Longitudinal assessment of extreme climate events in Kinnaur district, Himachal Pradesh, north-western Himalaya, India.

It is vital to keep an eye on changes in climatic extremes because they set the stage for current and potential future climate, which usually have a reasonable adverse impact on ecosystems and society. The present study examines the variability and trends in precipitation and temperature across seasons in the Kinnaur district, offering valuable insights into the complex dynamics of the Himalayan climate. Using Climatic Research Unit gridded Time Series (CRU TS) datasets from 1951 to 2021, the study analyzes the data to produce 28 climate indices based on India Meteorological Department (IMD) convention indices and Expert Team on Climate Change Detection and Indices (ETCCDI). Although there may be considerable variation in climate indices in terms of absolute values within different products, there is consensus in both long-term trends and inter-annual variability. Analysis shows that even within a small area, there is variability in the magnitude and direction of historic temperature trends. Initially, the data were subjected to rigorous quality control procedures, which involved identifying anomalies. Statistical analysis like trend analysis, employing Mann-Kendall test and Sen's slope estimator, reveal significant (p < 0.05) increase in consecutive dry days (CDD) at 0.03 days/year and decrease in consecutive wet days (CWD) at 0.02 days/year. Notably, the frequency of heavy precipitation occurrences showed an increasing trend. Changes in precipitation in the Western Himalaya are driven by a complex interplay of orographic effects, monsoonal dynamics, atmospheric circulation patterns, climate change, and localized factors such as topography, atmospheric circulation patterns, moisture sources, land-sea temperature contrasts, and anthropogenic influences. Moreover, in case of temperature indices, there is significant increasing trend observed. Temperature indices indicate a significant annual increase in warm nights (TN90p) at 0.06%/year and warm days (TX90p) at 0.11%/year. Extreme temperature events have been trending upward, with monthly daily maximum temperature (TXx) increasing by 1.5 °C yearly. This study enhances our comprehension of the global warming phenomenon and underscores the importance of acknowledging alterations in the water cycle and their repercussions on hydrologic resources, agriculture, and livelihoods in the cold desert of the northwestern Indian Himalaya.

Legacies of precipitation influence primary production in Panicum virgatum.

Precipitation is a key driver of primary production worldwide, but primary production does not always track year-to-year variation in precipitation linearly. Instead, plant responses to changes in precipitation may exhibit time lags, or legacies of past precipitation. Legacies can be driven by multiple mechanisms, including persistent changes in plant physiological and morphological traits and changes to the physical environment, such as plant access to soil water. We used three precipitation manipulation experiments in central Texas, USA to evaluate the magnitude, duration, and potential mechanisms driving precipitation legacies on aboveground primary production of the perennial C4 grass, Panicum virgatum. Specifically, we performed a rainout shelter study, where eight genotypes grew under different precipitation regimes; a transplant study, where plants that had previously grown in a rainout shelter under different precipitation regimes were moved to a common environment; and a mesocosm study, where the effect of swapping precipitation regime was examined with a single genotype. Across these experiments, plants previously grown under wet conditions generally performed better than expected when exposed to drought. Panicum virgatum exhibited stronger productivity legacies of past wet years on current-year responses to drought than of past dry years on current-year responses to wet conditions. Additionally, previous year tiller counts, a proxy for meristem availability, were important in determining legacy effects on aboveground production. As climate changes and precipitation extremes-both dry and wet-become more common, these results suggest that populations of P. virgatum may become less resilient.

Local adaptation of seed and seedling traits along a natural aridity gradient may both predict and constrain adaptive responses to climate change.

PREMISE: Variation in seed and seedling traits underlies how plants interact with their environment during establishment, a crucial life history stage. We quantified genetic-based variation in seed and seedling traits in populations of the annual plant Plantago patagonica across a natural aridity gradient, leveraging natural intraspecific variation to predict how populations might evolve in response to increasing aridity associated with climate change in the Southwestern U.S. METHODS: We quantified seed size, seed size variation, germination timing, and specific leaf area in a greenhouse common garden, and related these traits to the climates of source populations. We then conducted a terminal drought experiment to determine which traits were most predictive of survival under early-season drought. RESULTS: All traits showed evidence of clinal variation-seed size decreased, germination timing accelerated, and specific leaf area increased with increasing aridity. Populations with more variable historical precipitation regimes showed greater variation in seed size, suggestive of past selection shaping a diversified bet-hedging strategy mediated by seed size. Seedling height, achieved via larger seeds or earlier germination, was a significant predictor of survival under drought. CONCLUSIONS: We documented substantial interspecific trait variation as well as clinal variation in several important seed and seedling traits, yet these slopes were often opposite to predictions for how individual traits might confer drought tolerance. This work shows that plant populations may adapt to increasing aridity via correlated trait responses associated with alternative life history strategies, but that trade-offs might constrain adaptive responses in individual traits.

Forests buffer against variations in precipitation.

Atmospheric moisture recycling effectively increases the amount of usable water over land as the water can undergo multiple precipitation-evapotranspiration cycles. Differences in land cover and climate regulate the evapotranspiration flux. Forests can have deep roots that access groundwater facilitating transpiration throughout the dry season independent of precipitation. This stable transpiration buffers the forest against precipitation variability. However, it is not known whether the buffering effect, already modeled for tropical forests, is common to all forests globally. Here we apply a state-of-the-art Lagrangian moisture tracking model (UTrack) to study whether forest land cover in the upwind precipitationshed can lead to a reduction in monthly precipitation variability downwind. We found a significant buffering effect of forests in the precipitation variability of 10 out of 14 biomes globally. On average, if 50% of precipitation originates from forest, then we find a reduction in the coefficient of variation of monthly precipitation of 60%. We also observed that a high fraction of precipitation from non-forest land sources tends to have the opposite effect, that is, no buffering effect. The average variation of monthly precipitation was 69% higher in areas where 50% of precipitation originates from non-forest land sources in the precipitationshed. Our results emphasize the importance of land cover composition in the precipitationshed to buffer precipitation variability downwind, in particular forest cover. Understanding the influence of land cover in a precipitationshed on atmospheric moisture transport is key for evaluating an area's water-climate regulatory ecosystem services and may become increasingly important due to continued changes in land cover and climate change.

Divergent responses of primary production to increasing precipitation variability in global drylands.

Interannual variability in precipitation has increased globally as climate warming intensifies. The increased variability impacts both terrestrial plant production and carbon (C) sequestration. However, mechanisms driving these changes are largely unknown. Here, we examined mechanisms underlying the response of aboveground net primary production (ANPP) to interannual precipitation variability in global drylands with mean annual precipitation (MAP) <500 mm year-1 , using a combined approach of data synthesis and process-based modeling. We found a hump-shaped response of ANPP to precipitation variability along the MAP gradient. The response was positive when MAP < ~300 mm year-1 and negative when MAP was higher than this threshold, with a positive peak at 140 mm year-1 . Transpiration and subsoil water content mirrored the response of ANPP to precipitation variability; evaporation responded negatively and water loss through runoff and drainage responded positively to precipitation variability. Mean annual temperature, soil type, and plant physiological traits all altered the magnitude but not the pattern of the response of ANPP to precipitation variability along the MAP gradient. By extrapolating to global drylands (<500 mm year-1  MAP), we estimated that ANPP would increase by 15.2 ± 6.0 Tg C year-1 in arid and hyper-arid lands and decrease by 2.1 ± 0.5 Tg C year-1 in dry sub-humid lands under future changes in interannual precipitation variability. Thus, increases in precipitation variability will enhance primary production in many drylands in the future.

Biotic stability mechanisms in Inner Mongolian grassland.

Biotic mechanisms associated with species diversity are expected to stabilize communities in theoretical and experimental studies but may be difficult to detect in natural communities exposed to large environmental variation. We investigated biotic stability mechanisms in a multi-site study across Inner Mongolian grassland characterized by large spatial variations in species richness and composition and temporal fluctuations in precipitation. We used a new additive-partitioning method to separate species synchrony and population dynamics within communities into different species-abundance groups. Community stability was independent of species richness but was regulated by species synchrony and population dynamics, especially of abundant species. Precipitation fluctuations synchronized population dynamics within communities, reducing their stability. Our results indicate generality of biotic stability mechanisms in natural ecosystems and suggest that for accurate predictions of community stability in changing environments uneven species composition should be considered by partitioning stabilizing mechanisms into different species-abundance groups.

A discrete-time model for population persistence in habitats with time-varying sizes.

In this paper, we use periodic and stochastic integrodifference models to study the persistence of a single-species population in a habitat with temporally varying sizes. We extend a persistence metric for integral operators on bounded domains to that of integral operators on unbounded domains. Using this metric in the periodic model, we present new perspectives of the critical habitat size problem in the case of dynamically changing habitat sizes. Specifically, we extend the concept of critical habitat size to that of lower minimal limit size in a period-2 scenario, and prove the existence of the lower minimal limit size. For the stochastic model, we point out the importance of considering multiple time scales in the temporal variability of the habitat size. The models are relevant to biological scenarios such as seasonal variability of wetland habitat sizes under precipitation variability.

Enhanced interannual precipitation variability increases plant functional diversity that in turn ameliorates negative impact on productivity.

Although precipitation interannual variability is projected to increase due to climate change, effects of changes in precipitation variance have received considerable less attention than effects of changes in the mean state of climate. Interannual precipitation variability effects on functional diversity and its consequences for ecosystem functioning are assessed here using a 6-year rainfall manipulation experiment. Five precipitation treatments were switched annually resulting in increased levels of precipitation variability while maintaining average precipitation constant. Functional diversity showed a positive response to increased variability due to increased evenness. Dominant grasses decreased and rare plant functional types increased in abundance because grasses showed a hump-shaped response to precipitation with a maximum around modal precipitation, whereas rare species peaked at high precipitation values. Increased functional diversity ameliorated negative effects of precipitation variability on primary production. Rare species buffered the effect of precipitation variability on the variability in total productivity because their variance decreases with increasing precipitation variance.

Interannual precipitation variability dominates the growth of alpine grassland above-ground biomass at high elevations on the Tibetan Plateau.

The impact of global climate change on mountainous regions with significant elevational gaps is complex and often unpredictable. In particular, alpine grassland ecosystems, are experiencing changes in their spatial patterns along elevational gradients, which increases their vulnerability to degradation. Therefore, a more detailed understanding of spatiotemporal changes in alpine grassland productivity along elevational gradients and an elevation-dependent characterization of the effects of climatic variables on grassland productivity dynamics are essential. Thus, we conducted a study in the Tibetan Plateau, where we collected 2251 above-ground biomass (AGB) observations collected from 1986 to 2020. Mean annual temperature (TMP), annual precipitation (PRE), interannual precipitation variability (CVP), and snowmelt (SNMM) were chosen as influential variables. Using the Random Forest algorithm, we generated an AGB raster dataset covering the period 1989-2020 based on earth observation data at 30 m resolution to examine the dynamics of alpine grasslands and their response to climate change with respect to elevation. The results showed that the AGB of alpine grassland on the Tibetan Plateau was 49.17 g/m2. We observed an increasing trend in grassland AGB at high elevations, with a growth rate of about 0.28 g/m2 per year within the interval of 3100-4800 m. However, above the elevation of approximately 4400-4600 m, we observed a decoupling trend between grassland AGB and TMP. Moreover, at most elevations, the proportion of maximum partial correlation coefficients for CVP, PRE, and SNMM surpassed that of TMP. We found the dominant role of precipitation variability on grassland AGB dynamics, with 22.80 % and 18.86 % for CVP+ and CVP-, respectively. The proportion of CVP+ did not vary much at different elevations, whereas the proportion of CVP- increased with elevation, varying between 12.85 and 30.25 %. In the future, precipitation on the Tibetan plateau is expected to increase, potentially reversing its original positive impact.

Quantification of Asian monsoon variability from 68 ka BP through pollen-based climate reconstruction.

The glacial-interglacial variability of precipitation and its driving mechanism in monsoonal regions has long been a subject of debate. However, there are few records of quantitative climate reconstruction dating to the last glacial cycle in areas dominated by the Asian summer monsoon. Here, using a pollen-based quantitative climate reconstruction based on three sites in areas exposed to the Asian summer monsoon, we demonstrate that climate has undergone great variability over the past 68 ka. The differences between the last glacial and the Holocene optimum could have been as much as 35%-51% for precipitation, and 5-7 °C for mean annual temperature. Our findings also reveal regional heterogeneity during the abrupt climate events of Heinrich Event 1 and Younger Dryas, that drove drier conditions in southwestern China dominated by the Indian summer monsoon, and a wetter climate in central eastern China. The pattern of variation in reconstructed precipitation, exhibiting strong glacial-interglacial variability, is broadly consistent with the stalagmite δ18O records from Southwest China and South Asia. Our results of reconstruction quantify the sensitivity of the MIS3 precipitation to orbital insolation changes, and highlight the prominent influence of interhemispheric temperature gradients on Asian monsoon variability. Comparison with transient simulations and major climate forcings has shown that the mode of precipitation variability during the transition from the last glacial maximum to the Holocene has been significantly modulated by weak or collapsed Atlantic meridional overturning circulation events in addition to insolation forcing.

Does previous exposure to extreme precipitation regimes result in acclimated grassland communities?

Climate change will likely increase weather persistence in the mid-latitudes, resulting in precipitation regimes (PR) with longer dry and wet periods compared to historic averages. This could affect terrestrial ecosystems substantially through the increased occurrence of repeated, prolonged drought and water logging conditions. Climate history is an important determinant of ecosystem responses to consecutive environmental extremes, through direct damage, community restructuring as well as morphological and physiological acclimation in species or individuals. However, it is unclear how community restructuring and individual metabolic acclimation effects interact to determine ecosystem responses to subsequent climate extremes. Here, we investigated, if and how, differences in exposure to extreme or historically normal PR induced long-lasting (i.e. legacy) effects at the level of community (e.g., species composition), plant (e.g., biomass), and molecular composition (e.g., sugars, lipids, stress markers). Experimental grassland communities were exposed to long (extreme) or short (historically normal) dry/wet cycles in year 1 (Y1), followed by exposure to an identical PR or the opposite PR in year 2 (Y2). Results indicate that exposure to extreme PR in Y1, reduced diversity but induced apparent acclimation effects in all climate scenarios, stimulating biomass (higher productivity and structural sugar content) in Y2. In contrast, plants pre-exposed to normal PR, showed more activated stress responses (higher proline and antioxidants) under extreme PR in Y2. Overall, Y1 acclimation effects were strongest in the dominant grasses, indicating comparatively high phenotypical plasticity. However, Y2 drought intensity also correlated with grass productivity and structural sugar findings, suggesting that responses to short-term soil water deficits contributed to the observed patterns. Interactions between different legacy effects are discussed. We conclude that more extreme PR will likely alter diversity in the short-to midterm and select for acclimated grassland communities with increased productivity and attenuated molecular stress responses under future climate regimes.

Global evidence on the asymmetric response of gross primary productivity to interannual precipitation changes.

Understanding gross primary productivity (GPP) response to precipitation (PPT) changes is essential for predicting land carbon uptake under increasing PPT variability and extremes. Previous studies found that ecosystem GPP may have an asymmetric response to PPT changes, leading to the inconsistency of GPP gains in wet years compared to GPP declines in dry years. However, it is unclear how the asymmetric responses vary among vegetation types and under different PPT variabilities. This study evaluated the global patterns of asymmetries of GPP response to different PPT changes using two state-of-science global GPP datasets. The result shows that under mild PPT changes (|ΔPPT| ≤ 25%), grasslands, savannas, shrublands, and tundra show positive asymmetric responses (i.e., larger GPP gains in wet years than GPP losses in dry years), while other vegetation types show negative asymmetric responses (i.e., larger GPP losses in dry years than GPP gains in wet years). Conversely, all vegetation types show negative GPP asymmetric responses to moderate (25% < |ΔPPT| ≤ 50%) and extreme (|ΔPPT| > 50%) PPT changes. Thus, we propose a new non-linear asymmetric GPP-PPT model that incorporates three modes with regards to vegetation types. Meanwhile, we found that the spatial patterns of asymmetry were mainly driven by PPT amount and variability. Stronger and negative asymmetries were found in areas with smaller PPT amount and variability, while positive asymmetries were found in areas with higher PPT variability. These findings promote our understanding of carbon dynamics under increased PPT variability and extremes and provide new insights for land models to better predict future carbon uptake and its feedback to climate change.

Impact of a transformation from flood to drip irrigation on groundwater recharge and nitrogen leaching under variable climatic conditions.

The sustainability of agriculture in the Mediterranean climate is challenged by high irrigation water demands and nitrogen fertilizer losses to the environment, causing significant pressure on groundwater resources and groundwater-dependent ecosystems. Advanced irrigation technologies and improved fertilizer management have been promoted as key solutions to reduce the agricultural impact on aquatic systems. However, it remains unclear how different irrigation-fertilizer practices perform on the long-term under a highly variable climate, such as the Mediterranean one. Here, we conduct hydrological simulations over a fifty-year period to quantify the magnitude and dynamics of groundwater recharge and nitrogen leaching under five real-case irrigation-fertilizer practices observed in Valencia (eastern Spain). The Valencian Region is the largest citrus-producing region of Europe and current irrigation-fertilizer practices reflect the ongoing transformation of irrigation systems from flood to drip irrigation. Our simulations highlight three major implications of the irrigation transformation for groundwater resources. First, the transformation from flood to drip irrigation reduces the recharge fraction (19% vs. 16%) and especially the nitrogen leaching fraction (33% vs. 18%) on the long term. Second, the long-term performance of the two irrigation practices is subject to substantial inter-annual differences controlled by precipitation variability. The sensitivity of recharge and nitrogen leaching to annual meteorological conditions is stronger in drip irrigation, which eventually leads to a similar performance of flood and drip irrigation in wet years if fertilizer inputs are similar. Third, we identify a pronounced year-to-year nitrogen memory in the soil, whereby an enhanced (decreased) nitrogen leaching is observed after anomalously dry (wet) years, affecting the performance of irrigation-fertilizer practices. Overall, the study demonstrates the highly variable nature of the performance of irrigation-fertilizer practices, and the major findings can guide future efforts in designing sustainable water management strategies for agricultural areas with a Mediterranean climate.

Investigating false start of the main growing season: A case of Uganda in East Africa.

False start of the growing season (Fsos) is a component of the onset variability related to agronomic drought that adversely impact on agricultural production and productivity. In the sub-Saharan Africa (SSA) where agriculture heavily depends on rainfall, the Fsos tends to create confusion among farmers on when to start planting crops thereby affecting seed germination and normal growth after emergence. In this paper, we focus on the Fsos and the occurrence of dry spell especially before the Start of growing Season (SoS). We take advantage of the existing rainfall estimates (CHIRPS) and remotely sensed data for vegetation performance (NDVI) over the period 1999-2017 in combination with local knowledge derived from farmers to map out areas at risk of (i) dry spell at the SoS, and (ii) false timing of SoS or high probability of occurrence of the Fsos. We found that the North Eastern part of Uganda (8.8% of arable area) were at risk of dry spell throughout each year. However, the greater North (58.1% of arable area) was prone to dry spell during the onset of the March-May season. Areas in the South Western (3.7%) region were at risk during the onset of the September-November season. The probability that a location in Uganda experiences an Fsos falls between 0-53%. The findings in this study are vital for planning of predictive adaptation to the impacts of climate variability on agriculture amid struggle aimed at tackling food insecurity challenge in the SSA.

Hydro-climatological variability in Lagunas de Vilama System, Argentinean Altiplano-Puna Plateau, Southern Tropical Andes (22° S), and its response to large-scale climate forcings.

The Altiplano-Puna Plateau holds several shallow lakes, which are very sensitive to climate changes. This work is focused on a high-altitude lake system called Lagunas de Vilama (LVS), located in a complex climatic transition area with scarcity of continuous and homogeneous instrumental records. The objective of this study is to determine the regional spatial-temporal variability of precipitation and evaluate the seasonal and interannual lake responses. We use a lake-surfaces record derived from Landsat images to investigate links with regional precipitations and different climatic forcings. The results reveal that austral summer and autumn precipitations control the variability of the annual lake-surfaces. Also, we found intra-annual and interannual lags in the lake responses to precipitations, and identified several wet and dry stages. Our results show negative trends in precipitations and lake-surfaces, whose were strengthened by a shift to a warm phase of the Atlantic Multidecadal Oscillation in the 1990s. The El Niño Southern Oscillation, Pacific Decadal Oscillation, and Southern Annular Mode also exert a strong influence in the region. This study demonstrates that the variability of LVS lakes is strongly related to the South American Monsoon System dynamics and large-scale climate forcings from the Pacific and Atlantic Oceans. This work provides novel indices which demonstrated to be good indicators of regional hydro-climatological variability for this region of South America.

Contrasting responses of steppe Stipa ssp. to warming and precipitation variability.

Climate change, characterized by warming and precipitation variability, restricted the growth of plants in arid and semiarid areas, and various functional traits are impacted differently. Comparing responses of functional traits to warming and precipitation variability and determining critical water threshold of dominate steppe grasses from Inner Mongolia facilitates the identification and monitoring of water stress effects. A combination of warming (ambient temperature, +1.5°C and +2.0°C) and varying precipitation (-30%, -15%, ambient, +15%, and +30%) manipulation experiments were performed on four Stipa species (S. baicalensis, S. bungeana, S. grandis, and S. breviflora) from Inner Mongolia steppe. The results showed that the functional traits of the four grasses differed in their responses to precipitation, but they shared common sensitive traits (root/shoot ratio, R/S, and specific leaf area; SLA) under ambient temperature condition. Warming increased the response of the four grasses to changing precipitation, and these differences in functional traits resulted in changes to their total biomass, with leaf area, SLA, and R/S making the largest contributions. Critical water thresholds of the four grasses were identified, and warming led to their higher optimum precipitation requirements. The four steppe grasses were able to adapt better to mild drought (summer precipitation decreased by 12%-28%) when warming 1.5°C rather than 2.0°C. These results indicated that if the Paris Agreement to limit global warming to 1.5°C will be accomplished, this will increase the probability for sustained viability of the Stipa steppes in the next 50-100 years.

Influence of moisture source dynamics and weather patterns on stable isotopes ratios of precipitation in Central-Eastern Africa.

We report the first δ18O and δ2H data of Virunga rainfall in the Eastern Democratic Republic of the Congo, situated on the limit between Central and Eastern Africa. The dataset is from 13 rain gauges deployed at Mount Nyiragongo and its surroundings sampled monthly between December 2013 and October 2015. The δ18O and δ2H vary from -6.44 to 6.16‰, and -32.53 to 58.89‰ respectively, and allowed us to define a LMWL of δ2H = 7.60δ18O + 16.18. Three main wind directions, i.e. NE, E and SE, were identified in the upper atmosphere corresponding to three major moisture source regions. On the contrary, lower atmospheric winds are weaker in nature and originate mainly from the S and SW, creating a topographically-driven, more local moisture regime. The latter is due to the accumulation in the floor of the rift of water vapor from Lake Kivu forming a layer of isotopically enriched vapor that mediates the isotope enrichment of the falling raindrops. A strong seasonality is observed in both δ18O and δ2H data, and is primarily driven by combined seasonal and spatial variation in the moisture sources. The δ18O and δ2H seasonality is thus correlated to weather patterns, as the latter control the wet to dry season shifting, and vice versa. The key characteristic of seasonality is the variation of monthly precipitation amounts, since the mean monthly air temperature is nearly constant on an annual scale. Two regionally relevant hydrological processes contribute to the isotopic signature: namely moisture uptake from the isotopically enriched surface waters of East African lakes and from the depleted soil-water and plants. Consequently, the proportion of water vapor from each of these reservoirs in the atmosphere drives the enrichment or depletion of δ2H and δ18O in the precipitation. Thus, during wet periods the vapor from soil-plants evapotranspiration dominates yielding isotopically depleted precipitation, contrary to dry periods when vapor from lakes surface evaporation dominates, yielding isotopically enriched precipitation. At the global scale, our dataset reduces gaps in this region that has been poorly studied for δ18O and δ2H in precipitation. At the regional scale, the improved understanding of the ways land cover, moisture source seasonal and spatial dynamics, and atmospheric patterns impact precipitation spatial and temporal variabilities in Central-East African will contribute to the ongoing research on mitigating the impacts of ongoing climate change in Sub-Saharan Africa. The reduction of gaps and uncertainties in δ2H and δ18O of precipitation, and the understanding of their interrelation with weather patterns are essential for a better past, present and future environmental and climatic modelling at both local and regional scales.

Weekly variability of precipitation induced by anthropogenic aerosols: A case study in Korea in summer 2004.

We examine the effect of anthropogenic aerosols on the weekly variability of precipitation in Korea in summer 2004 by using Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models. We conduct two WRF simulations including a baseline simulation with empirically based cloud condensation nuclei (CCN) number concentrations and a sensitivity simulation with our implementation to account for the effect of aerosols on CCN number concentrations. The first simulation underestimates observed precipitation amounts, particularly in northeastern coastal areas of Korea, whereas the latter shows higher precipitation amounts that are in better agreement with the observations. In addition, the sensitivity model with the aerosol effects reproduces the observed weekly variability, particularly for precipitation frequency with a high R at 0.85, showing 20% increase of precipitation events during the weekend than those during weekdays. We find that the aerosol effect results in higher CCN number concentrations during the weekdays and a three-fold increase of the cloud water mixing ratio through enhanced condensation. As a result, the amount of warm rain is generally suppressed because of the low auto-conversion process from cloud water to rain water under high aerosol conditions. The inefficient conversion, however, leads to higher vertical development of clouds in the mid-atmosphere with stronger updrafts in the sensitivity model, which increases by 21% cold-phase hydrometeors including ice, snow, and graupel relative to the baseline model and ultimately results in higher precipitation amounts in summer.