Precipitation Frequency Research Articles

Extreme precipitation patterns in the Asia–Pacific region and its correlation with El Niño-Southern Oscillation (ENSO)

In the Asia–Pacific region (APR), extreme precipitation is one of the most critical climate stressors, affecting 60% of the population and adding pressure to governance, economic, environmental, and public health challenges. In this study, we analyzed extreme precipitation spatiotemporal trends in APR using 11 different indices and revealed the dominant factors governing precipitation amount by attributing its variability to precipitation frequency and intensity. We further investigated how these extreme precipitation indices are influenced by El Niño-Southern Oscillation (ENSO) at a seasonal scale. The analysis covered 465 ERA5 (the fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts) study locations over eight countries and regions during 1990–2019. Results revealed a general decrease indicated by the extreme precipitation indices (e.g., the annual total amount of wet-day precipitation, average intensity of wet-day precipitation), particularly in central-eastern China, Bangladesh, eastern India, Peninsular Malaysia and Indonesia. We observed that the seasonal variability of the amount of wet-day precipitation in most locations in China and India are dominated by precipitation intensity in June–August (JJA), and by precipitation frequency in December–February (DJF). Locations in Malaysia and Indonesia are mostly dominated by precipitation intensity in March–May (MAM) and DJF. During ENSO positive phase, significant negative anomalies in seasonal precipitation indices (amount of wet-day precipitation, number of wet days and intensity of wet-day precipitation) were observed in Indonesia, while opposite results were observed for ENSO negative phase. These findings revealing patterns and drivers for extreme precipitation in APR may inform climate change adaptation and disaster risk reduction strategies in the study region.

Diurnal Precipitation Features over Complex Terrains along the Yangtze River in China Based on Long-Term TRMM and GPM Radar Products

Based on the 20-year high-resolution precipitation data from TRMM and GPM radar products, diurnal features over complex terrains along the Yangtze River (YR) are investigated. Using the Fast Fourier Transform (FFT) method, the first (diurnal) and second (semi-diurnal) harmonic amplitude and phase of precipitation amount (PA), precipitation frequency (PF), and intensity (PI) are analyzed. The diurnal amplitudes of PA and PF have a decreasing trend from the west to the east with the decreasing altitude of large-scale terrain, while the semi-diurnal amplitudes of PA and PI depict the bimodal precipitation cycle over highlands. For the eastward propagation of PA, PF is capable of depicting the propagation from the upper to the middle reaches of YR, while PI shows the eastward propagation from the middle to the lower reaches of YR during nighttime and presents sensitivity to highlands and lowlands. According to the contribution of different-sized precipitation systems to PI over the highlands and lowlands, the small (<200 km2) ones contribute the least while the large ones (>6000 km2) contribute the most, but the medium ones (200–6000 km2) show a slightly larger contribution over the highlands than over the lowlands. The propagation of each scaled precipitation system along the YR is further analyzed. We found that small precipitation systems mainly happen in the afternoon without obvious propagation. Medium ones peak 2–4 h later than the small ones, with two eastward propagation directions at night from the middle reaches of YR to the east. The large ones are mainly located in lowlands at night, with two propagation routes in the morning over the middle and lower reaches of YR. Such a relay of the propagation of the medium and large precipitation systems explains the eastward movement of PI along the YR, which merits future dynamic studies.

Assessment of WRF (v 4.2.1) dynamically downscaled precipitation on subdaily and daily timescales over CONUS

Abstract. This study analyzes the quality of simulated historical precipitation across the contiguous United States (CONUS) in a 12 km Weather Research and Forecasting model version 4.2.1 (WRF v 4.2.1)-based dynamical downscaling of the fifth-generation ECMWF atmospheric reanalysis (ERA5). This work addresses the following questions. First, how well are the 3 and 24 h precipitation characteristics (diurnal and annual cycles, precipitation frequency, annual and seasonal mean and maximum precipitation, and distribution of seasonal maximum precipitation) represented in the downscaled simulation, compared to ERA5? And second, how does the performance of the simulated WRF precipitation vary across seasons, regions, and timescales? Performance is measured against the National Centers for Environmental Prediction/Environmental Modeling Center (NCEP/EMC) 4 km Stage IV and Oregon State University Parameter-Elevation Regressions on Independent Slopes Model (PRISM) data on 3 and 24 h timescales, respectively. Our analysis suggests that the 12 km WRF exhibits biases typically found in other WRF simulations, including those at convection-permitting scales. In particular, WRF simulates both the timing and magnitude of the summer diurnal precipitation peak as well as ERA5 over most of the CONUS, except for a delayed diurnal peak over the Great Plains. As compared to ERA5, both the month and the magnitude of the precipitation peak annual cycle are remarkably improved in the downscaled WRF simulation. WRF slightly overestimates 3 and 24 h precipitation maximum over the CONUS, in contrast to ERA5, which generally underestimates these quantities mainly over the eastern half of the CONUS. Notably, WRF better captures the probability density distribution (PDF) of 3 and 24 h annual and seasonal maximum precipitation. WRF exhibits seasonally dependent precipitation biases across the CONUS, while ERA5's biases are relatively consistent year round over most of the CONUS. These results suggest that dynamical downscaling to a higher resolution improves upon some precipitation metrics but is susceptible to common regional climate model biases. Consequently, if used as input data for domain-specific models, we suggest moderate bias correction be applied to the dynamically downscaled product.

Observed Changes in Interannual Precipitation Variability in the United States

AbstractCharacterizing changes in precipitation patterns over time is critical for hydrologically dependent fields like water resource management and agriculture. Here, we explore observed trends in interannual precipitation variability using a suite of metrics that describe changes in precipitation over time. We analyze daily in situ Global Historical Climatology Network precipitation data from 1970 to present over 17 internally consistent sub‐national United States domains using a regional Mann‐Kendall trend test. We find robustly increasing trends in annual mean precipitation and wet day frequency for most of the central and eastern U.S., but decreasing trends in the western U.S. Importantly, we identify widespread significant trends in interannual precipitation variability, with increasing variability in the southeast, decreasing variability in the far west, and mixed signals in the Rocky Mountains and north‐central U.S. Our results provide important context for water resource managers and a new observational standard for climate model performance assessments.

A Preliminary Analysis of Typical Structures and Microphysical Characteristics of Precipitation in Northeastern China Cold Vortexes

The northeastern China cold vortex (NCCV) is the main weather system affecting Northeast China. Based on the precipitation products from the dual-frequency precipitation radar (DPR) onboard the Global Precipitation Measurement core observatory (GPM) satellite, the precipitation structures and microphysical properties for different rain types in 6432 NCCVs from 2014 to 2019 were studied using dynamic composite analysis. Our results show that the precipitation in NCCVs is dominated by stratiform precipitation. Regions with high stratiform and convective precipitation frequency have a comma shape. The growth mechanism of precipitation particles changes at ~4 km in altitude, the lower particles grow through collision (more pronounced in convective precipitation), and the upper hydrometeors grow through the Bergeron process. Additionally, the precipitation structures and microphysical properties exhibit great regional variations in NCCVs. The rainfall for all rain types is the strongest in the southeast region within an NCCV, mainly characterized by higher near-surface droplet concentration, while precipitation events occur more frequently in the southeast region for all rain types. There are active rimming growth processes above the melting layer for convective precipitation in the western region of an NCCV. In the southeast region of an NCCV, the collision growth of droplets in both types of precipitation is the most obvious.

Relation between storm characteristics and extreme precipitation statistics over CONUS

In this paper we use a statistical framework to analyze the relation between storm properties and the statistics of extreme precipitation. We identify storm events using a 24-hour dry hiatus separation. We investigate the statistics of the hourly maximum intensity for the heaviest storm events at durations of 1 and 24 h. A two-parameter Weibull distribution is used to represent precipitation frequencies at several stations from a quality-controlled hourly precipitation dataset over the contiguous United States, encompassing seven climate zones. The Spearman correlation between the distribution parameters and a selection of storm properties (duration, intensity, decorrelation time, convective-like ratio) and station properties (elevation and latitude) is used to measure the relation of these properties with the statistics of extreme precipitation. Our results indicate that observed annual maximum hourly precipitation over the entire study area are likely samples from the used distribution, implying that a two-parameter Weibull distribution is suitable for modeling hourly and 24-hour precipitation extremes over the contiguous United States. The spatial variability of shape parameters obtained for hourly events showed lighter tails in the west coast when compared to the rest of CONUS, while the central-north displays heavier tails. We identify statistically significant links (at the 95% confidence level) between storm characteristics connected with the underlying processes (e.g., typical storm duration, typical temporal autocorrelation, proportion of convective-like storms) and the parameters of the distribution. Notably, characteristics typical of convective precipitation, e.g., sharp decorrelation time and high hourly intensity, tend to be related to distributions with heavier tails. These results provide a first step towards linking the characteristics of storms with the local statistics of extremes.

Global Simulation of the Madden–Julian Oscillation With Stochastic Unified Convection Scheme

AbstractA new spectral convection scheme, the stochastic unified convection scheme (stochastic UNICON), is implemented in a general circulation model. The global climate simulation using stochastic UNICON is evaluated and compared with UNICON, focusing on the simulation of the Madden–Julian oscillation (MJO). Stochastic UNICON extends the original UNICON by randomly sampling convective updrafts from the joint probability density function constructed at the near‐surface, generating a spectrum of convective updrafts in a physically based manner. The performances of UNICON and stochastic UNICON on simulating observed mean climates are comparable, while stochastic UNICON slightly reduces the mean bias of climate variables. For the simulation of intraseasonal variabilities, stochastic UNICON outperforms UNICON in many aspects. Stochastic UNICON improves the simulation of the intensity and propagation patterns of boreal winter MJO, which are too weakly simulated in UNICON. The coherency between MJO‐related convection and large‐scale circulation is also enhanced, which many climate models underestimate. The improvement of MJO simulation by stochastic UNICON is related to a better representation of the relationship between moisture and convection in the model. The increased frequency of shallow convection in stochastic UNICON leads to stronger moisture convergence that precedes convection activity peak and results in the more robust development of organized convection and more frequent intense precipitation. A precipitation budget analysis reveals that the moisture tendencies due to horizontal advection and convective process are consistently enhanced during MJO developing periods by stochastic UNICON.

Exploring the Best-Matching Precipitation Traits in Four Long-Term Mainstream Products over China from 1981 to 2020

As a major component of water cycle, the accuracy quantification of different precipitation products is critical for evaluating climate change and ecosystem functions. However, a lack of evidence is available to choose a precise precipitation product in relative applications. Here, to solve this limit, we analyze the spatiotemporal pattern and accuracy of four precipitation products, including CHIRPS V2.0, PERSIANN-CDR, ECMWF ERA5-Land, and GLDAS_NOAH025_3H, over China during the period of 1981–2020, based on the five precipitation traits (i.e., spatial pattern of multi-year average, annual trend, seasonality, frequency, and intensity), and meteorological gauge observations are taken as the benchmark. Our results show that, compared to other products, CHIRPS data has the strongest ability to present spatial pattern of multi-year average precipitation, especially in most parts of northeastern and southern China, and ERA5 has the weakest ability to simulate the multi-year average precipitation. All four precipitation products can accurately depict the spatial pattern of seasonality, among which CHIRPS and ERA5 have the highest and lowest fitting ability, respectively, but four products poorly describe the spatial pattern of precipitation intensity and frequency at a daily scale. These products only correctly predict the interannual precipitation trend in some local areas. Our findings provide evidences to select high-quality precipitation data, and could help to improve the accuracy of relative geophysical models.

Global evaluation of Doppler velocity errors of EarthCARE cloud-profiling radar using a global storm-resolving simulation

Abstract. The cloud-profiling radar (CPR) on the Earth Clouds, Aerosol, and Radiation Explorer (EarthCARE) satellite (EC-CPR) is the first satellite-borne Doppler radar. In a previous study, we examined the effects of horizontal (along-track) integration and simple unfolding methods on the reduction of Doppler errors in the EC-CPR observations, and those effects were evaluated using two limited scenes in limited-latitude and low-pulse-repetition-frequency (PRF) settings. In this study, the amount of data used was significantly increased, and the area of the data used was extended globally. Not only low-PRF but also high-PRF settings were examined. We calculated the EC-CPR-observed Doppler velocity from pulse-pair covariances using the radar reflectivity factor and Doppler velocity obtained from a satellite data simulator and a global storm-resolving simulation. The global data were divided into five latitudinal zones, and each standard deviation of Doppler errors for 5 dBZe after 10 km integration was calculated. In the case of the low-PRF setting, the error without unfolding correction for the tropics reached a maximum of 2.2 m s−1 and then decreased toward the poles (0.43 m s−1). The error with unfolding correction for the tropics became much smaller at 0.63 m s−1. In the case of the high-PRF setting, the error without unfolding correction for the tropics reached a maximum of 0.78 m s−1 and then decreased toward the poles (0.19 m s−1). The error with unfolding correction for the tropics was 0.29 m s−1, less than half the value without the correction. The results of the analyses of the simulated data indicated that the zonal mean frequency of precipitation echoes was highest in the tropics and decreased toward the poles. Considering a limitation of the unfolding correction for discrimination between large upward velocity and large precipitation falling velocity, the latitudinal variation in the standard deviation of Doppler error can be explained by the precipitation echo distribution.

Observed and projected changes in wet and dry spells for the major river basins in East Asia

AbstractSpatiotemporal changes in wet and dry spells had significantly contributed to climate‐related natural hazards in East Asia, especially in river basins undergoing warming. However, few studies have systematically analysed these changes for river basins at different latitudes. Herein, we investigated the observed and projected variations in wet and dry spells for East Asian river basins at different latitudes. We found that river basins at low latitudes (Yangtze and Pearl rivers) had obvious wet characteristics, whereas those at high latitudes (Amur and Yellow rivers) had obvious dry characteristics. In general, the river basins presented a ‘wet south but dry north’ spatial pattern. Long‐duration wet spells have been shown to be the primary contributor to total wet spells in low‐latitude river basins, while long‐duration dry spells have been found to be the primary contributor to total dry spells in high‐latitude river basins. Importantly, climate is changing from prolonged wet spells to short, intense wet spells in low‐latitude river basins, whereas the climate is changing from single, short dry spells to moderate, prolonged dry spells at high latitudes. These changes indicate a high probability of flash floods in river basins at low latitudes and a high probability of droughts at high latitudes. In the future, more temporally clustered heavy precipitation events and prolonged dry spells may lead to increasingly uneven precipitation in high‐latitude river basins and the Pearl River basin, especially under the higher shared socioeconomic pathway scenarios. In contrast, more frequent consecutive heavy precipitation events may aggravate the risk of flooding in the Yangtze River basin. These findings are expected to serve as a guide for flood and drought risk mitigation in East Asia under a warming climate.

Methodology for the Selection of the Representative Climate Scenario at Yongdam Watershed

The four representative concentration pathways (RCP) scenarios presented in the fifth Assessment Report (AR5) is still widely used by researchers to assess the future effects of climate change in water resources management. However, the lack of providing scientific basis in the selection and application of climate scenarios in numerical models can further increase the uncertainties in the results. Therefore, this study aims to present an analytical and practical methodology for the selection of the representative climate scenario at Yongdam watershed. Based on the findings presented in this study, RCP6.0 scenario best represented the daily minimum temperature at Yongdam watershed for the past decade; the daily precipitation was best represented by RCP4.5 scenario. Furthermore, all four climate scenarios had the tendency to overestimate the magnitude and frequency of precipitation, which is an important factor that should be considered in the selection of climate scenarios. The results and methodology presented in this study can serve as a guideline in the selection of the most applicable climate scenario in other regions.

The Impacts of Climate Change on the Hydrological Cycle and Water Resource Management

Global warming can alter the hydrological cycle in various forms such as increased cloudiness and latent heat fluxes, leading to more intensive and frequent precipitation extreme events (e.g., droughts, storms, and floods). [...]

Proteinaceous Matter in PM2.5 in Suburban Guiyang, Southwestern China: Decreased Importance in Long‐Range Transport and Atmospheric Degradation

AbstractProteinaceous matter (PrM) is a substantial constituent in bioaerosols. However, the sources and atmospheric processes of PrM remain large uncertainties. The characterizations, sources, and potential atmospheric processes of free amino acids (FAAs) and combined amino acids (CAAs) were investigated via a set of 1‐year fine particle (PM2.5) samples collected in suburban Guiyang (a hilly basin area in Southwest China). The annual average concentrations of FAAs and CAAs were 156.31 ± 41.52 and 315.36 ± 147.66 ng m−3, respectively. The dominant FAA and CAA species were proline, which was different from previous observations with glycine as a major species. The results indicated that the sources or atmospheric processes of aerosol PrM at this study site were different from previous observations in the urban and suburban areas. The analysis of AA‐nitrogen isotope compositions and air mass back trajectories suggested that the abundances of aerosol FAAs and CAAs were highly controlled by primary sources (particularly plants) with less impact from long‐range transport. Furthermore, the contributions of PrM degradation by ozone‐ and hydroxyl radical‐related processes to total FAAs were found to be minor. The overall results suggested that the long‐range transport and atmospheric degradation of PrM were insignificant factors affecting aerosol PrM abundance in this suburban area with the weak atmospheric oxidation capacity, high cloud cover rate, and frequent precipitation. Thus, the findings improve our understanding of the sources and atmospheric processes of aerosol PrM.

Evolution Characteristics of Meteorological Drought under Future Climate Change in the Middle Reaches of the Yellow River Basin Based on the Copula Function

Against the background of global warming and frequent extreme precipitation events, the changes in drought characteristics in the middle reaches of the Yellow River Basin (YRMB) have been particularly pronounced in recent years. Under the new situation, it is necessary to further our understanding of drought risk in the basin and its response mechanisms to climate change. In this study, YRMB was utilized as the research area. Based on the precipitation (P) and potential evapotranspiration (PET) data under four emission scenarios (historical and future), five timescales (SPEI-1, SPEI-3, SPEI-6, SPEI-9, and SPEI-12) of SPEI drought indices were estimated in this study. Drought events were identified using the run-length theory, and the spatial distribution values of drought frequency, duration, intensity, and severity were also examined. Based on the preferred copula function, the two-dimensional joint distribution of drought variables was established, and the two-dimensional return period of drought indices in the historical (1901–2014) and future (2022–2100 under SSP245 and SSP585 emission scenarios) periods were calculated. The results show that the SPEI index in the middle reaches of the YRMB is increasing in the future period and the basin tends to be more humid. Under the SSP245 and SSP585 scenarios, the frequency of long drought durations, high drought intensities, or severe drought events in the basin may be higher. The univariate return period is always higher than the joint return period, but lower than the co-occurrence return period, and both types of return periods can be used to assess range estimations in the future. The research results can provide support for understanding the spatiotemporal distribution characteristics of drought in the YRMB and improving the accuracy of drought decision making.

Evaluating the Simulation of CONUS Precipitation by Storm Type in E3SM

AbstractConventional low‐resolution (LR) climate models, including the Energy Exascale Earth System Model (E3SMv1), have well‐known biases in simulating the frequency, intensity, and timing of precipitation. Approaches to next‐generation E3SM, whether the high‐resolution (HR) or multiscale modeling framework (MMF) configuration, improve the simulation of the intensity and frequency of precipitation, but regional and seasonal deficiencies still exist. Here we apply a methodology to assess the contribution of tropical cyclones (TCs), extratropical cyclones (ETCs), and mesoscale convective systems (MCSs) to simulated precipitation in E3SMv1‐HR and E3SMv1‐MMF relative to E3SMv1‐LR. Across the United States, E3SMv1‐MMF provides the best simulation in terms of precipitation accumulation, frequency and intensity from MCSs and TCs compared to E3SMv1‐LR and E3SMv1‐HR. All E3SMv1 configurations overestimate precipitation amounts from and the frequency of ETCs over CONUS, with conventional E3SMv1‐LR providing the best simulation compared to observations despite limitations in precipitation intensity within these events.

Contributions of Climate Change and ENSO Variability to Future Precipitation Extremes Over California

AbstractThe El Niño/Southern Oscillation (ENSO) affects the occurrence frequency and intensity of extreme precipitation through modulations of regional heat and moisture fluxes. California experiences particularly strong ENSO influences and models project different to its extreme precipitation. It remains unclear how diverse projections of future precipitation extremes relate to inter‐model differences for those changing signals. Here, we use “large ensemble” simulations with multiple climate models along with the Coupled Model Intercomparison Project Phase 5 to investigate the range of precipitation extreme changes over California and the influences from ENSO‐related teleconnections. We found that precipitation amount increases are much larger during El Niño relative to La Niña years, mainly caused by the differences in frequency of extreme events during different phases. The ENSO‐driven effect is even larger than the overall climate change signal for the most extreme events, implying uncertainties from inter‐model differences in ENSO‐related SST variability for extreme precipitation changes.

A downscaling and bias correction method for climate model ensemble simulations of local-scale hourly precipitation

Ensemble simulations of climate models are used to assess the impact of climate change on precipitation, and require downscaling at the local scale. Statistical downscaling methods have been used to estimate daily and monthly precipitation from observed and simulated data. Downscaling of short-term precipitation data is necessary for more accurate prediction of extreme precipitation events and related disasters at the regional level. In this study, we developed and investigated the performance of a downscaling method for climate model simulations of hourly precipitation. Our method was designed to recognize time-varying precipitation systems that can be represented at the same resolution as the numerical model. Downscaling improved the estimation of the spatial distribution of hourly precipitation frequency, monthly average, and 99th percentile values. The climate change in precipitation amount and frequency were shown in almost all areas by using the 50 ensemble averages of estimated precipitation, although the natural variability was too large to compare with observations. The changes in precipitation were consistent with simulations. Therefore, our downscaling method improved the evaluation of the climatic characteristics of extreme precipitation events and more comprehensively represented the influence of local factors, such as topography, which have been difficult to evaluate using previous methods.

Increased erosion in a pre-Alpine region contrasts with a future decrease in precipitation and snowmelt

Climate change is affecting the hydromorphological system. In many places, changes in sediment dynamics are closely correlated to changes in precipitation frequency and magnitude. However, in nivo-pluvial regimes, the hydromorphological response to climate is more challenging to predict as it is not only the amount and occurrence of precipitation that is changing. The changes in precipitation type (i.e., snow or rain), snow accumulation, and snowmelt rates will also have a significant effect on the catchment net precipitation (composed of direct precipitation plus snowmelt contribution), and this may affect overland flow, erosion, stream discharge, sediment transport, and deposition. We investigated the impacts of climate change on hydrology and geomorphology in a small catchment (Emme, 127 km2) located in the Swiss pre-Alps by simulating the difference between the hydromorphological response to net precipitation in the present climate and in three climate scenarios at the end of the century using the CAESAR-Lisflood landscape evolution model. For the most extreme climate scenario (RCP8.5), simulations showed that despite the reduction in net precipitation (by 7 %) and discharge (by 4 %), sediment yield at the outlet of the catchment increased by 6 %. This is not only because precipitation falls more as rain than snow during the cold months, but also because heavy precipitation is expected to intensify. On a seasonal scale, we found that the amount of net precipitation, discharge, and erosion will increase in winter at the end of the century, while it will decrease in spring. In all three climate scenarios, net precipitation is projected to decrease in summer, but sediment yields may both decrease or increase. Autumn is the season with the greatest changes in erosion, while net precipitation remains constant or only slightly increases. Furthermore, we found that erosion and deposition patterns are changing spatially, with more erosion in mid-elevations and more deposition in valleys. Although our results are specific to the study site, we expect similar trends in other catchments of the pre-Alpine region.

Precipitation-type discrimination and changes in related climate indices in the upper Heihe River Basin during 1960–2021

Introduction: Precipitation in the upstream region of the Heihe River basin (UHRB) in the northeastern of the Tibetan Plateau, which is the main water source of the basin, has undergone drastic changes in extreme climate events in recent decades. In addition to the amount of precipitation, the type of precipitation has a substantial impact on hydrological processes.Methods: In this study, we compared the results from three methods aimed at improving precipitation type estimation based on daily precipitation type records for 24 discontinuous years. Based on the precipitation type distinction, we examined the spatial and temporal changes in the total precipitation, rainfall, snowfall and air temperature at the six stations as well as the spatial average of the UHRB during the past 62 years. We also analyzed changes in the quantity, duration magnitude, and frequency of extreme precipitation using the RClimDex model and statistical analysis.Results: The probability of detection value of the T3.6_4.5 method was 1.9%, indicating the estimation was closest to actual records. The analyses based on precipitation type diving showed that rainfall accounts for an average of 81.9% of the total precipitation received in a year. In the context of large scale climate warming, temperatures at all six stations increased significantly, but precipitation changes were only apparent at about half of the stations which were located in regions of higher elevation and influenced by both ENSO and the East Asian monsoon. Analysis of the spatial averages in the UHRB revealed that the annual drought events (CDD) were significantly alleviated, and that the growing season length (GSL) was significantly extended. The annual total precipitation, rainfall, and extreme precipitation indices (P99P, P95P, R95P, and SDII) increased in magnitude, and the frequency of extreme precipitation events (P10mm) also significantly increased.Discussion: The findings of this study indicate that under the background of climate warming, the changes of precipitation patterns in the UHRB which may have resulted in bringing better vegetation growth, but also the increasingly frequent extreme rainfall events may pose challenges to growing extreme rainfall events to agriculture and other human activities in local and downstream areas.

Spatial–temporal variation of extreme precipitation in the Yellow–Huai–Hai–Yangtze Basin of China

Climate warming leads to frequent extreme precipitation events, which is a prominent manifestation of the variation of the global water cycle. In this study, data from 1842 meteorological stations in the Huang–Huai–Hai–Yangtze River Basin and 7 climate models of CMIP6 were used to obtain the historical and future precipitation data using the Anusplin interpolation, BMA method, and a non-stationary deviation correction technique. The temporal and spatial variations of extreme precipitation in the four basins were analysed from 1960 to 2100. The correlation between extreme precipitation indices and their relationship with geographical factors was also analysed. The result of the study indicates that: (1) in the historical period, CDD and R99pTOT showed an upward trend, with growth rates of 14.14% and 4.78%, respectively. PRCPTOT showed a downward trend, with a decreasing rate of 9.72%. Other indices showed minimal change. (2) Based on SSP1-2.6, the intensity, frequency, and duration of extreme precipitation changed by approximately 5% at SSP3-7.0 and 10% at SSP5-8.5. The sensitivity to climate change was found to be highest in spring and autumn. The drought risk decreased, while the flood risk increased in spring. The drought risk increased in autumn and winter, and the flood risk increased in the alpine climate area of the plateau in summer. (3) Extreme precipitation index is significantly correlated with PRCPTOT in the future period. Different atmospheric circulation factors significantly affected different extreme precipitation indices of FMB. (4) CDD, CWD, R95pD, R99pD, and PRCPTOT are affected by latitude. On the other hand, RX1day and RX5day are affected by longitude. The extreme precipitation index is significantly correlated with geographical factors, and areas above 3000 m above sea level are more sensitive to climate change.