June Precipitation Research Articles

Tropical Interbasin Interaction as Effective Predictors of Late-Spring Precipitation Variability in the Southern Great Plains

Abstract The southern Great Plains experience fluctuating precipitation extremes that significantly impact agriculture and water management. Despite ongoing efforts to enhance forecast accuracy, the underlying causes of these climatic phenomena remain inadequately understood. This study elucidates the relative influence of the tropical Pacific and Atlantic basins on April–May–June precipitation variability in this region. Our partial ocean assimilation experiments using the Community Earth System Model unveil the prominent role of interbasin interaction, with the Pacific and Atlantic contributing approximately 70% and 30%, respectively, to these interbasin contrasts. Our statistical analyses suggest that these tropical interbasin contrasts could serve as a more reliable indicator for late-spring precipitation anomalies than El Niño–Southern Oscillation. The conclusions are reinforced by analyses of seven climate forecasting systems within the North American Multi-Model Ensemble, offering an optimistic outlook for enhancing real-time forecasting of late-spring precipitation in the southern plains. However, the current predictive skills of the interbasin contrasts across the prediction systems are hindered by the lower predictability of the tropical Atlantic Ocean, pointing to the need for future research to refine climate prediction models further. Significance Statement Agriculture and infrastructure in the southern plains face challenges from severe late-spring precipitation extremes. Traditional predictors like El Niño–Southern Oscillation (ENSO) lose effectiveness during the critical spring-to-summer transition, creating a forecasting gap. This study introduces the concept of tropical interbasin interactions, known to enhance seasonal predictability for late-spring precipitation in the southern plains. Novel climate model experiments highlight contributions from the tropical Pacific and Atlantic, offering a promising predictability that potentially surpasses the limitations of ENSO-based predictions. These outcomes hold the potential for developing operational forecasts of late-spring precipitation anomalies in the southern plains, enabling proactive risk management.

Changing role of water table and weather conditions in diameter growth of Scots pine on drained peatlands

We investigated the impact of water table (WT), monthly temperature, and precipitation of current and previous growing seasons on annual diameter growth of Scots pine in boreal drained peatlands. The data were collected from six sites across Finland. WT was monitored during 5-8 growing seasons depending on site during 2007-2014. The sites contained altogether 19 sample plots, where diameter growth from 339 trees was measured, resulting in 1,599 growth observations. Tree-level diameter growth was analysed using mixed linear models, including variables describing tree size, competition, and environment. The higher precipitation in June of the previous year and May of the current year increased diameter growth, whereas the higher temperature in July of the current year and the deeper WT in August of the previous year decreased growth. The results suggest that Scots pine grows better at shallow than deep WT in drained peatlands. This contradicts earlier findings that a deep WT is needed to support tree growth in drained peatlands. We suggest that the development of a mor layer on the peat is changing nutrient cycling and hydrology. The results encourage the avoidance of intensive drainage in forested peatlands, which may also diminish the adverse environmental impacts of peatland forestry.

On the present and future changes in Indian summer monsoon precipitation characteristics under different SSP scenarios from CMIP6 models

AbstractMonsoons are a vital part of the agriculture and economy of India which most of its population rely on for their livelihoods. It still is not clear how climate change will impact precipitation events over India due to the complexity of accurately modelling precipitation. Using twelve Coupled Model Intercomparison Project Six (CMIP6) models, we compared their performance to observed data taken from CRU as well as looking at the future changes in precipitation until the end of the twenty first century for the six precipitation homogenous regions over India. The individual models showed varying degrees of wet and dry biases and the ensemble mean of these models showed relatively lesser bias and improved spatial correlation. Out of 12 models, NorESM and MIROC6 models outperform other models in terms of capturing the spatial variability of precipitation over the Indian region. It is also found that due to lesser moisture transport from the adjoining seas represented through vertically integrated moisture transport (VIMT) analysis, there is consistent dry bias across the models. Further a comprehensive analysis of model performance across six homogeneous precipitation regions indicates that NorESM demonstrates better performance in the CNE and HR regions, EC-Earth excels in the PR, WC, and NE regions, while CMCC shows better performance specifically in the NW region compared to other models. Shared Socioeconomic Pathways (SSPs) were used for future projections and a slight increase in June, July, August, and September (JJAS) precipitation until the end of the century with SSP5-8.5 showing the largest increase. We found an increase in precipitation of 0.49, 0.74 and 1.4 mm/day under SSP1-2.6, SSP2-4.5 and SSP5-8.5 in the far future. The northeast region was shown to receive the largest increase in precipitation (2.9 mm/day) compared to other precipitation homogenous regions and northwest will experience largest shift in precipitation. Interestingly, the number of wet days is expected to increase in the northwest region implying more VIMT towards the region. Our results indicate that monsoon precipitation extremes across all the homogenous regions will increase into the future with a higher severity under fossil-fuelled development, although the models still show large biases lowering confidence in our results.

Space-time cluster analysis and maximum entropy modeling of Peste des petits ruminants (PPR) in Türkiye.

Peste des petits ruminants (PPR) is an economically important highly serious transboundary disease that mainly occurs in small ruminants such as sheep and goats. The aim of this study was to identify the probability of risk and and space-time clusters of Peste des Petits Ruminants (PPR) in Türkiye. The occurrence of PPR in Türkiye from 2017 to 2019 was investigated in this study using spatial analysis based on geographic information system (GIS). Between these dates, it was determined that 337 outbreaks and 18,467 cases. The highest number of outbreaks were detected in the Central Anatolia region. It was determined that PPR is seen more intensely in sheep compared to goats in Türkiye. In this study, 34 environmental variables (19 bioclimatic, 12 precipitation, altitude and small livestock density variables) were used to explore the environmental influences on PPR outbreak by maximum entropy modeling (Maxent). The clusters of PPR in Türkiye were identified using the retrospective space-time scan data that were computed using the space-time permutation model. A PPR prediction model was created using data on PPR outbreaks combination with environmental variables. Nineteen significant (p < 0.001) space-time clusters were determined. It was discovered that the variables altitude, sheep density, precipitation in june, and average temperature in the warmest season made important contributions to the model and the PPR outbreak may be strongly related with these variables. In this study, PPR in Türkiye has been characterized significantly spatio-temporal and enviromental factors. In this context, the disease pattern and obtained these findings will contribute to policymakers in the prevention and control of the disease.

Site conditions rather than provenance drive tree growth, climate sensitivity and drought responses in European beech in Germany

Ongoing climate change and associated extreme events strongly impact the growth and vitality of forest ecosystems in Europe. Because of its’ high drought sensitivity, European beech, which is considered as climax tree species in large parts of Central Europe, may specifically suffer. Hence, recent studies increasingly focus on the resistance and resilience of beech growth to climate change. Intra-specific variations in growth responses by comparing different beech provenances, however, received less attention, as did the question whether provenance selection can be used to mitigate potential future negative impacts of climate change. Therefore, we here investigated 24 provenances belonging to the International Beech Provenance Trial growing at three sites in Germany along a latitudinal gradient (study sites are referred to as ’North’, ‘Center’, ‘South’). Specifically, we compared tree-ring width (TRW), diameter breast height (DBH), climate-growth relationships, as well as drought resistance and resilience in the extreme years 2003 and 2018. Large differences in growth performance were observed between the three study sites. At site North, beech trees showed the highest DBH and TRW. Tree growth was predominantly driven by previous-year October and current-year winter temperature, whereas growth at sites Center and South was significantly impacted by summer SPEI and constrained by precipitation in late winter and early June, respectively. Overall, drought responses in 2003 were less variable than in 2018. We found increasing resistance and decreasing resilience from the wetter North to the drier South, but with minimal differences between the Center and the South. Whereas differences between study sites were large, provenance differentiation within sites was comparably low, substantiating that beech is a highly plastic tree species. Even though some provenances were found to perform slightly better or worse, differences were not statistically significant and show unclear patterns. Hence, we conclude that climate change will affect beech forests in Europe mainly depending upon site conditions, and that provenance selection may not ensure superior growth performance.

Climatic limitations of nearly endangered Juniperus rigida populations at their range edges in semiarid China

The treat of climate warming is expected to increase the frequency and severity of droughts and significantly affect tree growth and distribution ranges, particularly in regions without monsoons. The distribution limits of tree species are highly susceptible to climate change. A deeper understanding of how tree species respond to climate across their distribution ranges is crucial for accurately predicting forest dynamics in the face of climate warming. Using tree ring width data from 586 trees at 19 sites spanning the northernmost and southernmost limits of Juniperus rigida (near-threatened, IUCN: NT), we assessed the growth responses of J. rigida to climate at different distribution range limits. We observed significant differences in tree-growth variability between the southern and northern populations of J. rigida, characterized by an increasing growth trend at the southern range limit, but a decreasing trend at the northern limit since 1996. Moreover, tree growth at their northern limit was hindered by high temperatures and SPEI during summer months, whereas it was constrained by low temperatures in March and precipitation in June at the southern limit. Particularly noteworthy is the increased sensitivity of growth to SPEI and precipitation in recent decades (1996–2018) compared to previous decades (1961–1995), particularly at their northern distribution edge. We therefore conclude that the growth of J. rigida trees at the southern limit could benefit from climate warming, while increasing warming and drought could limit tree growth or even cause tree mortality at the northern range limits. These findings may serve as an early warning for the growth and survival of J. rigida trees in open forests at their northern distribution edges in the face of future climate warming.

Climatic Predictors of Long‐Distance Migratory Birds Breeding Productivity Across Europe

ABSTRACTAimOngoing climate changes represent a major determinant of demographic processes in many organisms worldwide. Birds, and especially long‐distance migrants, are particularly sensitive to such changes. To better understand these impacts on long‐distance migrants' breeding productivity, we tested three hypotheses focused on (i) the shape of the relationships with different climate variables, including previously rarely tested quadratic responses, and on regional differences in these relationships predicted by (ii) mean climatic conditions and (iii) by the rate of climate change in respective regions ranging from Spain to Finland.LocationEurope.Time Period2004–2021.Major Taxa StudiedLong‐distance migratory passerine birds.MethodsWe calculated breeding productivity from constant effort ringing sites from 11 European countries covering 34° of latitude, and extracted temperature‐ and precipitation‐related climate variables from E‐OBS and NASA MODIS datasets. To test our hypotheses, we fitted GLMM and Bayesian meta‐analytic models.ResultsWe revealed hump‐shaped responses of productivity to temperature, growing degree‐days, green‐up onset date, and precipitation anomaly, and negative responses to intense and prolonged rains across the regions. The effects of March temperature and April growing degree‐days were more negative in cold than in warm regions, except for the region with the highest accumulated heat, whereas increasing June precipitation anomalies were associated with higher productivity in both dry and wet regions. Productivity responses to climate were unrelated to the rate of climate warming.Main ConclusionsThe influence of climate on bird productivity proved to be frequently nonlinear, as expected by ecological theory. The rate of climate change is less important than regional interannual variability in climate (which is predicted to increase), but this may change with the progression of climate change in the future. Productivity declines in long‐distance migratory songbirds are particularly expected if out‐of‐norm water excess increases in frequency or strength.

Long-Term Response of Floodplain Meadow Normalized Difference Vegetation Index to Hydro-Climate and Grazing Pressure: Tamir River Plains, Mongolia

The greenery of floodplain meadows in arid regions, such as Mongolia, is influenced by climate, hydrology, and land use. In this study, we analyzed the NDVI (Normalized Difference Vegetation Index) of two floodplain meadows located along the South Tamir and Tamir Rivers using LANDSAT images. Our goal was to observe NDVI spatial changes, variations, and mean values in mid-August every six years from 1991 to 2015 and to identify the factors driving these differences. To achieve this, we conducted variance analysis to identify changes in NDVI and implemented Principal Component Analysis to determine the influence of hydro-meteorological factors and grazing intensity. Our findings indicate a significant decrease in greenness, as measured by pixel-scale NDVI, during the late summer period. This decrease was consistently observed, except for a series of harsh winters that followed relatively dry summers, resulting in a disastrous event called dzud, which led to the death of livestock. The decrease in NDVI was amplified by lower precipitation in June, higher temperatures and wind speed in July, and increased precipitation in August, along with a higher frequency of days with convective rain. Our findings have important implications for managing grazing in Mongolia’s grasslands, promoting sustainable land use, and mitigating sandstorms. The variance and average values of NDVI at the pixel level can serve as reliable markers of sustainable pasture management in areas where other vegetation measures are limited.

Permafrost melting enhances growth but leads to less intra-annual density fluctuations in boreal Larix gmelinii forests at its southernmost limit in northeast China

Permafrost melting due to climate warming in recent decades has produced significant effects on forest ecosystems, especially the boreal biome at its southernmost limit in Asia. How this warming affects wood formation of trees at intra-annual resolution is unclear, yet is crucial for assessing the impact of permafrost melting on boreal forest growth. In this study, we compared the radial growth and intra-annual wood density fluctuations (IADFs) of Dahurian larch (Larix gmelinii Rupr.) at a permafrost (PF) and a non-permafrost (NPF) site at the southernmost permafrost limit in northeast China and quantified their relationships with climate factors. Drought in early summer was the main factor limiting growth of Dahurian larch. The basal area increment (BAI) of trees at both sites increased initially and then decreased in the 1980s, probably in response to warm-dry climate conditions. Earlywood IADFs (IADF-E) occurred in 14.0% and 9.3% of dated rings at the NPF and PF sites, while the frequency of latewood IADFs (IADF-L) was 6.8% and 2.7% at these two sites. The frequency of IADF-E in trees at both sites was positively and negatively related to June temperatures (and vapor pressure deficit) and precipitation, respectively, suggesting drought stress in June triggered the formation of IADF-E. The IADF-Ls were probably formed in response to warm temperatures in the late growing season. A higher BAI and a lower frequency of IADF-Es of trees at the PF site than at the NPF site indicated that permafrost melting could alleviate drought stress in early summer and promote radial growth of Dahurian larch. This greatly improved forest carbon sequestration and wood quality of some northeastern Asian boreal forests may offset to some extent the adverse effects of warming-drying climates at some sites of northeast Asia. Larch IADF-Es recorded extreme droughts in early summer, giving us a new sight for reconstructing high-frequency extreme climate events. If climate warming continues, the benefits of permafrost melting will gradually disappear and even turn negative due to warmer-dryer climate conditions. Our findings provide valuable information for boreal forest management and conservation under future global warming.

Variation in the strength and stationarity of southern longleaf pine seasonwood climate-growth relationships

Climate change is predicted to cause asymmetric warming and increased precipitation variability across different seasons. These changes and their effects may be captured in subannual seasonwood measures of tree growth (i.e., earlywood, latewood). Longleaf pine is a foundational tree species throughout the broad southeastern U.S. Its latewood growth may be more variable and sensitive to climate change than earlywood, but prior studies have geographical and ecological sampling limitations. Here, we use dendroecological methods to develop ring-width and seasonwood (earlywood, latewood, and adjusted latewood) chronologies and analyze climate-growth relationships for longleaf pine from eight sites in the Southern Coastal Plain of Florida, USA. Sites spanned a range of environmental conditions to generate an ecologically representative dataset. We evaluated chronology strength and variability and determined monthly and seasonal correlations with precipitation and temperature. We furthermore evaluated climate-growth stationarity using a moving response function and bootstrapped transfer function stability tests. We found adjusted latewood chronologies were most climatically sensitive although totalwood chronologies had higher interseries correlations. Totalwood measurements were more variable than early- or latewood year to year. Tree growth was positively correlated with summer precipitation at six out of eight sites and negatively correlated with late summer maximum temperatures at six out of eight sites. Negative relationships between growth and maximum temperature occurred earlier in the year at southern sites and the positive effect of June precipitation on tree growth was notable, found at six out of eight sites. However, the strength and significance of climate-growth relationships were non-stationary through space and time, with shifts largely occurring post-1950s. Longleaf pine at its southern range extent was less sensitive to climate than more northern populations, which may indicate non-linear responses to warming captured at the species’ range margin. Our results highlight dynamic climate-growth relationships related to the broad range of environmental conditions where longleaf pine is found.

Utilizing Machine Learning Framework to Evaluate the Effect of Climate Change on Maize and Soybean Yield

In recent years, climate change patterns and extreme weather events have adversely affected agricultural production and have raised concerns about its effect on crop yields. These changes can affect the crop yield in many ways including the changes in the length of the growing season, planting and harvest time windows, precipitation amount and frequency, and the growing degree days, etc. So, it is important to analyze the effect of climate change on yield variability for a better understanding of its effect on the crops. This study aims to analyze the historical monthly county-level data for the state of Ohio to quantify maize (Zea mays) and soybean (Glycine max) yield temporal variability and to study the impact of proposed climate change scenarios on the yield. Machine learning algorithms were used to model the effect of monthly temperature and precipitation levels on yield variability, and to study the effect of climate change scenarios on yield. In addition, yield prediction models were integrated with proposed climate change scenarios for higher and lower emissions scenarios to predict the maize and soybean yield for the year 2100. To model the effect of weather parameters on temporal yield variability, the Random Forest model outperformed with RMSE of 0.61 Mt/ha and R2 of 0.73 for maize and with RMSE of 0.21 Mt/ha, R2 of 0.64 for soybean crop. Maximum temperature for July which has a negative correlation with yield was found to be the most dominant parameter for maize yield followed by the precipitation in August, July, and June which have a positive correlation with maize yield. Precipitation in August was found to be the most dominant weather parameter for soybean yield followed by maximum temperature in July. Based on the projected average increase in Ohio’s temperature and precipitation levels alone, maize yield was predicted to drop by 13.2% or 18.5% respectively due to lower emissions and higher emissions climate change scenario of Ohio. Similarly, a 6.64% and a 9.63% drop is expected in the soybean yield by the year 2100 for both lower emissions and higher emissions climate change scenarios. In economic terms based on current commodity values, this is an astounding loss of 254.7 to 369.7 million USD for maize and 535.9 – 751.1 million USD for soybean crop to the state of Ohio.

Nitrogen addition alleviates the adverse effects of drought on plant productivity in a temperate steppe.

Drought and nitrogen enrichment could profoundly affect the productivity of semiarid ecosystems. However, how ecosystem productivity will respond to different drought scenarios, especially with a concurrent increase in nitrogen availability, is still poorly understood. Using data from a 4-year field experiment conducted in a semiarid temperate steppe, we explored the responses of aboveground net primary productivity (ANPP) to different drought scenarios and nitrogen addition, and the underlying mechanisms linking soil properties, plant species richness, functional diversity (community-weighted means of plant traits, functional dispersion) and phylogenetic diversity (net relatedness index) to ANPP. Our results showed that completely excluding precipitation in June (1-month intense drought) and reducing half the precipitation amount from June to August (season-long chronic drought) both significantly reduced ANPP, with the latter having a more negative impact on ANPP. However, reducing half of the precipitation frequency from June to August (precipitation redistribution) had no significant effect on ANPP. Nitrogen addition increased ANPP irrespective of drought scenarios. ANPP was primarily determined by soil moisture and nitrogen availability by regulating the community-weighted means of plant height, rather than other aspects of plant diversity. Our findings suggest that precipitation amount is more important than precipitation redistribution in influencing the productivity of temperate steppe, and nitrogen supply could alleviate the adverse impacts of drought on grassland productivity. Our study advances the mechanistic understanding of how the temperate grassland responds to drought stress, and implies that management strategies to protect tall species in the community would be beneficial for maintaining the productivity and carbon sequestration of grassland ecosystems under climate drought.

Radial growth response of Pinus Yunnanensis to climate in high mountain forests of northwestern Yunnan, southwestern China

Understanding the relationship between tree growth and environmental conditions is essential to elucidating the impact of global climate change on forest ecosystems. We used the dendrochronology method to examine the growth sensitivity of a typical conifer to climate change in mountain forests of Central Hengduan Mountain. The study involved the establishment of tree ring width chronologies of Pinus yunnanensis in both Haba Snow Mountain (HB) and Yulong Snow Mountain (YL) in northwestern Yunnan, enabling the detection of the relationship between its radial growth and climates, i.e., monthly total precipitation, monthly temperatures (average minimum, mean and maximum) and monthly Palmer Drought Severity Index (PDSI). Response function and redundancy analysis (RDA) were used to identify correlations between climate variables and radial growth, and moving interval analysis was applied to determine the stability of climate-growth relationship. The findings demonstrated that the growth of P. yunnanensis had similar response patterns to climate change at two sites, exhibiting growth synchronization and common signals. Specifically, the radial growth of P. yunnanensis was negatively correlated with May temperature, while temperature in current October significantly promoted radial growth. Precipitation in June was the common climate variable with inverse effects between two sites, with positive impacts on YL and negative impacts on HB. The results of moving interval analysis were consistent with response function and RDA, presenting significant correlations in many years for those climatic variables significantly affecting tree growth. Stability analysis also revealed that the climate-growth relationship could fluctuate over a small range of time scales, induced by an abrupt change in climate. A forecast of strengthen in growth of P. yunnanensis forests was expected, since increases in precipitation and temperature of most months would benefit tree growth, and negative impacts of May temperature would be offset by the increase of precipitation in the corresponding month. These results could provide a basis for developing sustainable strategies of forest management under the climate change.

Soils of xerophytic meadows of the Middle Podesen’ya: on the issues of accumulation of organic substances and biochemical activity

Relevance. Natural meadow communities, belonging to the dry meadows group, in the conditions of a decrease in floodplain of the leading water artery in the Bryansk region — the Desna River are characterized by significant changes in the mode of economic use. However, a significant part of dry meadows is used as pasture lands, so the regime of intensive exploitation of these lands significantly changes the ecological regimes of phytocenoses, reducing the carbon-depositing functions. For xerophytic (dry) meadows of natural origin, the establishment of soil carbon reserves, the identification of biochemical and microbiological activity is especially important in the light of the low stability of these communities under pasture load and wide distribution throughout the territory of the Middle Podesen’ya.Methods. The research provided for field route studies and in-house data processing using the methods of trial sites, the method of ecological and floral classification, the method of ecological scales (according to G. Ellenberg), ecological and chemical methods — determination of organic carbon, the weight method, biochemical and microbiological methods for the study of the biocompatible body.Results. For the soils of xerophytic (dry) meadows, for the first time, carbon-absorbing capacity, enzymatic activity for urease, catalase, cellulase, depending on the phytocenotic complex, has been established for the Middle Podesen’ya. A positive strong correlation has been established with organic carbon and average monthly precipitation in June, July and August. Over a two-year observation period, the amount of total organic carbon in the soil changed in a number of associations communities: Festuco ovinae-Koelerium delavignei &gt; control &gt; Agrimonio eupatoriae-Poetum angustifoliae &gt; Caro carvi-Deschampsietum &gt; Anthoxantho-Agrostietum tenuis &gt; Hieracio pilosellae-Agrostietum tenuis &gt; Koelerio delavignei-Festucetum rubrae &gt; Anthyllidi-Trifolietum montani &gt; Polygalo vulgaris-Anthoxanthoetum.

Change and influence of agroclimatic conditions on oat yield in Yakutia

The results of the dynamics analysis of multi-year meteorological indicators and study of their influence on the yield of the released oat varieties in different agroclimatic zones of Yakutia are presented. It is shown that in the period from 1960 to 2021 the mean annual air temperature in Central Yakutia (Pokrovsk meteorological station) increased annually by 0.045 °C, from 1999 to 2021 – by 0.088 °C, the number of dry years in June increased from 67 to 92% due to a 21% increase in years with medium (HTC = 0.41-0.60) and very strong (HTC &lt; 0.21) drought. In July, drought was recorded in 50% of the years, in August – in 38%. In all agroclimatic zones in the period from 2014 to 2021 for June – August the average daily air temperature annually increased by 0.16...0.34 °С and their sum by 14...28 °С, with precipitation decreasing by 3-16 mm and HTC value by 0.04-0.12 units. Climate change from 2014 to 2021 was 3 to 8 times more intense than from 1999 to 2022. There was a strong variability of yields of the released oat varieties in each agroclimatic zone: Central – from 0.38 to 2.14 t/ha (V = 60–73%), Zarechnaya – from 0.31 to 3.55 t/ha (V = 41–49%), Srednelenskaya – from 1.51 to 4.66 t/ha (V = 30–36%). The greatest annual decrease in grain yield of oat varieties (by 0.25–0.26 t/ha) was observed in arid agroclimatic zones – Central (Yakutsk SCTS) and Zarechnaya (Megino-Kangalassky SCTS) – compared to the wetter Srednelenskaya zone (Olyokminsky SCTS – by 0.10 t/ha). More significant influence on the yield in the Central and Zarechnaya zones was made by precipitation and HTC of the growing season (r = 0.77...0.84), in the Srednelenskaya zone – by temperature (r = – 0.79). Negative effect of temperature on the yield in the Central zone was observed in June (r = – 0.83), Zarechnaya zone - in July (r = – 0.83), in the Srednelenskaya zone – in August (r = –0.86). Precipitation and HTC had the greatest influence on the yield in the Central zone in June and July (r = 0.56...0.59), Zarechnaya zone – July and August (r = 0.60...0.76). In the Srednelenskaya zone the relationship of the yield with precipitation and HTC in June and July was positive (r = 0.23...0.37), in August – negative (r = – 0.57...– 0.71). Significant variability in grain yields of the released oat varieties indicates the variability of weather conditions and the need to cultivate oat varieties that provide a more stable yield in different agroclimatic zones of Yakutia.

The relationship between the Bay of Bengal summer monsoon retreat and early summer rainfall in East Asia

As the upstream region of the Asian summer monsoon, the Bay of Bengal summer monsoon (BOBSM) system has impacts on rainfall patterns in East Asia. In this study, we investigate the impact of the interannual variability of the BOBSM retreat on China precipitation in early summer (June) of the following year. When the BOBSM retreat occurs earlier in the previous year, we find enhanced rainfall in both the northeastern and eastern parts of China. Conversely, when the retreat of the BOBSM is delayed in the previous year, there is a tendency for decreased rainfall in most of northeastern and eastern China, while rainfall in the northern part of the Taiwan island region tends to increase. Statistical analysis demonstrates the co-variability between China’s June precipitation anomalies and preceding wind anomalies in the eastern Bay of Bengal. The results indicate a strong relationship between the preceding BOBSM retreat and China precipitation anomalies in the following June. Furthermore, the analysis suggests that the BOBSM retreat is more of an independent signal rather than modulated by an Indian Ocean Dipole event.

Hydrological dynamics of snowmelt induced streamflow in a high mountain catchment of the Pyrenees under contrasting snow accumulation and duration years

AbstractSnowmelt drives a large portion of streamflow in many mountain areas of the world. However, the water paths from snowmelt to the arrival of the water in the streams are still largely unknown. This work analyzes for first time the influence of snowmelt on spring streamflow with different snow accumulation and duration, in an alpine catchment of the central Spanish Pyrenees. This study presents the water balance of the main melting months (May and June). Piezometric values, water temperature, electrical conductivity and isotope data (δ18O) allow a better understanding of the hydrological functioning of the basin during these months. Results of the water balance calculations showed that snow represented on average 73% of the water available for streamflow in May and June while precipitation during these months accounted for only 27%. However, rainfall during the melting period was important to determine the shape of the spring hydrographs. On average, 78% of the sum of both the snow water equivalent (SWE) accumulated at the beginning of May and the precipitation in May and June converted into runoff during the May–June melting period. The average evaporation‐sublimation during the 2 months corresponded to 8.4% of the accumulated SWE and rainfall, so that only a small part of the water input was ultimately available for soil and groundwater storage. When snow cover disappeared from the catchment, soil water storage and streamflow showed a sharp decline. Consequently, streamflow electrical conductivity, temperature and δ18O showed a marked tipping point towards higher values. The fast hydrological response of the catchment to snow and meteorological fluctuations, as well as the marked diel fluctuations of streamflow δ18O during the melting period, strongly suggests short meltwater transit times. As a consequence of this hydrological behaviour, independently of the amount of snow accumulated and of melting date, summer streamflow remained always low, with only small runoff peaks driven by rainfall events.

Soil water sources and their implications for vegetation restoration in the Three-Rivers Headwater Region during different ablation periods

Abstract. Amid global warming, the timely supplementation of soil water is crucial for the effective restoration and protection of the ecosystem. It is therefore of great importance to understand the temporal and spatial variations of soil water sources. The research collected 2451 samples of soil water, precipitation, river water, ground ice, supra-permafrost water, and glacier snow meltwater in June, August, and September 2020. The goal was to quantify the contribution of various water sources to soil water in the Three-Rivers Headwater Region (China) during different ablation periods. The findings revealed that precipitation, ground ice, and snow meltwater constituted approximately 72 %, 20 %, and 8 % of soil water during the early ablation period. The snow is fully liquefied during the latter part of the ablation period, with precipitation contributing approximately 90 % and 94 % of soil water, respectively. These recharges also varied markedly with altitude and vegetation type. The study identified several influencing factors on soil water sources, including temperature, precipitation, vegetation, evapotranspiration, and the freeze–thaw cycle. However, soil water loss will further exacerbate vegetation degradation and pose a significant threat to the ecological security of the “Chinese Water Tower”. It emphasizes the importance of monitoring soil water, addressing vegetation degradation related to soil water loss, and determining reasonable soil and water conservation and vegetation restoration models.

Potential impact of climatic factors on the distribution of Graphium sarpedon in China.

Graphium sarpedon is a significant foliar pest of Laurel plants in China. In this study, the MaxEnt model was used to investigate the distribution of G. sarpedon and predict its potential distribution areas in China in the future (2050s and 2090s) based on three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5), and key environmental variables affecting its distribution were identified. The results showed that under the current climatic conditions, the suitable distribution areas of G. sarpedon were 92.17°-134.96° E and 18.04°-33.61° N, including Yangtze Plain (Middle and Lower), Pearl River Delta, Yangtze River Delta, and Lingnan areas. Under the future climate conditions, the total suitable distribution area of G. sarpedon decreased, but the area of medium suitable area increased. The study identified 11 key environmental variables affecting the distribution of G. sarpedon, the most critical of which was Precipitation of Warmest Quarter (bio18) and precipitation in April, May, June, and September (prec4, prec5, prec6, and prec9). This study is beneficial for monitoring and preventing the possible changes of G. sarpedon and provides theoretical references for its prevention and control.

The palaeoclimatic potential of recent oak tree-ring width chronologies from Southwest Ukraine

Better insights into spatio-temporal climate signals are needed to understand more clearly the applicability to palaeoclimatic analysis and dendrochronological dating of the long tree-ring oak chronologies currently being compiled in Eastern Europe. This study investigates the climate sensitivity of two recent oak tree-ring width (TRW) chronologies from Transcarpathian and Ciscarpathian Ukraine and their coherence with 35 oak chronologies from Ukraine, Poland, Slovakia, Romania, and Hungary. The new Transcarpathian chronology consists of 247 TRW series of living trees from 13 sites covering the period 1836–2020, while the new Ciscarpathian chronology consists of 215 TRW series from 13 sites and spans the period 1775–2020. Despite the strong similarity between these two chronologies, their responses to climate differ significantly. Growing-season precipitation and particularly drought (three-month SPEI index) were found to be the primary drivers of oak growth on the border between the Carpathians and the northeastern Pannonian Basin. Spatial correlations of the Transcarpathian chronology show particularly high explained variability in the April-August SPEI index, roughly between 18.5–28.5°E and 45–52°N. In the Ciscarpathian, June precipitation primarily influenced oak radial growth but the spatial correlation was quite low. While the Transcarpathian TRW chronology was strongly correlated with eastern Slovakian and northwestern Romanian chronologies, the Ciscarpathian chronology revealed very low correlations with surrounding chronologies. This study indicates the great dendroarchaeological and palaeoclimatic potential of the Transcarpathian chronology and points to the need to analyse additional living trees from the Ciscarpathian region to understand the spatial variability of oak growth and its climate signal better.