Periods Of Precipitation Research Articles

Contrasting the Intraseasonal Precipitation in the Western and Eastern North Pacific During Boreal Winter

AbstractThe wintertime North Pacific exhibits two types of intraseasonal periodicity in daily precipitation, with a period of 10–20 and 30–90 days in the western and eastern North Pacific. This study aims to identify and compare characteristics and mechanisms of intraseasonal precipitation in these two regions using daily observational data. Our results indicate their notable differences in atmospheric circulations and dynamical processes, despite similarities in moisture sources. A wave train associated with the intraseasonal precipitation in the western North Pacific characterized by anomalous cyclones and anticyclones from West Siberia into the North Pacific is observed, accompanied by anomalous wave activity. By diagnosing local finite‐amplitude wave activity (LWA) budget, we demonstrate that the baroclinic eddy generation initiates the upstream growth of wave activity, whereas its downstream development is primarily attributed to the zonal advection of wave train. The upstream wave train induces barotropic and baroclinic instabilities in Kuroshio‐Oyashio extension (KOE). In contrast, the anomalous atmospheric circulations related to intraseasonal precipitation in the eastern North Pacific feature a tripolar structure, with downstream propagation of wave activity from the eastern North Pacific to the North American continent. Diabatic heating, along with local eddy generation, contributes to the upstream growth of wave activity. Residual term, possibly linked to the wave activity dissipation associated with wave breaking, extends the wave activity downstream. Thermal and baroclinic instabilities, associated with the diabatic heating and local eddy generation, create favorable conditions for the precipitation. This study may contribute to the improvement of intraseasonal precipitation prediction over the pan‐North Pacific region.

Air temperature and precipitation constraining the modelled wetland methane emissions in a boreal region in northern Europe

Abstract. Wetland methane responses to temperature and precipitation are studied in a boreal wetland-rich region in northern Europe using ecosystem process models. Six ecosystem models (JSBACH-HIMMELI, LPX-Bern, LPJ-GUESS, JULES, CLM4.5, and CLM5) are compared to multi-model means of ecosystem models and atmospheric inversions from the Global Carbon Project and upscaled eddy covariance flux results for their temperature and precipitation responses and seasonal cycles of the regional fluxes. Two models with contrasting response patterns, LPX-Bern and JSBACH-HIMMELI, are used as priors in atmospheric inversions with Carbon Tracker Europe–CH4 (CTE-CH4) in order to find out how the assimilation of atmospheric concentration data changes the flux estimates and how this alters the interpretation of the flux responses to temperature and precipitation. Inversion moves wetland emissions of both models towards co-limitation by temperature and precipitation. Between 2000 and 2018, periods of high temperature and/or high precipitation often resulted in increased emissions. However, the dry summer of 2018 did not result in increased emissions despite the high temperatures. The process models show strong temperature and strong precipitation responses for the region (51 %–91 % of the variance explained by both). The month with the highest emissions varies from May to September among the models. However, multi-model means, inversions, and upscaled eddy covariance flux observations agree on the month of maximum emissions and are co-limited by temperature and precipitation. The setup of different emission components (peatland emissions, mineral land fluxes) has an important role in building up the response patterns. Considering the significant differences among the models, it is essential to pay more attention to the regional representation of wet and dry mineral soils and periodic flooding which contribute to the seasonality and magnitude of methane fluxes. The realistic representation of temperature dependence of the peat soil fluxes is also important. Furthermore, it is important to use process-based descriptions for both mineral and peat soil fluxes to simulate the flux responses to climate drivers.

Climate matching models for Ceratapion basicorne (Coleoptera: Apionidae), a biocontrol agent of yellow starthistle

Abstract Ceratapion basicorne (Illiger) (Coleoptera: Apionidae), a weevil native to Europe and western Asia, shows promise for enhancing the control of yellow starthistle (Centaurea solstitialis L.), an invasive annual forb in the western United States. However, a paucity of data on this biocontrol agent’s environmental constraints has made it difficult to assess the suitability of potential release locations. Climate matching models were developed for C. basicorne to help identify areas of the western United States with similar climates to the source area of breeding colonies being used for releases (home location). The models used climate variables derived from daily estimates of minimum temperature, maximum temperature, precipitation, and soil moisture for a 30-yr period spanning 1991–2020 at 1 km2 resolution. Of the areas where C. solstitialis is known to occur, the Central California Foothills, Eastern Cascades Foothills, Columbia Plateau, and mountainous parts of northcentral Utah had the most similar climates to the home location. Of these areas, the Eastern Cascades foothills in northeastern California and Wasatch Range in Utah occurred at a similar latitude as the home location, which may be important to consider if C. basicorne has photoperiodic diapause. The least similar climates occurred in wet coastal regions, high-elevation (cold) mountains, and hot deserts; however, C. solstitialis has not been detected in most of these areas. The development of process-based models for predicting the establishment of this agent will require a more detailed understanding of the agent’s requirements for development and survival.

Analysis of Spatiotemporal Variation in Precipitation on the Loess Plateau from 1961 to 2016

This study utilized annual precipitation data collected from 76 meteorological stations located on the Loess Plateau and its adjacent regions. It employed empirical orthogonal function (EOF) analysis, the Mann–Kendall trend test (M-K), and continuous wavelet transform (CWT) to investigate the spatial distribution patterns, temporal trends, and periodicity of annual precipitation from 1961 to 2016. The results showed the following: (1) The long-term averages of annual rainfall on the Loess Plateau exhibited a general decline from the southeast to the northwest, with certain areas demonstrating a trend of reduction radiating outward from the central region. This precipitation regime was fundamentally governed by the interplay between geographic coordinates and topo-graphical characteristics. Nevertheless, this spatial distribution pattern is expected to undergo changes in the future. (2) Annual precipitation in the southern and eastern parts decreased significantly, while the western part reported the greatest increase, and thus the spatial variability of precipitation will decrease in the future. (3) Annual precipitation on the Loess Plateau generally has a period of about 4 years. The wavelet coherence analysis reveals that El Niño events, occurring over a brief 4-year interval, correlate with diminished precipitation patterns across the eastern and southern sectors of the Loess Plateau, consequently attenuating the precipitation’s spatial variability throughout the entire geographical domain. Therefore, in the future, when El Niño occurs, it is necessary to prevent droughts in the eastern and southern regions of the Loess Plateau.

Ecological Profile of the Flea Beetle Genus Calotheca Heyden in South Africa (Chrysomelidae, Galerucinae, Alticini).

In this work, the 25 species of the flea beetle genus Calotheca Heyden recorded for South Africa are considered. Starting from the updated species distribution and the topographic, temperature, and precipitation variables, as well as the vegetation types in the occurrence sites, through an analysis of ecological niche modelling, a possible ecological profile is provided, both for each species and the entire genus, highlighting some of the factors that drive their occurrence and distribution patterns. Along with the vegetation type, some climatic variables were found to be particularly influential, such as the mean temperature of both the wettest and driest quarters and also the mean precipitation of the wettest period. Finally, comparing the distribution of the areas of highest suitability returned by the model obtained for Calotheca, they largely overlap with the highest-density areas of Searsia, genus of Anacardiaceae, including the main host plants for these flea beetles.

Assessing water resource vulnerability based on remote sensing data-enhanced SWAT+ and High-Resolution precipitation data

Climate change and human activities have significantly impacted the global water cycle, increasingly threatening water security across various sectors. By improving the performance of hydrological models in simulating the water balance, including precipitation and evapotranspiration, we can better support decision-making for regional water resource management and the deployment of climate change adaptation measures. This study aims to enhance the simulation performance of the vegetation growth module in the SWAT + model and reduce its uncertainty by dynamically updating the model’s data files with satellite-derived leaf area index and phenology data. Additionally, this study modified the weather station allocation mechanism in SWAT + to fully utilize the high-resolution meteorological data grids. The simulation results show that the enhanced SWAT + model achieved a Nash-Sutcliffe Efficiency (NSE) between 0.84 and 0.90 and a PBIAS of less than 6 % for daily streamflow simulations at four hydrological stations in the Weihe River Basin. The enhanced SWAT + model’s water balance simulation results for the Weihe River Basin were used to analyze the vulnerability of water resources within the basin. The results indicate that the Qinling region, benefiting from its well-developed forest ecosystems, has the lowest green water vulnerability. The overall blue water vulnerability of the basin reached 1.12, suggesting that during periods of insufficient precipitation or intense evaporation, blue water resources may not meet the demands of agriculture, industry, ecology, and residential use. Among these, agricultural water use exhibits the highest vulnerability. Efficient irrigation technologies can be employed to improve irrigation water use efficiency, and the use of treated reclaimed water for agricultural irrigation can be promoted to reduce the demand for fresh blue water resources.

Changes in Extreme Daily Precipitation over the Contiguous United States from Convection-Permitting Simulations

Abstract The potential for changes in extreme precipitation events due to anthropogenic climate change may have significant societal impacts (e.g., agricultural productivity, property loss, and mortality). This project uses a dynamically downscaled, convection-permitting regional climate model to investigate extreme daily precipitation in the CONUS, defined explicitly as the 99th percentile 24-h accumulated value. The simulation output includes a historical (HIST) baseline (1990–2005) and two epochs at the end of the twenty-first century (EOC; 2085–2100) under intermediate and pessimistic emissions scenarios. Independent observations illustrate that HIST admirably represents extreme precipitation climatology for most locations in the domain. Comparisons between HIST and the two EOC scenarios for the 99th percentile of daily precipitation show statistically significant increases during December–May across the Midwest and Ohio Valley and statistically significant decreases for the southern Great Plains during December–February. Extreme value analysis further reveals increasing variability in precipitation extremes for eight climatologically unique cities across the CONUS by the end of the twenty-first century and significant increases in return period precipitation amounts for most cities examined. These results provide additional guidance for stakeholders to reduce societal impacts and economic loss from daily precipitation extremes and create a more climate-resilient society. Significance Statement This study uses a novel convection-allowing regional climate model to illustrate potential future changes in daily extreme rainfall amounts due to climate change. Future scenarios project robust increases in these events during some seasons for portions of the Midwest and Ohio Valley, whereas the southern Great Plains are projected to experience decreases. Furthermore, we find a notable increase in the variability of extreme daily precipitation across various CONUS cities by the end of the twenty-first century. Overall, our results further our understanding of how extreme precipitation events may change in the future and, therefore, help policymakers and stakeholders adapt to these impactful events.

Analysis of Water Dynamics at the Effluent Treatment Station of Cooperoque: Evaluation of Precipitation, Evaporation, and Infiltration of Effluent from a Milk Refrigeration Station

Purpose: The study aims to analyze water dynamics at the Cooperoque Effluent Treatment Station, focusing on the interactions between precipitation, evaporation, and effluent infiltration to enhance water resource management. Theoretical reference: The research references various studies and methodologies related to the quantification of evaporation from lakes and reservoirs, particularly in semi-arid regions, utilizing the Jensen-Haise Method for evaporation estimation. The research aligns with previous studies, such as Mallmann (2014), on water infiltration in soil management, emphasizing the importance of understanding water dynamics for sustainable resource management. Method: The study employs the Jensen-Haise Method to calculate evaporation rates, covering the period from January 2023 to October 2024. It examines the effects of precipitation, evaporation, and effluent infiltration on tank levels. Results and conclusion: The results reveal that tank levels are influenced by precipitation, evaporation, and effluent infiltration, with more significant declines during dry months and smaller reductions during periods of high precipitation. Evaporation rates, calculated using the Jensen-Haise Method, are higher in warmer months, contributing to lower tank levels, while these rates decrease in colder months. A notable anomaly occurred in May 2024 when effluent infiltration exceeded the volume of generated effluents and rainfall due to the activation of an irrigation system. Key findings indicate that lake levels drop more during dry months, with a significant negative water balance observed in May 2024 due to excessive infiltration during heavy rainfall. The study concludes that adaptive water management strategies are necessary to address climatic variations and improve the efficiency of the effluent treatment system. Implications of research: The research provides valuable insights for developing adaptive water management strategies to address climatic variations and improve the efficiency of effluent treatment systems. Continuous monitoring is emphasized as crucial for sustainable water resource management. Originality/value: The study highlights the complex interactions between precipitation, evaporation, and effluent dynamics, offering a foundation for improved water management practices and contributing to the preservation of regional water resources. The study contributes to the understanding of water dynamics at effluent treatment stations, offering practical insights for managing water resources effectively. It highlights the importance of adaptive strategies and continuous monitoring to maintain pond levels and optimize the treatment process.

Extremely rapid, yet noncatastrophic, preservation of the flattened-feathered and 3D dinosaurs of the Early Cretaceous of China

Northeast China's Early Cretaceous Yixian Formation preserves spectacular fossils that have proved extraordinarily important in testing evolutionary hypotheses involving the origin of birds and the distribution of feathers among nonavian dinosaurs. These fossils occur either flattened with soft tissue preservation (including feathers and color) in laminated lacustrine strata or as three-dimensional (3D) skeletons in "life-like" postures in more massive deposits. The relationships of these deposits to each other, their absolute ages, and the origin of the extraordinary fossil preservation have been vigorously debated for nearly a half century, with the prevailing view being that preservation was linked to violent volcanic eruptions or lahars, similar to processes that preserved human remains at Pompeii. We present high-precision zircon U-Pb geochronology from cores and outcrops, demonstrating that Yixian Formation accumulation rates are more than an order of magnitude higher than usually estimated. Additionally, we provide zircon provenance and sedimentological data from 3D dinosaur fossils, which imply that their death and burial occurred in collapsed burrows, rather than via a catastrophic volcanogenic mechanism. In the studied area, the three principal fossil-rich intervals of the Yixian occur as a cyclic sequence that correspond to periods of high precipitation. Using Bayesian-Markov Chain Monte Carlo approaches, we constrain the total duration of the sequence to less than ~93,000 y and suggest that climatic precession paced the expression of these cyclic sediments. Rather than representing multiple, Pompeii-like catastrophes, the Yixian Formation is instead a brief snapshot of normal life and death in an Early Cretaceous continental community.

Assessment of the impact of precipitation on environmental radiation levels: A case study of yeonggwang

This study investigated the correlation between different levels of precipitation and environmental radiation levels, focusing specifically on the Yeonggwang region adjacent to the Hanbit Nuclear Power Plant (NPP). The analysis utilized a dataset comprising environmental radiation and meteorological measurements collected from 2017 to 2023. To accomplish this, the study employed statistical methods like t-tests and ANOVA to assess whether significant variations in environmental radiation levels correspond to the presence or absence of precipitation and across varying precipitation intensities. Precipitation data were segmented into distinct categories—no rain, light rain (0–1 mm/h), and heavy rain (over 1 mm/h)—for a detailed analysis. The t-test results show a statistically significant elevation in environmental radiation levels during precipitation compared to conditions with no rain. Further ANOVA analysis confirms that this increase in environmental radiation levels is uniform across all regions and seasons, with the most pronounced increases during periods of heavy precipitation. The findings from this study could have important implications for enhancing radiation monitoring and safety protocols at nuclear facilities. These results highlight the necessity for ongoing, detailed monitoring of environmental radiation and meteorological conditions to more effectively predict and mitigate potential increases in radiation exposure due to precipitation.

Multifactor Analysis of Surface Deformation Dynamics during Economic Development

Surface deformation presents considerable hazards, significantly complicating the safeguarding of coastal urban infrastructure. Coastal region infrastructure and buildings are at risk due to climate change, sea level rise, and potential geohazards. This study aims to investigate the coupling between surface deformation and driving factors during the economic development of the Tianjin-Langfang region. Time series interferometric synthetic aperture radar technology is crucial for monitoring the spatiotemporal evolution of coastal cities in preventing geological disasters. SBAS-InSAR technology was utilized in long sequence observations, revealing that surface deformation in the Tianjin area from 2016 to 2023 ranged between –50 to 30 mm/year, and it showed a trend of first decreasing and then rising since 2016. During the research period, comprehensive analysis was conducted using data such as rainfall, land use conversion, groundwater depth characteristics, and seasonal changes. It was found that the deformation in the study area is closely related to key economic development industries. Analysis of groundwater aquifer depth and rainfall data revealed spatiotemporal heterogeneity in deformation rebound. Specifically, surface deformation was greater during months with little or no rainfall compared to periods of precipitation. We discussed the intensity of surface deformation and, in conjunction with the geological environment, provided assessments and recommendations for buildings and infrastructure in severely affected areas.

Impact of Harvest Delay and Barley Variety on Grain Nutritional Composition and Mycotoxin Contamination.

This study investigated the effects of delayed harvesting, varying meteorological conditions, and barley variety on Fusarium spp. infection rates, nutritional composition, and mycotoxin contamination in barley grains. Field experiments were conducted from 2020 to 2022 and involved two barley varieties: 'Laureate' for malting and 'Luokė' for feed. The results indicated that the dominant Fusarium species isolated were F. avenaceum, F. culmorum, F. poae, F. sporotrichioides, F. tricinctum, and F. equiseti. These tended to increase in number with delayed harvest times and were more prevalent during harvest periods of higher precipitation (p < 0.05). Malting barley had higher starch and lower protein content compared to feed barley (p < 0.05). Delayed harvesting generally increased dry matter, crude fat, and crude ash contents while decreasing crude protein, zinc, and iron contents (p < 0.05). Mycotoxin analysis revealed significant differences under specific weather conditions. HT-2 toxin levels were higher under slightly warmer and wetter conditions during flowering, with harvest conditions similar to the long-term average. Zearalenone levels increased with dry, warm growing seasons followed by rainy harvests. Nivalenol and enniatin levels increased with rainy growing seasons and dry, warm harvests. Deoxynivalenol concentrations did not reach the limit of quantification throughout the study. No consistent trend was observed for higher contamination in any specific barley variety (p > 0.05). The strongest correlations between mycotoxins and nutritional value indicators were observed with less-studied mycotoxins, such as nivalenol and enniatins, which exhibited negative correlations with crude protein (p < 0.01), crude fat (p < 0.05), and zinc (p < 0.01), and positive correlations with crude ash (p < 0.05) and phosphorus (p < 0.01).

Assessment of Emergency Water Sources Using Electrical Resistivity Tomography: A Case Study in the Longmen Shan Fault Zone

The Longmen Shan fold and thrust belt, situated on the eastern margin of the Qinghai–Tibet Plateau, is prone to disasters like earthquakes and debris flows. Thus, applying rapid assessment methods for emergency water sources in disaster-affected areas is crucial for local populations and ensuring an effective response to disasters. In this study, we employed electrical resistivity tomography (ERT) to investigate groundwater resources in post-disaster regions. By integrating the results from ERT profiles with geological and borehole information, we determined the lithology and depth of aquifers. Additionally, we analyzed groundwater recharge and discharge patterns relative to surface water during various precipitation periods and generated a hydrogeological profile for the region. Borehole information confirmed our inferred lithology and aquifer depth, thereby ensuring a reliable water supply during emergencies. This study demonstrates the feasibility of ERT for rapidly identifying water resources in geologically complex environments, providing a scientific foundation for water resource management in disaster-prone regions.

Comparison of Different Numerical Methods in Modeling of Debris Flows—Case Study in Selanac (Serbia)

Flow-type landslides are not typical in this region of the Balkans. However, after the Tamara cyclone event in 2014, numerous such occurrences have been observed in Serbia. This paper presents the initial results of a detailed investigation into debris flows in Serbia, comparing findings from two programs: RAMMS DBF and Geoflow SPH. Located in Western Serbia, the Selanac debris flow is a complex event characterized by significant depths in the initial block and entrainment zone. Previous field investigations utilized ERT surveys, supplemented by laboratory tests, to characterize material behavior. Approximately 450,000 m3 of material began to flow following an extreme precipitation period, ultimately traveling 1.2 km to the deposition zone. For validation purposes, ERT profiles from both the deposition zone and the source area were utilized, with particular attention given to areas where entrainment was substantial, as this had a significant impact on the final models. The first objective of this research is to conduct a detailed investigation of debris flow using field investigations: geophysical (ERT) and aerial photogrammetry. The second objective is to evaluate the capacity of two debris flow propagation models to simulate the reality of these phenomena. The GeoFlow-SPH code overestimated the maximum propagation thickness in comparison to the RAMMS model. The numerical results regarding final depths closely align, especially when considering the estimated average depth in the deposition zone. The results confirm the necessity of using multiple simulation codes to more accurately predict specific events.

Non-breeding conditions induce carry-over effects on survival of migratory birds

Identifying the processes that limit populations is a foundational objective of ecology and an urgent need forconservation. For migratory animals, researchers must study individuals throughout their annual cycles to determine how environmental conditions limit demographic rates within each period of the annual cycleand also between periods through carry-over effects and seasonal interactions.1,2,3,4,5,6 Our poor understanding of the rates and causes of avian migration mortality7 hinders the identification of limiting factors and the reversal of widespread avian population declines.8,9 Here, we implement new methods to estimate apparent survival (hereafter survival) during migration directly from automated telemetry data10 in Kirtland's Warblers (Setophaga kirtlandii) and indirectly from mark-recapture data in Black-throated Blue Warblers (S.caerulescens). Previous experimental and observational studies of our focal species and other migratory songbirds have shown strong effects of Caribbean precipitation and habitat quality on food availability,11,12,13,14 body condition,12,13,14,15,16,17,18,19 migration timing,11,12,15,16,20,21,22,23 natal dispersal,24,25 range dynamics,26 reproductive success,20,22,27 and annual survival.18,19,20,23,28,29,30,31 Building on this research, we test the hypotheses that environmental conditions during the non-breeding period affect subsequent survival during spring migration and breeding. We found that reduced precipitation and environmental productivity in the non-breeding period strongly influenced survival in both species, primarily by reducing survival during spring migration. Our results indicate that climate-driven environmental conditions can carry over to affect survival in subsequent periods and thus likely play an important role in year-round population dynamics. These lethal carry-over effects may be widespread and are likely magnified by intensifying climate change.

Detection of Dominant Rainfall Patterns in Indonesian Regions Using Empirical Orthogonal Function (EOF) and Its Relation with ENSO and IOD Events

Several studies indicate that Indonesia’s position on the equator, where winds from the northern and southern hemispheres converge, leads to year-round rainfall in Indonesia. Previous studies have also shown the presence of monsoon winds over Indonesia, which causes rain in Indonesia to follow the Asian and Australian monsoon wind patterns. Recently, variations in rainfall patterns and intensity in Indonesia have been highly volatile and difficult to predict. This study uses gridded data analysis of ocean-atmospheric rainfall for 69 years (1948–2016) to detect monsoonal, equatorial, and local signals and relate them to ENSO and IOD events. Rainfall analysis reveals that the first mode accounts for 38.57%, the second 13.92%, and the third 8.93% of the total variance. These results show that these variants are very variable, both in space and time. Monsoonal patterns were detected in the southern region of Indonesia, equatorial patterns in northern Sumatra and western Kalimantan, while local patterns were detected in Maluku and the Maluku Islands. Furthermore, the monsoonal and local rainfall patterns are strongly correlated (&gt; 0.85) with local SST, but the equatorial rainfall pattern is weakly correlated (&lt; 0.5) with local SST. Note that the equatorial pattern is associated with the Inter Tropical Convergence Zone (ITCZ) phase. The varied vector correlation map illustrates the asymmetric fluctuations in sea surface temperature and the simultaneous existence of winds coming from the west from the Indian Ocean and winds coming from the east from the Pacific Ocean during the period of heavy precipitation.

Algorithmically detected rain-on-snow flood events in different climate datasets: a case study of the Susquehanna River basin

Abstract. Rain-on-snow (RoS) events in regions of ephemeral snowpack – such as the northeastern United States – can be key drivers of cool-season flooding. We describe an automated algorithm for detecting basin-scale RoS events in gridded climate data by generating an area-averaged time series and then searching for periods of concurrent precipitation, surface runoff, and snowmelt exceeding predefined thresholds. When evaluated using historical data over the Susquehanna River basin (SRB), the technique credibly finds RoS events in published literature and flags events that are followed by anomalously high streamflow as measured by gauge data along the river. When comparing four different datasets representing the same 21-year period, we find large differences in RoS event magnitude and frequency, primarily driven by differences in estimated surface runoff and snowmelt. Using dataset-specific thresholds improves agreement between datasets but does not account for all discrepancies. We show that factors such as meteorological forcing and coupling frequency, as well as choice of land surface model, play roles in how data products capture these compound extremes and suggest care is to be taken when climate datasets are used by stakeholders for operational decision-making.

Assessing the Impacts of Climate Change on Geographical Distribution of Tea (Camellia sinensis L.) in Kenya with Maximum Entropy Model

Climate change has been disturbing the present species distribution ranges, resulting in the shifting of cultivation areas and decreases in production and quality. Tea (Camellia sinensis L.), which seeks optimum climatic resources, is a key cash crop economically in Kenya. In this study, the shifting of tea suitability was projected with the MaxEnt model under the SSP (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) climate scenarios for the 2050s and 2090s relative to the 1970–2000 distribution. Analysis under the current climatic condition showed that the proportions of optimal and medium- and marginal-suitable areas were 2%, 3%, and 24% of the total area, respectively, and located in south-western (SW), central, and north-eastern (NE) Kenya and, to some extent, in the Rift Valley. It was projected that the potential suitable tea-growing areas would migrate from the western areas to the central, eastern, and north-eastern highlands in Kenya. It was detected that the precipitation of the driest period (July), precipitation of the wettest quarter (April, May, and June), and annual temperature range could be the main climatic factors determining the shift in tea distribution. Compared to the current distribution (29%), the climatically suitable areas for tea production could reach 32.58% of Kenya’s land area under the SSP1-2.6 scenarios in the 2050s and 35.08% in the 2090s under the SSP5-8.5 scenario. On the contrary, it was found that the optimal climate-suitable habitats were projected to shrink by 2% and 1% in the 2050s and 2090s under all scenarios on the west side of the Great Rift Valley compared to the current distribution. In comparison, the sizes of medium- and marginal-suitable habitats would increase by 1% and 3%, respectively. The findings indicated that unless adaptive climate actions are taken, climate change could reduce the tea planting areas in western Kenya. Meanwhile, climate suitability was projected to expand upward on the east side of the Rift Valley, enhancing the potential distribution of tea. The developed climate information could be used to design and implement adaptation interventions in the lower elevation areas. Finally, we highlight that the available scientific literature on the climate suitability of tea in Kenya should be broadened by adding non-climatic factors.

Mitigating the effects of extreme weather on crop yields: insights from farm management strategies in the Netherlands

Abstract Weather extremes can drive substantial crop losses. Farm level management strategies play a critical role in mitigating the impacts of and consequences for farmer livelihoods and food security. While the impacts of extreme weather on crop yields are well documented in recent studies, these predominantly focused on expansive geographical scales and commonly overlooked the critical role of management practices in modulating the dynamics of weather-crop sensitivities. In our study, a unique data-set is used that explores the timely relationship between extreme weather and crop yields at farm level in the Netherlands. We cover 10 types of crops and elucidate the role of soil types, irrigation and nutrient application in modulating the relationship between extreme weather and crops. We show substantial impacts from drought during the growing- and harvesting period and excessive precipitation during the planting- and growing period. Severe droughts show significant (p≤0.05) reductions in yield for all crops, and lead to yield reductions up to 24 percent relative to average yields during the growing period. Meanwhile, eight crops show significant reductions in yield due to severe water excess during the planting period, with yield reductions up to 18 percent. Soils such as sand or loess amplify the negative impact of drought on crop yield, while softening the impact of excessive precipitation. Irrigation and to a lesser extent nutrient application are shown to moderately decrease the impact of extreme weather on crop yield. Our findings contribute valuable insights to guide local adaptation priorities which are critical given the projected increase in the intensity and frequency of extreme weather under climate change.

Spatial and Temporal Variations of Climate Resources during the Growing Season of Early-Season Rice in Hunan Province

The rising temperatures and changes in precipitation due to climate change have significantly impacted agricultural production. Evaluating the effects of climate change on rice production is crucial for improving rice cultivation techniques and ensuring food security. It is essential to comprehensively examine the climatic, spatial, and temporal variations during the duration of crop production. Previous research has mainly focused on different rice planting areas, rice types, and various growth stages of rice. However, more research is needed on the climatic changes during the crop-growing season in specific regions. Therefore, this study compiled complete daily meteorological data from 37 meteorological stations in Hunan Province from 1961 to 2020. The period from 1961 to 2020 was divided into three segments: 1961–1980 (a), 1981–2000 (b), and 2001–2020 (c), to analyze the characteristics of agricultural climate resource changes during different growth stages of early-season rice in Hunan Province. Results show that the heat resources were significantly increased (accumulated temperature growth rate of 43.36 °C/10a), the sunshine resources were decreased by −14.60 h/10a, and the precipitation resources were slightly increased by 6.85 mm/10a. The increase in heat resources mainly occurs during the vegetative growth stage of early-season rice. Additionally, the high-value regions of heat resources and precipitation in period c are 97.8% and 34.2% higher than the average values of periods a and b, respectively. In contrast, the regions with high sunshine hours significantly decreased in period c compared to periods a and b. In summary, the heat, sunshine, and water resources in the central and eastern regions of Hunan Province increase simultaneously, and appropriate cultivation measures should be adopted in the future to improve the yield and resource utilization efficiency of early-season rice in a double-cropping system.