Spatiotemporal Variability Of Precipitation Research Articles

Long-Term Variation Patterns of Precipitations Driven by Climate Change in China from 1901 to 2022

Studying long-term precipitation trends is crucial for sustainable development, as the proper utilization of water resources is essential for maintaining a sustainable water supply. The objective and novelty of this paper was to reveal the gradual mutation process of precipitation in China over a century. This study utilized monthly precipitation data from 1901 to 2022 (at a century scale) to analyze and explore the spatiotemporal variability in precipitation across different time scales and regions with a trend analysis, an abrupt change analysis, and gravity center models. The findings indicate that (1) from 1901 to 2022, the precipitation in China generally decreased from the southeast coastal areas toward the northwest inland regions. (2) There were significant differences in the migration of precipitation gravity centers among the different study regions, with the least dispersion being observed in the Liao River basin, while the Hai River basin, various river basins in the northwest, and the Pearl River basin exhibited certain regularities in gravity center movement, and other regions showed periodic variations. (3) Over the period from 1901 to 2022, there was a trend of transitioning from lower to higher precipitation levels. (4) According to continuous long-term abrupt change tests, the timing of precipitation shifts varied across different basins. Precipitation, as a crucial component of natural resources, directly impacts various aspects of socio-economic life. Research findings provide decision support for regional flood control and disaster reduction and offer scientific decisions for ecological security.

Regional Precipitation Regimes and Evaluation of National Precipitation Datasets against Satellite-Based Precipitation Estimates, Republic of Georgia

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 In Caucasus, evaluations often rely on outdated data from nearby rivers.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

Reconstructing a new terrestrial water storage deficit index to detect and quantify drought in the Yangtze River Basin

With the intensification of global climate change, droughts have frequently been occurring in the Yangtze River Basin (YRB), significantly affecting the production patterns, lives, and socioeconomic development of humans. Drought characteristics must be comprehensively identified and quantified to reduce the damage caused by droughts in the YRB. The spatiotemporal variability of precipitation, runoff, soil moisture, groundwater change (GWSC) and terrestrial water storage change (TWSC) in the YRB was comprehensively estimated using the Gravity Recovery and Climate Experiment (GRACE), hydrological and in situ observations by decomposing the variabilities into seasonal, sub-seasonal, trend, and interannual. The new weighted GRACE drought standardized index (WGDSI) and weighted groundwater standardized index (WGWSI) were reconstructed by weighing the seasonal, trend, interannual and sub-seasonal of TWSC and GWSC. They were compared with the standardized soil moisture index (SSI06), standardized precipitation index (SPI06), and standardized runoff index (SRI06). Additionally, the drought characteristics identified based on the observations of the water storage deficit, severity, peak, duration, and recovery time in the YRB were also quantified using the WGDSI/WGWSI over the YRB. The results indicated that soil moisture, TWSC, and GWSC in the YRB increased from 2003 to 2019, mainly based on seasonal and interannual signals. The correlation coefficients between the WGDSI and the SSI06, SPI06, and SRI06 at the monthly were 0.84, 0.56, and 0.75, respectively, representing increases of 9 %, 14 %, and 21 % compared to that with the unweighted GRACE drought standardized index, respectively. The interannual variability of the hydrologic variables was more consistent with the drought events in the YRB, which was beneficial for detecting droughts. Two severe serious droughts occurred in the YRB from 2003 to 2019. In 2006, a continuous seven-month-long drought occurred, with a peak at − 28.974 km3, a severity of − 174.767 km3∙month, an average drought recovery rate of 0.83 km3/month, and a recovery time of 30 months, while in 2011, a continuous five-month-long drought occurred, with a peak at − 18.384 km3, a severity of − 78.106 km3∙month, an average drought recovery rate of 0.40 km3/month, and a recovery time of 39 months. The results indicated that the WGDSI could effectively identify drought events and measure their severity accurately, offering a more holistic understanding of drought conditions compared to other available indices. The index proposed in this study can be applied to generate new datasets and methods for quantifying and detecting droughts on a global scale.

Spatiotemporal variations of precipitation during the rainy season over the three-rivers headwater region of tibetan plateau from 1990 to 2020

Spatiotemporal variations of precipitation during the rainy season over the three-rivers headwater region of tibetan plateau from 1990 to 2020

Performance Evaluation of TerraClimate Monthly Rainfall Data after Bias Correction in the Fes-Meknes Region (Morocco)

Morocco’s meteorological observation network is quite old, but the spatial coverage is insufficient to conduct studies over large areas, especially in mountainous regions, such as the Fez-Meknes region, where spatio-temporal variability in precipitation depends on altitude and exposure. The lack of station data is the main reason that led us to look for alternative solutions. TerraClimate (TC) reanalysis data were used to remedy this situation. However, reanalysis data are usually affected by a bias in the raw values. Bias correction methods generally involve a procedure in which a “transfer function” between the simulated and corrected variable is derived from the cumulative distribution functions (CDFs) of these variables. We explore the possibilities of using TC precipitation data for the Fez-Meknes administrative region (Morocco). This examination is of great interest for the region whose mountain peaks constitute the most important reservoir of water in the country, where TC data can overcome the difficulty of estimating precipitation in mountainous regions where the spatio-temporal variability is very high. Thus, we carried out the validation of TC data on stations belonging to plain and mountain topographic units and having different bioclimatic and topographic characteristics. Overall, the results demonstrate that the TC data capture the altitudinal gradient of precipitation and the average rainfall pattern, with a maximum in November and a minimum in July, which is a characteristic of the Mediterranean climate. However, we identified quasi-systematic biases, negative in mountainous regions and positive in lowland stations. In addition, summer precipitation is overestimated in mountain regions. It is considered that this bias comes from the imperfect representation of the physical processes of rainfall formation by the models. To reduce this bias, we applied the quantile mapping (QM) method. After correction using five QM variants, a significant improvement was observed for all stations and most months, except for May. Validation statistics for the five bias correction variants do not indicate the superiority of any particular method in terms of robustness. Indeed, results indicate that most QM methods lead to a significant improvement in TC data after monthly bias corrections.

Predicted changes in future precipitation and air temperature across Bangladesh using CMIP6 GCMs

Understanding spatiotemporal variability in precipitation and temperature and their future projections is critical for assessing environmental hazards and planning long-term mitigation and adaptation. In this study, 18 Global Climate Models (GCMs) from the most recent Coupled Model Intercomparison Project phase 6 (CMIP6) were employed to project the mean annual, seasonal, and monthly precipitation, maximum air temperature (Tmax), and minimum air temperature (Tmin) in Bangladesh. The GCM projections were bias-corrected using the Simple Quantile Mapping (SQM) technique. Using the Multi-Model Ensemble (MME) mean of the bias-corrected dataset, the expected changes for the four Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) were evaluated for the near (2015–2044), mid (2045–2074), and far (2075–2100) futures in comparison to the historical period (1985–2014). In the far future, the anticipated average annual precipitation increased by 9.48%, 13.63%, 21.07%, and 30.90%, while the average Tmax (Tmin) rose by 1.09 (1.17), 1.60 (1.91), 2.12 (2.80), and 2.99 (3.69) °C for SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. According to predictions for the SSP5-8.5 scenario in the distant future, there is expected to be a substantial rise in precipitation (41.98%) during the post-monsoon season. In contrast, winter precipitation was predicted to decrease most (11.12%) in the mid-future for SSP3-7.0, while to increase most (15.62%) in the far-future for SSP1-2.6. Tmax (Tmin) was predicted to rise most in the winter and least in the monsoon for all periods and scenarios. Tmin increased more rapidly than Tmax in all seasons for all SSPs. The projected changes could lead to more frequent and severe flooding, landslides, and negative impacts on human health, agriculture, and ecosystems. The study highlights the need for localized and context-specific adaptation strategies as different regions of Bangladesh will be affected differently by these changes.

Authigenic beryllium isotopes reveal fluctuations in the East Asian monsoon over the past two millennia

Reconstructing climate variability beyond human records allows reconstruction of past and prediction of future climate change. However, a lack of high-resolution paleoclimate archives and effective climate proxies has hitherto limited reconstruction of the spatiotemporal evolution of the East Asian summer monsoon (EASM). In this study, the ratio of the meteoric cosmogenic 10Be (10Bemet) to silicate-weathered 9Be in annually laminated sediments from Maar Lake Xiaolongwan (NE China) was utilized to reconstruct EASM precipitation over the past two millennia. We find two apparent humid periods during the transitions of the Dark Age Cold Period–Medieval Climate Anomaly (DACP–MCA, ∼700 CE) and MCA–Little Ice Age (MCA–LIA, ∼1250 CE). The interval of these two humid periods is consistent with previous proposition of ∼500-yr oscillations of EASM in Northeast Asia. Although there are some phase variabilities, the pattern of temporal variation from 400 to 1600 CE are synchronous with other regional climate records from the EASM region. However, the spatial pattern shows an anti-phase synchronization between the EASM and the transition zone between the EASM and the Indian summer monsoon (ISM), revealing a “dry northeastern and wet southwestern” mode during the MCA. The climate change fluctuations derived here from 10Bemet/9Be in maar lake sediments are more straightforward than Chinese cave δ18O records and global temperature anomalies, providing a unique climate proxy for detecting variations of paleo-precipitation flux in specific regions. The overall slight weakening of EASM is consistent with a long-term cooling trend, which is likely regulated by solar irradiance. The apparent decrease of EASM during the transition from MCA to LIA is interpreted as the main control of explosive volcanic eruptions. The internal fluctuations and the spatiotemporal variability of precipitation are likely associated with the integrated effect of ISM and El Niño-Southern Oscillation.

Wavelet Analysis for Studying Rainfall Variability and Regionalizing Data: An Applied Study of the Moulouya Watershed in Morocco

This study analyzes the spatiotemporal variability of precipitation at the scale of the Moulouya watershed in eastern Morocco, which is very vulnerable to the increasing water shortage. For this purpose, we opted for wavelet transformation, a method based on the spectral analysis of data which allows for periodic components of a rainfall time series to change with time. The results obtained from this work show spectral power across five frequency ranges of variability: 1 to 2 years, 2 to 4 years, 4 to 8 years, 8 to 16 years, and 16 to 32 years. The duration of significant power at these frequencies is generally not homogeneous and varies from station to station. The most widespread frequency over the entire study area was found in the 4- to 8-year range. This mode of variability can last up to 27 consecutive years. In most of the basin, this mode of variability was observed around the period between 1990 and 2010. Oscillations at 8 to 16 years in frequency appear in only five series and over different time periods. The 16- to 32-year mode of variability appears in 15 stations and extends over the period from 1983 to 2008. At this level, signal strength is very weak compared to other higher-frequency modes of variability. On the other hand, the mode of variability at the 1- to 2-year frequency range appeared to be continuous in some stations and intermittent in others. This allowed us to regionalize our study basin into two homogeneous clusters that only differ in variability and rainfall regime.

Long-term spatiotemporal variability of precipitation and its linkages with atmospheric teleconnections in the Yellow River Basin, China

AbstractPrecipitation is widely considered as a crucial index toward the apprehension of global climate change. Hence, it becomes imperative to explore spatiotemporal patterns and the interlinked factors of precipitation in the basin. In the study, the spatial and temporal variability of precipitation and the individual or integrated effects of various atmospheric teleconnections on precipitation variations are explored in the Yellow River Basin. The total precipitation showed a slightly declining tendency during 1950–2019 and the dependence relationship of precipitation gradient on latitude and longitude is different in various seasons and elevations. The spatiotemporal variability of precipitation is more sensitive to the latitude gradient. For each 1-degree increase in longitude and latitude, the average annual precipitation increases/decreases by 10.73 and 57.24 mm, respectively. Moreover, the precipitation spatiotemporal patterns could be interpreted by four empirical orthogonal functions (EOFs) modes about 71.9% of precipitation variations. The strength of the linkages between various circulation factors and precipitation varied at different time scales. The integrated effects of multiple factors should be taken into consideration in explaining precipitation variability at all time scales. It is expected that the study can be helpful for understanding the internal mechanism of the hydrological cycle in the YRB.

Spatio-temporal rainfall variability and its impacts on the hydrological response of nature-based solutions

ABSTRACT The high spatio-temporal variability of precipitation makes the hydrological responses of nature-based solutions (NBS) indeterminate. Hence, this study investigated the hydrological responses of a semi-urban catchment and three NBS scenarios concerning different spatio-temporal rainfall data from both C-band radar and X-band radar. Multi-Hydro, the fully-distributed and physically-based hydrological model, is employed to study the spatio-temporal rainfall variability and the resulting hydrological impacts on the NBS scenarios. The scale-independent indicator of maximum probable singularity (γs ) within the Universal Multifractals (UM) framework is used to quantify the spatio-temporal variability of rainfall and catchment responses across scales. The main results show that the hydrological performances of the NBS scenarios can be largely underestimated or overestimated because of the spatio-temporal rainfall variability, with a relative error ranging from −91% to 199%, and NBS can effectively reduce surface runoff across scales, which is characterised by a lower γs .

Spatio-temporal assessment of Gridded precipitation products across topographic and climatic gradients in Colombia

Gridded precipitation products (GPPs) represent an alternative to and a complement to gauge-based observations of precipitation, improving the representation of spatio-temporal precipitation variability in regions with scarce gauge networks. However, GPPs' accuracy varies among products, temporal resolution, and regions, indicating the need for particular regional performance assessments. In this study, we evaluate the performance of eight state-of-the-art GPPs (CHIRPSv2, CMORPHv1, ERA5, ERA5-Land, IMERG, MSWEPv2.8, PERSIANN-CCS, and PERSIANN-CDR) over the steep topographic and climatic gradients of Colombia, in northwestern South America. We use a point-to-pixel comparison between ground-based observations from 1334 gauges with the corresponding grid cell of each GPP at 3-day, monthly, seasonal (DJF, MAM, JJA, SON), and annual scales over 2005–2014. Five categorical indices are used to assess the ability of each GPP to capture different 3-day precipitation intensity events correctly. The Kling-Gupta efficiency and its components are used to assess the GPPs' performance over Colombia and its five natural regions. Our results show that, at the 3-day scale, GPPs can correctly identify the occurrence of no-precipitation events (< 1 mm/day), but their capacity to classify precipitation events (≥ 1 mm/day) is low. The best performance is observed at the monthly scale, particularly at low elevation zones (0–1000 m.a.s.l), compared to 3-day and annual scales. Seasonally, GPPs tend to perform better during the dry season compared to the wet season in all regions. Overall, CHIRPSv2 outperforms other GPPs throughout the country and its five natural regions for all elevation zones and temporal scales, followed closely by MSWEPv2.8 and IMERG. PERSIANN-CCS and ERA5 products had the lowest performance, mainly over the driest and higher-altitude regions, respectively. This study provides insights into the performance of GPPs in complex climatic and topographic settings and, importantly, suggests the most suitable products for climate, hydrological, or ecological studies in a climatic, hydrological, and ecologically-strategic region.

Spatio-temporal variation of precipitation projection based on bias-adjusted CORDEX-SA regional climate model simulations for arid and semi-arid region

Global warming significantly affects the hydrological cycle that influences hydrological systems worldwide. Knowledge of precipitation variation under a changing climate can provide effective ways to deal with its impacts on water resource management. Hence, in this study, spatiotemporal variability of precipitation under future climatic scenarios was studied using suitable regional climate models (RCMs) extracted from the South Asia Coordinated Regional Climate Downscaling Experiments (CORDEX-SA) based on the control period (1976-2005). Additionally, this research attempted to evaluate the changes in precipitation patterns in Iran by integrating output from a set of RCMs extracted from CORDEX-SA with selected bias-correction (BC) methods, namely quantile ranking-based bias correction (QRBC), linear scaling (LS), empirical quantile mapping (EQM), Gamma quantile mapping (GQM), and Gamma-Pareto quantile mapping (GPQM). Regarding the findings, the performance of RCMs varied based on the climates of regions. Moreover, QRBC played an essential role in improving the output of RCMs to simulate precipitation values. Under RCP4.5 and RCP8.5, the projection of seasonal precipitation indicated that a slight wetting pattern might occur across the northern area in all seasons, especially in the southern regions. Whereas the southern area exhibited a strong wetting tendency in autumn, and the maximum percentage changes (PC) of precipitation were projected to increase by 35% for the mid (2040-2070) and far future (2070-2100) periods, based on RCP4.5 and RCP8.5, respectively. This study will be helpful in understanding the uncertainties in CORDEX-SA RCM projections of climate changes in Iran. Using the outcomes of this study, strategies can be adopted to better manage water resources for various regions of Iran.

Spatiotemporal Variation Characteristics of Precipitation in the Huaihe River Basin, China, as a Result of Climate Change

Climate change is a global scientific problem, and its impact on the spatiotemporal variations of precipitation has been a crucial research topic. Although previous studies have used different methods to evaluate the precipitation characteristics of the Huaihe River Basin, the time series were short and the few stations could not fully and accurately represent the precipitation characteristics. In this study, daily temperature and precipitation data were collected from 233 meteorological stations in the Huaihe River Basin from 1960–2020. The Mann–Kendall test was used to analyze the trend and significance of interannual and interseasonal scale changes in temperature and precipitation in the Basin, respectively. The correlation between temperature and precipitation was analyzed using the Pearson correlation coefficient method. The spatial distribution of the significance of temperature and precipitation changes and the spatial distribution of the correlation between temperature and precipitation in the basin were plotted. The temperature in the basin tended to increase on interannual and interseasonal scales, with more noticeable changes in spring and winter. Precipitation showed an overall decreasing trend but an increasing trend in localized areas in the south. A decreasing trend in the interseasonal variation scale was observed in spring, an increasing trend in winter, a decreasing trend in the northeastern region in summer, an increasing trend in the southwestern region, and an increasing trend in the northern and southern parts in autumn were observed. The correlation between average temperature and precipitation on interannual and interseasonal scales was analyzed using Pearson’s correlation coefficient method, and the annual average temperature and annual average precipitation in the Huaihe River basin were found to be negatively correlated, except for sporadic areas that showed extremely weakly positive correlations or no correlations.

Precipitation in eastern China over the past millennium varied with large-scale climate patterns

Modern precipitation variability over East China is known to be characterized by meridional tripole and dipole structures, linked to atmosphere and ocean dynamics. As the instrumental data may be influenced by anthropogenic global warming, it is unclear whether the physical mechanism underlying the tripole and dipole pattern have remained constant since the pre-industrial period. Here we investigate spatiotemporal precipitation variability over the past 1150 years using three high-resolution stalagmite δ18O records from southern, central and northern China. Principal component analysis results suggest that the first principal component, reflecting large-scale Asian monsoon strength, is closely linked to solar variability. The second and third principal components, which reflect rainfall, reveal tripole and dipole patterns that persist over the last millennium and are driven by the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO). We find that interactions between the monsoon, PDO, and AMO influence spatiotemporal rainfall patterns in East China.

Evaluation of the Spatiotemporal Distribution of Precipitation Using 28 Precipitation Indices and 4 IMERG Datasets over Nepal

Accurate accounting of spatiotemporal variability of precipitation is essential for understanding the changing climate. Among the available precipitation estimates, the Global Precipitation Measurement (GPM) is an international satellite network providing advanced global precipitation estimates. The integrated multi-satellite retrievals for GPM (IMERG) algorithm combines information from the GPM satellite constellation to estimate precipitation and yields a better performance in detecting precipitation events and spatial resolution. Here, we used twenty years (2001–2020) of IMERG Final data over the entire Nepal to analyze the spatial and temporal distribution of precipitation. This study evaluates the dynamic characteristics of the precipitation amounts, intensities, frequencies, and other relevant data across Nepal, using four IMERG datasets: (i) microwave only, (ii) infrared only, (iii) multi satellites gauge uncalibrated, and (iv) multi satellites gauge calibrated. A total of 28 precipitation indices was computed: threshold-based counts, consecutive days, precipitation amounts and extremes, precipitation intensity, percentile-based extremities, proportion-based indices, and additional seasonal indices. Results show that all four IMERG datasets are promising in capturing spatial details. The frequency of wet days corresponds with ground-based precipitation. Still, most indices, including consecutive wet days, annual and monsoon precipitation, and days when precipitation equaled or exceeded 20 and 50 mm, were substantially underestimated. In addition, the microwave-only dataset highly underestimated the precipitation amount. Notably, a substantial proportion of false alarms is a problem for all four IMERG datasets. Moreover, our results demonstrate that the IMERG uncalibrated dataset tends to overestimate precipitation during heavy precipitation events. These advantages and shortcomings of IMERG datasets over the rugged terrain of Nepal can provide useful feedback for sensor and algorithm developers to overcome limitations and improve retrieval algorithms. The study findings are helpful to the broader data users and practitioners for effective water decision applications.

Spatiotemporal variability of precipitation and surface temperature in the southern mesoregion of amazonas, Brazil, during the occurrence of ENSO

Impacts of El Niño – Southern Oscillation (ENSO) climatic phenomena in the southern mesoregion of the Amazon is still poorly understood. Thus, the objective of this study was to analyze the impacts of ENSO of moderate and strong categories on precipitation (ppt) and surface temperature (ts) in the southern mesoregion of Amazonas. The research was carried out with ppt data obtained by the product TRMM_3B43 and ts of the product MOD11C3 in the municipalities of Apuí, Boca do Acre, Canutama, Humaitá, Lábrea, Manicoré and Novo Aripuanã. The Niño Indices were obtained from the National Oceanic Atmospheric Administration. Ts was organized into averages and ppt in seasonal totals from 1998 to 2019, to obtain its provisional climatological normal in the dry and wet seasons. The results showed that ENSO significantly influenced the pattern of ppt and ts in the southern mesoregion of Amazonas. El Niño (EN) had more impact on changing the pattern of ppt and ts than La Niña (LN). The largest reductions in ppt and increases in Ts occurred in the EN periods of 1998/01 and 2015/16, while the occurrence of LN decreased the ppt more expressively in the periods of 2007/08 and 2011/12.

Investigation of precipitation and extreme indices spatiotemporal variability in Seyhan Basin, Turkey

Abstract Spatial and temporal variability of precipitation increases with the effect of climate change. In this study, the Seyhan Basin has been determined as the study area. It is aimed to examine the spatiotemporal variability of precipitation and extreme precipitation indices in the Seyhan Basin. For this purpose, the period 1970–2019 was divided into three periods with the change point detection methods (Pettitt, Buishand rank and standard normal homogeneity test). Trends were examined by applying modified Mann–Kendall and Spearman's rho tests to precipitation and extreme indices for all periods and sub-periods. Then, temporal and spatial analyses of extreme indices were performed. According to the results obtained, there is no precipitation homogeneity throughout the basin. While the threat of drought comes to the fore with the decrease in rainy days and precipitation in the north, the risk of flooding is effective with the increase in precipitation intensity in the south.

Contrasting Climatic Trends of Atmospheric River Occurrences Over East Asia

AbstractAtmospheric rivers (ARs) are increasingly recognized as a major driver of hydrological cycles, and are projected to increase around the world under a changing climate. However, the long‐term trends of ARs over East Asia (EA) remains less elucidated. Here we fill the gap by developing a longest‐ever archive of EA ARs, and examine its role in determining spatiotemporal precipitation variability over EA. We find contrasting changes in AR occurrences, with more frequent ARs in low latitudes but less in high latitudes during the period 1950–2020. The “dipole” pattern of decadal changes in AR occurrences is dictated by atmospheric dynamics (i.e., winds) in the north but thermodynamics (i.e., moisture) in the south. The reduced AR occurrences explain 49% of decreased annual precipitation in northern China, while more AR‐related precipitation is observed in southern China. Our results provide new insights into regional hydroclimate over EA by connecting it with large‐scale weather systems.

Spatio-Temporal Variation of Precipitation and Evaporation on the Tibetan Plateau and Their Influence on Regional Drought

The Tibetan Plateau (TP) is an important water source in Asia, and precipitation and evaporation patterns at different geographical and temporal scales play a significant role in managing water resource distribution. Based on quality control data from 87 meteorological stations, this study analyzed the spatial and temporal evolution patterns of precipitation and pan evaporation (Epan) on the TP in 1966–2016 using the Mann–Kendall test, the moving t-test, wavelet analysis, Sen’s slope method, and correlation analysis. The results revealed that the average mean temperature in the TP area increased by about 2.1 °C during the study period, and precipitation steadily increased at an average rate of 8.2 mm/10a, with summer and autumn precipitation making up about 80% of the year. In contrast, Epan showed an overall decreasing trend at a decline rate of 20.8 mm/10a, with spring and summer Epan values making up about 67% of the year. The time series of the precipitation and Epan within the TP region clearly exhibit nonstationary features. Precipitation is more concentrated in the southeast than in the northwest, while Epan is mostly concentrated in the southwest and northeast of the plateau around the Qaidam Basin. The “evaporation paradox” phenomenon was common in the TP region for about 40 years (1960s–1990s) and gradually faded in the 21st century. In addition, we introduced a standardized precipitation evaporation index (SPEI) to investigate the differences and relationships between precipitation and Epan time series over the past 50 years. The findings indicate that the southern Qinghai was dominated by an arid trend, while the central and southeast TP remained wet. Droughts and floods coexist in the eastern Qinghai and southern Tibet areas with high population concentrations, and the risk of both is rising as the inhomogeneity of precipitation distribution in the TP region will increase in the future. This study can be used as a reference for managing water resources and predicting regional drought and flood risk.

Spatio-Temporal Variation of Precipitation in the Qinling Mountains from 1970 to 2100 Based on CMIP6 Data

Estimating future precipitation changes in the Qinling Mountains has significance, for understanding how to reveal the basic characteristics of the atmospheric water cycle in mountainous areas under the action of monsoons and the temporal- and spatial-variation mechanism of water resources in the ‘central water tower’, under the background of climate change. Based on four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) of the CMIP6 model, the Taylor diagram method was used to select the best regional simulation model, according to historical observation data (1970–2014). On this basis, the precipitation change and circulation background of the Qinling Mountains over the next 86 years (2015–2100) were analyzed. The results show that the simulation effect of the optimal mode is better than that of the single mode. Under the four scenarios, the variation trends of the annual precipitation in the Qinling Mountains from 2015 to 2100 were 4.4 mm/10a, 18.5 mm/10a, 18.1 mm/10a, and 19.1 mm/10a, respectively. By the middle of this century (2041–2060), compared with the reference period of 1995–2014, the average annual precipitation in the Qinling Mountains under the four scenarios will increase by 64.1 mm, 7 mm, 28.8 mm, and −51 mm, respectively. By the end of this century (2081–2100), the average annual precipitation under the four scenarios will increase by 29.5 mm, 77.2 mm, 82.9 mm, and 21.2 mm, respectively. The abnormal increase (decrease) of water vapor, transported northward from the western Pacific and the Bay of Bengal, is the main reason for the abnormal increase (decrease) of precipitation in the flood season in the Qinling Mountains. With the increase in emission scenarios, the influence of the South Asian summer monsoon on precipitation in the Qinling Mountains becomes more significant.