Regional Precipitation Research Articles

Impact of Atmospheric River and Local Topography on “21·7” Extremely Heavy Rainfall in Henan Province, China

An extremely heavy rainfall occurred in Henan Province, China, from July 19th to 21st in 2021, with large precipitation, long duration and wide precipitation area. Impact of water vapor transportation from atmospheric river (AR) on the rainfall was studied through reanalysis data and weather research and forecasting (WRF) model. Precipitation reached over 600 mm around Mount Song, which lasted for 48 h. The AR provided sufficient water vapor condition for the long-lasting rainfall. Regional averaged hourly precipitation was positively correlated with the amplitude of Integrated Horizontal Water Vapor Transport (IVT) and negatively correlated with IVT divergence (IVTD). Maximum precipitation regions were consistent with large IVT and IVTD regions. Peaks of IVT and IVTD were advancing of precipitation peak. Precipitation was affected by Mount Song through influencing spatial distribution and vertical structure of ARs and vertical velocity. Orographic lifting and wind converging around Mount Song caused the heavy rainfall in Zhengzhou City on July 20th. Precipitation, large IVT, IVTD and updrafts region located northwesterly of Mount Song in half mountain and without mountain tests. Comparing sensitivity tests with control simulation, air mass transporting by the AR and convective systems slowed down (or stagnated) when met the mountain, resulting in long lasting duration and large precipitation.

Effect of Water Tank Size and Supply on Greenhouse-Grown Kidney Beans Irrigated by Rainwater in Cold and Arid Regions of North China

In response to water scarcity in the Bashang area of northwest Hebei Province, a cold and arid region in north China, and to address the diminishing groundwater levels caused by pumping irrigation, this study investigated the impact of rainwater tank size and water supply on kidney beans production in greenhouses under various precipitation scenarios to determine the production potential and development strategies for regional precipitation resources. Under the background of average annual precipitation, kidney bean yield increased with increasing reservoir volume and shorter irrigation cycles. Under a 4-day irrigation cycle, the water demand satisfaction rate of kidney beans reached 100% water demand when the rainwater tank size was 15.7 m3. Against the wide variation in multi-year regional precipitation from 1992 to 2023, the annual effect of rainwater harvest was simulated using precipitation data collected 20 years with an 80% precipitation guarantee rate. The average minimum yield reduction rate obtained was 9.4%, and the corresponding minimum rainwater tank size was 29.5 m3. By superimposing the rainwater harvested in the shed and nonshed areas, the volume of the reservoir without yield reduction could be reduced to 20.0 m3. The sum of discharged and inventory water was much greater than the water scarcity in each water supply situation. Simulating and analyzing the effect of the relationship between rainwater tank size and water supply on rainwater harvesting in regional farmland by year provides important data affecting the construction of regional rainwater storage facilities and water supply efficiency. To achieve a high, stable yield of kidney beans grown in a greenhouse with shed film and shed area rainwater harvesting in north China, 2.6 m3 supplementary groundwater irrigation is still needed during the annual growing season.

Downscaling TRMM Monthly Precipitation in Cloudy and Rainy Regions and Analyzing Spatiotemporal Variations: A Case Study in the Dongting Lake Basin

High-resolution and accurate precipitation data are essential for hydrological, meteorological, and ecological research at the watershed scale. However, in regions with complex terrain and significant rainfall variability, the limited number of rain gauge stations (RGS) is insufficient, and the spatial resolution of existing satellite precipitation data is too low to capture detailed precipitation patterns at the watershed scale. To address this issue, the downscaling of satellite precipitation products has become an effective method to obtain high-resolution precipitation data. This study proposes a monthly downscaling method based on a random forest model, aiming to improve the resolution of precipitation data in cloudy and rainy regions at mid-to-low latitudes. We combined the Google Earth Engine (GEE) platform with a local Python environment, introducing cloud cover characteristics into traditional downscaling variables (latitude, longitude, topography, and vegetation index). The TRMM data were downscaled from 25 km to 1 km, generating high-resolution monthly precipitation data for the Dongting Lake Basin from 2001 to 2019. Furthermore, we analyzed the spatiotemporal variation characteristics of precipitation in the study area. The results show the following: (1) In cloudy and rainy regions, our method improves resolution and detail while maintaining the accuracy of precipitation data; (2) The response of monthly precipitation to environmental variables varies, with cloud cover characteristics contributing more to the downscaling model than vegetation characteristics, helping to overcome the lag effect of vegetation characteristics; and (3) Over the past 20 years, there have been significant seasonal trends in precipitation changes in the study area, with a decreasing trend in winter and spring (January–May) and an increasing trend in summer and autumn (June–December). These results indicate that the proposed method is suitable for downscaling monthly precipitation data in cloudy and rainy regions of the Dongting Lake Basin.

Computational-Aided Approach for the Optimization of Microfluidic-Based Nanoparticles Manufacturing Process.

In the last few years, the microfluidic production of nanoparticles (NPs) is becoming a promising alternative to conventional industrial approaches (e.g., nanoprecipitation, salting out, and emulsification-diffusion) thanks to the production efficiency, low variability, and high controllability of the production parameters. Nevertheless, the development of new formulations and the switching of the production process toward microfluidic platforms requires expensive and time-consuming number of experiments for the tuning of the formulation to obtain NPs with specific morphological and functional characteristics. In this work, we developed a computational fluid dynamic pipeline, validated through an ad hoc experimental strategy, to reproduce the mixing between the solvent and anti-solvent (i.e., acetonitrile and TRIS-HCl, respectively). Moreover, beyond the classical variables able to describe the mixing performances of the microfluidic chip, novel variables were described in order to assess the region of the NPs formation and the changing of the amplitude of the precipitation region according to different hydraulic conditions. The numerical approach proved to be able to capture a progressive reduction of the nanoprecipitation region due to an increment of the flow rate ratio; in parallel, through the experimental production, a progressive increment of the NPs size heterogeneity was observed with the same fluid dynamic conditions. Hence, the preliminary comparison between numerical and experimental evidence proved the effectiveness of the computational strategy to optimize the NPs manufacturing process.

Land–atmosphere feedbacks weaken the risks of precipitation extremes over Australia in a warming climate

The importance of land–atmosphere feedbacks on regional precipitation changes has been recently noted. However, how land–atmosphere feedbacks shape daily precipitation distributions, particularly the tails of precipitation distributions associated with extreme events, remains unclear on a regional scale. Herein, using the latest land–atmosphere coupling experiments, this study reveals a consistent weakening effect of land–atmosphere feedbacks on the future increase in precipitation extremes over Australia, revealing the most pronounced reduction (56.8%) for the long-term (2080–2099) projection under the low emission (SSP1-2.6) scenario. This weakening effect holds true for shifts in the extreme tail of precipitation distribution, resulting in a reduced risk of precipitation extremes in a warming climate. Land‒atmosphere feedbacks offset 28%–60% of the occurrence risk for the 99th percentile of daily precipitation, with the largest reduction of 172% when precipitation exceeds the 99.7th percentile in the long-term projection under the high emission (SSP5-8.5) scenario. Considering less water replenishment, these feedbacks may reduce the risk of flooding but potentially expedite droughts, highlighting the role of land–atmosphere feedbacks in extreme event projection and regional climate adaptation.

Association between precipitation and mortality due to diarrheal diseases by climate zone: A multi-country modeling study.

Precipitation could affect the transmission of diarrheal diseases. The diverse precipitation patterns across different climates might influence the degree of diarrheal risk from precipitation. This study determined the associations between precipitation and diarrheal mortality in tropical, temperate, and arid climate regions. Daily counts of diarrheal mortality and 28-day cumulative precipitation from 1997 to 2019 were analyzed across 29 locations in eight middle-income countries (Argentina, Brazil, Costa Rica, India, Peru, the Philippines, South Africa, and Thailand). A two-stage approach was employed: the first stage is conditional Poisson regression models for each location, and the second stage is meta-analysis for pooling location-specific coefficients by climate zone. In tropical climates, higher precipitation increases the risk of diarrheal mortality. Under extremely wet conditions (95th percentile of 28-day cumulative precipitation), diarrheal mortality increased by 17.8% (95% confidence interval [CI] = 10.4%, 25.7%) compared with minimum-risk precipitation. For temperate and arid climates, diarrheal mortality increases in both dry and wet conditions. In extremely dry conditions (fifth percentile of 28-day cumulative precipitation), diarrheal mortality risk increases by 3.8% (95% CI = 1.2%, 6.5%) for temperate and 5.5% (95% CI = 1.0%, 10.2%) for arid climates. Similarly, under extremely wet conditions, diarrheal mortality risk increases by 2.5% (95% CI = -0.1%, 5.1%) for temperate and 4.1% (95% CI = 1.1%, 7.3%) for arid climates. Associations between precipitation and diarrheal mortality exhibit variations across different climate zones. It is crucial to consider climate-specific variations when generating global projections of future precipitation-related diarrheal mortality.

Quantile Delta-Mapped Spatial Disaggregation Analysis for Climate Variations over the Yangtze River Basin

Abstract Significant increases in temperature and precipitation due to global warming affect socioeconomics. Accurate analysis is needed for future temperature and precipitation variations across the Yangtze River basin (YRB). A novel quantile delta-mapped spatial disaggregation (QDMSD) approach was developed in this study to analyze temperature and precipitation changes for the first time. The evaluation results show that the QDMSD has a similar performance in simulating temperature with the bias correction and spatial disaggregation (BCSD) model, while it shows improvement in reproducing precipitation. Projections indicate the annual-mean temperature will increase from 2020 to 2080 under shared socioeconomic pathway (SSP) scenarios SSP2-4.5 and SSP5-8.5. The projected temperature obtained from five downscaled GCMs has the smallest range of differences in summer. Conversely, annual-mean temperatures significantly decrease from 2081 to 2100 under SSP2-4.5. In terms of spatial distribution characteristics, most of the positive changes tend to expand across the YRB. The annual-mean precipitation will increase from 2020 to 2080 but decrease from 2081 to 2100 under SSP2-4.5 over the YRB. In terms of spatial distribution, precipitation in the southeast region of the YRB will increase, and the maximum variations in precipitation will occur downstream of the YRB. The QDMSD method reproduces observed precipitation trends well and enhances simulation accuracy in the YRB. For projected temperature, there will be a widespread increase across the YRB; for projected precipitation, significant increases will occur in the eastern YRB. These findings support policymaking to address potential risks from temperature and precipitation changes across multiple sectors (e.g., agriculture and industry).

Mean flow and eddy summer moisture transport over East Asia in reanalysis data and a regional climate simulation

Understanding the impact of atmospheric variability on climatological mean moisture transport is crucial because moisture transport determines continental water availability as well as convective organization and resulting precipitation. Here, we analyze the mean flow and eddy components of summer moisture transport in the downwind of the Tibetan Plateau (TP), a region that is characterized by interactions between monsoon systems, extratropical circulation, and mountainous weather systems. Using 40 years of ERA5 reanalysis data and a regional WRF simulation, we determine the absolute and relative contributions of mean flow and eddy moisture transport from multi-daily to sub-daily scales. We also link these components to large-scale circulation indices, precipitation, evaporation, and mesoscale convective systems (MCSs). The results show that the largest contributions of eddies to the climatological mean moisture transport are found in the immediate downwind region of the TP. Half of the total eddy transport downwind of the TP is due to multi-daily eddy transport and the other half is due to daily to sub-daily eddy transport. Regional precipitation anomalies are dominated by the mean flow component of southerly moisture influxes which in turn are positively correlated with different South Asian summer monsoon indices and negatively correlated with the West Northern Pacific monsoon index. The eddy transport from the south is positively correlated with a lower jet latitude but does not show any significant correlations with precipitation or MCS activity, likely due to the dominant role of the mean flow moisture transport. While the relative contributions of eddies to the climatological mean moisture transport are similar in ERA5 and WRF, the correlations between moisture transport components and large-scale circulation indices are generally weaker in WRF. This suggests that the dynamical downscaling does not significantly change the role of eddy moisture transport averaged for the region, but it resolves processes that decouple the moisture transport from its large-scale forcing.

Neural Hierarchical Interpolation for Standardized Precipitation Index Forecasting

In the context of climate change, studying changes in rainfall patterns is a crucial area of research, remarkably so in arid and semi-arid regions due to the susceptibility of human activities to extreme events such as droughts. Employing predictive models to calculate drought indices can be a useful method for the effective characterization of drought conditions. This study applies two type of machine learning methods—long short-term memory (LSTM) and Neural Hierarchical Interpolation for Time Series Forecasting (N-HiTS)—to develop and deploy artificial neural network models with the aim of predicting the regional standardized precipitation index (SPI) in four regions of Zacatecas, Mexico. The predictor variables were a set of climatological time series data spanning from 1964 to 2020. The results suggest that the N-HiTS model outperforms the LSTM model in the prediction and forecasting of SPI time series for all regions in terms of performance metrics: the Mean Squared Error, Mean Absolute Error, Coefficient of Determination and ξ correlation coefficient range from 0.0455 to 0.5472, from 0.1696 to 0.6661, from 0.9162 to 0.9684 and from 0.9222 to 0.9368, respectively, for the regions under study. Consequently, the outcomes revealed the successful performance of the N-HiTS models in accurately predicting the SPI across the four examined regions.

Hydrochemical and isotopic characteristics on the southern and northern slopes of the Himalayas: spatio-temporal controls and source apportionment

Water-soluble ions, inorganic nitrogen, and stable isotopes in precipitation were assessed from the southern (Koshi Tappu and Khandbari) and northern slopes (Lhasa and SET) of the Himalayas to understand the sources, chemistry of regional precipitation, and climatic processes. Water soluble ions showed distinct seasonal variation, with higher concentrations in the non-monsoon. The concentration of ionic species was highest in Koshi Tappu, followed by Lhasa, SET, and Khandbari. The sources were from the terrigenous (Ca2+, HCO3−), marine (Na+ and Cl−), anthropogenic (SO42−, NO3−, and NH4+), terrigenous and marine (Mg2+), and biomass-burning (K+). The southern slope, relative to the northern, was more prone to anthropogenic emissions with higher deposition. Among all sites, inorganic nitrogen deposition at Koshi Tappu was higher than the threshold value (10 kg ha−1 y−1). The isotopic composition during the study period was higher in non-monsoon, started declining from June, and depleted in July and August compared to other months, i.e., the monsoon mature phase, along the south-to-north transect. The diminished value of stable isotopes in precipitation with increasing altitude underlines the evidence of the orographic effect in isotopic composition. Our study delineated that the higher/lower d-excess value increased with altitude on the southern/northern slope of the Himalayas. The backward trajectory analysis and the National Centers for Environmental Prediction's Final (NCEP FNL) datasets identified that most of the trajectories arrived from warm and humid low-latitude regions during monsoon and westerlies in non-monsoon. Thus, the chemical characteristics and stable isotopic composition of precipitation differed on the southern and northern slopes of the Himalayas by orographic effect and various sources. This study provides new insights into the atmospheric environment and climatic control of stable isotopes in the Himalayan Tibetan Plateau and facilitates monitoring of transboundary air pollution.

WRF numerical simulation of summer precipitation and its application over the mountainous southern Tibetan Plateau based on different cumulus parameterization schemes

The extreme scarcity of meteorological observation data caused by harsh natural environments greatly limits our understanding of precipitation and related atmospheric processes over the mountainous regions of the southern Tibetan Plateau and its surrounding areas (hereafter mountainous southern TP). Precipitation simulation has been challenging in this region due to the complex topography and large elevation differences. Considering the high sensitivity of precipitation to the choice of cumulus parameterization scheme (CPS) over the TP, this study systematically evaluated the precipitation simulation performance of 11 CPSs in July 2018 using the WRF model. The characteristics of atmospheric circulation and gradient variation of precipitation were also revealed based on the optimal CPS over this region. The results indicated that the scale-aware schemes (KIAPS SAS [KSAS] and multi-scale Kain–Fritsch [MSKF]) demonstrated excellent potential for precipitation simulations. Due to the reasonable expression of atmospheric stability and the resulting accurate simulation of the timing and amount of regional heavy precipitation events, the KSAS scheme was superior to the MSKF scheme. The output of the KSAS-configured experiment revealed two main water vapor transport channels for the mountainous southern TP in summer, namely the southern monsoonal channel and the western westerly channel. Based on the precipitation profiles along the typical paths of these two channels (longitudinal path of 95.5°E and latitudinal path of 29.5°N), two precipitation belts and one precipitation belt existed on the southern and western slopes of the TP, respectively.

Impacts of Climatic Fluctuations and Vegetation Greening on Regional Hydrological Processes: A Case Study in the Xiaoxinganling Mountains–Sanjiang Plain Region, Northeastern China

The Xiaoxinganling Mountains–Sanjiang Plain region represents a crucial ecological security barrier for the Northeast China Plain and serves as a vital region for national grain production. Over the past two decades, the region has undergone numerous ecological restoration projects. Nevertheless, the combined impact of enhanced vegetation greening and global climate change on the regional hydrological cycle remains inadequately understood. This study employed the distributed hydrological model ESSI-3, reanalysis datasets, and multi-source satellite remote sensing data to quantitatively evaluate the influences of climate change and vegetation dynamics on regional hydrological processes. The study period spans from 2000 to 2020, during which there were significant increases in regional precipitation and leaf area index (p < 0.05). The hydrological simulation results exhibited strong agreement with observed river discharge, evapotranspiration, and terrestrial water storage anomalies, thereby affirming the ESSI-3 model’s reliability in hydrological change assessment. By employing both a constant scenario that solely considered climate change and a dynamic scenario that integrated vegetation dynamics, the findings reveal that: (1) Regionally, climate change driven by increased precipitation significantly augmented runoff fluxes (0.4 mm/year) and water storage components (2.57 mm/year), while evapotranspiration trends downward, attributed primarily to reductions in solar radiation and wind speed; (2) Vegetation greening reversed the decreasing trend in evapotranspiration to an increasing trend, thus exerting a negative impact on runoff and water storage. However, long-term simulations demonstrated that regional runoff fluxes (0.38 mm/year) and water storage components (2.21 mm/year) continue to increase, mainly due to precipitation increments surpassing those of evapotranspiration; (3) Spatially, vegetation greening altered the surface soil moisture content trend in the eastern forested areas from an increase to a decrease. These findings suggested that sub-regional ecological restoration initiatives, such as afforestation, significantly influence the hydrological cycle, especially in areas with higher vegetation greening. Nevertheless, persistent increases in precipitation could effectively mitigate the moisture deficits induced by vegetation greening. The study’s outcomes provide a basis for alleviating concerns regarding potential water consumption risks associated with future ecological restoration and extensive vegetation greening projects, thereby offering scientific guidance for sustainable water resource management.

How Has the Ferrel Cell Contributed to the Maintenance of Antarctic Sea Ice at Low Levels From 2016 to 2022?

AbstractThis study investigates the specific circulation anomalies that have sustained the low Antarctic sea ice state since 2016. Firstly, we find a significant strengthening and southward shift in the Ferrel Cell (FC) during 2016–2022, resulting in a marked increase in southward transport of heat and moisture. Secondly, this enhanced FC is closely associated with a stronger mid‐latitude wave pattern. This pattern is zonally asymmetric and greatly amplifies the poleward advections of heat and moisture, leading to the increased downward longwave radiation, more liquid precipitation and sea ice retreat in specific regions, including the western Pacific and Indian Ocean sectors, Ross and northern Weddell Seas. The mechanism deduced from the short‐term period is further supported by the results of 40 ensemble members of simulations. The southward expansion of the FC and sea ice decline are closely linked to La Niña‐like conditions but may also be driven by anthropogenic global warming.

Has IMERG_V07 Improved the Precision of Precipitation Retrieval in Mainland China Compared to IMERG_V06?

Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) (IMERG) is the primary high spatiotemporal resolution precipitation product of the GPM era. To assess the applicability of the latest released IMERG_V07 in mainland China, this study systematically evaluates the error characteristics of IMERG_V07 from the perspective of different seasons, precipitation intensity, topography, and climate regions on an hourly scale. Ground-based meteorological observations are used as the reference, and the performance improvement of IMERG_V07 relative to IMERG_V06 is verified. Error evaluation is conducted in terms of precipitation amount and precipitation frequency, and an improved error component procedure is utilized to trace the error sources. The results indicate that IMERG_V07 exhibits a smaller RMSE in mainland China, especially with significant improvements in the southeastern region. IMERG_V07 shows better consistency with ground station data. IMERG_V07 shows an overall improvement of approximately 4% in capturing regional average precipitation events compared to IMERG_V06, with the northwest region showing particularly notable enhancement. The error components of IMERG_V06 and IMERG_V07 exhibit similar spatial distributions. IMERG_V07 outperforms V06 in terms of lower Missed bias but slightly underperforms in Hit bias and False bias compared to IMERG_V06. IMERG_V07 shows improved ability in capturing precipitation frequency for different intensities, but challenges remain in capturing heavy precipitation events, missing light precipitation, and winter precipitation events. Both IMERG_V06 and IMERG_V07 exhibit notable topography dependency in terms of Total bias and error components. False bias is the primary error source for both versions, except in winter, where high-altitude regions (DEM > 1200 m) primarily contribute to Missed bias. IMERG_V07 has enhanced the accuracy of precipitation retrieval in high-altitude areas, but there are still limitations in capturing precipitation events. Compared to IMERG_V06, IMERG_V07 demonstrates more concentrated error component values in the four climatic regions, with reduced data dispersion and significant improvement in Missed bias. The algorithm improvements in IMERG_V07 have the most significant impact in arid regions. False bias serves as the primary error source for both satellite-based precipitation estimations in the four climatic regions, with a secondary contribution from Hit bias. The evaluation results of this study offer scientific references for enhancing the algorithm of IMERG products and enhancing users’ understanding of error characteristics and sources in IMERG.

Characteristics of Atmospheric Diabatic Heating of the Southwest China Vortex That Induces Extreme Rainstorms in Sichuan

In this study, we aimed to demonstrate the importance of diabatic heating in extreme rainstorm weather events induced by the Southwest China vortex (SWCV) in different precipitation regions with a similar circulation background. The results showed that atmospheric diabatic heating had indicative significance for the intensity evolution of the SWCV and the precipitation area. Changes in the diabatic heating intensity preceded the intensity evolution of the SWCV, and the diabatic heating region was consistent with the heavy precipitation region. The variation in diabatic heating was mainly due to the positive contribution of its vertical transport term. The two types of spatially non-uniform heating effects were similar; however, the western type was located southeast of the SWCV, with an asymmetric distribution on the southeastern and northwestern sides. The eastern type was located in the northeast of the SWCV, with an asymmetric distribution on the northeastern and southwestern sides. The vertically non-uniform heating effect played a decisive role in the distribution and evolution of the spatially non-uniform heating terms. The vertically non-uniform heating effect affected the intensity evolution of the SWCV. In contrast, the horizontally non-uniform heating effect, in opposition to the vertically non-uniform heating effect, had a slightly weaker intensity than the vertically non-uniform heating effect. For the SWCV system, which induces extreme rainstorms, the magnitude of the horizontally non-uniform heating effect could reach that of vertically non-uniform heating; thus, the possible impact of horizontally non-uniform heating should be considered.

Little evidence of hysteresis in regional precipitation, when indexed by global temperature rise and fall in an overshoot climate simulation

Abstract Society has set the aim of stabilising climate at key temperature thresholds, such as global warming at or below 1.5°C or 2.0°C above preindustrial levels. However, greenhouse gas emissions are failing to decline, and if they continue on their current trajectory it is likely that such thresholds will be crossed in the decades ahead. Because of this risk, there is an emerging focus on overshoot, where, for a temporary period, global warming is allowed to cross critical thresholds to reach a peak value before decreasing to the desired limit. A key question about overshoots is whether there are hysteresis effects—that is, whether global or regional climate has properties that differ between the phase of global warming increase and the phase of decreasing. Here, we analyse temperature and precipitation data from five Earth System Models (ESMs) forced by the SSP5-3.4-OS CMIP6 overshoot scenario. We look at the level of precipitation during two periods of near-identical global warming: one whilst temperatures are rising, and the other when they are falling. For global means, we find a statistically significant difference between precipitation values during the two periods. This is an example of hysteresis, as the reversion to an earlier global warming state results in a level of global rainfall which is different from that observed when warming was increasing. Spatial disaggregation of rainfall differences between the two near-identical warming levels shows the largest differences in the tropical region, which are statistically significant for four of the five ESMs. When considering much smaller regions, including parts of the tropics, there remains some evidence of hysteresis. However, the differences are no longer statistically significant against a background of substantial interannual rainfall variability. We discuss the implications of our findings for climate impacts assesments.

Impact of El Niño, Indian Ocean dipole, and Madden–Julian oscillation on land surface temperature in Kuching City Sarawak, during the periods of 1997/1998 and 2015/2016: a pilot study

ABSTRACT The severe El Niño events of 1997/1998 and 2015/2016 caused significant disruptions in Southeast Asia, particularly in Borneo, resulting in hazardous haze and acute water shortages. This study examines the influence of El Niño, the Indian Ocean Dipole (IOD), and the Madden–Julian oscillation (MJO) on regional climate, using time-series data from February 1993 to December 2020. Data from El Niño, IOD, and MJO indices were integrated with Landsat 5 and 8 land surface temperature records, allowing for a detailed analysis of their combined effects on regional temperature and precipitation patterns. Time-series trend decomposition and the generalized linear mixed model approach identified the Oceanic Niño Index (ONI) as a significant driver of temperature increases and dry spell occurrences during the peak El Niño years. On the other hand, ONI correlated strongly with mean monthly temperatures, underscoring its dominant influence. In addition, the IOD was found to significantly affect regional temperatures with a regression coefficient of 0.38867 (p = 0.0455), indicating its significant but less pronounced impact compared with ONI. These findings clarify the dynamics between key climate indices and their impact on regional climate extremes, offering critical insights for improving climate resilience and adaptation in tropical regions.

Disentangling ecological drivers of interspecific achromatic plumage variation in birds

AbstractAimUnderstanding the ecological determinants of interspecific achromatic (light‐to‐dark) plumage variation in birds is crucial yet challenging due to the complex interplay of climatic, habitat‐related, and morphological influences. This study aimed to disentangle the effects of temperature, precipitation, habitat openness, body mass and hand‐wing index (HWI, a widely used single‐parameter proxy for the extent to which a species relies on flight) on shaping achromatic plumage variation among bird species.LocationGlobal.Time PeriodContemporary.Major Taxa StudiedBirds.MethodsBased on data from over 8000 sessile bird species globally, we employed phylogenetic linear regressions to account for achromatic plumage colour in relation to temperature, precipitation, habitat openness, body mass and HWI, while correcting for phylogenetic non‐independence between species. Furthermore, we conducted phylogenetic path analyses to decompose direct from indirect effects.ResultsWe found that temperature, precipitation, habitat openness and body mass exerted separate but interactive effects on the variation in achromatic colour across species. Species inhabiting cold, wet or densely vegetated environments were darker coloured, while smaller species were lighter. Darker plumage was more strongly related to higher precipitation in colder regions for nocturnal species. For diurnal species, darker plumage was more closely associated with higher precipitation in more open habitats, whereas lighter plumage was more linked to lower mass in denser habitats. Noteworthy was the identification of a substantial correlation between achromatic colour and HWI. Diurnal species that are more aerial were lighter. Conversely, nocturnal flyers, especially females, tended to be darker.Main ConclusionsThe findings highlight the multifaceted nature of plumage coloration evolution, with adaptations for thermal efficiency, crypsis, signalling, waterproofing or protection against bacteria. However, the variable relative importance of these factors among groups emphasizes the significance of each factor in different contexts.

A preliminary integrated analysis of regional paleoclimate variations in China over the past ∼ 21 ka

In this study, we employ biological, geochemical and mineral, and physical proxies to quantitatively and semi-quantitatively reconstruct regional paleoclimate variations in China over the past ∼21 thousand years (ka). We have constructed state-of-the-art transfer functions between proxies and climatic variables in East Asia, revealing substantial paleoclimate variability, and demonstrate significant diversity of paleoclimate variations in regions of China over the past ∼21 ka. Compared with observational data between 1961 and 1990, averaged mean annual temperature (MAT) was ∼5 °C (3–8 °C) lower during the Last Glacial Maximum (LGM, ∼21 ± 3 ka), and ∼ 2 °C (1–3 °C) higher during Holocene Optimum (HO, ±9 ka) in China; while averaged mean annual precipitation (MAP) and averaged summer precipitation varied between 30 and 150%, with enhanced seasonality during the warmer Holocene (8–5 ka). Our quantitative and semi-quantitative paleoclimate reconstructions reveal both similarities and contrasts with previous studies of regional temperature and precipitation variability. The most remarkable paleoclimate variability is recorded in the transitional zone between the humid monsoon and arid desert regions of central and northern China. We conducted a dynamic downscaling paleoclimate simulation with a regional climate model (RegCM4), using the output from the fully-forced transient simulation of the global climate (TraCE-21 K) as the prescribed boundary conditions, to simulate regional climate changes at high spatial resolution in China over the past ∼21 ka. The results improve paleoclimate simulations at regional scales, but reveal differences in comparison with TraCE-21 K, thereby highlighting uncertainties in the simulation modeling. Moreover, we compare proxy-based paleoclimate reconstructions and the output of TraCE-21 K to identify inconsistencies in relation to regional paleoclimate variations, and confirm a generally consistent warming trend in MAT from the LGM to the HO followed by a cooling trend during the late Holocene. An overall increase in both annual and summer precipitation is observed from LGM to Holocene. This general paleoclimate pattern is likely to have been driven by northern hemisphere ice volume and atmospheric greenhouse gas concentrations (GHGs) during the last deglaciation, and boreal summer insolation during the Holocene. This study represents the first attempt to use multi sources and large datasets of proxy reconstructions and numerical simulations to evaluate regional paleoclimate variability in China since the LGM. Our research provides a comprehensive overview of climate change over the past 21 ka and underscores the critical importance of conducting high-resolution simulations and quantitative paleoclimate studies. This approach is essential for deciphering patterns of paleoclimate change that are currently poorly defined.

Bridging molecular dynamics and additive manufacturing: A study of Al-12 at% Si alloy solidification dynamics

This manuscript provides a detailed analysis of the molecular dynamics of the directional solidification process in Aluminum-Silicon (Al-12 % at Si) alloys, with a particular emphasis on applications in additive manufacturing. Utilizing molecular dynamics (MD) simulations, the study examines large systems containing 5–15 million atoms to investigate various facets of the solidification process. These include the dynamics of interface motion and the formation of Silicon (Si) precipitates. The research reveals significant variations in interface velocities and orientations across different thermal gradients and growth rates, underscoring the intricate interaction between thermal and solute flows in the microstructural development of Al-Si alloys. These findings are vital for comprehending and refining the solidification process in additive manufacturing, ultimately enhancing the mechanical strength and reliability of the final products. The paper highlights the critical role of microstructure control in printed metals and proposes future research directions, aiming to apply these insights to more complex alloy compositions and manufacturing contexts. In the concluding phase, the scikit-image library was employed to analyze dendritic formations in solidifying Al-Si alloys using MD simulations. This analysis delineates trends in dendritic count, spacing, perimeter, and area over time, offering essential perspectives on the solidification process and its implications for the alloy's microstructure and mechanical characteristics. The Si content in the Al-Si alloy used can be considered eutectic in the solidified structure. Si atoms are predominantly located at grain boundaries and precipitate regions. Coordination number analysis further confirms the presence of Si in these locations. This microstructure, characterized by a primary Al/Al-Si matrix and Si-rich eutectic regions, aligns with experimental observations in rapid solidification processes in additive manufacturing.