Changes In Mean Precipitation Research Articles

Next-Generation Drought Intensity–Duration–Frequency Curves for Early Warning Systems in Ethiopia’s Pastoral Region

The pastoral areas of Ethiopia are facing a recurrent drought crisis that significantly affects the availability of water resources for communities dependent on livestock. Despite the urgent need for effective drought early warning systems, Ethiopia’s pastoral areas have limited capacities to monitor variations in the intensity–duration–frequency of droughts. This study intends to drive drought intensity–duration–frequency (IDF) curves that account for climate-model uncertainty and spatial variability, with the goal of enhancing water resources management in Borana, Ethiopia. To achieve this, the study employed quantile delta mapping to bias-correct outputs from five climate models. A novel multi-model ensemble approach, known as spatiotemporal reliability ensemble averaging, was utilized to combine climate-model outputs, exploiting the strengths of each model while discounting their weaknesses. The Standardized Precipitation Evaporation Index (SPEI) was used to quantify meteorological (3-month SPEI), agricultural (6-month SPEI), and hydrological (12-month SPEI) droughts. Overall, the analysis of historical (1990–2014) and projected (2025–2049, 2050–2074, and 2075–2099) periods revealed that climate change significantly exacerbates drought conditions across all three systems, with changes in drought being more pronounced than changes in mean precipitation. A prevailing rise in droughts’ IDF features is linked to an anticipated decline in precipitation and an increase in temperature. From the derived drought IDF curves, projections for 2025–2049 and 2050–2074 indicate a significant rise in hydrological drought occurrences, while the historical and 2075–2099 periods demonstrate greater vulnerability in meteorological and agricultural systems. While the frequency of hydrological droughts is projected to decrease between 2075 and 2099 as their duration increases, the periods from 2025 to 2049 and from 2050 to 2074 are expected to experience more intense hydrological droughts. Generally, the findings underscore the critical need for timely interventions to mitigate the vulnerabilities associated with drought, particularly in areas like Borana that depend heavily on water resources availability.

The Role of Leaf Area Changes Within Plant CO2 Physiological Impacts on the Global Hydrological Cycle

AbstractRising atmospheric CO2 concentrations enhance greenhouse warming and drive changes to plant physiology, leading to innumerable climate impacts. This study explores the impacts of plant responses on hydrological cycling at 2x preindustrial CO2 concentrations by analyzing simulations that isolate plant physiological effects using the Community Earth System Model versions 1 and 2. We find that leaf area growth increases canopy evaporation, which offsets transpiration declines, and dampens changes in global mean evapotranspiration, precipitation, and runoff in a CESM2 experiment with dynamic leaf area. These leaf area impacts are also evident in the differences between CESM1 and CESM2, with CESM2 better capturing observed leaf area magnitudes but potentially overestimating leaf area‐CO2 sensitivity, highlighting the importance of plant CO2 physiology on hydrological cycle changes and the need to improve its representation in climate models.

An Evaluation of Dynamical Downscaling Methods Used to Project Regional Climate Change

AbstractIn the past decade, dynamical downscaling using “pseudo‐global‐warming” (PGW) techniques has been applied frequently to project regional climate change. Such techniques generate signals by adding mean global climate model (GCM)‐simulated climate change signals in temperature, moisture, and circulation to lateral and surface boundary conditions derived from reanalysis. An alternative to PGW is to downscale GCM data directly. This technique should be advantageous, especially for simulation of extremes, since it incorporates the GCM's full spectrum of changing synoptic‐scale dynamics in the regional solution. Here, we test this assumption, by comparing simulations in Europe and Western North America. We find that for warming and changes in temperature extremes, PGW often produces similar results to direct downscaling in both regions. For mean and extreme precipitation changes, PGW generally also performs surprisingly well in many cases. Moisture budget analysis in the Western North America domain reveals why. Large fractions of the downscaled hydroclimate changes arise from mean changes in large‐scale thermodynamics and circulation, that is, increases in temperature, moisture, and winds, included in PGW by design. The one component PGW may have difficulty with is the contribution from changes in synoptic‐scale variability. When this component is large, PGW performance could be degraded. Global analysis of GCM data shows there are regions where it is large or dominant. Hence, our results provide a road map to identify, through GCM analyses, the circumstances when PGW would not be expected to accurately regionalize GCM climate signals.

On the Extrapolation of Generative Adversarial Networks for Downscaling Precipitation Extremes in Warmer Climates

AbstractWhile deep‐learning downscaling algorithms can generate fine‐scale climate projections cost‐effectively, it is unclear how effectively they extrapolate to unobserved climates. We assess the extrapolation capabilities of a deterministic Convolutional Neural Network baseline and a Generative Adversarial Network (GAN) built with this baseline, trained to predict daily precipitation simulated by a Regional Climate Model (RCM) over New Zealand. Both approaches emulate future changes in annual mean precipitation well, when trained on historical data, though training on a future climate improves performance. For extreme precipitation (99.5th percentile), RCM simulations predict a robust end‐of‐century increase with future warming (∼5.8%/C on average from five simulations). When trained on a future climate, GANs capture 97% of the warming‐driven increase in extreme precipitation compared to 65% in a deterministic baseline. Even GANs trained historically capture 77% of this increase. Overall, GANs offer better generalization for downscaling extremes, which is important in applications relying on historical data.

How Do Driving Factors Affect the Ecological Restoration Degree in Different Basins? A Case Study of Six River Basins in Yunnan, China

Ecological space provides human beings with the material resources and living environment needed for life; it is the basis for human survival and development, and ecological restoration is directly related to the sustainable development of human society. As an important ecological security barrier in China, the ecological restoration of the six river basins in Yunnan Province directly affects the ecological security of surrounding provinces and neighboring countries. At present, there is still a lack of research on the differences in ecological restoration between river basins. Therefore, we assessed the spatiotemporal differences in ecological restoration degree in terms of ecosystem patterns, ecosystem quality, and ecosystem services in Yunnan Province from 2000 to 2019 and explored their influencing factors in the six river basins. The results showed the following: ① The six river basins differed in terms of changes in ecosystem patterns over the 20-year period, with the share of settlement ecosystems increasing in the six river basins. The most pronounced changes in ecosystem patterns occurred in the Nu River Basin. There were also differences in the ecosystem transformation priorities of the six river basins. In addition to this, among the four selected indicators, fractional vegetation cover, net primary productivity, and soil conservation increased, but water retention exhibited a stable deteriorating trend. ② Yunnan Province’s ecological restoration degree as a whole is in a relatively stable state. There is no significant improvement or significant deterioration in the region. The best ecological restoration degree of the six river basins is the Pearl River Basin, with a trend of gradual stabilization improvement, and the worst is the Nu River Basin, with a state of gradual stabilization deterioration. ③ The factors that most influence the Ecological Restoration Index (ERI) of the six river basins are mean annual precipitation change rate, mean annual precipitation, annual mean temperature, ecological engineering, and border index. The precipitation change rate was the most important factor influencing ecological restoration in the six river basins, while the border index was the most important factor influencing the differences in ERI in the six river basins. In the future, ecological restoration measures in the six river basins of Yunnan Province should take into account regional differences, strengthen governmental supervision, and emphasize the impact of border factors on neighboring river basins to promote a balanced degree of ecological restoration in Yunnan Province as a whole.

Vulnerability to extreme weather events: mapping future hazards in Wielkopolska region, Poland

The aim of this study is to assess future hazards due to extreme meteorological events in the Wielkopolska region, Poland, based on five climate model projections and three scenarios: SSP126, 370, and 585. The paper analyzes the changes of mean and extreme precipitation, mean and extreme temperatures, and humidity index, as well as changes in difference between maximum temperatures observed from day to day and changes in difference between mean atmospheric pressure at the sea level observed from day to day. Additionally, we look at possible future occurrence of wildfires due to changes in fire weather conditions. Based on climate model projections, future hazard due to extreme meteorological events in Wielkopolska region is to be more serious and will be most noticeable in the end of twenty-first century and for two higher scenarios: SSP370 and SSP585. For near future, 2021–2050, projected conditions of meteorological extremes for analyzed scenarios are quite consistent. Therefore, there is a strong need for implementing adaptation actions. Nevertheless, such activities are so far lacking, and several adaptation options are not present in local and national legislation, even though they are recognized as effective.

Intra-growing season dry-wet spell pattern is a pivotal driver of maize yield variability in sub-Saharan Africa.

Climate variability plays a crucial role in the annual fluctuations of crop yields, posing a substantial threat to food security. Maize, the main cereal in sub-Saharan Africa, has shown varied yield trends during increasingly warmer growing seasons. Here we explore how sub-seasonal dry-wet spell patterns contribute to this variability, considering the spatial heterogeneity of crop responses, to map weather-related risks at a regional level. Our results show that shifts in specific dry-wet spell patterns across growth stages influence maize yield fluctuations in sub-Saharan Africa, explaining up to 50-60% of the interannual variation, which doubles that explained by mean changes in precipitation and temperature (30-35%). Precipitation primarily drives the onset of dry spells, while the influence of temperature increases with event intensity and peaks at the start of the growing season. Our large-scale, data-limited analysis approach has the potential to inform climate-smart agriculture in developing regions.

Asymmetric Sea Surface Salinity Response to Global Warming: “Fresh Gets Fresher but Salty Hesitates”

AbstractEfforts to detect long‐term changes in global mean evaporation minus precipitation over the ocean remain ambiguous. Here we define an ad hoc sea surface salinity index to assess the observed and simulated intensification of the freshwater flux pattern over the global ocean and, thus, of the overall water cycle. A recent salinity reconstruction shows a long‐term amplification of the climatological patterns, thereby supporting the popular “fresh gets fresher, salty gets saltier” paradigm. Unlike in a previous study, no systematic underestimation of this amplification is found in the latest generation of global climate models. Yet, the “fresh gets fresher” paradigm is much more robust than its “salty gets saltier” counterpart and the proposed salinity index does not yet provide a strong constraint on the model‐dependent projected intensification of the global water cycle intensification along the 21st century.

Elevation dependent change in ERA5 precipitation and its extremes

Mountain regions are recognised as hot-spots of climate change. Although the existence of an Elevation-Dependent Warming has been extensively confirmed in several mountain areas of the globe, fewer studies have analysed the elevational stratification of temporal trends of other climate variables, and particularly for precipitation. This study analyses changes in mean precipitation and its extremes in ERA5 global reanalysis data in key mountain areas of the globe, along with their elevational dependence, from 1951 to 2020. These include the Tibetan Plateau, the US Rocky Mountains, the Greater Alpine Region, and the Andes, as representative of different latitudes and climatic influences. Our analysis reveals common patterns of elevational dependent change in precipitation and its extremes in most of the mountainous areas, which emerge beyond their geographical differences. A positive elevational gradient of trends of extreme precipitation indices is found in the Tibetan Plateau, the Greater Alpine Region, and the subtropical Andes, highlighting a wetting effect (positive trends) at very high elevations. In contrast, the Rocky Mountains exhibit a negative elevational gradient, with a drying effect (negative trends) increasing with the elevation. Notably, a simple linear regression proved to be effective to describe the stratification of change in the Greater Alpine Region and the Rocky Mountains, whereas more complex vertical patterns need to be considered for the Andes and the Tibetan Plateau. Mean precipitation, heavy (≥\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge$$\\end{document}10 mm) precipitation and the length of consecutive wet days show a consistent elevation-dependent stratification within each of the study areas, suggesting possible common driving mechanisms.

Impacts of future climate change on rice yield based on crop model simulation—A meta-analysis

Rice is one of the world's major food crops. Changes in major climatic factors such as temperature, rainfall, solar radiation and carbon dioxide (CO2) concentration have an important impact on rice growth and yield. However, many of the current studies that predict the impact of future climate change on rice yield are affected by uncertainties such as climate models, climate scenarios, model parameters and structure, and showing great differences. This study was based on the assessment results of the impact of climate change on rice in the future of 111 published literature, and comprehensively analyzed the impact and uncertainty of climate change on rice yield. This study utilized local polynomial (Loess) regression analysis to investigate the impact of changes in mean temperature, minimum temperature, maximum temperature, solar radiation, and precipitation on relative rice yield variations within a complete dataset. A linear mixed-effects model was used to quantitatively analyze the relationships between the restricted datasets. The qualitative analysis based on the entire dataset revealed that rice yields decreased with increasing average temperature. The precipitation changed between 0 and 25 %, it was conducive to the stable production of rice, and when the precipitation changed >25 %, it would cause rice yield reduction. The change of solar radiation was less than −1.15 %, the rice yield increases with the increase of solar radiation, and when the change of solar radiation exceeds −1.15 %, the rice yield decreases. Elevated CO2 concentrations and management practices could mitigate the negative effects of climate change. The results of a quantitative analysis utilizing the mixed effects model revealed that average temperature, precipitation, CO2 concentration, and adaptation methods all had a substantial impact on rice production, and elevated CO2 concentrations and management practices could exert positive influences on rice production. For every 1 °C and 1 % increase in average temperature and precipitation, rice yield decreased by 3.85 % and 0.56 %, respectively. For every 100 ppm increase in CO2 concentration, rice yield increased by 7.1 %. The variation of rice yield under different climate models, study sites and climate scenarios had significant variability. Elevated CO2 concentrations and management practices could compensate for the negative effects of climate change, benefiting rice production. This study comprehensively collected and analyzed a wide range of literature and research, which provides an in-depth understanding of the impacts of climate change on rice production and informs future research and policy development.

Sensitivity of the global hydrological cycle to the altitude of stratospheric sulphate aerosol layer

Abstract Stratospheric aerosol geoengineering (SAG) has been proposed as one of the potential options to offset the impacts of anthropogenically induced climate change. Previous modelling studies have shown that the efficacy of the cooling via SAG increases with altitude of the aerosol layer. It has been also shown that the stratospheric heating associated with SAG could stabilize the tropical atmosphere and weaken the tropical hydrological cycle. Using a global climate model, we perform a systematic study by prescribing volcanic sulphate aerosols at three different altitudes (22 km, 18 km and 16 km) and assess the sensitivity of the global and tropical mean precipitation to the altitude. We find that even though the efficacy of cooling increases with altitude of the aerosol layer, the global and tropical mean precipitation changes are less sensitive to the height of the aerosol layer. This is because the magnitude of both the global and tropical mean precipitation reduction increases with aerosol altitude in response to increasing efficacy of aerosols, but this sensitivity related to the slow response is nearly offset by the sensitivity of fast precipitation adjustments to aerosol altitude. A perspective and analysis based on atmospheric energy budget is presented to explain the lack of sensitivity of the hydrological cycle to the altitude of the stratospheric sulphate aerosol layer.

A new scenario free procedure to determine flood peak changes in the Harz Mountains in response to climate change projections

Study areaSix catchments of different hydrological characteristics in the Harz Mountains, Germany. Study focusA new scenario free method for determining changes of flood peaks considering climate change is developed. Compared to existing methods, it accounts for heavy rainfall changes by a newly developed factor with two seasons and establishes a numerical relationship to a greater number of relevant climate predictors. For easier application, it is based on frequently available daily measurements. A functional test of the factor for heavy rainfall changes and its adjustment algorithm for the precipitation time series is performed. Using a regional AR5 ensemble, for the first time the error and the uncertainty of a new scenario free method are estimated and compared with an existing method. The new method is applied in the Harz Mountains, where the sensitivity of the region to different climate predictors is investigated. New hydrological insights for the regionThe adjusting algorithm for precipitation is able to adjust the time series while maintaining mass balance. The new method has a lower error than the reference method, with better matches of changes in the median of the climate ensemble as well as the most ensemble members. In general, the uncertainty of the seasonal results is below the climate uncertainty of the AR5 ensemble. Regarding future flood peaks, the regional catchments are most sensitive to mean precipitation changes, followed by heavy rainfall changes especially in the winter season. Mean temperature changes are of minor significance, but the catchments characteristics are important. The new method can be recommended for assessments of climate change impacts on floods in low to average mountain regions in Germany and Europe.

Projected regional changes in mean and extreme precipitation over Africa in CMIP6 models

Precipitation plays a crucial role in Africa’s agriculture, water resources, and economic stability, and assessing its potential changes under future warming is important. In this study, we demonstrate that the latest generation of coupled climate models (CMIP6) robustly project substantial wetting over western, central, and eastern Africa. In contrast, southern Africa and Madagascar tend toward future drying. Under shared socioeconomic pathways (defined by Shared Socioeconomic Pathways SSP2-4.5 and SSP5-8.5), our results suggest that most parts of Africa, except for southern Africa and Madagascar, will experience very wet years five times more often in 2050–2100, according to the multi-model median. Conversely, southern Africa and Madagascar will experience very dry years twice as often by the end of the 21st century. Furthermore, we find that the increasing risk of extreme annual rainfall is accompanied by a shift toward days with heavier rainfall. Our findings provide important insights into inter-hemispheric changes in precipitation characteristics under future warming and underscore the need for serious mitigation and adaptation strategies.

Projected Changes in Mean and Extreme Precipitation over Northern Mexico

Abstract Northern Mexico is home to more than 32 million people and is of significant agricultural and economic importance for the country. The region includes three distinct hydroclimatic regions, all of which regularly experience severe dryness and flooding and are highly susceptible to future changes in precipitation. To date, little work has been done to characterize future trends in either mean or extreme precipitation over northern Mexico. To fill this gap, we investigate projected precipitation trends over the region in the NA-CORDEX ensemble of dynamically downscaled simulations. We first verify that these simulations accurately reproduce observed precipitation over northern Mexico, as derived from the Multi-Source Weighted-Ensemble Precipitation (MSWEP) product, demonstrating that the NA-CORDEX ensemble is appropriate for studying precipitation trends over the region. By the end of the century, simulations forced with a high-emissions scenario project that both mean and extreme precipitation will decrease to the west and increase to the east of the Sierra Madre highlands, decreasing the zonal gradient in precipitation. We also find that the North American monsoon, which is responsible for a substantial fraction of the precipitation over the region, is likely to start later and last approximately three weeks longer. The frequency of extreme precipitation events is expected to double throughout the region, exacerbating the flood risk for vulnerable communities in northern Mexico. Collectively, these results suggest that the extreme precipitation-related dangers that the region faces, such as flooding, will increase significantly by the end of the century, with implications for the agricultural sector, economy, and infrastructure. Significance Statement Northern Mexico regularly experiences severe flooding and its important agricultural sector can be heavily impacted by variations in precipitation. Using high-resolution climate model simulations that have been tested against observations, we find that these hydroclimate extremes are likely to be exacerbated in a warming climate; the dry (wet) season is projected to receive significantly less (more) precipitation (approximately ±10% by the end of the century). Simulations suggest that some of the changes in precipitation over the region can be related to the North American monsoon, with the monsoon starting later in the year and lasting several weeks longer. Our results also suggest that the frequency of extreme precipitation will increase, although this increase is smaller than that projected for other regions, with the strongest storms becoming 20% more frequent per degree of warming. These results suggest that this region may experience significant changes to its hydroclimate through the end of the century that will require significant resilience planning.

Analysis of recent trends and spatiotemporal changes of droughts over Serbia using high-resolution gridded data

The purpose of this study is to analyze the spatiotemporal variations in drought in Serbia over recent decades using the standardized precipitation evapotranspiration index (SPEI). The analysis is performed for time series of 1-, 3-, 6-, and 12-month SPEI indices (SPEI-01, SPEI-03, SPEI-06 and SPEI-12, respectively) calculated using the E-OBS gridded dataset with a horizontal resolution of 0.1° for the period of 1950–2022. In general, it was found that negative SPEI trends prevailed in Serbia for all months and all analyzed SPEI timescales, indicating a more frequent appearance of droughts in recent decades. Moreover, for a large majority of month-timescale combinations, the area with a negative trend was larger than the area with a positive trend. For several reasons, we focused on the SPEI for August. First, the SPEI for this month shows one of the most pronounced negative trends, which is rather consistent over different timescales and consistent in terms of the area over which the trend was found to be significant. Statistically significant negative trends of SPEI-03, −06 and − 12 for August were found over 11, 17 and 38% of the country area, respectively. To better understand the trends and changes in the SPEI for August, focusing on extreme and severe drought events, an innovative trend analysis (ITA) was applied. It was found that the occurrence of both extreme and severe SPEI drought categories has doubled over the last thirty years in comparison with the previous thirty-year period. Additionally, more frequent transitions from neutral and wet categories to dry categories were observed through an application of the Markov chain. Second, the special focus on SPEI-03, −06 and − 12 for August was motivated by the fact that we found a significant correlation between these index values and the annual maize production in Serbia, indicating that the SPEI for August can be useful for the assessment of drought impact on agriculture. To better understand interannual variability and long-term trends, this paper also explores the relations between the SPEI over Serbia and large-scale circulation patterns, together with general global and continental warming trends. Our findings indicate that drought changes over recent decades may be driven by the interplay of long-term warming and large-scale circulation patterns. In the context of climate change, especially climate projections, Serbia is situated in a region for which climate projections of mean precipitation change demonstrate weak signals and often with conflicting signs of change within multimodel ensembles. From this point of view, our results can be seen as a contribution to a better understanding of changes in extremes, in our case droughts, that can be hidden by inconclusive changes in the mean values. Finally, due to the similar situation in terms of precipitation and drought trends and changes, our results may be relevant for a wider region, and not only for Serbia.

An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)

Abstract. Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate.

Constraints on regional projections of mean and extreme precipitation under warming

The projected changes in the hydrological cycle under global warming remain highly uncertain across current climate models. Here, we demonstrate that the observational past warming trend can be utilized to effectively co1nstrain future projections in mean and extreme precipitation on both global and regional scales. The physical basis for such constraints relies on the relatively constant climate sensitivity in individual models and the reasonable consistency of regional hydrological sensitivity among the models, which is dominated and regulated by the increases in atmospheric moisture. For the high-emission scenario, on the global average, the projected changes in mean precipitation are lowered from 6.9 to 5.2% and those in extreme precipitation from 24.5 to 18.1%, with the inter-model variances reduced by 31.0 and 22.7%, respectively. Moreover, the constraint can be applied to regions in middle-to-high latitudes, particularly over land. These constraints result in spatially resolved corrections that deviate substantially and inhomogeneously from the global mean corrections. This study provides regionally constrained hydrological responses over the globe, with direct implications for climate adaptation in specific areas.

Storylines for Future Projections of Precipitation Over New Zealand in CMIP6 Models

AbstractLarge uncertainty exists in the sign of long‐term changes in regional scale mean precipitation across the current generation of global climate models. To explore the physical drivers of this uncertainty for New Zealand, here we adopt a storyline approach applying cluster analysis to spatial patterns of future projected seasonal mean precipitation change across CMIP6 models (n = 43). For the winter precipitation change signal, the models split roughly into two main groups: both groups have a very robust wet signal across the west coast of the South Island but differ notably in terms of the sign of precipitation change across the north of the North Island. These far north winter precipitation differences appear related to how far the Hadley cell edge and regional eddy‐driven jet shift across the models relative to their historical positions. In contrast, for summer, most models have a markedly weaker and spatially non‐uniform response, where internal variability often plays a large role. However, a small group of models predict a robust wet signal across most of the country in summer. This “wet model” group is characterized by a regional La Niña‐like increase in high pressure shifted further to the south‐east of New Zealand, associated with more frequent north‐easterly flow over the country and accompanied by significant warming of local sea surface temperatures. This regional circulation response appears related to changes in stationary Rossby wave paths as opposed to changes in La Niña occurrence frequency itself.

Lacustrine rhythmites from the Mulhouse Basin (Upper Rhine Graben, France): a sedimentary record of increased seasonal climatic contrast and sensitivity of the climate to orbital variations through the Eocene-Oligocene Transition

The Eocene-Oligocene Transition (EOT) marks the passage from Eocene greenhouse to Oligocene icehouse conditions. It holds keys to our understanding of the behavior of climate systems under major pCO2 shifts. While the environmental impact of the EOT is rather homogenous in oceans, it is much more heterogeneous on continents. Although little to no changes are recorded in some regions, several EOT studies in western Eurasia suggest an increase in seasonal climatic contrast (e.g., higher amplitude of changes in mean temperature or precipitation), along with a higher sensitivity of the climate to orbital variations. However, these variations remain to be properly documented through changes in sedimentary facies and structures and forcing mechanisms. Here we investigate the depocenter of the Mulhouse Basin (Upper Rhine Graben; URG) revealing a prominent transition from massive mudstones to laminated sediments and varves, alongside the emergence of astronomically-forced mudstone-evaporite alternations. These changes are identified in the distal and proximal parts of the southern URG, where they consist of millimeter-thick mudstone-evaporite couplets and siliciclastic-carbonate couplets. The elemental composition and micro-facies analysis of the laminae show a recurrent depositional pattern consistent with a seasonal depositional process, which suggests that they are varves. We propose that the occurrence of varved sediments, together with the observed orbital cyclicity in the southern URG, reflects an increase in seasonal climatic contrast, and an increase in the sensitivity of climate to orbital variations across the EOT. We show that similar changes were noticed in the Rennes and Bourg-en-Bresse basins, and that of other western Eurasian records for similar climatic conditions. This work emphasizes the potential of high-resolution sedimentary structures to serve as markers of climate change across the EOT.

Unveiling climate change impacts on agricultural sustainability: insights from the united states

Climate change poses significant threats to agricultural systems, necessitating a comprehensive understanding of its impact for effective adaptation strategies. This study examines the influence of climate change on agriculture in the United States, primarily focusing on temperature shifts and precipitation variations. Utilizing historical data and climate projections, we analyse trends in mean temperature and precipitation patterns from 1950 to 2020. The results indicate a noteworthy increase in annual mean temperature over the years, attributed to climate change. This rise in temperature has multifaceted implications, including heat stress in crops and exacerbation of drought conditions. The study also explores the complex relationship between precipitation patterns and climate change, highlighting regional variations and potential shifts in future precipitation trends. By projecting data under SSP 1-1.9 emission scenario, we assess potential changes in mean temperatures, hot days, and precipitation for 2040-2059 periods. In conclusion, this study sheds light on the interplay between climate change and agricultural systems, emphasizing the need for adaptive strategies to secure food production and mitigate potential risks. The findings underscore the urgency of proactive measures to safeguard agricultural sustainability and resilience in the face of evolving climatic conditions.