Search Results (15)

Flash droughts adversely affect agriculture and ecosystems due to their rapid depletion of soil moisture (SM). However, few studies assessed the impacts of flash droughts on crops, especially in the agricultural regions of southern China. In this study, we investigated flash droughts using crop root zone SM in the main agricultural region of southern China. Additionally, solar-induced chlorophyll fluorescence (SIF) served as a vegetation index to explore the crop response to flash droughts. The results reveal that the SIF exhibited an upward trend from 2001 to 2020 in the study area, indicating the enhanced photosynthetic capacity of crops and subsequent yield improvement. Hotspots of flash drought frequency occurred in the eastern areas of both the upper and lower Yangtze River regions, specifically in areas where the most rapid types of flash droughts were particularly prevalent. The average duration of flash droughts in the southern agricultural region was 6–12 pentads, a sufficiently long duration to significantly hinder crop photosynthesis, resulting in negative SIF standardized anomalies. The area affected by flash droughts in the southern agricultural region presented a downward trend during 2001–2020, with flash droughts of the longest duration in the recent decade, specifically in 2019, 2010, and 2013. The response frequency and time of SIF to flash droughts were >80% and <2 pentads, respectively, indicating that crops in the study area have a high sensitivity to flash droughts. In the northern part of the middle Yangtze River region and the southwestern and southeastern parts of the South China region, the mean values of the standardized anomalies of the SIF were lower than −0.5 during flash droughts, suggesting that crops in these areas were severely affected by flash droughts. During the late summer of 2019, the study area experienced a precipitation shortage coupled with high evapotranspiration capacity. This unfavorable combination of meteorological conditions can quickly lead to a substantial depletion of SM, ultimately triggering flash droughts that can be devastating for crops. Our findings can enhance the understanding of the impacts of flash droughts on crops in agricultural regions, as well as provide early warning signals of flash droughts for farmers to make appropriate mitigation strategies. Full article

Moroccan wetlands host up to half a million wintering birds and provide a stopover for tens of thousands of migrants, while they are inhabited by few nesting species. Most of this avifauna prefers to use the large coastal wetlands or reservoirs, while many species are dispersed across hundreds of small inland wetlands of various types. In this study, we monitored the wintering avifauna of 11 wetlands of the Saïss plain and its adjacent Atlas Mountains (north–center of Morocco), during six wintering seasons (2017–2018 to 2022–2023), with the objective of assessing the importance of this region as a waterbird wintering area. Using the richness of the species, we determine the bird population changes during this pentad and between the different types of wetlands (natural, human-made, and natural wetlands). During this study, we recorded 51 species, belonging to 17 families, among which exist four remarkable birds: the endangered Oxyura leucocephala, the vulnerable Aythya ferina and the near-threatened Aythya nyroca and Limosa limosa. Bird diversity is higher in human-made ecosystems than in peri-urban and natural ecosystems, while the populations’ size is similar in urban and non-urban wetlands. With regard to bird conservation, these inland wetlands, mainly the small ones, are threatened by recurrent droughts and various anthropic stressors, which we describe using our observations of the two last decades (2003–2023). The loss of habitat is significant, reaching 348.5 hectares, while the impacts of reduced precipitation and temperature increase are particularly evident in the mountainous natural lakes. Full article

Given the changing climate, understanding the recent variability in large-scale rainfall patterns is a crucial task in order to better understand the underlying hydrological processes that occur within a watershed. This study aims to investigate how rainfall events in western Japan have changed due to climate change and how these changes have affected runoff–turbidity dynamics during the rainy season. To address the research objectives, we analyzed two decades of precipitation records in the Gōno River watershed and examined the associated runoff–turbidity dynamics during floods using turbidity–discharge (T-Q) loops, quantified using an enhanced hysteresis index. Our findings revealed a kind of intense rainfall event occurring every 3 to 4 years. Additionally, spatial pentad analysis showed varying intensities of accumulated precipitation, indicating that extreme rainfall is not confined to a specific spatial zone. Regarding turbidity–discharge behavior, we found that clockwise hysteresis patterns were caused by sediment sources from near-channel areas, while anticlockwise patterns were caused by soil erosion from nearby areas. Another notable finding was that turbidity peaks during floods may represent the earlier (or later) arrival of turbid water from distant upstream sources due to intense precipitation. One of the key challenges in quantifying hysteresis patterns is that there is no agreed-upon definition for how to determine the start and end of a flood event. This can lead to bias in the quantification of these patterns. Full article

Fully understanding the past characteristics of climate and patterns of climate change can contribute to future climate prediction. Tree-ring stable oxygen isotope ratio (δ¹⁸O) is crucial for high-resolution research of past climate changes and their driving mechanisms. A tree-ring δ¹⁸O chronology from 1896 to 2019 was established using Pinus tabulaeformis Carr. from the Yimeng Mountains (YMMs) in the central part of eastern China. We found that precipitation from the 41st pentad (five days) of the previous year to the 40th pentad of the current year (P_41–40) was the main factor influencing the YMMs tree-ring δ¹⁸O change. We then created a transfer function between P_41–40 and tree-ring δ¹⁸O. The reconstructed P_41–40 explained 39% of the variance in the observed precipitation during the common period of 1960–2016. Over the past 124 years, the YMMs experienced 19 dry years and 20 wet years. The spatial correlation results indicate that the reconstructed precipitation could, to some extent, represent the precipitation changes in Shandong Province, and even the central part of eastern China, from the early 20th century to the present. In addition, it was found that the trends in YMMs tree-ring δ¹⁸O were similar at both high frequency and low frequency to those in tree-ring δ¹⁸O series from Mt. Tianmu in eastern China and from Jirisan National Park in southern South Korea. However, the YMMs tree-ring δ¹⁸O was only correlated at low frequency with the tree-ring δ¹⁸O of the Ordos Plateau in northwestern China and that of Nagano and Shiga in central Japan, which are far from the YMMs. The changes in precipitation and tree-ring δ¹⁸O in the YMMs were, to some extent, influenced by the Pacific decadal oscillation. Full article

The term flash drought describes a special category of drought with rapid onset and strong intensity over the course of days or weeks. To characterize the impact of flash droughts on vegetation coverage, this study assessed the influence of soil water deficits on vegetation dynamics in the northeastern South America region by combining time series of vegetation index, rainfall, and soil moisture based on satellite products at a daily time scale. An 18-year analysis, from 2004 to 2022, of the Normalized Difference Vegetation Index (NDVI), Standard Precipitation Index (SPI), and surface soil moisture (SSM) was performed based on three different satellite remote sensing estimates: the spinning enhanced visible and infrared imager (SEVIRI) and the integrated multi-satellite retrievals algorithm (IMERG), and the soil moisture and ocean salinity (SMOS). The results revealed that flash drought events exerted dramatic impacts on terrestrial ecosystems in the study region during the first two decades of the 2000s, with changes in seasonal and regional vegetation dynamics. Further, the fixed-threshold values to characterize flash drought events were suggested as the timing when the water deficit was less than −1.0 units and vegetation index reached the value equal to +0.3 during five consecutive weeks or more, coupled with soil moisture rates below 40% percentile, leading to a strong region-wide drought throughout the entire region. Additionally, the results of linear least squares trend analyses revealed a negative trend in the pentad-SEVIRI radiance for the solar channel 1 within the semiarid ecosystems of the study region (i.e., the Caatinga biome) that was suggested as a reduction in clouds in the 18 years of the study. Developing combined threshold measures of flash drought based on satellite remote sensing may lead to an accurate assessment of flash drought mitigation. Full article

The diurnal variation in precipitation and its evolution are important foundations for understanding the regional impact of climate change and the parameterization of the model. Based on the daily precipitation data set of 23 national meteorological stations during 1970–2019, the spatial and temporal distribution characteristics of precipitation concentration degree (PCD) and precipitation concentration period (PCP) in Gansu province were evaluated on daytime and nocturnal scales. The results show the following: (1) Annual precipitation ranges from 69.1 ± 24.7 mm to 578.3 ± 96.6 mm, mainly (54.1 ± 2.6%) occurring at night, and the spatial distribution of the nocturnal precipitation rate is positively (r = 0.53, p < 0.01) correlated with annual precipitation; the wetting trend (12.7 mm/10 a, p < 0.01) in the past 50 years is obvious, and is mainly dominated by the frequency of precipitation (r = 0.58, p < 0.001), with both performing better during the day. (2) Most PCD is located between 0.55 and 0.75, showing a basic distribution pattern for daytime greater than nocturnal, higher values, and stronger interannual fluctuations in arid areas; the significant decreasing trend (p < 0.05) of PCD is very clear and highly consistent, especially in the high-altitude area, and the increase in precipitation in the dry season and the improvement in precipitation uniformity in the wet season play a key role. (3) PCP often fluctuates slightly around the 39th–41st pentad, but the general rule that daytime values are smaller than night values and the interannual variability is larger in arid areas also requires special attention; PCP has shown a relatively obvious advance trend in a few regions, but this is because the prominent and complex changes in the monthly precipitation distribution pattern have not been fully reflected. Along with continuous humidification, the decrease in PCD and the advance of PCP are likely to be the priority direction of precipitation evolution in the arid region of Northwest China, especially during the day. These findings provide a new perspective for understanding regional climate change. Full article

This study analyzed the main features (onset, demise, and length) of the South American Monsoon System (SAMS) projected in different time slices (2020–2039, 2040–2059, 2060–2079, and 2080–2099) and climate scenarios (SSP2–4.5 and SSP5–8.5). Eight global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) that perform well in representing South America’s historical climate (1995–2014) were initially selected. Thus, the bias correction–statistical downscaling (BCSD) technique, using quantile delta mapping (QDM), was applied in each model to obtain higher-resolution projections than their original grid. The horizontal resolution adopted was 0.5° of latitude × longitude, the same as the Climate Prediction Center precipitation analysis used as a reference dataset in BCSD. The QDM technique improved the monsoon onset west of 60° W and the simulated demise and length in southwestern Amazonia. Raw and BCSD ensembles project an onset delay of approximately three pentads compared to the historical period over almost all regions and a demise delay of two pentads northward 20° S. Additionally, the BCSD ensemble projects a reduced length with statistical significance in most South Atlantic Convergence Zone regions and a delay of three pentads in the demise over the Brazilian Amazon from the second half of the 21st century. Full article

The lack of sufficient precipitation data has been a common problem for water resource planning in many arid and semi-arid regions with sparse and limited weather monitoring networks. Satellite-based precipitation products are often used in these regions to improve data availability. This research presents the first validation study in Syria for Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) estimates using in-situ precipitation data. The validation was performed using accuracy and categorical statistics in the semi-arid Barada Basin, Syria, between 2000 and 2020. Multiple temporal scales (daily, pentad, monthly, seasonally, and annual) were utilized to investigate the accuracy of CHIRPS estimates. The CHIRPS results indicated advantages and disadvantages. The main promising result was achieved at the seasonal scale. Implementing CHIRPS for seasonal drought was proven to be suitable for the Barada Basin. Low bias (PB_winter = 2.1%, PB_wet season = 12.7%), high correlation (r_{wet season} = 0.79), and small error (ME = 4.25 mm/winter) support the implementation of CHIRPS in winter and wet seasons for seasonal drought monitoring. However, it was observed that CHIRPS exhibited poor performance (inland pentads) in reproducing precipitation amounts at finer temporal scales (pentad and daily). Underestimation of precipitation event amounts was evident in all accuracy statistics results, and the magnitude of error was higher with more intense events. CHIRPS results better corresponded in wet months than dry months. Additionally, the results showed that CHIRPS had poor detection skill in drylands; on average, only 20% of all in-situ precipitation events were correctly detected by CHIRPS with no effect of topography found on detection skill performance. This research could be valuable for decision-makers in dryland regions (as well as the Barada Basin) for water resource planning and drought early warning systems using CHIRPS. Full article

In order to focus on pentad-scale precipitation forecasts, we investigated the coupling relationship between 500 hPa geopotential height (Z500) anomalies and precipitation anomalies using the China Meteorological Administration Global Land Surface ReAnalysis Interim (CRA40/Land) gridded precipitation dataset from 1999 to 2018 and the National Centers for Environmental Prediction 1 reanalysis dataset for Z500. We obtained a dynamical–statistical downscaling model (DSDM) on the pentad scale and used the daily Z500 forecast product for sub-seasonal to seasonal forecasts (15–60 days) of the FGOALS-f2 model as the predictor. Our results showed that pentad-scale prediction of precipitation is the key to bridging the current deficiencies in sub-seasonal forecasts. Compared with the FGOALS-f2 model, the pentad DSDM had a higher skill for prediction of precipitation in China at lead times longer than four pentads throughout the year and of two pentads in the summer months. FGOALS-f2 had excellent precipitation predictability at lead times less than three pentads (15 days), so the proposed pentad DSDM could not perform better than FGOALS-f2 in this period. However, at lead times greater than four pentads, the precipitation prediction scores (such as the anomaly correlation coefficient (ACC), the temporal correlation coefficient (TCC) and the mean square skill score (MSSS)) of the pentad DSDM for the whole of China were higher than those of the FGOALS-f2 model. With the rate of increase ranging from 76% to 520%, the mean ACC scores of pentad DSDM were basically greater than 0.04 after a lead time of five pentads, whereas those of the FGOALS-f2 were less than 0.04. An analysis of the Zhengzhou “720” super heavy rainstorm event showed that the pentad DSDM also had better predictability for the distribution of precipitation at lead times of three pentads than the FGOALS-f2 model for the extreme precipitation event. Full article

Based on daily precipitation data from 1960 to 2017 in the rainy season in east China, to a given percentile threshold of one observation station, the time that precipitation spends below threshold is defined as quiet time $\tau$. The probability density functions $\tau$ in different thresholds follow power-law distributions with exponent $\mathsf{\beta }$ of approximately 1.2 in the day, pentad and ten-day period time scales, respectively. The probability density functions $\tau$ in different regions follow the same rules, too. Compared with sandpile model, Γ function describing the collapse behavior can effectively scale the quiet time distribution of precipitation events. These results confirm the assumption that for observation station data and low-resolution precipitation data, even in China, affected by complex weather and climate systems, precipitation is still a real world example of self-organized criticality in synoptic. Moreover, exponent $\beta$ of the probability density function $\tau$, mean quiet time ${\overline{\tau }}_q$ and hazard function $H_q$ of quiet times can give sensitive regions of precipitation events in China. Usual intensity precipitation events (UPEs) easily occur and cluster mainly in the middle Yangtze River basin, east of the Sichuan Province and north of the Gansu Province. Extreme intensity precipitation events (EPEs) more easily occur in northern China in the rainy season. UPEs in the Hubei Province and the Hunan Province are more likely to occur in the future. EPEs in the eastern Sichuan Province, the Guizhou Province, the Guangxi Province and Northeast China are more likely to occur. Full article

This study uses four-year radar-based precipitation organization and reanalysis datasets to study the mechanisms that lead to the abrupt springtime onset of precipitation associated with isolated storms in the Southeast United States (SE US). Although the SE US receives relatively constant precipitation year-round, previous work demonstrated a “hidden” summertime maximum in isolated precipitation features (IPF) whose annual cycle resembles that of monsoon climates in the subtropics. In the SE US, IPF rain abruptly ramps up in May and lasts until sometime between late August and early October. This study suggests that the onset of the IPF season in the SE US is brought about by a combination of slow thermodynamic processes and fast dynamic triggers, as follows. First, in the weeks prior to IPF onset, a gradual seasonal build-up of convective available potential energy (CAPE) occurs in the Gulf of Mexico. Then, in one-to-two pentads prior to onset, the upper-tropospheric jet stream shifts northward, favoring the presence of slow-moving frontal systems in the SE US. This poleward shift in the jet stream location in turn allows the establishment of the North Atlantic subtropical high western ridge over the SE US which, with associated poleward transport of high CAPE air from the Gulf of Mexico, leads to the establishment of the warm-season regime of IPF precipitation in the SE US. Full article

Precipitation serves as a crucial factor in the study of hydrometeorology, ecology, and the atmosphere. Gridded precipitation data are available from a multitude of sources including precipitation retrieved by satellites, radar, the output of numerical weather prediction models, and extrapolation by ground rain gauge data. Evaluating different types of products in ungauged regions with complex terrain will not only help researchers in applying scientific data, but also provide useful information that can be used to improve gridded precipitation products. The present study aims to evaluate comprehensively 12 precipitation datasets made by raw retrieved products, blended with rain gauge data, and blended multiple source datasets in multi-temporal scales in order to develop a suitable method for creating gridded precipitation data in regions with snow-dominated regions with complex terrain. The results show that the Multi-Source Weighted-Ensemble Precipitation (MSWEP), Global Satellite Mapping of Precipitation with Gauge Adjusted (GSMaP_GAUGE), Tropical Rainfall Measuring Mission (TRMM_3B42), Climate Prediction Center Morphing Technique blended with Chinese observations (CMORPH_SUN), and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) can represent the spatial pattern of precipitation in arid/semi-arid and humid/semi-humid areas of the Qinghai-Tibet Plateau on a climatological spatial pattern. On interannual, seasonal, and monthly scales, the TRMM_3B42, GSMaP_GAUGE, CMORPH_SUN, and MSWEP outperformed the other products. In general, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN_CCS) has poor performance in basins of the Qinghai-Tibet Plateau. Most products overestimated the extreme indices of the 99^th percentile of precipitation (R₉₉), the maximal of daily precipitation in a year (Rmax), and the maximal of pentad accumulation of precipitation in a year (R_5dmax). They were underestimated by the extreme index of the total number of days with daily precipitation less than 1 mm (dry day, DD). Compared to products blended with rain gauge data only, MSWEP blended with more data sources, and outperformed the other products. Therefore, multi-sources of blended precipitation should be the hotspot of regional and global precipitation research in the future. Full article

The Haihe River basin of North China is characterized by extremely low per capita water resources and a consistently long-term decreasing trend of precipitation and runoff over the last few decades. This study analyzes the climatological features of rainy season (May–September) precipitation in the Haihe River basin and its branch systems based on a high-density hourly observational dataset during 2007–2017. We show that there are two high-rainfall zones in the basin, with one along the south of the Yanshan Mountains to Taihang Mountains and another along the Tuma River in the south. Rainstorm centers exist amidst the two zones. July generally sees the highest precipitation, followed by August, and May has the lowest precipitation. The major flood season is reached between the third pentad of July and the fourth pentad of August. The precipitation is high at night but low in the daytime. In the pre-flood season before early July, rainfalls mostly arrive at 16:00–21:00 h. After entering the major flood season, the diurnal precipitation has two peaks, one at 17:00–22:00 h and the other at 0:00–7:00 h. In the post-flood season after mid-August, the most rain occurs at night, with the peak appearing at 0:00–8:00 h. The short-duration precipitation is mainly distributed in the mountainous areas, and the long-duration precipitation that contributes most to seasonal rainfalls appears in the plain areas, and the continuous precipitation mostly occurs in the windward slopes of the Taihang Mountains and the Yanshan Mountains. In addition, urbanization process around large city stations may have affected the rainy season precipitation to a certain extent in the Haihe River basin, with large and medium city stations experiencing around 10% higher precipitation than small city stations. However, this issue needs to be investigated exclusively. Full article

Rapidly developing droughts, including flash droughts, have frequently occurred throughout East Asia in recent years, causing significant damage to agricultural ecosystems. Although many drought monitoring and warning systems have been developed in recent decades, the short-term prediction of droughts (within 10 days) is still challenging. This study has developed drought prediction models for a short-period of time (one pentad) using remote-sensing data and climate variability indices over East Asia (20°–50°N, 90°–150°E) through random forest machine learning. Satellite-based drought indices were calculated using the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture, Tropical Rainfall Measuring Mission (TRMM) precipitation, Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST), and normalized difference vegetation index (NDVI). The real-time multivariate (RMM) Madden–Julian oscillation (MJO) indices were used because the MJO is a short timescale climate variability and has important implications for droughts in East Asia. The validation results show that those drought prediction models with the MJO variables (r ~ 0.7 on average) outperformed the original models without the MJO variables (r ~ 0.4 on average). The predicted drought index maps showed similar spatial distribution to actual drought index maps. In particular, the MJO-based models captured sudden changes in drought conditions well, from normal/wet to dry or dry to normal/wet. Since the developed models can produce drought prediction maps at high resolution (5 km) for a very short timescale (one pentad), they are expected to provide decision makers with more accurate information on rapidly changing drought conditions. Full article

Alpine precipitation is an important component of the mountain hydrological cycle and may also be a determinant of water resources in inland river basins. In this study, based on field observation data of the upper Shule River and daily precipitation records of the Tuole weather station during 2009–2015, temporal distribution characteristics of alpine precipitation and their vertical differentiation were evaluated mainly using percentages of precipitation anomalies (Pa), coefficient of variation (Cv), precipitation concentration degree (PCD) and concentration period (PCP). The results indicated that the inter-annual variability of annual precipitation was generally small, with a Pa that was only somewhat larger in low altitude zones for individual years; the inter-annual fluctuation of monthly precipitation increased noticeably, but the Cv and precipitation can be described as a power function. Annual distribution was basically consistent; more than 85.6% of precipitation was concentrated during the period from May to September; PCD ranged between 0.71 and 0.83 while the PCP was located within the 37th–41st pentads. Diurnal variation of precipitation was defined, mainly occurring from 1500 to 0100 Local Standard Time, and displayed a vertical change that was dominated by precipitation intensity or precipitation frequency. The temporal distribution of alpine precipitation has a noticeable vertical differentiation, and this is likely to originate from the diversity of precipitation mechanisms in mountainous terrain areas. Full article