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In East Asia, where concentrated summer precipitation often leads to climate disasters, understanding the factors that cause such extreme rainfall is crucial for effective forecasting and preparedness. The western North Pacific subtropical high (WNPSH) is a key driver of summer precipitation variability, and therefore, its monitoring is critical to predicting the wet or dry periods during the East Asian summer monsoon. Using the Geo-KOMPSAT 2A (GK2A) satellite cloud amount data and ERA5 reanalysis data during the years 2020–2023, this study identified three leading empirical orthogonal function (EOF) modes and investigated the associated WNPSH variability at synoptic and subseasonal scales. The analysis includes a linear regression of meteorological fields onto the principal component (PC) time series. All three modes play a role in the spatiotemporal variability of the WNPSH, exhibiting lead–lag relationships. In particular, the second mode is responsible for its northwestward shift and intensification. As the WNPSH moves northwestward, the position of the monsoon rain band also shifts, and its intensity is modulated mainly by the moisture transport along the WNPSH boundary. Our results highlight the potential of high-resolution, real-time data from the GK2A satellite to elucidate WNPSH variability and its impact on the East Asian summer monsoon. By addressing the variability of the WNSPH using GK2A data, we pave the way for the development of a real-time monitoring framework with GK2A, which will improve our predictability and readiness for extreme weather events in East Asia. [ABSTRACT FROM AUTHOR]

We investigated the influence of the El Niño‐Southern Oscillation (ENSO) on inter‐annual precipitation variability in the far‐eastern Pacific (FEP) and northern South America (NSA) using an approach based on phase synchronization (PS). First, we carried out a detailed analysis of observational data to define the inter‐annual variability, eliminate the seasonal residual frequencies in hydro‐climatic anomalies, and assess the statistical significance of PS. Additionally, we characterized the seasonality of regional patterns of sea surface temperature, surface pressure levels, low‐level winds and precipitation anomalies associated with the ENSO states. We found that the positive (negative) precipitation anomalies experienced in the FEP and NSA differ from those previously reported in the literature. In particular, the Guianas (northeastern Amazon) and the Caribbean constitute two regions with negative (positive) rainfall anomalies during El Niño (La Niña), separated by a zone of non‐significant anomalies along the Orinoco Low‐level Jet corridor. Moreover, we showed that the ENSO signal is phase‐locked with inter‐annual rainfall and low‐level wind variability in most of the study regions. Furthermore, we found consistency in the PS between the Central and Eastern Pacific El Niño indices and hydroclimatic anomalies over the Pacific. However, some areas exhibited PS, although they did not show significant precipitation anomalies, suggesting that the influence of ENSO on tropical climatology manifests not only in terms of the magnitude of anomalies but also in terms of the phases only. Our approach advances the understanding of climatic anomalies in tropical regions and provides new insights into the non‐linear interactions between ENSO and hydroclimatic processes in tropical Americas. [ABSTRACT FROM AUTHOR]

Assessments of future droughts are essential tools due to the potential for serious damage to the environment, economy, and society, particularly under climate change. This study proposes a framework for assessing drought characteristics at different scales, periods, and emission scenarios modeled by phase 6 of the Coupled Model Intercomparison Project. The four drought characteristics were determined by applying the Run theory to a standardized precipitation index time series, and the severe drought areas were detected by the Jenks Natural Breaks and Kriging methods. The study produced four main findings. (1) A stochastic weather generator, AWE-GEN, captures the variability of precipitation with inter- and intra-annual stochastic properties, and presents naturally occurring variability as an ensemble. (2) According to the ensemble average of drought characteristics, future droughts are projected to become less frequent with similar durations and intensity due to future rise in precipitation. However, the ensemble (stochastic or natural) and spatial variabilities are expected to increase, making drought management difficult (e.g., future decrease of 18% in DE max for END585). (3) Different temporal scales can affect the detection and characterization of drought events. Smaller temporal scales identify mild drought events of short duration and low severity, while larger scales merge and extend drought events, resulting in more prolonged and severe droughts. (4) Severe drought areas can expand compared with a control period for drought duration and severity, but may decrease for drought interval and frequency especially for the END period (e.g., 24% and 17% increase for DD max and D S max , and 85% and 78% decrease for DI mean and DE max for SPI3 and END585). The framework proposed in this study is expected to provide important information for the building of strategies required to adapt to and mitigate the potential impacts of drought in the future. [ABSTRACT FROM AUTHOR]

Given the significant importance of spring precipitation for agricultural production in China and the presence of the spring predictability barrier, scientists have dedicated extensive efforts to understand the factors influencing spring precipitation variability and explore new predictors. However, the effects of Arctic stratospheric ozone (ASO) on precipitation in China during boreal spring, if any, and the underlying mechanisms remain unclear. We found the robust influences of March ASO on the differences in the precipitation and evaporation in April over Eastern China during 1980–2020. When ASO decreases in March, it tends to result in a higher and colder tropopause in the polar, a stronger subtropical jet stream, an intensified local Hadley circulation accompanied by anomalous downward motion over Eastern China, and consequently, drying in this region, and vice versa. These findings suggest that the likelihood of April moistening over East Asia may be potentially predicted by employing the ASO index. Plain Language Summary: Food production in East Asia, which is home to a quarter of the world's population, holds immense importance. The spring season in this region marks the crop planting period, making the precipitation during this time crucial for agricultural production. However, it is challenging to predict spring moistening/drying over East Asia. Therefore, there is a need for new predictors to enhance our understanding of spring precipitation variability. Whether a connection exists between Arctic stratospheric ozone (ASO) and spring precipitation over EC has remained unknown. Here, we have highlighted a strong relationship between ASO in March and moistening over EC in April, particularly in the middle and lower reaches of the Yangtze River (YRB). Specifically, an increase (decrease) in March ASO corresponds to moistening (drying) over YRB in April. The implications of these findings are significant for forecasting spring precipitation over East Asia, which is crucial for agricultural planning and production. Key Points: There are robust influences of March Arctic stratospheric ozone (ASO) on the precipitation in April over Eastern China (EC) during 1980–2020Depletion of ASO in March tends to result in decreased precipitation over EC in AprilDecreased ASO results in the higher but warmer tropopause, stronger subtropical jet, and anomalous downward motion over EC [ABSTRACT FROM AUTHOR]

This study compares projected and past seasonal precipitation trends in the Eastern Black Sea Basin, Turkey. Historical data from twelve stations representing the basin during 1981–2010 was used, while statistically downscaled data from two representative concentration pathway scenarios (RCP4.5 and RCP8.5) outputs of the GFDL-ESM2M general circulation model were utilized for 2021–2050. To determine the seasonal trend behaviors of precipitation variables and transitions between consecutive months, the Innovative Polygon Trend Analysis (IPTA) was implemented. Furthermore, the star concept was employed to illustrate the changing sizes between consecutive periods. Both scenarios showed considerable summer and autumn declines at almost all locations, with low seasonal precipitation variability. These scenarios indicated January to be the important month for trend shift, except for Rize, Pazar, and Hopa stations. The formation of several polygons, polygons intersecting, and polygons not forming on the global regression line show that the hydro-climatic cycle might be chaotic. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystem resilience is crucial for maintaining the structural and functional stability of ecosystems following disturbances. However, changes in resilience over the past few decades and the risk of future resilience loss under ongoing climate change are unclear. Here, we identified resilience trends using two remotely sensed vegetation indices, analyzed the relative importance of potential driving factors to resilience changes, and finally assessed the risk of future resilience loss based on the output data of eight models from CMIP6. The results revealed that more than 60% of the ecosystems experienced a conversion from an increased trend to a declined trend in resilience. Attribution analysis showed that the most important driving factors of declined resilience varied regionally. The declined trends in resilience were associated with increased precipitation variability in the tropics, decreased vegetation cover in arid region, increased temperature variability in temperate regions, and increased average temperature in cold regions. CMIP6 reveals that terrestrial ecosystems under SPP585 are expected to experience more intense declines in resilience than those under SSP126 and SSP245, particularly in cold regions. These results highlight the risk of continued degradation of ecosystem resilience in the future and the urgency of climate mitigation actions. [ABSTRACT FROM AUTHOR]

The changing global climate, characterized by rising surface air temperatures, shifting precipitation patterns, and heightened occurrences of extreme weather events, is anticipated to profoundly impact the environment, economy, and society worldwide. This impact is particularly acute in African nations like Angola, where crucial sectors, such as agriculture, rely heavily on climate variability and exhibit limited adaptive capacity. Given that the majority of Angola's agriculture is rain-fed and serves as a vital source of livelihood for the populace, the country is especially vulnerable to climate change, particularly in its southern region. Climate change has caused severe damage in Angola, especially in the southern part of the country, where the worst droughts in decades have affected over 3.81 million people, resulting in food and water shortages. Between 2005 and 2017, climate-related disasters cost the country about 1.2 billion US dollars, further exacerbating the economic and social challenges faced by the population. This study presents a systematic review of the effects of climate change on agriculture in Angola, with a focus on the southern region. Employing the PRISMA2020 methodology, the review examined 431 documents from databases such as Scopus and Web Science, spanning from 1996 to 2023, with 63 meeting inclusion criteria. The review reveals a paucity of research on the short and long-term impacts of climate change on Angolan agriculture. Projections indicate a rise in temperatures and a general decrease in precipitation, with the southern region experiencing a more pronounced decline. Agricultural productivity may suffer significantly, with models suggesting a potential 7% reduction by 2050. [ABSTRACT FROM AUTHOR]

Morocco, as a Mediterranean and North African country, is acknowledged as a climate change hotspot, where increased drought and related water resource shortages present a real challenge for human and natural systems. However, its geographic position and regional characteristics make the simulation of the distribution and variability of precipitation particularly challenging in the region. In this study, we propose an approach where the Laboratoire de Météorologie Dynamique Zoom (LMDZ) GCM is run with a stretched grid configuration developed with enhanced resolution (35 km) over the region, and we apply run‐time bias correction to deal with the atmospheric model's systematic errors on large‐scale circulation. The bias‐correction terms for wind and temperature are built using the climatological mean of the adjustment terms on tendency errors in an LMDZ simulation relaxed towards ERA5 reanalyses. The free reference run with the zoomed configuration is compared to two bias‐corrected runs. The free run exhibits noticeable improvements in mean low‐level circulation, high frequency variability and moisture transport and compares favourably to precipitation observations at the local scale. The mean simulated climate is substantially improved after bias correction w.r.t. to the uncorrected runs. At the regional scale, the bias‐correction showed improvements in moisture transport and precipitation distribution, but no noticeable effect was observed in mean precipitation amounts, interannual variability and extreme events. To address the latter, model tuning after grid refinement and developing more "scale‐aware" parameterizations are necessary. The observed improvements on the large‐scale circulation suggest that the run‐time bias correction can be used to drive regional climate models for a better representation of regional and local climate. It can also be combined with "a posteriori" bias correction methods to improve local precipitation simulation, including extreme events. [ABSTRACT FROM AUTHOR]

The climatology and variability of the January to February (JF) season in eastern Africa's (EA) precipitation are examined during the 1960–2020 period, as off‐season climate could have dire consequences, considering agricultural practices tie to the seasonal cycle of precipitation. The analysis in this study is divided into four parts. The first is the climatological background of variability during the JF season. Second, the spatiotemporal variability of the leading mode of the JF precipitation is described using an empirical orthogonal function (EOF) method. Third, anomalous atmospheric circulations linked to the variability of the JF precipitation were examined through composite analysis. Fourth, the link between JF precipitation and sea surface temperature (SST) is explored using composite and correlation analyses. The leading mode (EOF1) shows a monopole variation, with a positive anomaly in the entire region accounting for 55.1% of the total variance. EOF1 is linked to the SST anomaly (SSTA) over the tropical Indian Ocean (TIO). A warm (cool) SSTA in the TIO induces diabatic warming/adiabatic cooling (diabatic cooling/adiabatic warming). This leads to the rising (sinking) of warm and moist air (cold and dry air) from the lower to higher (higher to lower) troposphere via the ascending (descending) branch of the Walker circulation and contributes to the upper warm (cold) temperature anomaly centred at ~300 hPa. The warm (cold) anomaly is closely associated with the upper‐level westerly (easterly) and divergence (convergence) anomalies at the upper side of the warm (cold) core, coupled with ascending (descending) and deep wet (dry) anomalies below the warm (cold) core. This induces moisture convergence (divergence) and unstable (stable) conditions that favour (suppresses) precipitation over EA. Consequently, this study may facilitate the prediction of the JF precipitation and decrease in socio‐economic losses in EA. [ABSTRACT FROM AUTHOR]

Precipitation is a key component in hydrologic processes. It plays an important role in hydrological modeling and water resource management. However, many regions suffer from limited and data scarcity due to the lack of ground-based rain gauge networks. The main objective of this study is to evaluate other source of rainfall data such as remote sensing data (three different satellite-based precipitation products (CHIRPS, PERSIANN, and GPM) and a reanalysis (ERA5) against ground-based data, which could provide complementary rainfall information in semiarid catchment of Tunisia (Haffouz catchment), for the period between September 2000 and August 2018. These remotely sensed-data are compared for the first time with observations in a semiarid catchment in Tunisia. Twelve rain gauges and two different interpolation methods (inverse distance weight and ordinary kriging) were used to compute a set of interpolated precipitation reference fields. The evaluation was performed at daily, monthly, and yearly time scales and at different spatial scales, using several statistical metrics. The results showed that the two interpolation methods give similar precipitation estimates at the catchment scale. According to the different statistical metrics, CHIRPS showed the most satisfactory results followed by PERSIANN which performed well in terms of correlation but overestimated precipitations spatially over the catchment. GPM underestimates the precipitation considerably, but it gives a satisfactory performance temporally. ERA5 shows a very good performance at daily, monthly, and yearly timescale, but it is unable to represent the spatial variability distribution of precipitation for this catchment. This study concluded that satellite-based precipitation products or reanalysis data can be useful in semiarid regions and data-scarce catchments, and it may provide less costly alternatives for data-poor regions. [ABSTRACT FROM AUTHOR]

Understanding the long-term spatiotemporal variability of precipitation at the regional scale is critical for developing flood and drought control strategies and water resource management. This study assessed the spatiotemporal variability of monthly precipitation over the Khyber Pakhtunkhwa province of Pakistan for 1998–2019 using hierarchical cluster analysis to cluster 156 Tropical Rainfall Measuring Mission grids. Statistical properties of clusters were calculated and the relationship of geographical features such as latitude, longitude, and altitude and statistical variables including standard deviation, maximum and minimum precipitation, and coefficient of variation (CV) with average precipitation was assessed. Findings showed that northeast parts received maximum precipitation while north and southern regions received less precipitation. Temporal analysis showed two clusters of rainy months (February, March, April, May, July, and August) and dry months (January, June, September, October, November, and December). The region was divided into two homogeneous precipitation regions. From January to April and November to December, cluster 1 occupied northern parts with maximum average precipitation while cluster 2 southern parts. From June to September, cluster 2 covered the northeast and southern parts with the highest average precipitation. During May, cluster 2 received the highest average precipitation in the northeast and southeast parts, whereas cluster 1 covered the northwest and southwest. In October, cluster 2 received maximum average precipitation covering the northeast. CV suggested higher temporal variability in cluster 2 (67.75–102.36)% than cluster 1 (65.82–99.55)%. Precipitation correlation showed that CV opposed the longitude and averages, whereas latitude and altitude demonstrated minimal correlations. These insights can assist decision-makers in devising suitable strategies to plan and control unexpected volumes of precipitation. [ABSTRACT FROM AUTHOR]

Analyzing water resources in areas with few hydrometeorological stations, such as those in post-Soviet countries, is difficult due to station closures after 1989. In Caucasus, evaluations often rely on outdated data from nearby rivers. We evaluated one national-level precipitation dataset, the Water Balance of Georgia (WBG) with two satellite-based precipitation products from 1981 to 2021, including the Climate Hazards Group Infrared Precipitation with Station (CHIRPS) data and CHIRPS blended with a dense rain gauge network (geoCHIRPS). We modeled mean annual precipitation from geoCHIRPS as a function of coastal distance and elevation. CHIRPS underestimated precipitation in the cold and wet seasons (R2 = 0.74, r = 0.86) and overestimated dry season precipitation, while geoCHIRPS performed well in all seasons (R2 = 0.86, r = 0.92). Distance from the coast was a more important predictor of precipitation than elevation in western Georgia, while precipitation correlated positively with elevation in the east. At four hydroelectric plants, the underperformance as a percentage of capacity (∼37%) corresponds with the percentage difference between differences in precipitation products (∼38%), suggesting that plants designed based on WBG may be systematically overdesigned, but further work is needed to determine the reasons for the underperformance of the plants and frequency. We conclude that 1) the existing WBG does not accurately reflect elevation–precipitation relationships near the coast, and 2) for accurate analysis of spatiotemporal precipitation variability and its impacts on hydropower generation and environmental and sustainable water resource management, it is essential to calibrate satellite-based precipitation estimates with additional rain gauge data. [ABSTRACT FROM AUTHOR]

Convective/advective precipitation partitions refer to the divisions of precipitation that are either convective or advective in nature, relative to the total precipitation amount. These distinct partitions can have a significant influence on the stable isotope composition of precipitation. This study analyzed and compared the effect of precipitation partitions on δ18O in precipitation (δ18Op) by using daily precipitation stable isotope data from Changsha station and monthly precipitation stable isotope data from the Global Network of Isotopes in Precipitation (GNIP), under different time scales, time intervals (i.e., annual, warm season, and cold season), and precipitation intensities. The results showed that the correlation between the convective precipitation fraction (CPF) and total precipitation amount was influenced by the intensity of convection in different time intervals. On both the daily and monthly scales, the CPF decreased as the precipitation amount increased in the warm season, while it increased with increasing precipitation amount in the cold season. Regardless of the season, daily δ18Op at Changsha station consistently increased with an increase in daily CPF. On a daily scale, the effect of convective activity on δ18Op was stronger than that of the "precipitation amount effect" in the cold season, as compared to the situation in the warm season. As a result, the regression line slope between δ18Op and CPF increased with increasing precipitation intensity in the warm season, meaning that as the CPF increased, the δ18Op increased at a faster rate under higher precipitation intensity. Similarly, the slope increased with increasing precipitation intensity in the cold season. This suggests that precipitation intensity and convection intensity can affect the relationship between δ18Op and CPF. Our findings shed light on how different precipitation partitions affect stable isotope composition of precipitation, thus enhancing our understanding of the variability of precipitation stable isotopes in the monsoon regions of China. Significance Statement: This study aims to better elucidate the influence of different precipitation partitions on precipitation stable isotopes. In the eastern monsoon region of China, stable isotopes in precipitation showed a robust positive relationship with convective precipitation faction. On a daily scale, the convective activity enhanced the influences of the "precipitation amount effect" on precipitation stable isotopes in the warm season and reduced such influences in the cold season. These results improve our understanding of stable isotopic variability of precipitation in the eastern monsoon region, China. [ABSTRACT FROM AUTHOR]

Changes in precipitation impact water availability in river basins; therefore, it is important to perform detailed analyses of precipitation variables within regions to better understand drivers of precipitation variability. This study, which focuses on the Apalachicola-Chattahoochee-Flint River Basin in the southeastern United States, provides an analysis of precipitation variability during 1980–2021 and connects that information to circulation variables while also exploring the alignment between recent and projected precipitation changes. Data include daily precipitation totals from 33 stations, monthly values for circulation indices, and downscaled precipitation projections from climate models. Results show the pressure gradient across the southwestern North Atlantic Ocean and southeastern United States—which is a function of the strength and position of the Bermuda High—is strongly correlated with the precipitation variables and might be an important control of precipitation variability in the basin. In contrast, most teleconnection indices are relatively weakly correlated with precipitation. The basin has generally been getting wetter, with summer having the largest increases in precipitation totals and precipitation days and thus large decreases in maximum consecutive dry days. Increases in heavy-precipitation variables are relatively small, with the largest increases in the northern portion of the basin. Precipitation is projected to increase in the next several decades compared to recent decades, with heavy precipitation expected to have the largest increase. Since the Bermuda High is likely the dominant driver of precipitation in the basin, more information is needed about specific changes to the Bermuda High in upcoming decades to better determine how precipitation might change. [ABSTRACT FROM AUTHOR]

It is increasingly recognized that the assumption of stationarity is not always appropriate for estimating return periods from meteorological time series under the effects of climate change and climate variability. Here, we assessed the capability of a non-stationary framework for modeling seasonal precipitation series using Generalized Additive Models for Location, Scale and Shape (GAMLSS), a well-established approach for modeling hydro-meteorological variables under non-stationary conditions. Seasonal precipitation series were considered from 95 stations covering the period of 1970–2021 across Turkey. Four widely used homogeneity tests showed that the seasonal precipitation series were generally reliable, with no obvious anthropogenic influences or errors. The parameters of the fitted distributions were modeled as a function of large-scale oscillation indices known to control precipitation across Turkey, namely the North Atlantic Oscillation (NAOI), North Sea-Caspian Pattern (NCPI), Mediterranean Oscillation (MOI), and Southern Oscillation (SOI). The model with oscillation indices performed better at 85%, 79%, 76%, and 54% of sites for autumn, winter, spring, and summer, respectively, than the model with no covariates. In particular, the NCPI was seen as a significant predictor during the winter, while the MOI captured precipitation variability well across the country during autumn and summer. The NAOI appeared as another important predictor during all seasons except summer, while the SOI appeared as a significant explanatory variable in certain regions. Using the non-stationary models, we then computed seasonal precipitation estimates for different return periods (i.e., 20, 50, and 100 years) and considered the minimum and maximum possible extreme precipitation scenarios at each site. We show how the use of simple minimum/maximum values derived from the non-stationary models can help provide water resource managers and policy makers with a plausible range of extreme values, rather than the single deterministic value obtained from the traditional stationary approach. [ABSTRACT FROM AUTHOR]

The Bay of Bengal Storm (BBS) frequently occurs during the "double-peak periods" in (1) May (pre-peak period) and (2) October to November (post-peak period). Exploring precipitation variation and its anomalies during these periods is crucial for understanding climate change in the Qinghai-Tibet Plateau (QTP). Precipitation products of MSWEP v2 (Multi-Source Weighted Ensemble Precipitation Version 2) along with precipitation observations from meteorological stations and BBS data from the Guam Joint Typhoon Warning Center from 1979 to 2020 were employed for the analysis. The objective of the present study was to investigate the anomalous characteristics and multi-temporal variability of regional precipitation over the QTP and its relationship with the BBS using the empirical orthogonal function (EOF), rotated empirical orthogonal function (REOF), and percentage calculation method. There was a consistent spatial distribution of precipitation on the QTP during double-peak periods based on the first mode of EOF. However, the second mode of EOF identified a northeast-southwest reverse in precipitation distribution. The QTP was categorized into five precipitation anomalous subregions during double-peak periods using REOF. Precipitation showed significant increases (12.6 mm/10a in May and 5.1 mm/10a in October to November) in specific regions. Precipitation anomalies on the QTP during double-peak periods exhibited positive anomalies at various timescales (monthly, ten-day, and pentad), with stronger BBS influence in the pre-peak period. From 1979 to 2020, all monthly precipitation anomalies on the QTP during double-peak periods were accompanied by BBS, with an 8% probability. The rates of precipitation anomalies under the influence of BBS were about 18% and 28% in the ten-day and pentad timescales, respectively, with BBS contributing the most to pentad precipitation anomalies. Daily precipitation anomalies during the pre-peak and post-peak periods were influenced by BBS to varying extents (30%, 20%, and 25% in May, October, and November, respectively). Extreme daily precipitation days affected by BBS represented 19%, 16%, and 21% of the statistical period extreme precipitation days in May, October, and November, respectively, with higher rates in the post-peak period. [ABSTRACT FROM AUTHOR]

Climate change–induced precipitation unpredictability has disastrous consequences for closed basins with sensitive hydrological equilibrium. Identifying changes and trends in precipitation characteristics in such catchments is an important step towards minimizing potential disasters. This study explores the precipitation variability of the Konya Closed Basin (Turkey), an over-exploited semi-arid basin. For this purpose, monthly precipitation data for the period 1971–2020 (50 years) of 11 meteorological observation gauges operated by the Turkish State Meteorological Service in the basin were utilized. Precipitation data were examined using two graphical innovative trend methods namely innovative polygon trend analysis (IPTA) and trend polygon star concept (TPSC) approaches. With these methods, periodic features in monthly precipitation data and trend transitions between months can be interpreted visually and linguistically. IPTA and TPSC methods were applied separately to both arithmetic mean data and standard deviation for each month's precipitation data of 11 stations. A general increasing trend in precipitation was obtained in most of the months for the stations used in the IPTA application. Most of the TPSC arrows, which were distributed throughout all four regions for both the arithmetic mean and standard deviation, were in the I and III regions. Based on the TPSC graphs, the longest transition arrows between two consecutives occurred in the first months of autumn (highly increasing) and summer (highly decreasing) in most of the stations. The results of this study are of great importance for the policies to be sustained regarding the ongoing climate change in the agricultural sector in KCB, which is both a water scarce basin and a region with intensive agricultural activities. [ABSTRACT FROM AUTHOR]

Variations in rainfall are a significant characteristic of semi-arid climates, and it is expected that climate change will increase this variability in many such regions. To effectively plan and manage water resources, mitigate floods and droughts, and control erosion, among other tasks, it is essential to comprehend the spatiotemporal variability of rainfall. Although many approaches have been proposed and applied to rainfall data in various regions around the world, our understanding of the spatiotemporal variability of rainfall remains limited. Previous studies have mainly focused on the amount and spatial patterns of rainfall, with limited investigations of spatiotemporal variability at different scales. To address this knowledge gap, this study employed a spatiotemporal framework to evaluate the dispersion and uncertainty of precipitation in Iran. The study utilized data from 50 synoptic stations spanning the period between 1980 and 2020 and applied the concept of entropy to examine the spatiotemporal variability of precipitation. The marginal entropy (ME) was used to analyze the variability of monthly, seasonal, and annual precipitation series. In addition, the apportionment entropy (AE) was applied to the time series to investigate the intra-annual and decadal distribution of monthly and annual precipitation values. The study also utilized the Mann–Kendall test to examine the marginal and relative entropy trends of the study stations. Standardized variability index results revealed that September had the highest rainfall variability, with an average of 0.529, while January had the lowest rainfall variability, with an average of 0.083. Precipitation variability was found to be higher in the summer and spring seasons than in the winter and fall. Moreover, the mean value of the standardized variability index (SVIAE) during the study period was found to be 0.661. Stations with an index value less than 0.661 were found to have a more uniform and evenly distributed rainfall and lower variability. The spatial distribution of annual SVIME indicates that stations in the central and southeastern regions of Iran have higher irregularity. Also, the results show that each season has a unique spatial variability pattern of precipitation irregularity. In the spring, the stations with the highest variability are stations number Chabahar, Jask, Kish, Bandar abbas, Bandar lengeh, Iranshahr, and Zabol. In the summer, stations Zabol, Booshehr, Kish, Bandar lengeh, and Ahvaz exhibit the highest variability. Also, in the autumn season, stations Chabahar, Jask, Iranshahr, Zahedan, and Bandar abbas show the highest variability. In the winter, the southern and southeastern parts of Iran, including stations such as Chabahar, exhibit the highest precipitation variability. [ABSTRACT FROM AUTHOR]

Invasive clonal species may exhibit different growth strategies than their native clonal competitors. In this study, we examined the spatial distribution of tiller outgrowth and the bud bank by comparing the investment in phalanx versus guerilla growth of a native and invasive perennial grass in North America. We also examined the effect of altered precipitation frequency, clipping, and competition on their clonal growth strategies. Investment in phalanx and guerilla growth was assessed by examining live propagule and tiller production from the plant crown versus its rhizomes. Although invasive Bromus inermis and native Pascopyrum smithii exhibited similar clonal growth strategies as young seedlings, their clonal growth strategies significantly differed by the end of their first growing season. Pascopyrum smithii invested in dual phalanx and guerilla tiller outgrowth and bud placement, and B. inermis primarily invested in phalanx tiller outgrowth and bud placement. Competition rather than intra-annual precipitation variability and clipping altered the clonal growth strategy of these species. Intra- and inter- specific competition did not alter tiller outgrowth for either species. However, inter-specific competition caused both species to alter their bud placement. Bromus inermis shifted more buds from phalanx to guerilla positions while P. smithii shifted in the opposite direction. This may enable invasive B. inermis to expand while confining native P. smithii to more localized areas in the future. Clonal growth strategies appear to be species specific and responsive to inter-specific competition. Investigating the belowground bud aspect of clonal growth can reveal the mechanism driving the future aboveground clonal growth strategy of native and invasive rhizomatous grasses and help inform the patterns of invasion within a plant community. [ABSTRACT FROM AUTHOR]

The South Asian summer monsoon strongly modulates regional temperature and humidity. While extreme dry heat peaks in the pre‐monsoon season, recent literature suggests that extreme humid heat can continue to build throughout the monsoon season. Here we explore the influence of monsoon onset and subseasonal precipitation variability on the occurrence of extreme wet bulb temperatures (Tw) across South Asia. We find that extreme Tw events often occur on rainy days during the monsoon season. However, the influence of precipitation on Tw varies with the background climatology of surface specific humidity. In climatologically drier areas, positive Tw anomalies tend to occur when precipitation increases due to either early onset or wet spells during the monsoon. In contrast, in climatologically humid areas, positive Tw anomalies occur during periods of suppressed precipitation, including both delayed onset and dry spells during the monsoon. Plain Language Summary: The combination of high heat and humidity poses greater risks to human health, productivity, and well‐being relative to elevated temperatures alone. South Asia has already experienced some of the most extreme humid heat observed on Earth. Typically, the highest temperatures in South Asia occur during the pre‐monsoon season in March‐May. While the precipitation and cloudiness associated with the summer monsoon reduce extreme air temperatures, the increased humidity can contribute to the occurrence of extreme humid heat events. Our research finds that a majority of extreme Tw events across South Asia happen on rainy days during the monsoon season. This is especially true for regions where surface humidity is typically low during the monsoon season, and Tw tends to be higher during heavier than usual precipitation spells and during years when the monsoon season starts earlier in the calendar year. In regions with high background surface humidity, however, Tw is more intense when there is less precipitation than usual or when the monsoon onset is delayed. These results help to identify additional times with high risk of heat stress for outdoor workers, and provide a new way of understanding how monsoon variations influence local humid heat. Key Points: In contrast to dry heat, most extreme wet bulb temperature events in South Asia take place on rainy days during the monsoon seasonLocal background specific humidity determines whether wet bulb temperatures are intensified by enhanced or suppressed precipitationBaseline moisture availability also influences whether early or delayed monsoon onset intensifies wet bulb temperature anomalies [ABSTRACT FROM AUTHOR]

Pesticides have well-documented negative consequences to control crop pests, and natural predators are alternatives and can provide an ecosystem service as biological control agents. However, there remains considerable uncertainty regarding whether such biological control can be a widely applicable solution, especially given ongoing climatic variation and climate change. Here, we performed a meta-analysis focused on field studies with natural predators to explore broadly whether and how predators might control pests and in turn increase yield. We also contrasted across studies pest suppression by a single and multiple predators and how climate influence biological control. Predators reduced pest populations by 73% on average, and increased crop yield by 25% on average. Surprisingly, the impact of predators did not depend on whether there were many or a single predator species. Precipitation seasonality was a key climatic influence on biological control: as seasonality increased, the impact of predators on pest populations increased. Taken together, the positive contribution of predators in controlling pests and increasing yield, and the consistency of such responses in the face of precipitation variability, suggest that biocontrol has the potential to be an important part of pest management and increasing food supplies as the planet precipitation patterns become increasingly variable. [ABSTRACT FROM AUTHOR]

As wildfires increase in size and severity, large areas of forest are undergoing substantial increases in shrub cover. In forests where water is the limiting resource, the partitioning of soil water between shrubs and young trees may determine how shrubs affect tree growth and water-stress. Here we evaluated juvenile trees (average age = 32 years) of two dominant conifer species in the southern Sierra Nevada of California (Abies concolor (white fir) and Pinus jeffreyi (Jeffrey pine)) growing in the presence or absence of shrubs. The two shrub species included Arctostaphylos patula and Ceanothus cordulatus , a nitrogen-fixing species. We analyzed the δ2H and δ18O values of xylem water for both tree and shrub species to assess how shrub cover affects the water-uptake patterns of conifers and whether there is niche partitioning between trees and shrubs. We found that growing near shrubs did not have a significant effect on the water source dynamics of either tree species, with similar source water contributions calculated for conifers growing in both the presence and absence of shrubs. Using a tree-ring analysis of growth and δ13C from 2016 to 2021, a period of high precipitation variability, we found that shrub cover had a positive effect on tree growth while decreasing carbon discrimination, which may be due to increased nitrogen availability from Ceanothus cordulatus. Overall, our results suggest that growing in the presence of shrubs does not alter the water uptake patterns of white fir and Jeffrey pine and instead may have a positive effect on the growth rates of these species during both wet and dry years. [ABSTRACT FROM AUTHOR]

This study explores the spatiotemporal variability of the onset, end, and duration of the rainy season in Senegal. These phenological parameters, crucial for agricultural planning in West Africa, exhibit high interannual and spatial variability linked to precipitation. The objective is to detect and spatially classify these indices across Senegal using different approaches. Daily precipitation data and ERA5 reanalyses from 1981 to 2018 were utilized. The employed method enables the detection of key dates. Subsequently, the Kohonen algorithm spatially classifies these indices on topological maps. The results indicate a meridional gradient of the onset, progressively later from the southeast to the northwest, whereas the end follows a north–south gradient. The duration varies from 45 days in the north to 150 days in the south. The use of self-organizing maps allows for classifying the onset, end, and duration of the season into four zones for the onset and end, and three zones for the duration of the season. They highlight the interannual irregularity of transitions, with both early and late years. The dynamic analysis underscores the complex influence of atmospheric circulation fields, notably emphasizing the importance of low-level monsoon flux. These findings have tangible implications for improving seasonal forecasts and agricultural activity planning in Senegal. They provide information on the onset, end, and duration classes for each specific zone, which can be valuable for planning crops adapted to each region. [ABSTRACT FROM AUTHOR]

Life and civilization in arid regions depend on the availability of freshwater. Arid alpine river basins, where hydrological processes are highly sensitive to rapid warming, act as vital water towers for lowland oases. However, scientific understanding of precipitation variability and related cryosphere–hydrology processes is extremely limited because of the scarcity of in situ observations. The upper Danghe River basin (UDB; ∼14,000 km2) is an arid and westerly dominated basin on the northeastern Tibetan Plateau and is the water source for the Dunhuang Oasis in China. We have established a comprehensive cryosphere–hydrometeorology observation network in the basin since 2014. At present, the network consists of 21 automatic rain gauges, 22 soil freeze–thaw monitoring stations, 4 automatic weather stations (AWS), and a 50-m gradient meteorological tower with an eddy covariance system. In particular, the 18 sites, located in remote areas without public networks, are equipped with new-generation BeiDou-3 communication terminals that enable the observations to be easily, safely, and reliably read and quality controlled in near–real time from offices in the city or at home. This integrated observation network over the UDB that facilitates the monitoring of cryosphere–hydrology processes, land–atmosphere interactions, and local weather processes. In addition, the observations are helpful for the objective evaluation, and continual improvement, of hydrological models, satellite-retrieval products, and reanalysis datasets. Finally, the network is expected to promote a better understanding of the status and role of water towers in arid zones and to provide basic data support for the sustainable development of the Dunhuang Oasis and the Belt and Road. [ABSTRACT FROM AUTHOR]

The impact of precipitation variability on food production is very significant. For food-insecure rural areas, understanding the nature of precipitation variability and its teleconnection has paramount importance in guiding regional and local-level decisions. In this study, we analyzed the monthly, seasonal, and annual precipitation variability and the strength of its teleconnection with the global sea-surface temperature (SST) and El Niño/La Niña Southern Oscillation (ENSO) indices in the food-insecure rural areas of Tigray region, Ethiopia. The precipitation, SST, and ENSO indices data for the study were used from 1979 to 2019. A summary of descriptive statistics and Mann-Kendall test methods were applied to detect the existence of trends, and Sen's slope and coefficient of variation are used to analyze the magnitude of the trend and degree of variation in the precipitation pattern. Further, Pearson's correlation is used to determine the effect of ENSO, and SST variations on the precipitation using the canonical correlation analysis. The results revealed that the precipitation over the three districts is characterized by a distinctive bimodal pattern with limited rains in March–May preceding the main rainy season June–September. The limited amount of precipitation, exacerbated by a higher degree of variability, makes the food production in the three districts more uncertain. Besides, there was a very significant decline in the trend of March–May average precipitation and a significant decline in the trend of the annual average precipitation in Hintalo area. The SST of central and eastern equatorial Pacific Ocean, and northeast and northwest equatorial Atlantic Ocean was strongly correlated with the April average precipitation of the three districts. Further, SST of the south, west, and southwest of the equatorial Indian Ocean, and west equatorial Pacific Ocean was associated with July–September average precipitation with greater variation in strength among of the three districts. Moreover, July's average precipitation of the three districts, April's average precipitation of Atsbi and Eirop, and May's precipitation of Hintalo are found significantly associated with the ENSO indices of JFM, FMA, MJJ, and MAM. Therefore, the task of achieving food security in the three districts should incorporate the design of informed food production strategies that can adapt to the limited and variable precipitation based on these SST and ENSO indices. [ABSTRACT FROM AUTHOR]

The tectonically active western Himalayan landscape evolved as a consequence of the interaction of major fluvial systems with long‐term erosional processes. To understand how landslide‐driven erosion impacts the geomorphic evolution of the terrain, we correlated the denudation rates and estimated exhumation ages with their conditioning factors, such as topographic matrices and precipitation intensity. We studied the occurrences of landslides as a function of the primary erosional drivers over precipitation variabilities, such as western disturbance (WD) and Indian summer monsoon (ISM), across the major river catchments in the western Himalayas. Our observation indicated that the phase of the differential precipitation pattern has a substantial impact on the variations in fluvial erosion rates over geological timescales, triggered by landslides. However, erosion patterns are more explicitly linked to tectonically driven topographic growth across the western Himalayan region. The result suggests that the WD precipitation pattern has a significant impact on landslide‐driven erosion across the Chenab, Beas and Sutlej catchments, which extend from the Tethyan to the higher Himalayas and can frequently contribute to increased denudation rates. The interaction of seismicity, litho‐tectonics (MCT–MBT), steep channel gradient (~ > 250) and high steepness (>252 m0.9) may be frequently contributing to an increase in rates of erosion (~ > 2 mm/y) throughout the catchments influenced by the WD, whereas the Yamuna, Ganga and Kali catchments, which are highly impacted by the ISM precipitation pattern and have comparable lower denudation rates (~ < 1.5–2 mm/y) and exhumation ages, are mostly triggered by elevated precipitation intensity (> ~ 2000 mm/y) associated with higher relief change (~3000–5000 m) over the lesser to southern Himalayan front. [ABSTRACT FROM AUTHOR]

Understanding historical droughts in northern China is challenging due to the limited time records of meteorological stations. In this study, we reconstructed the precipitation variability in the middle Taihang Mountains over 414 years by using the tree‐ring width of Pinus tabulaeformis. Based on our climate response analysis, Pinus tabulaeformis growth at the sampling sites was mainly restricted by the total precipitation from August of the previous year to June of the current year (P8‐C6), which was used as the dependent variable for precipitation reconstruction. Spatial analysis demonstrated that the reconstructed precipitation contained obvious spatial representativeness in the Taihang Mountains. We compared the precipitation sequence with other dryness/wetness sequences around the study area, revealing common drought events in most of northern China. Furthermore, the multi‐taper method (MTM) demonstrated a significant period of 2–4 years of the reconstructed precipitation. The precipitation variability in the Taihang Mountains may be influenced by the El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multidecadal Variability (AMV) and has exhibited a negative correlation in recent decades. This study has reconstructed the historical changes in wet and dry conditions to offer a reference for the utilization of modern water resources, especially by linking the decrease in precipitation in the study area with the downfall of the Ming Dynasty. [ABSTRACT FROM AUTHOR]

The predicted intensification of the North American Monsoon is expected to alter growing season rainfall patterns in the southwestern United States. These patterns, which have historically been characterized by frequent small rain events, are anticipated to shift towards a more extreme precipitation regime consisting of fewer, but larger rain events. Furthermore, human activities are contributing to increased atmospheric nitrogen deposition throughout this dryland region.Alterations in rainfall size and frequency, along with changes in nitrogen availability, are likely to have significant consequences for above‐ground net primary production (ANPP) and plant community dynamics in drylands. The conceptual bucket model predicts that a shift towards fewer, but larger rain events could promote greater rates of ANPP in these regions by maintaining soil moisture availability above drought stress thresholds for longer periods during the growing season. However, only a few short‐term studies have tested this hypothesis, and none have explored the interaction between altered rainfall patterns and nitrogen enrichment.To address this knowledge gap, we conducted a 14‐year rainfall addition and nitrogen fertilization experiment in a northern Chihuahuan Desert grassland to explore the long‐term impacts of changes in monsoon rainfall size and frequency, along with chronic nitrogen enrichment, on ANPP (measured as peak biomass) and plant community dynamics.Contrary to bucket model predictions, small frequent rain events promoted comparable rates of ANPP to large infrequent rain events in the absence of nitrogen enrichment. It was only when nitrogen limitation was alleviated that large infrequent rain events resulted in the greatest ANPP. Furthermore, we found that nitrogen enrichment had the greatest impact on plant community composition under the small frequent rainfall regime.Synthesis. Our long‐term field experiment highlights limitations of the bucket model by demonstrating that water and nitrogen availability sequentially limit dryland ecological processes. Specifically, our findings suggest that while water availability is the primary limiting factor for above‐ground net primary production in these ecosystems, nitrogen limitation becomes increasingly important when water is not limiting. Moreover, our findings reveal that small frequent rain events play an important but underappreciated role in driving dryland ecosystem dynamics. [ABSTRACT FROM AUTHOR]

Atmospheric Rivers (ARs), corridors of intensive water vapor transport, have received much attention recently due to their potentially large economic and societal impacts. However, a comprehensive understanding of the interannual variability of ARs over East Asia is still lacking. This study examines the frequency of AR occurrence over East Asia based on the EAR5 reanalysis. It is shown that the frequency of AR occurrence over East Asia displays obvious seasonality, with its peak in early boreal summer. ARs contribute to up to 50% of total precipitation and largely modulate the interannual variability of precipitation in East Asia during early boreal summer. The interannual variability of ARs over East Asia during early boreal summer is largely controlled by the Indo-western Pacific Ocean Capacitor (IPOC) effect, which is mainly triggered by El Niño-Southern Oscillation and sometimes by Indian Ocean dipole. During early boreal summer, a higher frequency of AR occurrence over East Asia is associated with anomalous anticyclonic circulation (AAC) over the Indo-western Pacific region. The AAC, the atmospheric signal of the IPOC mode, indicates an enhanced East Asian summer monsoon and a northwestward shift of the western North Pacific subtropical high, favoring the AR occurrence over East Asia. This study illustrates that a strong positive Indian Ocean dipole event could impact AR activity over East Asia in the following summer by triggering the IPOC effect. The IPOC-related signals 2–4 months ahead could be useful to predict the AR occurrence over East Asia during early boreal summer. [ABSTRACT FROM AUTHOR]

A reliable projection of future risk of decadal megadrought is crucial to adaption and mitigation over eastern China in future climate changes. However, it's difficult to forecast the time of megadrought, which is dominated by internal variability of the model. Using a 50-member ensemble of simulations from the Community Earth System Model Version 2 Large Ensemble (CESM2-LE), it is found that, under the medium-high emission scenario (i.e., SSP3-7.0), internal variability account for all the uncertainty of decadal precipitation variability over eastern China, and the interdecadal Pacific oscillation (IPO) could contribute about 30% to the internal uncertainty during future period (2021–2080). Finally, an emergent constraint based on IPO phase is applied to reduce the uncertainty of simulated precipitation and to forecast the future megadrought risk. The constrained precipitation changes show that northern China will experience a high megadrought risk in the 2050s–2060s, and Yangtze River Valley will experience a high megadrought risk in the 2030s–2040s. These will have great benefit to specific strategies of social infrastructure in the future. [ABSTRACT FROM AUTHOR]

Winter precipitation is critical for glacier growth, snow accumulation, and terrestrial storage on the Tibetan Plateau (TP). However, less attention has been paid to the changes in winter precipitation on the TP. In this study, based on the newly developed high-accuracy precipitation dataset, our diagnosis illustrated a distinct precipitation deficit over the southern TP and northern Indian continent (STNI) in December. Together with the ERA5 reanalysis, CESM1.1 large ensemble experiments, and pacemaker experiments, the dynamic diagnosis revealed that the precipitation deficit was attributed to the decrease in dynamic effects. In particular, the enhanced descending motion, accompanied by the strengthened anticyclone and regional meridional circulation over the STNI, resulted in the precipitation deficit. The changes in circulation system related to the precipitation deficit could be attributed to the Pacific and Indian sea surface temperature (SST) variability. With the negative interdecadal Pacific oscillation (IPO), there were circumglobal alternative geopotential height anomalies and an anomalous anticyclone over the southern TP, and descending motion around the STNI associated with the enhanced Walker circulation over the Indo-Pacific, which exhibited a similar pattern to the precipitation deficit over the STNI in the observations. In addition, the synergistic effect of Pacific and Indian SST variability can improve the simulated precipitation deficit over the STNI relative to the Pacific SST variability alone. These results imply a contribution of the tropical SST variability to the precipitation trends over the STNI in early winter and provide an insight into the understanding of climate warming on the winter climate over the TP. [ABSTRACT FROM AUTHOR]

The seasonal variability of precipitation has a profound impact on water demand for India's agricultural and socio‐economic sectors which are associated with continental and surrounding oceanic moisture sources controlled by dynamic and thermodynamic processes. In this study, moisture sources have been tracked by the Lagrangian trajectory approach over four homogeneous regions: Northwest India (NWI), Central India (CEI), Northeast India (NEI) and South Peninsular India (SPI). ERA‐Interim reanalysis data are used throughout the study for three decades from 1989 to 2018. The results indicate that the multidecadal variability of precipitation has strengthened towards the mid‐decade (1999–2008), mainly attributable to moisture source transport from the Arabian Sea. These enhancement patterns of moisture sources have been widespread over Central India for all three decades. Moisture availability in the boundary layer highly affects the precipitation and it is found that 80% of the moisture above the boundary layer contributes >10% of monsoonal precipitation occurrences. Further, the NEI drying trend in monsoonal rainfall is found to be related to the consequent weakening of the land–ocean temperature gradient (LOTG) during all three decades in this region and the absence of low cloud cover over the region throughout the study period. In addition, the moisture sources are regulated by prevailing large‐scale features such as frequency of La Niña, northward shifting of low‐level jet and strengthening of Hadley cell. [ABSTRACT FROM AUTHOR]

The southwestern United States is highly sensitive to drought, prompting efforts to understand and predict its hydroclimate. Oftentimes, the emphasis is on wintertime precipitation variability, yet the southwestern United States exhibits a summertime monsoon where a significant portion of annual precipitation falls through daily convection activities manifested by a midtropospheric ridge of high pressure. Here, we examine synoptic patterns of the southwestern ridge through a k-means clustering analysis and assess how these synoptic patterns translate into streamflow changes in the upper Colorado River basin. A linear perspective suggests ∼17% of upper Colorado River discharge at the Lee's Ferry, Arizona, gauge comes from summertime monsoon rains. The ridge of high pressure exhibits diversity in its intensity, structure, and position, inducing changes in moisture advection and precipitation. A ridge shifted north or east of its climatological center increases moisture and precipitation over the southwestern United States, while a ridge toward the south or northwest inhibits precipitation. A ridge east of its climatological center contributes to increased streamflow, whereas a ridge west or northwest of its climatological center decreases streamflow. Cooling in the central tropical Pacific and the Pacific meridional mode region favors an eastward shift of the ridge of high pressure corresponding to wet days. Eastern tropical Pacific warming favors a southward shift of the ridge corresponding to dry days. These results support an intermediate scale between climate forcing and summertime Colorado River discharge through changes in the intensity, structure, and position of the southwestern ridge of high pressure, integral to the U.S. Southwest hydroclimate. [ABSTRACT FROM AUTHOR]

Agroclimatic regionalization is an effective way to utilize agricultural climate resources in a reasonable manner. Accurate and objective agroclimatic regionalization plays a great directive role in ecological layout and decision support for agriculture farming. The purpose of this article was to investigate the influence of climate change on agroclimatic regions in China. Following the same regionalization principle concept as the theory and techniques of agroclimatic regionalization, three agroclimatic regions, the Tibetan High Cold Region (THCR), Northwest Arid Region (NAR), and Eastern Monsoon Region (EMR) were identified in China. The changes in the three agroclimatic regions were analyzed from 1961 to 2020 in the past and from 2006 to 2060 in the future. Future changes in agroclimatic regions were estimated from 2006 to 2030 and from 2031 to 2060 under scenarios RCP2.6, RCP4.5, and RCP8.5 for greenhouse gas emissions. The borders of agoclimatic regions had changed as a result of global climate warming and precipitation variability. There was a surplus in the geographical displacement and range of agroclimatic region borders in 1991 to 2020, especially when compared to those in 1961–1990. The TCHR exhibited significant spatial variation, with its northeast corner shifting nearly 170 km to the southwest. In the future, the area ratio of the THCR will be 26% by 2031–2060 under the RCP8.5 scenario, with the highest decline (1% compared to that in the reference period of 1981–2005), while under the RCP4.5 and RCP2.6 scenarios it will stabilize the area ratio at 27%. The eastern boundary of the NAR will migrate south or east, while the center boundary will rise northward. Under all three climatic scenarios, the area ratio will be 25% (down 1%). The range of the EMR will expand. The area ratio of the EMR will increase by 1% under the RCP2.6 and RCP4.5 scenarios and by 2% under the RCP8.5 scenario. Overall, our study may facilitate an in-depth understanding of agroclimatic regions changes and thus provide a scientific reference for the distribution of agricultural production and sustainable development under climate change in China. [ABSTRACT FROM AUTHOR]

We investigated nine indices of spatiotemporal extreme precipitation events over Nicaragua during 2001–16, from GPCC, Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), and IMERG, and their correlation with teleconnection patterns. The main objectives were to evaluate the variability of extreme precipitation events, to know the performance of IMERG and CHIRPS in the characterization of these extreme events, using GPCC and four rain gauges as references, and finally to determine the teleconnection patterns that have the highest correlation with these indices. The spatial coverage of the area with the highest number of consecutive days with daily precipitation less than 1 mm corresponds to the Pacific region, with annual mean values of up to 120 continuous days. Some extreme precipitation event indices (RR, RX1day, and RX5day) show a decreasing trend, suggesting that the study area has been experiencing a reduction of extreme precipitation indices in terms of intensities and duration throughout the study period. In addition, it was observed that CHIRPS shows a better fit when dealing with precipitation events that do not exceed certain thresholds and IMERG improves when describing intense precipitation event patterns. We found that the tropical Pacific SST EOF (EOFPAC), Niño-3.4, Pacific warm pool region (PACWARM), and SOI have a greater influence on extreme precipitation events, these results suggest that they are being controlled by ENSO episodes, providing a better understanding of the climate configuration, as a prediction and forecasting potential, useful for agriculture, land use, and risk management. [ABSTRACT FROM AUTHOR]

This study investigates the coupled variability of temperature and precipitation in eastern China during summer using empirical orthogonal function (EOF) analysis to better understand and mitigate simultaneous occurrences of extreme events, such as compound droughts and heat waves. Two dominant modes are identified: the first exhibits a strong warming and drying trend in the region north of the Yangtze River, with the opposite occurring in the south; the second illustrates decadal oscillations in temperature and precipitation, alternating between cool-wet conditions and warm-dry conditions in southern China. The underlying mechanisms for these leading modes are revealed through correlation, composite analysis, and model simulations. The first mode is associated with a negative Pacific-Japan teleconnection in the lower atmosphere and a stationary Rossby wave train across Eurasia in the upper troposphere, which are influenced by global warming and sea surface temperature anomalies in the western North Atlantic. The second mode is linked to alternating active periods of the North Atlantic Oscillation (NAO) and Pacific Decadal Oscillation (PDO). The NAO exerts a significant influence on the summer climate in eastern China during its active phases, while the PDO shows an opposite effect when the NAO is less active. These findings provide valuable implications for long-term planning and adaptation strategies to better cope with compound extreme events in eastern China. [ABSTRACT FROM AUTHOR]

Basin-scale outcrop analyses of fluvial architecture in the Palaeogene San Juan Basin, New Mexico, document lateral and vertical trends in channel, floodplain and palaeosol characteristics. Herein, the uppermost part of the Palaeocene Nacimiento Formation and lower Eocene Cuba Mesa and Regina Members of the San Jose Formation are identified as deposits of large fluvial fans based on trends observed across the basin. Stratigraphic trends suggest two packages originated by fluvial fan progradation. Progradation of the lower fan system provides a new explanation for the transitional nature of a disconformity at the Nacimiento-San Jose Formation contact, previously thought to be a low-angle unconformity. The two fan systems are separated by a retrogradational interval that culminates in a depositional hiatus at the contact between the Cuba Mesa and Regina Members. This, combined with poor age constraints, indicates that the duration of the disconformity at the base of the Cuba Mesa Member may have been overestimated. Furthermore, the succession is interpreted as deposits of variable-discharge rivers, based on the combined abundance of upper flow regime and high deposition rate sedimentary structures indicative of intense flooding events, preservation of in-channel bioturbation and paedogenic modification indicating periods of prolonged dryness, lack of identifiable bar strata and alternations of poorly drained and well-drained floodplain deposits with pedofacies indicating alternating wetdry cycles. This dataset adds to a growing body of evidence linking the formation of large fluvial fans to discharge variability and thus to hydroclimates with significant inter- and intra-annual precipitation variability and intense rainfall. A longterm stratigraphic shift from poorly drained to well-drained floodplain deposits across two progradational fan successions indicates that a predictive model suggesting downstream decreases in soil drainage conditions is not encompassing of all large fan systems, and instead suggests a transition to a more arid climate across the Palaeocene-Eocene boundary. [ABSTRACT FROM AUTHOR]

Beneficial and negative effects of species interactions can strongly influence water fluxes in forest ecosystems. However, little is known about how trees dynamically adjust their water use when growing with interspecific neighbours. Therefore, we investigated the interaction effects between Fagus sylvatica (European beech) and Picea abies (Norway spruce) on water-use strategies and aboveground structural characteristics. We used continuous in situ isotope spectroscopy of xylem and soil water to investigate source water dynamics and root water uptake depths. Picea abies exhibited a reduced sun-exposed crown area in equally mixed compared with spruce-dominated sites, which was further correlated to a reduction in sap flow of −14.5 ± 8.2%. Contrarily, F. sylvatica trees showed +13.3 ± 33.3% higher water fluxes in equally mixed compared with beech-dominated forest sites. Although a significantly higher crown interference by neighbouring trees was observed, no correlation of water fluxes and crown structure was found. High time-resolved xylem δ2H values showed a large plasticity of tree water use (−74.1 to −28.5‰), reflecting the δ2H dynamics of soil and especially precipitation water sources. Fagus sylvatica in equally mixed sites shifted water uptake to deeper soil layers, while uptake of fresh precipitation was faster in beech-dominated sites. Our continuous in situ water stable isotope measurements traced root water uptake dynamics at unprecedented temporal resolution, indicating highly dynamic use of water sources in response to precipitation and to neighbouring species competition. Understanding this plasticity may be highly relevant in the context of increasing water scarcity and precipitation variability under climate change. [ABSTRACT FROM AUTHOR]

In a recent study, Benestad and colleagues found that the distribution of global precipitation variability in ERA5 appears to have shifted towards smaller spatial scales over the course of the twentieth century. Using an alternative wavelet‐based analysis, we demonstrate that the trends are located almost entirely over the tropical oceans. The phenomenon can be explained by a remarkable shift from parameterized to explicitly resolved convection in this region. The slightly coarser resolved JRA‐55 reanalysis data set exhibits no such trend. A comparison with the conventional data‐only version JRA‐55C reveals that assimilated satellite data can introduce an additional trend in tropical precipitation amount, but does not, on its own, alter the characteristics of tropical precipitation in JRA‐55. An artificial dual‐diurnal cycle in ERA5 total precipitation and convective available potential energy (CAPE) leads us to the conclusion that the unexpected regime shift is induced primarily by changes in the observation system and not real‐world climate change. [ABSTRACT FROM AUTHOR]

Surface winds and precipitation over the tropical oceans are related to sea surface temperature (SST) through multiple mechanisms. Greater SST is associated with greater conditional instability, which in turn is more conducive to deep convection. The associated mass and flow responses can extend to the surface, via associated pressure gradients imprinted on the top of the planetary boundary layer (PBL). SST also influences surface pressure and wind directly through its control over PBL temperature, as explained by Lindzen and Nigam. The authors examine the relative magnitudes of these two influences over the eastern tropical Pacific on subseasonal precipitation variability during northern summer, when and where SST gradients are largest and the direct influence via PBL temperature is expected to be strongest. Geopotential at 1000 hPa is partitioned into two components: the geopotential at the PBL top (the PBL top is chosen to be 850 hPa, supported by an analysis of the vertical structure of geopotential and temperature) and the PBL thickness. These fields are composited on quintiles of daily ITCZ precipitation both with and without a high-pass filter that isolates subseasonal time scales. The PBL thickness varies little between the highest and lowest precipitation quintiles, while the PBL top geopotential varies much more. This supports a view in which the direct contribution of SST to the surface pressure and flow fields, including the associated PBL convergence over sharp SST maxima, can be viewed as a steady forcing on the rest of the column, while free-tropospheric transients contribute most of the variability associated with precipitation on subseasonal time scales. [ABSTRACT FROM AUTHOR]

The article "Climatic legacy effects on the drought response of the Amazon rainforest" by Van Passel et al. (2022) has been corrected to address a coding mistake in the calculation of the maximal drought impact. The correction does not change the main findings of the article, and the trends of frequency and intensity of dry and wet events remain unaffected. The corrected version of the article, along with corrected figures, can be found in the Supporting Information. The document also includes corrigendum figures that visually compare the original stability metrics with the corrected stability metrics, showing a positive linear trend for both resistance and resilience. For more detailed information, refer to Data S1. [Extracted from the article]

An increasing, but spatially inhomogeneous, trend in Tibetan Plateau (TP) precipitation, and especially the precipitation anomalies in southeastern TP (TPSE), has become the subject of major scientific concern. The Indian summer monsoon (ISM) is one of the TPSE's most important moisture sources, and its characteristics are therefore key for precipitation changes. Here we present the ISM activities (ISM onset/retreat date, ISM duration, and ISM intensity) and the percentages of varied moisture sources in TPSE, using OLR datasets and Hysplit modeling with gbl reanalysis. The recent precipitation anomalies in TPSE are analyzed with CMFD reanalysis. Major findings: (1) The ISM in TPSE generally begins later, retreats earlier, is of shorter duration, and weaker in intensity. (2) Uniformly decreasing (increasing) precipitation trends are found in TPSE for periods 1979 − 2018 and 1999 − 2018 (1979 − 1998). (3) Moistures along with the ISM are the primary controls of TPSE precipitation (~ 85% in summer); these are also verified by the generally same linear trends observed in ISM moistures and TPSE precipitation in summer. (4) The precipitation anomalies in TPSE are closely related with the ISM activities: the ISM onset date (retreat date) and its variabilities affect precipitation during May − June (September − October); precipitation during July − August correlates positively with the ISM duration and its intensity. The ISM activities impact the percentages of ISM moistures and finally affect the precipitation amount and their trends. These results will contribute to precipitation-related studies as hydrology, ecology, and paleoclimate reconstructions in TP. [ABSTRACT FROM AUTHOR]

Analyzing trends in precipitation data is crucial for understanding the effects of climate change and making informed decisions about water management and crop patterns. The objective of the presented study was to investigate precipitation trends, analyze temporal and spatial variations and identify potential change points in Turkey throughout the period from 1980 to 2019. Precipitation data were analyzed for both regional and 81 meteorological stations in Turkey on a monthly, seasonal, and annual basis. Spearman rank correlation and Mann–Kendall tests were utilized to detect possible trends and Sen's slope test to estimate the magnitude of change throughout the entire time series. The average precipitation amount of Turkey was determined 639.2 mm between the years 1980 and 2019. While Central Anatolian and Eastern Anatolian regions had below 639.2 mm, other regions were above. The range of seasonal precipitation values were found for winter 128.7–320.8 mm, 108.9–260.0 mm for spring, 43.9–109.3 mm for summer, and 79.7–238.4 mm for autumn. The analysis of the data revealed no significant increase or decrease in annual values on a regional basis, with the greatest change on a seasonal basis being observed in the winter. The 40-year trends of annual precipitation data belonging to 81 stations were decreasing in 23 provinces and increasing in 58 provinces, and 11 of them (14% of the total) were found to be statistically significant. Moreover, November was found to be a month of particular significance in terms of precipitation changes across the country, with a decrease observed in 80 out of 81 provinces. Spatial distribution analysis showed that the magnitude of variation in precipitation decreased as one moved from the southern to the northern regions of the country. [ABSTRACT FROM AUTHOR]

Exploration of the spatiotemporal variability in precipitation gradients (PGs) is important for understanding the spatial differences in precipitation and optimizing hydrological process simulations. Here, the spatiotemporal distribution of precipitation and PG was analyzed in the Tianshan and Qilian Mountains based on national meteorological station data from 1961 to 2017. The relationships between PG and relative humidity and wind speed were explored. The results show that precipitation exhibits a significant increasing trend during the last decades. Precipitation in the Tianshan Mountains is greater in the north and west, the maximum precipitation height (MPH) occurs at 1942.5 m a.s.l., and the precipitation change rate is higher in the west than in the east. Precipitation in the eastern Qilian Mountains is greater, the MPH is approximately 2850 m a.s.l., and the precipitation change rate decreases from the middle to the western and eastern sections. There are noticeable differences in PG between the two mountain areas. Annually, the PG in the Tianshan and Qilian Mountains, except for the Yili Valley, has increased significantly. The PG change rate in the western Qilian Mountains is higher. Monthly, the PG increases most significantly from June to August. Precipitation is positively correlated with elevation in the Tianshan Mountains from April to October and in the western and eastern sections of the Qilian Mountains every month, while that in the middle Qilian Mountains decreases with increasing elevation from November to January. The PG in both mountain regions experienced abrupt changes around the 1970s–1980s, and most areas increased significantly after the abrupt changes, showing a clear humidification phenomenon. Except for some subregions, PG is directly proportional to relative humidity and inversely proportional to wind speed. [ABSTRACT FROM AUTHOR]

The greenhouse effect continues to cause unparalleled changes in drought conditions in regions like Dukan basin. Even though droughts have been increasing in terms of occurrence and intensification in Iraq, limited studies have been conducted to predict future drought events with their characteristics under different climate forcing scenarios. This study was done in the Dukan basin to evaluate future drought characteristics, namely magnitude, duration, intensity, and frequency, using four climate models from CMIP6 under Shared Socio-economic Pathways (SSPs) for two distinct periods of 2020–2050 (near future) and 2050–2080 (far future). The Coupled Model Intercomparison Project (CMIP6) data was dynamically downscaled and then bias corrected using a quantile mapping (QM) approach, with the Climatic Research Units (CRU TS4.04) rainfall data as locus. AgriMetSoft SD-GCM tool was used to downscale the station data. Drought characteristics were characterized at a 12-month scale using the runs theory in AgriMetSoft Drought Monitoring and Prediction (DMAP) software. Among the four CMIP6 models used, the BCC_ESM2_0 was accurate (R2 = 0.952, RMSE = 16.4) than the other models in projecting precipitation. The results indicated that drought regimes with magnitudes from − 0.08 to − 1.4 will intensify from 2024 to 2030. The lowest SPI values ( - 0.03 ± - 1.42 ) were observed under SSP2.6 D2 and the highest SPI values ( - 1.83 ± - 0.72 ) were observed under SSP8.5 D2. Except for SSP2.6 D1, all other scenarios projected frequent drought regimes in the region with high magnitudes and prolonged durations. The findings also showed significant (p < 0.05) temporal variability in precipitation particularly for SSP585 scenarios. Remarkably, the findings of this study provide a basis for the formulation of drought preparedness, risk reduction, and management policies in Iraq. [ABSTRACT FROM AUTHOR]

The precipitation variability and trends were investigated in the Usumacinta River Basin (URB) for the period 1959–2018, based on imputed and homogenized data records from 60 meteorological stations in Mexico and Guatemala. The homogenization process played a crucial role in enhancing the quality of the original precipitation series, reducing regional inconsistencies and improving temporal and spatial coherence. The dataset reliably captured large‐scale climate variations, revealing three regions with similar precipitation variability and trends in the URB. Notably, maximum precipitation occurred at 636 m a.s.l., while minimum precipitation was at 1531 m a.s.l., indicating an orographic effect in the region. Extreme precipitation events were linked to El Niño–Southern Oscillation. Although the Mann–Kendall test showed statistically significant negative trends in only 18% of the stations, integration of Sen's slope analysis and 30‐year normals and dry year occurrences highlighted a progressive shift towards dryer conditions throughout the study period in the URB. These drier conditions could notably affect regions with higher precipitation, requiring special attention due to possible socioeconomic impacts associated with drought events. By identifying these vulnerable regions, policymakers and stakeholders can proactively plan and execute adaptive measures to mitigate the potential impacts of droughts on communities, ecosystems, and economic activities within the basin. [ABSTRACT FROM AUTHOR]

Precipitation is affected by intricate atmospheric dynamic and thermodynamic processes. Horizontal winds are frequently used to represent the dynamic component as winds play a critical role in transporting moisture. Previous studies on precipitation over the Tibetan Plateau (TP) focused on the influence of summer monsoons and westerlies in isolation. However, the collective seasonal dynamics and their combined effects on the precipitation distribution remain less explored. This study aims to determine the seasonal evolutions of the wind patterns and the associated regional precipitation patterns over the TP using a neural network approach and focuses on their interannual variability and long‐term trends. A self‐organizing map (SOM) was used to classify the wind patterns based on 500 hPa winds and related precipitation from the ERA5 reanalysis. The classified wind patterns show seasonal shifts between the Asian summer monsoon circulations and the westerlies along with the westerly jets migrating between the north and south of the TP from summer to winter. The locations of abundant precipitation during the winter and transition seasons are mainly associated with variations in the intensity and locations of the strong westerlies. There is a significant positive trend in the occurrences of the summer‐type wind pattern, which has likely led to a wetter TP, and an earlier‐ended winter and advanced spring wind patterns. The interannual variability of westerlies is highly related to the variability of precipitation in the western TP during its wet season (January–April). In the eastern TP, the interannual variability of the precipitation is linked to the wind patterns associated with the westerly jets to the south of the TP, while precipitation variability in the central TP is controlled by thermodynamic components. This study reveals the spatial precipitation distributions according to the different wind patterns and identifies the contributions from atmospheric components to the regional precipitation over the TP. [ABSTRACT FROM AUTHOR]

Rainfall in the Eastern Mediterranean is strongly modulated by complex topography and localized mesoscale processes. General circulation models (GCMs) struggle to capture daily precipitation variability in the region, both in time and in space. Rain in the Eastern Mediterranean occurs within a hierarchy of scales, as synoptic scale structures often drive local rainfall patterns. Daily rain prediction in the region can therefore benefit from analog downscaling—a nonlinear regression of a high‐resolution predictand from past synoptic‐scale predictors. We present a multiscaled downscaling algorithm of daily rain over Israel. The underlying goal is to create a mechanism‐based tool that will improve the analysis and prediction of precipitation on short time scales in models that cannot produce the field explicitly. We train the algorithm using coarse grid ERA5 reanalysis data and measurements from 21 rain gauges. The routine uses a k‐nearest neighbours algorithm to find the most similar past instances (i.e., analogs) for every predicted day. Analog selection is performed in two steps, based on scale (synoptic and local), as to not overshadow correlative but local predictors. The algorithm also includes several unique aspects tailored to Mediterranean climate: subdaily predictors of cyclone life cycles; representation of upper level cyclonic drivers; and the inclusion of rainfall potential using the Modified K‐Index (MKI). The proposed algorithm has better accuracy (66% correct predictions) compared to non‐downscaled reanalysis and climatological predictions. It better captures the spatial rainfall variance, mitigates the "drizzle bias," and improves skill in extreme event prediction. However, it underestimates very rainy events and has trouble fully representing the spatial variance in the region. Nonetheless, our algorithm represents the potential for computationally inexpensive downscaling of daily precipitation in the Mediterranean with various possible applications, for example, characterization of droughts and storms, linking hydrological and synoptic scale processes and introducing uncertainty estimates using large ensembles. [ABSTRACT FROM AUTHOR]

Elevated spring and summer rainfall in the U.S. Midwest is often associated with a strong Great Plains low-level jet (GPLLJ), which transports moist air northward to the region from the Gulf of Mexico. While the intensity of hourly precipitation extremes depends on local moisture availability and vertical velocity, sustained moisture convergence on longer time scales depends on horizontal moisture advection from remote sources. Therefore, the magnitude of moisture convergence in the Midwest depends in part on the humidity in these moisture source regions. Past work has identified the time-mean spatial distribution of moisture sources for the Midwest and studied how this pattern changes in years with anomalous rainfall. Here, using reanalysis products and an Eulerian moisture tracking model, we seek to increase physical understanding of this moisture source variability by linking it to the GPLLJ, which has been studied extensively. We find that on interannual time scales, an anomalously strong GPLLJ is associated with a shift in the distribution of moisture sources from land to ocean, with most of the anomalous moisture transported to—and converged in—the Midwest originating from the Atlantic Ocean. This effect is more pronounced on synoptic time scales, when almost all anomalous moisture transported to the region originates over the ocean. We also show that the observed positive trend in oceanic moisture contribution to the Midwest from 1979 to 2020 is consistent with a strengthening of the GPLLJ over the same period. We conclude by outlining how projected changes in a region's upstream moisture sources may be useful for understanding changes in local precipitation variability. Significance Statement: In this work, we study how the origin of moisture that forms precipitation in the U.S. Midwest covaries with large-scale atmospheric circulation. Our results show that an intensification of the mean winds tends to increase the proportion of total rainfall that originates from the ocean. This analysis may help to constrain future projections of rainfall extremes in the central United States, as projected changes in humidity over the ocean are typically more robust and better understood than those over land. [ABSTRACT FROM AUTHOR]

An extreme torrential rain (ETR) event occurred in Henan Province, China, during 18–21 July 2021. Based on hourly rain-gauge observations and ERA5 reanalysis data, the ETR was studied from the perspective of kinetic energy (K), which can be divided into rotational wind (VR) kinetic energy (KR), divergent wind kinetic energy (KD), and the kinetic energy of the interaction between the divergent and rotational winds (KRD). According to the hourly precipitation intensity variability, the ETR process was divided into an initial stage, a rapid increase stage, and maintenance stage. Results showed that the intensification and maintenance of ETR were closely related to the upper-level K, and most closely related to the upper-level KR, with a correlation coefficient of up to 0.9. In particular, the peak value of hourly rainfall intensity lagged behind the KR by 8 h. Furthermore, diagnosis showed that K transformation from unresolvable to resolvable scales made the ETR increase slowly. The meridional rotational wind (uR) and meridional gradient of the geopotential (φ) jointly determined the conversion of available potential energy (APE) to KR through the barotropic process, which dominated the rapid enhancement of KR and then caused the rapid increase in ETR. The transportation of K by rotational wind consumed KR, and basically offset the KR produced by the barotropic process, which basically kept KR stable at a high value, thus maintaining the ETR. [ABSTRACT FROM AUTHOR]