Interannual Variability Of Precipitation Research Articles

Impact of ENSO on extreme precipitation in Southwest Asia

The El Niño-Southern Oscillation (ENSO) is a primary driver of interannual variability in extreme precipitation in many regions worldwide. Understanding the relationship between ENSO and extreme precipitation is crucial, as it has implications for understanding the interannual variability of flood risk. We investigated the frequency of extreme daily precipitation in Southwest Asia across different seasons during El Niño and La Niña using the daily GPCP and ERA5 precipitation datasets for the period 1997–2022. Extreme precipitation at each grid point is defined as daily accumulated precipitation exceeding the 95th percentile on wet days, where a wet day is defined as one with at least 0.1 mm rainfall. El Niño is associated with an overall increase in the frequency of extreme precipitation in Southwest Asia during autumn, winter, and spring, whereas La Niña shows the opposite effect. To explore the dynamics of El Niño and La Niña teleconnections to Southwest Asia, we applied a feature tracking method on the ERA5 relative velocity at 850 hPa in different seasons. Overall, the storm track density and the mean intensity of storms increase in Southwest Asia during El Niño and decrease during La Niña in autumn, winter, and spring. In summer, El Niño favors less frequent extreme precipitation in the southern parts of Southwest Asia, where the tropical summer monsoon circulation is dominated, while La Niña is associated with more frequent extreme precipitation in this region. This pattern is expected, as the monsoon circulation is weaker during El Niño and stronger during La Niña. In line with this, we identified a decrease in the mean intensity of storms in the southern parts of Southwest Asia during El Niño, with the opposite occuring during La Niña. Our findings have important implications for understanding interannual variability of extreme precipitation in Southwest Asia and providing a framework for predicting such events.

The Performance of GPM IMERG Product Validated on Hourly Observations over Land Areas of Northern Hemisphere from Global Meteorological Stations

The integrated multi-satellite retrievals for the global precipitation measurement (IMERG) data, which is the latest generation of multi-satellite fusion inversion precipitation product provided by the Global Precipitation Measurement (GPM) mission, has been widely applied in hydrological research and applications. However, the quality of IMERG data needs to be validated, as this technology is essentially an indirect way to obtain precipitation information. This study evaluated the performance of IMERG final run (version 6.0) products from 2001 to 2020, using three sets of gauge-derived precipitation data obtained from the Integrated Surface Database, China Meteorological Administration, and U.S. Climate Reference Network. The results showed a basic consistency in the spatial pattern of annual precipitation total between IMERG data and gauge observations. The highest and lowest correlations between IMERG data and gauge observations were obtained in North Asia (0.373, p < 0.05) and Europe (0.308, p < 0.05), respectively. IMERG data could capture the bimodal structure of diurnal precipitation in South Asia but overestimates a small variation in North Asia. The disparity was attributed to the frequency overestimation but intensity underestimation in satellite inversion, since small raindrops may evaporate before arriving at the ground but can be identified by remote sensors. IMERG data also showed similar patterns of interannual precipitation variability to gauge observation, while overestimating the proportion of annual precipitation hours by 2.5% in North America, and 2.0% in North Asia. These findings deepen our understanding of the capabilities of the IMERG product to estimate precipitation at the hourly scale, and can be further applied to improve satellite precipitation retrieval.

The first firn core from Peter I Island – capturing climate variability across the Bellingshausen Sea

Abstract. Peter I Island is situated in the Bellingshausen Sea, a region that has experienced considerable climate change in recent decades. Warming sea surface temperatures and reduced sea ice cover have been accompanied by warming surface air temperature, increased snowfall, and accelerated mass loss over the adjacent ice sheet. Here we present data from the first firn core drilled on Peter I Island, spanning the period 2001–2017 CE. The stable water isotope data capture regional changes in surface air temperature and precipitation (snow accumulation) at the site, which are highly correlated with the surrounding Amundsen–Bellingshausen seas and the adjacent Antarctic Peninsula (r > 0.6, p < 0.05). The firn core data, together with the unique in situ data from an automatic weather station, confirm the high skill of the ERA5 reanalysis in capturing daily mean temperature and inter-annual precipitation variability, even over a small sub-Antarctic island. This study demonstrates the suitability of Peter I Island for future deep-ice-core drilling, with the potential to provide a valuable archive to explore ice–ocean–atmosphere interactions over decadal to centennial timescales for this dynamic region.

Role of Tropical Disturbances along the South Asian Monsoon Trough in the 2022 Pakistan Floods and the Implications for Interannual Variability

Abstract This study examined the atmospheric circulation patterns that were responsible for the severe flooding that occurred in Pakistan in 2022. It focused on the role of westward-propagating tropical disturbances (TDs) along the South Asian monsoon trough, which are associated with flood-related precipitation events. The study also investigated the interannual precipitation variation in Pakistan over 23 years from 2000 to 2022, using satellite-derived precipitation and atmospheric reanalysis. The results showed high precipitation in southern and central Pakistan, implying tropical influences. The precipitation was the highest in the past 23 years. The massive rainfall was brought by several TDs under the highest water vapor conditions, although a TD of South Asia climatologically tends to weaken before affecting Pakistan. Enhanced easterlies along the Indo-Gangetic Plain, part of the enhanced monsoon trough, supported high water vapor conditions over Pakistan. The high water vapor was also partly supported by the long-lasting active phase of the South Asian monsoon intraseasonal oscillation in 2022. Moreover, the La Niña condition increased moisture transport as a background. On an interannual time scale, the enhanced moisture flux over the Indo-Gangetic Plain resulted in higher precipitation over Pakistan, as occurred in 2022. These high (low) water vapor and precipitation can be partly explained by La Niña (El Niño). However, La Niña and El Niño may not control the TD activity over South Asia. Thus, for 2022, the high water vapor is somewhat empirically predictable, but the active TD activity can be coincidental. Significance Statement In 2022, Pakistan was hit by catastrophic flooding that affected 15% of the population. The analysis of the atmospheric circulation associated with the flooding indicates that weak but rain-bearing tropical disturbances played a significant role in flooding. Several tropical disturbances stayed or moved into Pakistan, bringing massive rainfall although, usually, they tend to weaken before hitting Pakistan. In the past 23 years, La Niña–related weather patterns have partly explained the year-to-year precipitation variation in Pakistan. However, in 2022, the unusually heavy flooding was due to the combined La Niña effect and tropical disturbance activity. Because it is still difficult to predict the seasonal tropical disturbance activity from La Niña, El Niño, and other climatic conditions, seasonal prediction of these floods remains challenging.

A non-stationary bias adjustment method for improving the inter-annual variability and persistence of projected precipitation

Hydrological studies depend heavily on environmental variables, such as precipitation and resulting runoff, which exhibit highly seasonal and intermittent behaviour in semiarid basins. In these basins, the use of traditional methods to adjust biases in time series projections can lead to inaccurate results regarding the impacts of climate change. This study introduces a non-stationary bias adjustment methodology (NS) specifically designed for environmental variables characterized by sporadic events and substantial intensity variability, such as precipitation. The methodology involves establishing a probability threshold to adapt the occurrence of precipitation events and utilizes a quantile mapping method based on a non-stationary theoretical and parametric distribution to adjust biases associated with precipitation intensity. The NS method is applied to daily precipitation projections from seven regional climatic models under the RCP 8.5 scenario spanning 2006–2100, alongside historical concurrent data from 1970 to 2005. The present method is compared to the widely used quantile delta mapping approach (QDM), revealing significant differences in performance related to the distribution of precipitation events throughout the year and the behaviour of mean and extreme intensity values. Both approaches show reliable performance, with root mean square errors between the empirical distribution functions of the corrected hindcast time series and the observations being lower than or close to 1 mm for the percentiles smaller than 50th. The error increases with the percentiles, particularly at stations located at higher altitudes. In these locations, QDM doubles or triples the error obtained with the non-stationary approach for percentiles higher than 75th, reaching up to 34 mm. The proposed methodology demonstrates promising potential in reducing uncertainties associated with systematic errors in inter-annual precipitation variability. It is a first step to jointly apply a similar approach to all involved driving variables. Such methods are key to assessing hydrological responses and associated impacts in semi-arid mountainous basins all around the Globe.

The Impact of Major Ecological Projects on the Water Yield of Mountain Basins, Northern China

Water yield, one of the most valuable and important ecological indicators, reflects the renewable capacity of regional water resources. The Taihang Mountains are a natural ecological barrier and an important source of water production for the North China Plain. Two large-scale projects involving returning farmland to forest and grassland have significantly changed the distribution of land use in the Taihang Mountains, and also affect the water production characteristics of the Taihang Mountains. Taking the Hutuo River Basin, a typical river in the Taihang Mountainous region, as the study area, the InVEST model is utilized to calculate the spatial and temporal changes in water yield capacity in the Hutuo River basin, and four scenarios were set to judge the impact of different ecological projects on the water yield of the mountainous watershed of the Hutuo River. The results showed that the water yield in the five study periods was 218.58–376.44 mm. The interannual variations in both precipitation and water yield of the study area in the last decade were large. The water yield is mainly concentrated in the northeast region of the upper reaches of the basin, and the smallest is the northwest and central regions of the upper reaches. The water yield in each year in the study area is mainly less than 400 mm, accounting for more than 60% of the study area, and the water yield has shown a large regional expansion in the past 10 years. Grassland has the largest water yield capacity of all land use types, and climate change has basically no effect on the water yield capacity of different land use types. The ecological project of returning farmland to forestland has a negative impact on the water yield capacity, whereas the water yield capacity increases after returning farmland to grassland. The water conservancy project of river training has a negative impact on the water yield capacity of the Hutuo River mountainous basin. The research results provide theoretical data for judging the relationship between vegetation restoration and water yield in mountainous watersheds, a scientific basis for evaluating the implementation effect of major projects, and strong data support for water resource management in the North China Plain.

An intrinsic low-frequency atmospheric mode of the Indonesian-Australian summer monsoon

AbstractDeep convection in the Indo-Pacific warm pool is vital in driving global atmospheric overturning circulations. Year-to-year variations in the strength and location of warm pool precipitation can lead to significant local and downstream hydroclimatic impacts, including floods and droughts. While the El Niño-Southern Oscillation (ENSO) is recognized as a key factor in modulating interannual precipitation variations in this region, atmospheric internal variability is often as important. Here, through targeted atmospheric model experiments, we identify an intrinsic low-frequency atmospheric mode in the warm pool region during the austral summer, and show that its impact on seasonal rainfall is comparable to ENSO. This mode resembles the horizontal structure of the Madden-Julian Oscillation (MJO), and may play a role in initiating ENSO as stochastic forcing. We show that this mode is not merely an episodic manifestation of MJO events but primarily arises from barotropic energy conversion aided by positive feedback between convection and circulation.

Aridity drives the response of soil total and particulate organic carbon to drought in temperate grasslands and shrublands.

The increasing prevalence of drought events in grasslands and shrublands worldwide potentially has impacts on soil organic carbon (SOC). We leveraged the International Drought Experiment to study how SOC, including particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) concentrations, responds to extreme drought treatments (1-in-100-year) for 1 to 5 years at 19 sites worldwide. In more mesic areas (aridity index > 0.65), SOC and POC concentrations decreased by 7.9% (±3.9) and 15.9% (±6.2) with drought, respectively, but there were no impacts on MAOC concentrations. However, drought had no impact on SOC, POC, or MAOC concentrations in drylands (aridity index < 0.65). The response of SOC to drought varied along an aridity gradient, concomitant with interannual precipitation variability and standing SOC concentration gradients. These findings highlight the differing response magnitudes of POC and MAOC concentrations to drought and the key regulating role of aridity.

Impact of Summer North Atlantic Sea Surface Temperature Tripole on Precipitation over Mid–High-Latitude Eurasia

Abstract Eurasia is a sensitive and high-risk region for global climate changes, where climate anomalies significantly influence natural ecosystems, human health, and economic development. The North Atlantic tripole (NAT) sea surface temperature anomaly is crucial to interannual precipitation variations in Eurasia. Several studies have focused on the link between the NAT and climate anomalies in winter and spring. However, the mechanism by which the summer NAT impacts climate anomalies in Eurasia remains unclear. This study examines how the NAT impacts interannual variations of summer precipitation in mid–high-latitude Eurasia. Precipitation variations are associated with the atmospheric teleconnection triggered by the NAT. When the NAT is in its positive phase, the anomalous atmospheric diabatic heating over the North Atlantic excites an equivalent-barotropic Rossby wave train response that propagates eastward toward Eurasia, resulting in atmospheric circulation anomalies over the region. The combined effects of atmospheric circulation, radiative forcing, and water vapor transport anomalies lead to decreased precipitation across northern Europe and central Eurasia, with higher precipitation anomalies over northeast Asia. Finally, numerical experiments verify that the summer NAT excites atmospheric teleconnections that propagate downstream, affecting precipitation anomalies in mid–high-latitude Eurasia. This study provides a scientific basis for predicting Eurasian summer precipitation and strengthening disaster management strategies.

Unraveling the role of the western North Pacific circulation anomaly in modulating Indian summer monsoon rainfall variability beyond ENSO

The Indian summer monsoon (ISM) rainfall interannual variability is known to be strongly linked to the El-Niño–Southern Oscillation (ENSO). This linear relationship is the primary factor in controlling the interannual variation in ISM precipitation. However, there are many outlier cases, and such deviations pose significant challenges in seasonal prediction over this region. Here we show that such challenges can be attributed to anomalous atmospheric pressure patterns in the Western North Pacific (WNP) region. The anticyclonic circulation anomaly over WNP region causes the easterly wind toward the Indian subcontinent, leading to positive precipitation anomalies with stronger low-level moist convergence, while the cyclonic circulation decreases ISM precipitation. The linear baroclinic model simulation results further support that the WNP circulation pattern can serve as an independent factor for forecasting precipitation over India. The WNP circulation anomaly play the crucial role generating ISM precipitation particularly for July and September. Our study suggests that the role of the WNP circulation anomaly should be carefully considered as the secondary prevailing mechanism on the subseasonal timescale during the boreal summer in addition to the ENSO signal.

Upwind Moisture Controls on Interannual Variations of Precipitation and Vegetation in China's Drylands

AbstractDryland precipitation depends on upwind and local moisture sources via moisture recycling. How upwind moisture variations affect interannual variations of downwind precipitation and vegetation in China's drylands remains unclear. We used high‐resolution moisture tracking data sets and found terrestrial moisture (93%) was the dominant moisture source for China's drylands, especially from drylands themselves (46%). In most dryland grids, we observed strong correlations between precipitation and upwind moisture sources from 2003 to 2022 (median r = 0.55), with a more significant effect in drier areas. These demonstrated the upwind moisture control on interannual variations of dryland precipitation, in which internal moisture from drylands exceeds the influence of external terrestrial sources. The upwind moisture variations, especially the recycled moisture of drylands, propagate to influence downwind vegetation greenness in precipitation‐sensitive dryland areas. Our findings revealed that upwind moisture variations induced by climate or land‐cover changes have important implications for water and food security in China's drylands.

Assessing changes in intra- and inter-annual precipitation variability using advanced statistical inference techniques

ABSTRACT Aiming to find statistically significant changes on the usual monthly weather conditions in Alentejo, Portugal, in the past 40 years, time series of precipitation from a grid of locations in Alentejo were studied using an unconventional approach. The time series were divided into 4 decades and disposed in contingency tables with two factors, Year and Month. Then, log-linear models were fitted to those tables. The model deviances for Year and Month represent the weight of each factor in explaining precipitation variability and Year:Month deviance is an estimate of the lack of independence between both factors, representing changes in intra-annual precipitation variability. The set of all the models deviances, per decade and location, were analysed using ANOVA techniques, first to compare the four decades, then to perform a crossed comparison between decades and between four pre-defined zones. Results indicate significant differences between the oldest and recent decades in terms of intra-annual precipitation variability, which could be interpreted as a trend towards softening the differences in precipitation between the wet months of the year. Furthermore, two homogeneous sub-regions could be defined in Alentejo, a large interior region and a smaller one close to the Atlantic Ocean.

Dominant Role of Eurasian Evaporation on the Moisture Sources of the Interannual Variations in Central Asian Summer Precipitation

Abstract The precipitation changes in arid and semiarid central Asia have great impacts on the local fragile ecosystem. The summer precipitation in central Asia shows obvious interannual variations, but the corresponding crucial moisture transporting processes remain unclear. Therefore, this study employs the Lagrangian flexible particle (FLEXPART) diffusion model to achieve this goal. Results show that the moisture of climatological summer precipitation in central Asia is mainly from the local regions, the surrounding western and northern Eurasian regions. The contribution of local evaporation from western central Asia is about 2 times that from eastern central Asia. At the interannual time scale, the moisture variations are mainly influenced by the local regions and western Eurasia, while the local evaporation is mainly from western central Asia. Totally, the Eurasian evaporation plays a dominant role in the interannual variations of central Asian summer precipitation by contributing more than 90% of the total moisture. The moisture transports associated with central Asian summer precipitation interannual variations are impacted by the anomalous cyclones over the western and northeastern parts of central Asia during the wet years, which enhance the moisture convergence and hence increase the summer precipitation in central Asia. The anomalous cyclone over the western part of central Asia is correlated with the changes in the intensity of Eurasian summer subtropical westerly jet (ESSWJ), while the anomalous cyclone over the northeastern part of central Asia is correlated with both ESSWJ and the British–Baikal Corridor pattern teleconnection in association with the polar front jet.

An assessment of the vulnerability and adaptation potential of sugarcane production to water stress, southern Africa

The high spatial variability of precipitation, heightened frequency of droughts and concomitant increases in exposure to water stress across southern Africa due to climate change, presents significant challenges for sugarcane production and the regional sugarcane production value chain. While production has intensified in the past few decades, yields have declined due to increased climatic variability and agronomic management approaches. Increased precipitation variability has enhanced sugarcane vulnerability to water stress and is likely to negatively affect yields. Combining crop simulations and relationships between sugarcane water use and observed rainfall, we introduce a crop productivity ratio (CPR) which assesses sugarcane water stress for six sugarcane mills across southern Africa. The CPR and simulation results were used to assess the adaptation potential or ‘space’ for mill areas that have varying rates of exposure and abilities to adapt to water stress. Simulation results were used to determine the long-term adaption potential of mill areas and to surmise the causes of yield declines. The results were used to offer recommendations to reduce vulnerabilities and enhance adaptation to water stress. We conclude that the amplification of inter-annual precipitation variability will enhance the exposure of sugarcane to water stress and require adaptation interventions. Adapting to external shocks is a multifaceted exercise that requires a holistic approach that includes every aspect of the sugarcane value chain.

Enhanced Mid-to-Late Summer Precipitation over Midlatitude East Asia under Global Warming

Abstract East Asian summer monsoon precipitation is projected to increase under greenhouse warming with strong intraseasonal variation. Using a 35-member CESM Large Ensemble and 30 CMIP6 models, this study reveals that in July and August, maximum rainfall changes in East Asia take place in the midlatitudes, influencing regions encompassing North and Northeast China, the Korean Peninsula, and Japan. The intensified precipitation is attributed to the combined effect of the thermodynamic and dynamic components. The former stems from the enriched low-level moisture, which peaks in continental East Asia in July and August, under global warming. The dynamic effect is due to the enhanced upward motion, associated with the enhanced southerlies throughout the troposphere over midlatitude East Asia. The southerlies also act to intensify the low-level monsoonal circulation, strengthening moisture transport from the tropical ocean to the midlatitudes. In addition to the mean-state changes, the precipitation interannual variability in this region also intensifies, partly due to the enhanced low-level moisture and partly associated with enhanced large-scale circulation anomalies, such as the northwestern Pacific anticyclone. The enhanced background precipitation, along with the intensified interannual variability, may lead to more rainy summers in a warmer climate, with instances where historically extreme precipitation events become more frequent, posing challenges for water resource management and agriculture in the region.

Asymmetry of winter precipitation event predictions in South China

Winter precipitation anomalies in South China (SC) frequently result in severe disasters. However, the evaluation of prediction performance and distinctions between positive precipitation anomaly events (PPA, wet condition) and negative precipitation anomaly events (NPA, dry condition) in current operational models remains incomplete. This study employed the Climate Forecast System version 2 (CFSv2) to assess winter precipitation prediction accuracy in SC from 1983 to 2021. Differences in predicting PPA and NPA events and the underlying physical mechanisms were explored. The results indicate that CFSv2 can effectively predict interannual variations in winter precipitation in SC, as there is a significant time correlation coefficient of 0.68 (0.62) between observations and predictions, with a lead time of 0 (3) months. The model revealed an intriguing asymmetry in prediction skills: PPA outperformed NPA in both deterministic and probabilistic prediction. The higher predictability of PPA, as indicated by the perfect model correlation and signal-to-noise ratio, contributed to its superior prediction performance when compared to NPA. Physically, tropical signals from the ENSO and extratropical signals from the Arctic sea ice anomaly, were found to play pivotal roles in this asymmetric feature. ENSO significantly impacts PPA events, whereas NPA events are influenced by a complex interplay of factors involving ENSO and Arctic sea ice, leading to low NPA predictability. The capability of the model to replicate Arctic sea ice signals is limited, but it successfully predicts ENSO signals and reproduces their related circulation responses. This study highlights the asymmetrical features of precipitation prediction, aiding in prediction models improvement.

Disturbance amplifies sensitivity of dryland productivity to precipitation variability.

Variability of the terrestrial global carbon sink is largely determined by the response of dryland productivity to annual precipitation. Despite extensive disturbance in drylands, how disturbance alters productivity-precipitation relationships remains poorly understood. Using remote-sensing to pair more than 5600 km of natural gas pipeline corridors with neighboring undisturbed areas in North American drylands, we found that disturbance reduced average annual production 6 to 29% and caused up to a fivefold increase in the sensitivity of net primary productivity (NPP) to interannual variation in precipitation. Disturbance impacts were larger and longer-lasting at locations with higher precipitation (>450 mm mean annual precipitation). Disturbance effects on NPP dynamics were mostly explained by shifts from woody to herbaceous vegetation. Severe disturbance will amplify effects of increasing precipitation variability on NPP in drylands.

Anthropogenic Changes in Interannual-to-Decadal Climate Variability in CMIP6 Multiensemble Simulations

Abstract As well as having an impact on the background state of the climate, global warming due to human activities could affect its natural oscillations and internal variability. In this study, we use four initial-condition ensembles from the CMIP6 framework to investigate the potential evolution of internal climate variability under different warming pathways for the twenty-first century. Our results suggest significant changes in natural climate variability and point to two distinct regimes driving these changes. The first is a decrease in internal variability of surface air temperature at high latitudes and all frequencies, associated with a poleward shift and the gradual disappearance of sea ice edges, which we show to be an important component of internal variability. The second is an intensification of the interannual variability of surface air temperature and precipitation at low latitudes, which appears to be associated with El Niño–Southern Oscillation (ENSO). This second regime is particularly alarming because it may contribute to making the climate more unstable and less predictable, with a significant impact on human societies and ecosystems.

The impact of grazing on biodiversity and forest succession in the Brazilian dry forest region is constrained by non-equilibrium dynamics

The impacts of grazing on rangelands have historically been studied within the framework of the equilibrium model, which predicts significant impacts of grazing on ecosystems. However, in recent decades, studies have observed a non-equilibrium pattern, suggesting that abiotic factors play a primary role compared to grazing. These studies are primarily focused on rangelands, despite animal husbandry occurring in other biomes, such as seasonally dry tropical forests. Our study examines the influence of goat grazing on biodiversity and forest succession in the Brazilian dry forest (Caatinga). Considering its high interannual precipitation variability, we hypothesize a response that aligns with the non-equilibrium paradigm. We established a gradient of grazing intensity and history in areas at different stages of vegetation succession. A survey of tree - shrub and herbaceous species was conducted at each site and the biomass of both strata was quantified. Linear mixed models and Permanova were employed to assess differences in richness, composition, structure, and biomass among the areas. Our results suggest that grazing (history and intensity) and forest fallow age did not affect species richness, but only species composition. Low and high grazing intensity drive ecosystems toward similar compositions, which align with the non-equilibrium model predictions. Biomass in the herbaceous layer remained unaffected by grazing history, intensity, or forest fallow age, whereas woody biomass was influenced by grazing intensity in older forest fallows. Although trees in low-intensity grazing sites were significantly taller compared to those in other levels, overall, grazing did not disrupt the natural succession process. Older forest fallows exhibited greater diversity and higher basal area compared to new forest fallows, irrespective of grazing intensity. Our findings suggest that: a) grazing has minimal effects on biodiversity and biomass due to non-equilibrium dynamics, and b) with appropriate management, grazing can coexist with the conservation of the Caatinga.

Earth system model’s capability of predicting drought-induced crop failure

We used the Meteorological Research Institute Earth System Model to investigate land precipitation and net primary production (NPP, proxy for agricultural production here) in terms of food and water security. In the preindustrial state, the largest decrease in Southeast Asian precipitation (> 20%) occurs along with the largest El Niño and positive phase of the Atlantic multidecadal oscillation, consistent with the 1876-78 Great Drought, leading to the largest decrease in NPP (~ 20%); >2 standard deviations, extreme dryness and crop failure. In relatively arid regions (e.g., India and northeastern Brazil), the largest decreases in precipitation and NPP reach ≥ 50%, particularly 80 ~ 90% in Deccan, India. In the 21st century warming projection (Shared Socioeconomic Pathways 5-8.5, the largest CO2 emission scenario), the interannual variability of precipitation and NPP in Monsoon Asia increase under the influence of enhanced El Niño-Southern Oscillation. Although the increased precipitation variability indicates more frequent severer droughts than in the preindustrial state, this severity does not influence NPP so much: the increased NPP variability is negligible compared to the significant increase in normal NPP by CO2 fertilization effect, which indicates usually rich harvests. Compared to a recent severe crop failure (− 25% in Japan in 1993), the simulated preindustrial drought-induced NPP decreases of ≥ 50% in parts of low latitudes are extraordinarily large enough to correspond to devastating crop failures. The model indicates that great famines before the 20th century were natural in origin, and that manmade factors, such as harsh taxes and hoarding and export of grain, made the famines more devastating.