Will trees or grasses profit from changing rainfall regimes in savannas?

Increasing rainfall variability is widely expected under future climate change scenarios. How will savanna trees and grasses be affected by growing season dry spells and altered seasonality and how tightly coupled are tree-grass phenologies with rainfall? We measured tree and grass responses to growing season dry spells and dry season rainfall. We also tested whether the phenologies of 17 deciduous woody species and the Soil Adjusted Vegetation Index of grasses were related to rainfall between 2019 and 2023. Tree and grass growth was significantly reduced during growing season dry spells. Tree growth was strongly related to growing season soil water potentials and limited to the wet season. Grasses can rapidly recover after growing season dry spells and grass evapotranspiration was significantly related to soil water potentials in both the wet and dry seasons. Tree leaf flushing commenced before the rainfall onset date with little subsequent leaf flushing. Grasses grew when moisture became available regardless of season. Our findings suggest that increased dry spell length and frequency in the growing season may slow down tree growth in some savannas, which together with longer growing seasons may allow grasses an advantage over C3 plants that are advantaged by rising CO2 levels.

Multi-datasets to monitor and assess meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region.

This study analyzed the meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region from 1994 to 2016. In recent decades, this region has faced prolonged and severe droughts, leading to marked reductions in agricultural productivity and significant challenges to food security and water availability. The datasets employed included a digital elevation model, land use and cover data, soil characteristics, climatic data (temperature, wind speed, solar radiation, humidity, and precipitation), runoff data, images from the MODIS/TERRA and AQUA sensors (MOD09A1 and MODY09A1 products), and soil water content. A variety of methods and products were used to study these droughts: the meteorological drought was analyzed using the Standardized Precipitation Index (SPI) derived from observed precipitation data, while the hydrological drought was assessed using the Standardized Soil Index (SSI), the Nonparametric Multivariate Standardized Drought Index (NMSDI), and the Parametric Multivariate Standardized Drought Index (PMSDI). These indices were determined using water balance components, including streamflow and soil water content, from the Soil Water Assessment Tool (SWAT) model, and evapotranspiration data from the Surface Energy Balance Algorithm for Land (SEBAL). The findings indicate that the methodology effectively identified variations in water dynamics and drought periods in a headwater basin within Brazil's semiarid region, suggesting potential applicability in other semiarid areas. This study provides essential insights for water resource management and resilience building in the face of adverse climatic events, offering a valuable guide for decision-making processes.

Trend analysis of extreme rainfall indices from CHIRPS precipitation estimates over the Lake Tana sub-basin, Abbay Basin of Ethiopia.

Ethiopia is among the African nations most susceptible to climate change because of its frequent droughts and heavy rainfall. Therefore, hydrological and water management problems require an investigation of regional variability and extreme rainfall patterns. This study analyzed the spatiotemporal trends of extreme rainfall in the Lake Tana sub-basin (LTSB) of Ethiopia's upper Blue Nile basin (UBNB) between 1981 and 2019. The trend and geographic patterns of ten extreme rainfall indices are evaluated using high-resolution data from Climate Hazards Group InfraRed Precipitation Stations (CHIRPS). The researcher used RClimDex, an R software tool, to analyze the ten severe rainfall indices. The variability of the extreme rain indices was also assessed by applying the standard anomaly index (SAI). The trend analysis shows that the majority of rainfall indices decreased in the majority of station locations. Among the rainfall locations, the decreasing trend was only significant in 40% consecutive wet days (CWD), 13.33% (R95p and R99p), and 6.66% highest rainfall amount in a 1-day period (RX1day). In contrast, significant positive patterns were revealed in the incidence of rainfall events of number of heavy precipitation days (R10mm), annual total wet day rainfall (PRCPTOT), and consecutive dry days (CDD), with significant positive trends of 26.66% (R10mm) and 40% (PRCPTOT). Furthermore, a spatial distribution result of extreme rainfall trends reveals considerable variations between stations location. Thus, these findings point to the necessity of creating adaptation and mitigation plans for climate change variability within the sub-basin.

Exploring climate shifts in the Ganga-Brahmaputra basin based on rainfall and temperature variability.

Climate change has a significant impact on the Ganga-Brahmaputra (GB) basin, the major food belt of India, which frequently experiences flooding and varied incidences of drought. The current study examines the changing trend of rainfall and temperature in the GB basin over a period of 30 years to identify areas at risk with an emphasis on the Paris Agreement's mandate to keep increasing temperatures below 2 °C. The maximum temperature anomaly in the middle Ganga plains recorded an increase of more than 1.5 °C year-1 in 1999, 2005, and 2009. Some extreme events were observed in the Brahmaputra basin during 1999, 2009, and 2010, where a prominent temperature increase of 1.5 °C year-1 was observed. The minimum temperature revealed an increasing trend for the G-B basin with an anomalous increase of 0.04 to 0.06 °C year-1. The rainfall variability across the Ganga basin shows a rising tendency over the lower Ganga region while the Brahmaputra basin showed a downward trend. To identify the statistical relation between the Global climatic oscillations and regional climate, Standardized Precipitation Index (SPI) and Niño 3.4 were used. The wet and dry period estimation shows a rise in flood conditions in the Ganga basin whereas, in the Brahmaputra basin, an increase in drought frequency was observed. The correlation based on Niño 3.4 and SPI3 presents a negative relation for the monsoon season in the G-B basin revealing a situation of drought occurrence (SPI3 below 0) with increased Nino 3.4 values (El Niño above + 0.4C).

Rainfall anomalies are a significant driver of cropland expansion.

Rainfall anomalies have long occupied center stage in policy discussions, and understanding their impacts on agricultural production has become more important as climate change intensifies. However, the global scale of rainfall-induced productivity shocks on changes in cropland is yet to be quantified. Here we identify how rainfall anomalies impact observed patterns of cropped areas at a global scale by leveraging locally determined unexpected variations in rainfall. Employing disaggregated panel data at the grid level, we find that repeated dry anomalies lead to an increase in cropland expansion in developing countries. No discernible effects are detected from repeated wet events. That these effects are confined to developing countries, which are often dominated by small-holder farmers, implies that they may be in response to reduced yields. The estimates suggest that overall, in developing countries, dry anomalies account for ∼9% of the rate of cropland expansion over the past two decades. We perform several tests to check for consistency and robustness of this relationship. First, using forest cover as an alternative measure, we find comparable reductions in forest cover in the same regions where cropland expands due to repeated dry anomalies. Second, we test the relationship in regions where yields are buffered from rainfall anomalies by irrigation infrastructure and find that the impact on cropland expansion is mitigated, providing further support for our results. Since cropland expansion is a significant driver of deforestation, these results have important implications for forest loss and environmental services.

Living and Responding to Climatic Stresses: Perspectives from Smallholder Farmers in Hanang' District, Tanzania.

This study sought to assess how smallholder farmers have been living and responding to impacts of climate change in Hanang' District, Tanzania. Qualitative and quantitative data were collected using key informant interviews, household surveys, focus group discussions (FGDs) and field observations. Quantitative data from the questionnaire survey were analyzed using Statistical Package for Social Sciences (SPSS), whilst, qualitative data were exposed to content analysis. Rainfall and temperature trends were analyzed using Microsoft Excel and the significance of the trends determined using Mann-Kendall and CUSUM analysis. Most respondents (78%) revealed decreased rainfall amounts and changed onset, and 94% reported increased temperature. Farmers disclosed that droughts and floods are major climatic stresses in the area; this was substantiated by observed increasing and decreasing temperature and rainfall trends respectively. This corroborated with most respondents who perceived decreased rainfall amounts and changed onset, and reported increased temperature levels. Response strategies include crop diversification and drought-resistant crop varieties, migration, abandoning some crops, and short-cycle crops. However, smallholder farmers have been failing to effectively address climatic challenges. We argue that they are still heavily reliant on social, economic, and policy support to improve their adaptive capacity, particularly, transformative responses.

Interactions of urbanisation, climate variability, and infectious disease dynamics: insights from the Coimbatore district of Tamil Nadu.

Climate change and shifts in land use/land cover (LULC) are critical factors affecting the environmental, societal, and health landscapes, notably influencing the spread of infectious diseases. This study delves into the intricate relationships between climate change, LULC alterations, and the prevalence of vector-borne and waterborne diseases in Coimbatore district, Tamil Nadu, India, between 1985 and 2015. The research utilised Landsat-4, Landsat-5, and Landsat-8 data to generate LULC maps, applying the maximum likelihood algorithm to highlight significant transitions over the years. This study revealed that built-up areas have increased by 67%, primarily at the expense of agricultural land, which was reduced by 51%. Temperature and rainfall data were obtained from APHRODITE Water Resources, and with a statistical analysis of the time series data revealed an annual average temperature increase of 1.8 °C and a minor but statistically significant rainfall increase during the study period. Disease data was obtained from multiple national health programmes, revealing an increasing trend in dengue and diarrhoeal diseases over the study period. In particular, dengue cases surged, correlating strongly with the increase in built-up areas and temperature. This research is instrumental for policy decisions in public health, urban planning, and climate change mitigation. Amidst limited research on the interconnections among infectious diseases, climate change, and LULC changes in India, our study serves as a significant precursor for future management strategies in Coimbatore and analogous regions.

Assessment of Spatio-temporal variability of climate in the lower Gangetic alluvial plain.

Global climate change is a cause of concern as extreme events have intensified in recent years, with increased floods and droughts also reported in the Lower Gangetic Plain (LGP). Assessments from Regional Climatic Models (RCM) cannot capture the local climate variability necessary for devising an action plan for climate risk mitigation. The present study aims to fill this gap by assessing the long-term local-scale climate variability using Modified Mann-Kendall (MMK) and Centroidal Day (CD) shifts for the Patna district, which can be extended to other districts in the LGP. The time series is split into two halves to account for changes due to urbanization in recent three to four decades. CD analysis shows a forward shift in the monsoonal and annual rainfall in recent decades. The variability in total rainfall has become more pronounced post-1985 during monsoon, postmonsoon, and winter seasons. An increase of 64.53 mm (18.9%) in surface runoff and a strong correlation between built-up area and precipitation further cement the role of urbanization in local climate change. Despite a 5.74% decrease in monsoonal rainfall, a 3.51 mm/day increase in rainfall intensity is observed during the monsoon. The implications of these variabilities have posed new challenges for the agricultural production and management of water resources and the interactions between groundwater and surface runoff.

The eco-evolutionary significance of rainfall constancy for facultative CAM photosynthesis.

A flexible use of the crassulacean acid metabolism (CAM) has been hypothesised to represent an intermediate stage along a C3 to full CAM evolutionary continuum, when relative contributions of C3 vs CAM metabolism are co-determined by evolutionary history and prevailing environmental constraints. However, evidence for such eco-evolutionary interdependencies is lacking. We studied these interdependencies for the leaf-succulent genus Drosanthemum (Aizoaceae, Southern African Succulent Karoo) by testing for relationships between leaf δ13 C diagnostic for CAM dependence (i.e. contribution of C3 and CAM to net carbon gain), and climatic variables related to temperature and precipitation and their temporal variation. We further quantified the effects of shared phylogenetic ancestry on CAM dependence and its relation to climate. CAM dependence is predicted by rainfall and its temporal variation, with high predictive power of rainfall constancy (temporal entropy). The predictive power of rainfall seasonality and temperature-related variables was negligible. Evolutionary history of the tested clades significantly affected the relationship between rainfall constancy and CAM dependence. We argue that higher CAM dependence might provide an adaptive advantage in increasingly unpredictable rainfall environments when the anatomic exaptation (succulence) is already present. These observations might shed light on the evolution of full CAM.

CAM plant expansion favored indirectly by asymmetric climate warming and increased rainfall variability.

Recent observational evidence suggests that nighttime temperatures are increasing faster than daytime temperatures, while in some regions precipitation events are becoming less frequent and more intense. The combined ecological impacts of these climatic changes on crassulacean acid metabolism (CAM) plants and their interactions with other functional groups (i.e., grass communities) remain poorly understood. Here we developed a growth chamber experiment to investigate how two CAM-grass communities in desert ecosystems of the southwestern United States and northern Mexico respond to asymmetric warming and increasing rainfall variability. Grasses generally showed competitive advantages over CAM plants with increasing rainfall variability under ambient temperature conditions. In contrast, asymmetric warming caused mortality of both grass species (Bouteloua eriopoda and Bouteloua curtipendula) in both rainfall treatments due to enhanced drought stress. Grass mortality indirectly favored CAM plants even though the biomass of both CAM species Cylindropuntia imbricata and Opuntia phaeacantha significantly decreased. The stem's volume-to-surface ratio of C. imbricata was significantly higher in mixture than in monoculture under ambient temperature (both P < 0.0014); however, the difference became insignificant under asymmetric warming (both P > 0.1625), suggesting that warming weakens the negative effects of interspecific competition on CAM plant growth. Our findings suggest that while the increase in intra-annual rainfall variability enhances grass productivity, asymmetric warming may lead to grass mortality, thereby indirectly favoring the expansion of co-existing CAM plants. This study provides novel experimental evidence showing how the ongoing changes in global warming and rainfall variability affect CAM-grass growth and interactions in dryland ecosystems.

Interaction of livestock grazing and rainfall manipulation enhances herbaceous species diversity and aboveground biomass in a humid savanna.

Understanding of the interaction of livestock grazing and rainfall variability may aid in predicting the patterns of herbaceous species diversity and biomass production. We manipulated the amount of ambient rainfall received in grazed and ungrazed savanna in Lambwe Valley-Kenya. The combined influence of livestock grazing and rainfall on soil moisture, herbaceous species diversity, and aboveground biomass patterns was assessed. We used the number of species (S), Margalef's richness index (Dmg), Shannon index of diversity (H), and Pileou's index of evenness (J) to analyze the herbaceous community structure. S, Dmg, H and J were higher under grazing whereas volumetric soil water contents (VWC) and aboveground biomass (AGB) decreased with grazing. Decreasing (50%) or increasing (150%) the ambient rainfall by 50% lowered species richness and diversity. Seasonality in rainfall influenced the variation in VWC, S, Dmg, H, and AGB but not J (p = 0.43). Overall, Dmg declined with increasing VWC. However, the AGB and Dmg mediated the response of H and J to the changes in VWC. The highest H occurred at AGB range of 400-800 g m-2. We attribute the lower diversity in the ungrazed plots to the dominance (relative abundance > 70%) of Hyparrhenia fillipendulla (Hochst) Stapf. and Brachiaria decumbens Stapf. Grazing exclusion, which controls AGB, hindered the coexistence among species due to the competitive advantage in resource utilization by the more dominant species. Our findings highlight the implication of livestock grazing and rainfall variability in maintaining higher diversity and aboveground biomass production in the herbaceous layer community for sustainable ecosystem management.

Soil texture mediates tree responses to rainfall intensity in African savannas.

Rainfall variability is a major determinant of soil moisture, but its influence on vegetation structure has been challenging to generalize. This presents a major source of uncertainty in predicting vegetation responses to potentially widespread shifts in rainfall frequency and intensity. In savannas, where trees and grasses coexist, conflicting lines of evidence have suggested, variously, that tree cover can either increase or decrease in response to less frequent, more intense rainfall. Here, we use remote sensing products and continent-wide soil maps for sub-Saharan Africa to analyze how soil texture and fire mediate the response of savanna tree cover to rainfall climatology. Tree cover increased with mean wet-season rainfall and decreased with fire frequency, consistent with previous analyses. However, responses to rainfall intensity varied: tree cover dramatically decreased with rainfall intensity on clayey soils, at high rainfall, and with rainfall spread over longer wet seasons; conversely, on sandy soils, at low rainfall, and with shorter wet seasons, tree cover instead increased with rainfall intensity. Tree cover responses to rainfall climatology depend on soil texture, accounting for substantial variation in tree cover across African savannas. Differences in underlying soils may lead to divergent responses of savannas to global change.

The impact of inter-annual rainfall variability on African savannas changes with mean rainfall.

Savannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520-780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580-780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wet extremes because of strong resource competition and the increased frequency of fires. At high mean rainfall (780 mm/year), increased variability enhanced savanna resilience. Here, resources were no longer limiting and the slow tree dynamics buffered against variability by maintaining a stable population during 'dry' extremes, providing the basis for growth during wet extremes. Simultaneously, high rainfall years had a weak marginal benefit on grass cover due to density-regulation and grazing. Our results suggest that the effects of the slow tree and fast grass dynamics on tree-grass interactions will become a major determinant of the savanna vegetation composition with increasing rainfall variability.

Termites promote resistance of decomposition to spatiotemporal variability in rainfall.

The ecological impact of rapid environmental change will depend on the resistance of key ecosystems processes, which may be promoted by species that exert strong control over local environmental conditions. Recent theoretical work suggests that macrodetritivores increase the resistance of African savanna ecosystems to changing climatic conditions, but experimental evidence is lacking. We examined the effect of large fungus-growing termites and other non-fungus-growing macrodetritivores on decomposition rates empirically with strong spatiotemporal variability in rainfall and temperature. Non-fungus-growing larger macrodetritivores (earthworms, woodlice, millipedes) promoted decomposition rates relative to microbes and small soil fauna (+34%) but both groups reduced their activities with decreasing rainfall. However, fungus-growing termites increased decomposition rates strongest (+123%) under the most water-limited conditions, making overall decomposition rates mostly independent from rainfall. We conclude that fungus-growing termites are of special importance in decoupling decomposition rates from spatiotemporal variability in rainfall due to the buffered environment they create within their extended phenotype (mounds), that allows decomposition to continue when abiotic conditions outside are less favorable. This points at a wider class of possibly important ecological processes, where soil-plant-animal interactions decouple ecosystem processes from large-scale climatic gradients. This may strongly alter predictions from current climate change models.

Reconciling seasonal hydraulic risk and plant water use through probabilistic soil-plant dynamics.

Current models used for predicting vegetation responses to climate change are often guided by the dichotomous needs to resolve either (i) internal plant water status as a proxy for physiological vulnerability or (ii) external water and carbon fluxes and atmospheric feedbacks. Yet, accurate representation of fluxes does not always equate to accurate predictions of vulnerability. We resolve this discrepancy using a hydrodynamic framework that simultaneously tracks plant water status and water uptake. We couple a minimalist plant hydraulics model with a soil moisture model and, for the first time, translate rainfall variability at multiple timescales - with explicit descriptions at daily, seasonal, and interannual timescales - into a physiologically meaningful metric for the risk of hydraulic failure. The model, parameterized with measured traits from chaparral species native to Southern California, shows that apparently similar transpiration patterns throughout the dry season can emerge from disparate plant water potential trajectories, and vice versa. The parsimonious set of parameters that captures the role of many traits across the soil-plant-atmosphere continuum is then used to establish differences in species sensitivities to shifts in seasonal rainfall statistics, showing that co-occurring species may diverge in their risk of hydraulic failure despite minimal changes to their seasonal water use. The results suggest potential shifts in species composition in this region due to species-specific changes in hydraulic risk. Our process-based approach offers a quantitative framework for understanding species sensitivity across multiple timescales of rainfall variability and provides a promising avenue toward incorporating interactions of temporal variability and physiological mechanisms into drought response models.

Functional diversity increases ecological stability in a grazed grassland.

Understanding the factors governing ecological stability in variable environments is a central focus of ecology. Functional diversity can stabilize ecosystem function over time if one group of species compensates for an environmentally driven decline in another. Although intuitively appealing, evidence for this pattern is mixed. We hypothesized that diverse functional responses to rainfall will increase the stability of vegetation cover and biomass across rainfall conditions, but that this effect depends on land-use legacies that maintain functional diversity. We experimentally manipulated grazing in a California grassland to create land-use legacies of low and moderate grazing, across which we implemented rainout shelters and irrigation to create dry and wet conditions over 3 years. We found that the stability of the vegetation cover was greatly elevated and the stability of the biomass was slightly elevated across rainfall conditions in areas with histories of moderate grazing. Initial functional diversity-both in the seed bank and aboveground-was also greater in areas that had been moderately grazed. Rainfall conditions in conjunction with this grazing legacy led to different functional diversity patterns over time. Wet conditions led to rapid declines in functional diversity and a convergence on resource-acquisitive traits. In contrast, consecutively dry conditions maintained but did not increase functional diversity over time. As a result, grazing practices and environmental conditions that decrease functional diversity may be associated with lasting effects on the response of ecosystem functions to drought. Our results demonstrate that theorized relationships between diversity and stability are applicable and important in the context of working grazed landscapes.

Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable.

Assessment of climate change induced rainfall trend and variability with non-parametric and linear approach for Sirajganj district, Bangladesh.

The monthly and annual trends and variance of rainfall have been studied for five stations in an economically important Bangladeshi district named Sirajganj since 1965 to 2021. Natural disasters have prevalent in Sirajganj which is indispensable to assess. But, several researchers have been normally focused on river bank management and flood risk assessment. However, no extensive research has been conducted on Sirajganj based on non-normally distributed time series meteorological data such as rainfall time series so the current study is very important. In this study, the non-parametric Mann-Kendall and Sen's methods have been used to determine the statistical significance of a positive or negative trend in rainfall data. Also, cumulative sum charts and bootstrapping, one-way ANOVA, Tukey's range tests, and linear regression have been used to discover the incidence of abrupt changes, compare the significant difference in monthly and annual rainfall data, multiple comparisons amidst mentioned stations to find changes, and to investigate the changeover on dry and rainy days, respectively. The analysis showed a statistically significant decreasing trends in monthly and annual rainfall series. As well, changes from positive to negative direction have been recognized in the February, May, July, September, and annual rainfall time sequence. Besides, ANOVA and Tukey's range tests revealed a statistically substantial difference in all monthly and annual rainfall volume excluding January, March, and June. Additionally, these two tests demonstrated momentous differences in all monthly and annual frequency of rainfall categories excepting January and April. However, Linear regression analysis revealed that the number of dry days gradually reduced at the end of the dry winter, though the number of rainy days decreased during the rainy season. As in, the number of rainy days replaces the number of dry days during the dry season and vice versa during the rainy season. Even though, with very few exceptions, the volume of rainfall decreases throughout the year. The outcomes of this research might helpful for implementing the planning and evaluating hydrological projects on Sirajganj district.

Orbitally forced and internal changes in West African rainfall interannual-to-decadal variability for the last 6000 years.

Recent variability in West African monsoon rainfall (WAMR) has been shown to be influenced by multiple ocean-atmosphere modes, including the El Niño Southern Oscillation, Atlantic Multidecadal Oscillation and the Interdecadal Pacific Oscillation. How these modes will change in response to long term forcing is less well understood. Here we use four transient simulations driven by changes in orbital forcing and greenhouse gas concentrations over the past 6000 years to examine the relationship between West African monsoon rainfall multiscale variability and changes in the modes associated with this variability. All four models show a near linear decline in monsoon rainfall over the past 6000 years in response to the gradual weakening of the interhemispheric gradient in sea surface temperatures. The only indices that show a long-term trend are those associated with the strengthening of the El Niño Southern Oscillation from the mid-Holocene onwards. At the interannual-to-decadal timescale, WAMR variability is largely influenced by Pacific-Atlantic - Mediterranean Sea teleconnections in all simulations; the exact configurations are model sensitive. The WAMR interannual-to-decadal variability depicts marked multi-centennial oscillations, with La Niña/negative Pacific Decadal Oscillation and a weakening and/or poleward shift of subtropical high-pressure systems over the Atlantic favoring wet WAMR anomalies. The WAMR interannual-to-decadal variability also depicts an overall decreasing trend throughout the Holocene that is consistent among the simulations. This decreasing trend relates to changes in the North Atlantic and Gulf of Guinea Sea Surface Temperature variability. Supplementary Information: The online version contains supplementary material available at 10.1007/s00382-023-07023-y.

Observations of enhanced rainfall variability in Kenya, East Africa.

Understanding local patterns of rainfall variability is of great concern in East Africa, where agricultural productivity is dominantly rainfall dependent. However, East African rainfall climatology is influenced by numerous drivers operating at multiple scales, and local patterns of variability are not adequately understood. Here, we show evidence of substantial variability of local rainfall patterns between 1981 and 2021 at the national and county level in Kenya, East Africa. Results show anomalous patterns of both wetting and drying in both the long and short rainy seasons, with evidence of increased frequency of extreme wet and dry events through time. Observations also indicate that seasonal and intraseasonal variability increased significantly after 2013, coincident with diminished coherence between ENSO (El Nino Southern Oscillation) and rainfall. Increasing frequency and magnitude of rainfall variability suggests increasing need for local-level climate change adaptation strategies.