. Abnormally high temperature significantly increased the active layer thickness (ALT), resulting in melting of the ice layer and formation of a thawed interlayer, which was the direct causing factor for ALD. By altering the local material, micro-topography, and thermal conditions, ALD activity significantly increases RTS susceptibility. Understanding the mechanisms of ALD formation and evolution into RTS provides a theoretical foundation for infrastructure development and disaster mitigation in extreme environments.

Modelling and mapping the abundance of lingonberry (Vaccinium vitis-idaea L.) in Norway

Lingonberry (Vaccinium vitis-idaea L.) grows in a range of nature types in the boreal zone, and understanding factors affecting the abundance of the plant, as well as mapping its spatial distribution, is important. The abundance of the species can be an indicator of ecosystem changes, and lingonberry can also be a source for commercial utilisation of berry resources. Using country-wide data from 6404 field plots of the Norwegian national forest inventory (NFI), we modelled the relationship between lingonberry cover and airborne laser scanning (ALS) and satellite metrics and bioclimatic variables describing the forest structure, terrain, soil properties and climate using a generalised mixed-effects model with a quasipoisson distribution. The validation carried out with an independent set of 2124 NFI plots indicated no obvious bias in predictions. The most important predictors were found to be interactions between dominant tree species, stand basal area and latitude, as well as the reflectance in the near-infrared band from Sentinel-2 satellite imagery, the dominant height based on the ALS variable and the long-term mean summer (June–August) temperature. The results provide an indicator of the effects of global warming, as well as the possibility of giving forest management prescriptions that favour lingonberry and locating the most abundant lingonberry sites in Norwegian forests.

Feasibility of machine learning-based rice yield prediction in India at the district level using climate reanalysis and remote sensing data

CONTEXTYield forecasting, the science of predicting agricultural productivity before the crop harvest occurs, helps a wide range of stakeholders make better decisions around agricultural planning. OBJECTIVEThis study aims to investigate whether machine learning-based yield prediction models can capably predict Kharif season rice yields at the district level in India several months before the rice harvest takes place. METHODOLOGYThe methodology involved training 19 machine learning models such as CatBoost, LightGBM, Orthogonal Matching Pursuit, and Extremely Randomized Trees on 20 years of climate, satellite, and rice yield data across 247 of India's rice-producing districts. In addition to model-building, a dynamic dashboard was built understand how the reliability of rice yield predictions varies across district. RESULTS AND CONCLUSIONSThe results of the proof-of-concept machine learning pipeline demonstrated that rice yields can be predicted with a reasonable degree of accuracy, with out-of-sample R2, MAE, and MAPE performance of up to 0.82, 0.29, and 0.16 respectively. This performance outperformed test set performance reported in related literature on rice yield modelling in other contexts and countries. In addition, SHAP value analysis was conducted to infer both the importance and directional impact of the climate and remote sensing variables included in the model. Important features driving rice yields included temperature, soil water volume, and leaf area index. In particular, higher temperatures in August correlate with increased rice yields, particularly when the leaf area index in August is also high. Building on the results, a proof-of-concept dashboard was developed to allow users to easily explore which districts may experience a rise or fall in yield relative to the previous year. The dashboard show that the model may perform better in some regions than in others. For instance, the absolute percentage error for predicted versus actual yields ranged from an average of 7.1 % in districts in Uttarakhand to an average of 14.7 % in Uttar Pradesh. SIGNIFICANCEThis study underscores the potential for policymakers to consider scaling and operationalizing machine learning approaches to rice yield prediction in the context of agricultural early warning systems to deliver timely crop yield forecasts on a rolling basis throughout the season, thereby equipping agricultural decision-makers with the ability to make informed choices on irrigation scheduling, fertilizer application, and harvest planning to optimize crop output and resource use.

Tree Ring Blue Intensity-Based August Temperature Reconstruction for Subtropical Central China

Tree-ring blue intensity (BI) has the potential to provide information on past summer temperatures of a similar quality to that of tree-ring maximum latewood density and at a substantially reduced cost. To explore the applicability of BI in subtropical regions, the inverted BI for the earlywood, latewood, and the delta BI (DBI) parameters, together with tree-ring width of subalpine fir (Abies fargesii Franch.) in the Shennongjia area of China, were measured, and the corresponding chronologies were developed. The relationships of these chronologies with the monthly mean temperature and monthly precipitation were explored via correlation analysis. Results show that the DBI chronology is closely related to the temperature in August of the current year, indicating that BI, specifically delta BI, data are suitable for use in dendroclimatology studies in subtropical areas. The resultant mean temperature August reconstruction, based on DBI, explains 40.8% of the temperature variance and is robustly validated using independent periods from the calibration. This pilot study not only highlights the potential of DBI for temperature reconstruction in China but also offers valuable insights into historical climate variations in the Shennongjia region. Moreover, it shows the potential for utilizing such tree-ring data from low-latitude regions to derive past climate data in subtropical warm-humid zones.

Tree-Ring Chronologies from the Upper Treeline in the Russian Altai Mountains Reveal Strong and Stable Summer Temperature Signals

Radial tree growth at high-elevation and high-latitude sites is predominantly controlled by changes in summer temperature. This relationship is, however, expected to weaken under projected global warming, which questions the reliability of tree-ring chronologies for climate reconstructions. Here, we examined the growth–climate response patterns of five tree-ring width (TRW) and maximum latewood density (MXD) chronologies of larch (Larix sibirica) from upper-treeline ecotones in the Altai Mountains, which is a key region for developing millennial-long dendroclimatic records in inner Eurasia. The TRW and MXD chronologies exhibited significant year-to-year coherency within and between the two parameters (p < 0.001). While TRW is mostly influenced by temperature changes during the first half of the growing season from June to July (r = 0.66), MXD is most strongly correlated with May–August temperatures (r = 0.73). All seasonal temperature signals are statistically significant at the 99% confidence level, temporally stable back to 1940 CE, the period with reliable instrumental measurements, and spatially representative for a vast area of inner Eurasia between northeastern Kazakhstan in the west, northern Mongolia in the east, southern Russia in the north and northwestern China in the south. Our findings demonstrate the paleoclimatic potential of TRW and especially MXD chronologies and reject any sign of the ´divergence problem´ at these high-elevation, mid-latitude larch sites.

600 years of wine must quality and April to August temperatures in western Europe 1420–2019

Abstract. This study investigates the validity of wine must quality as an April-to-August temperature proxy between 1420 and 2019 based on expert ratings and quality measurements from Germany, Luxembourg, eastern France, and the Swiss Plateau. This is highly relevant as uncertainties remain on past climate variations during this period. The evidence was reviewed according to the best practice of historical climatology. Expert ratings tended to agree with Oechsle density measurements that gradually replaced them from the 1840s. A statistical model calibrated to predict wine must quality from climate data explains 75 % of the variance, underlining the potential value of wine must quality as a climate proxy. Premium crops were collected in years of early harvest involving high insolation during maturation, while poor crops resulted from very late harvests in cold and wet summers. An analysis of daily weather types for high- and low-quality years after 1763 shows marked differences. On a decadal timescale, the average quality was highest from 1470 to 1479, from 1536 to 1545, and from 1945 to 1954. Poor crops were collected in periods with prevailing cold and wet summers such as 1453 to 1466, 1485 to 1494, 1585 to 1614, 1685 to 1703, 1812 to 1821, and 1876 to 1936. In the period of enhanced warming after 1990, high quality became the rule.

The Added Value of Statistical Seasonal Forecasts

Seasonal climate predictions can assist with timely preparations for extreme episodes, such as dry or wet periods that have associated additional risks of droughts, fires and challenges for water management. Timely warnings for extreme warm summers or cold winters can aid in preparing for increased energy demand. We analyse seasonal forecasts produced by three different methods: (1) a multi-linear statistical forecasting system based on observations only; (2) a non-linear random forest model based on observations only; and (3) process-based dynamical forecast models. The statistical model is an empirical system based on multiple linear regression that is extended to include the trend over the previous 3 months in the predictors, and overfitting is further reduced by using an intermediate multiple linear regression model. This results in a significantly improved El Niño forecast skill, specifically in spring. Also, the Indian Ocean dipole (IOD) index forecast skill shows improvements, specifically in the summer and autumn months. A hybrid multi-model ensemble is constructed by combining the three forecasting methods. The different methods are used to produce seasonal forecasts (three-month means) for near-surface air temperature and monthly accumulated precipitation seasonal forecast with a lead time of one month. We find numerous regions with added value compared with multi-model ensembles based on dynamical models only. For instance, for June, July and August temperatures, added value is observed in extensive parts of both Northern and Southern America, as well as Europe.

Influence of weather conditions in Central Polissia, Ukraine, on the expression of quality indicators in potato cultivars of different maturity groups

For Ukrainians, potatoes are a key foodstuff and the most important strategic crop in the vegetable segment, and therefore it is vital to investigate the quality characteristics of potato tubers. The purpose of this study was to investigate the influence of various meteorological factors on the taste and starch content of tubers of different potato cultivars. The study employed laboratory, analytical, mathematical, and statistical methods. Both positive and negative correlation between starch content in tubers, taste, average monthly temperature, and precipitation were found in cultivars of different ripeness groups. For some potato cultivars, the positive effect on the starch content in tubers was due to the synergistic interaction of temperatures in August and precipitation in July, while for other cultivars this effect was determined by temperature and precipitation in August. It was found that an increase in temperature in August contributed to the improvement of the taste characteristics of early-ripening cultivars, while for middle early and mid-ripening genotypes, increased temperatures in June and August were key factors, and middle-late cultivars responded to increased precipitation in August. For each of the 19 cultivars studied, periods with a positive effect of average monthly temperature and precipitation on the improvement of taste were identified. The cluster analysis helped to identify potato cultivars with high starch content – Lietana, Opillia, Vzirets, and Oleksandryt, with high taste qualities – Lietana, Mezhyrichka 11, Vzirets, Avanhard, Partner, Oleksandryt, Fanatka, Rostavytsia, and Opillia. The findings of this study can serve as a scientific basis for the formulation of policies aimed at mitigating the effects of climate change and adapting existing cultivars to support sustainable potato production in a particular region and creating new plastic potato genotypes with sustainable quality characteristics

Response of radial growth of different timberline species to climate change in Yading Nature Reserve, Sichuan, China

The radial growth of trees in alpine timberline is particularly sensitive to climate change. We sampled and disposed tree-ring cores of three coniferous tree species including Juniperus saltuaria, Abies forrestii, and Larix potaninii at alpine timberline in Yading Nature Reserve. The standard tree-ring chronology was used to explore the response of radial growth of different timberline species to climate change. The results showed that radial growth of L. potaninii increased after 2000, while that of A. forrestii declined after 2002, and J. saltuaria showed a significant decreasing growth trend in the past 10 years. Such results indicated divergent growth responses to climate factors among the three tree species at alpine timberline. The radial growth of J. saltuaria was sensitive to temperature, and was positively correlated with the minimum temperature from previous October to current August, the mean tempera-ture from previous November to current April and from current July to October, but was negatively associated with the relative humidity from current July to October. The radial growth of A. forrestii showed negative correlation with mean temperature and the maximum temperature from May to June in the current year, while it exhibited positive association with the relative humidity and the Palmer drought severity index from May to June in the current year. L. potaninii radial growth was positively associated with mean temperature and the maximum temperature of November-December in the previous year, the maximum temperature of current March and mean temperature of current August. The temporal stability of climate-growth relationship varied among different timberline species. The positive correlation between radial growth of A. forrestii and J. saltuaria and temperature gradually decreased, while the posi-tive relationship of L. potaninii radial growth and temperature gradually increased. Under the background of climate warming, rapid rise in surface air temperatures may promote the radial growth of L. potaninii, while inhibit that of J. saltuaria and A. forrestii, which may change the position of regional timberline.

Varied growth response of high alpine Rhododendron myrtifolium and forest zone tree species to climate warming in the Eastern Carpathians, Ukraine

Plants growing along altitudinal transects in alpine and mountainous areas respond differently to climatic conditions. The present study is centred on the unique and ecologically significant species, Rhododendron myrtifolium Schott & Kotschy, an evergreen clump-forming or prostrate dwarf shrub. This high-mountain endemic plant grows at several localities in isolated massifs of the Eastern Carpathians, but the greatest numbers of sites can be found in the subalpine and alpine belts of the Chornohora range. The main objectives of this study were (1) to assess the dendrochronological potential of Rhododendron myrtifolium as a new species in dendrochronological research and (2) to compare the growth response of R. myrtifolium (sampling elevation: 1800–1950 m a.s.l.) with Picea abies Karst. (1350–1500 m a.s.l.) and Abies alba Mill. (950–1050 m a.s.l.) collected from the upper and lower forest belts. Tree-ring material from 97 trees and shrubs enabled the construction of three site chronologies from sites located within the altitudinal transect. The longest chronology, covering the previous 184 years, was developed for fir. The chronology for the rhododendron was the shortest at 66 years. This species is the most sensitive of the three species analysed. The highest positive r-value (r=0.71) was obtained between the rhododendron chronology and the warm-season temperature (from March to July). Also, the growth of this species was significantly positively correlated with the summer temperature (r=0.50). In contrast, fir and spruce demonstrated a similar inverse relationship with August temperatures.

Revising Alpine summer temperatures since 881 CE

Europe experienced severe heat waves during the last decade, which impacted ecological and societal systems and are likely to increase under projected global warming. A better understanding of pre-industrial warm-season changes is needed to contextualize these recent trends and extremes. Here, we introduce a network of 352 living and relict larch trees (Larix decidua Mill.) from the Matter and Simplon valleys in the Swiss Alps to develop a maximum latewood density (MXD) chronology calibrating at r = 0.8 (p > 0.05, 1901–2017 CE) against May–August temperatures over Western Europe. Machine learning is applied to identify historical wood samples aligning with growth characteristics of sites from elevations above 1900 m asl to extend the modern part of the chronology back to 881 CE. The new Alpine record reveals warmer conditions in the tenth century, followed by an extended cold period during the late Medieval times, a less-pronounced Little Ice Age culminating in the 1810s, and prolonged anthropogenic warming until present. The Samalas eruption likely triggered the coldest reconstructed summer in Western Europe in 1258 CE (-2.32 °C), which is in line with a recently published MXD-based reconstruction from the Spanish Pyrenees. Whereas the new Alpine reconstruction is potentially constrained in the lowest frequency, centennial timescale domain, it overcomes variance biases in existing state-of-the-art reconstructions and sets a new standard in site-control of historical samples and calibration/ verification statistics.

Влияние орошения на продуктивность отечественных сортов картофеля в условиях предкамья Республики Татарстан

The article presents the results of the study of varieties of Russian selecia presented by the Federal State Budgetary Scientific Institution "Federal Potato Research Center named after A.G. Lorch". In the studies conducted in 2023 on the basis of Agrobiotechnopark LLC at the Kazan State Agrarian University, the following potato varieties of domestic selection were presented: early-ripening - Meteor and Gulliver; medium-early potato varieties Ariel, Krasa Meschery and Surprise; medium-ripe - Grand and Pennant and Purple potato variety. Irrigation has had a positive effect on all the studied domestic potato varieties. When analyzing such indicators as the flatness of the development of the leaf surface, the height of the plant, the increase in the mass of the tops and tubers and taking into account the yield, all the studied varieties on irrigation gave the highest indicators than when cultivated on the bogar. The weather conditions of the growing season of 2023 differed significantly from the average long-term data. Since the air temperature in May, July and August was higher than the average annual values. As for, 46.79 mm of precipitation fell in May, which is 23 % higher than the average annual data, June was drier (only 6 mm of precipitation fell, which is 10% of the norm), in July and August precipitation fell only – 50.3 and 37.1 % of the monthly norm, respectively. According to the results of the analysis of the leaf surface area of domestic varieties, it can be judged that the use of irrigation on potatoes in 2023 showed positive dynamics in all variants compared to the cultivation of this crop on bogar. Thus, its maximum value of 19,909 thousand m2/ha in the flowering phase was achieved with irrigation of the medium-ripened potato variety Grand, which is 2205 thousand m2/ha higher than when cultivating this variety on bogar. The maximum yield of 21.8 t/ha was obtained for the medium-ripened potato variety Grand, which is 9.28 t/ ha higher when cultivating this variety without watering. The medium–early potato variety Ariel also formed a fairly high yield - 20.94 t/ ha.

Zooperiphyton on Anti-Fouling Coatings and Changes of Its Coenotic Structure

The features of the zooperiphyton communities' forming on experimental substrates - protective coatings with antifouling properties, based on industrial alkyd enamel PF-167 modified by cationic biocides 1-dodecylpyridine oleate and 1-dodecylpyridinium bis(2-ethylhexyl) phosphate in the bay of the Kaniv reservoir (the Dnieper river) have been studied. Some features of successional changes in the Zebra mussel and Bryozoans' (pearlwort) communities were discussed. On the contrast to the previous years, when the water temperature in August (time of high development of bryozoan colonies) was lower, the continual succession of communities with <i>Dreissena'</i>s dominance was not interrupted by the bryozoan's development. The protective coatings containing 8% of cationic biocides demonstrated high antifouling activity. In this study, no connections between the cenotic structure and nature of antifouling coatings were found.

Warm Early Summer Compensated Reduction in Photosynthesis Caused by 2022 Late Summer Extreme Drought Over the Tibetan Plateau

AbstractThe Tibetan Plateau (TP) is ecologically delicate, its vegetation highly sensitive to climate variations. In 2022, China endured an unprecedented compound drought‐heatwave, escalating TP's August temperature to a record high since 2000. This study examined this event's impact on TP's photosynthesis using multi‐source satellite‐based products. We demonstrated persistent high temperatures from April to August 2022, accompanied by shifting soil water (SW). Initially moist from April to June, the soil turned notably dry, hitting its lowest point in August. Consequently, early summer witnessed a substantial enhancement in gross primary productivity (GPP) and near‐infrared reflectance of vegetation (NIRv) predominantly due to high temperatures, except for reduction in the eastern and southeastern TP. June recorded the largest positive GPP anomaly since 2000. As summer progressed, severe drought, not high temperatures, dominated, causing obvious negative anomalies in GPP and NIRv, especially in August, concentrated in the central and southwestern TP. Separating the growing season into May–June–July (MJJ) and August–September (AS) revealed a clear contrast. Enhancement in photosynthesis during MJJ compensated the decline in AS, making average positive GPP and weak negative NIRv anomalies in the entire growing season. Specifically, MJJ saw GPP magnitudes of 5.724 TgC mo−1 in FluxSat, 9.491 TgC mo−1 in GPP v2.2 and OCO‐2‐based Solar‐induced chlorophyll fluorescence (GOSIF), and 0.004 in NIRv. Conversely, AS experienced a decline: −4.802 TgC mo−1 in FluxSat, −2.837 TgC mo−1 in GOSIF GPP, and −0.006 in NIRv. This delicate balance underscores the intricate interplay between early growth conditions, subsequent environmental stressors, and vegetation's adaptive responses.

Study of the soybean varieties quantitative traits variability in the Central Non-Chernozem Earth Region conditions

In the experiments, the formation of the yield of new early-ripening soybean varieties Georgiy, Slavyanka and Snezhana under the conditions of the Central Non-Chernozem Region was studied and an assessment was made of the influence of hydrothermal conditions on the variability and conjugation of soybean agronomic traits. Field experiments were carried out in 2020-2022. at the Institute of Seed Production and Agrotechnologies, a branch of the FGBNU FNAC VIM (Ryazan region), located in the forest-steppe agro-climatic zone of the Non-Chernozem zone of the Russian Federation. The soil is dark gray forest, heavy loamy in granulometric composition, of medium fertility (humus content - 4.54%), with an average content of exchangeable potassium and mobile phosphorus. Through correlation analysis, a significant positive relationship was established between the duration of the growing season and the HTC (r = 0.916 + 0.09), with the average daily temperature in August (r = 0.896 + 0.04). The height of plants and the height of attachment of the lower bean in the varietal section changed to an average degree (V = 7.96-21.38%). The greatest variability over the years was noted for the number of beans (V=31.92%) and the weight of seeds per plant (V=38.03%). The weight of 1000 seeds changed the least during the years of the study (V = 8.54-13.38%). The yield of the studied varieties is directly related to the number of beans and seeds per plant, and has no significant relationship with the height of the plant. The results of the research were used in the development of varietal technologies for the cultivation of soybeans in the conditions of the Ryazan region.

Linkage between the boreal spring Antarctic oscillation and the temperature dipole mode over the Tibetan Plateau in summer

As the extratropical Southern Hemispheric most prominent atmospheric mode, Antarctic oscillation (AAO) can impact the climate system via multi-spherical interactions, whereas its potential influence on the temperature anomaly over the Tibetan Plateau (TP) remains unclear. By employing ERA5 reanalysis during 1979–2018, we have identified a significant in-phase relationship between April–May AAO and the boreal summer (June–August) temperature anomaly over the TP. The AAO significantly modulates the meridional circulation in the Atlantic sector where the climatic subtropical jet is weaker than other regions in the subtropics as well as the equatorward extension of midlatitude jet. The divergence of transient eddy momentum related to the positive AAO strengthens the northward movement of the South American meridional circulation and cross-equatorial airflow in the low troposphere. Due to the Coriolis force, the cross-equatorial airflow turns southwesterly above the tropical North Atlantic, weakening the climatic northeasterly and the feedback of wind-evaporation-sea surface temperature (SST). Consequently, an anomalous warm SST persists into the boreal summer and triggers a Rossby wave train, which propagates along the North Atlantic-TP pathway. As a result, the positive phase of TP's temperature dipole mode with an eastern warm anomaly and a western cold anomaly appears. The numerical experiments conducted by the linear baroclinic model provide further evidence for the Rossby wave origination and propagation. The AAO, therefore, may act as a valuable predictor for the climate predictions around the TP.

Solar-driven chemisorption cogeneration system integrated with thermal energy storage

In this study, a power and cooling cogeneration system is introduced, consisting of a chemisorption cycle, a latent heat thermal energy storage (TES) system employing phase change materials (PCM), and a solar system employing compound parabolic collectors (CPC). The system is targeted at being employed in a residential area in Shiraz City and TRNSYS and MATLAB software environments are utilized to simulate and assess the system. In the system, power is generated by a turbine with the pressure difference elicited through the chemical reaction in the chemisorption cycle. Also, the cooling is produced via the evaporation of ammonia in the evaporator. The effect of the supplied hot source temperature for the reaction in the adsorbent bed was investigated. It was observed that in the 100–200 °C heat source temperature range, the total energy efficiency increased from 0.313 to 0.467 and the COP for the refrigeration process reduced from 0.71 to 0.53. Also, the maximum overall energy and exergy efficiency in this temperature range were 0.46 and 0.405, respectively. Also, at the heat source temperature of 200 °C, the average maximum electrical power and cooling capacity were gauged at 2.7 kW and 14.5 kW, respectively. In the TES system with a volume of 1.5 m3, the maximum achievable capacity was 250 kWh and the solar system showed its highest temperature in July and August. It was observed that heat source temperature augments the production capacity of the system while it reduced the coefficient of performance (COP) of the system. Sustainable development goals (SDG) impact [Display omitted]