Regional Rainfall Research Articles

Statistical Modelling of the Annual Rainfall Pattern in Guanacaste, Costa Rica

Rainfall in Guanacaste, Costa Rica, has marked wet/dry phases: the rainy season is punctuated by a short midsummer drought, and the dry season frequently has months of no rain. In this region, spring and summer rainfall peaks are important for local rain-fed agriculture and annual total for groundwater recharge and hydroelectricity production. We propose a novel model of rainfall in this region, the double-Gaussian model, which uses monthly total rainfall data collected from 1980 to 2020 from two meteorological observation stations. Our model provides an intuitive way of describing the seasonality of rainfall, the inter-annual variability of the cycle, and variability due to the monthly Oceanic Niño Index, ONI. We also consider two alternative models, a regression model with ARMA errors and a Tweedie model, as a means of assessing the robustness of our conclusions to violations of the assumptions of the double-Gaussian model. We found that the data provide strong evidence of an increase/decrease in rainfall in both temporal maxima during La Niña/El Niño (negative/positive ONI) conditions but no evidence of a decade-scale trend after accounting for ONI effects. Finally, we investigated the problem of forecasting future rainfall based on our three models. We found that when ONI is incorporated as a predictor variable, our models can produce substantial gains in prediction accuracy of spring, summer, and annual totals over naive methods based on monthly sample means or medians.

The characteristics and evolution process of presummer intense regional rainfall over the Pearl River Delta metropolitan region

AbstractThe presummer intense regional rainfall events (RREs) over the Pearl River Delta (PRD) metropolitan region have been defined using rainy stations, maximum instantaneous regional rainfall coefficient (RRCt) and maximum rainfall intensity based on the rain gauge data from 2008 to 2017. Most of intense RREs with the maximum rainfall intensity about 20–60 mm·h−1 and the lifetime shorter than 24 h have the primary rainfall peak from noon to afternoon. Based on the rainfall pattern at 3 h prior to the events start, the intense RREs can be classified into two groups that one is southeastward propagation mode originating from the northwestern mountains of PRD and another is coastal mode from South China Sea (SCS). During the premonsoon‐onset period, the first type of RREs is the main mode causing the heavy rain in the cities of the inland region owing to the anomalous cold air from north confronting the wet and warm air from south with the increased southwesterly winds resulting in the strengthening frontal zone and moisture convergence. After the summer monsoon onset, the main rainfall pattern changes to the coastal mode having the significant impact on the coastal cities. The obvious anomalous cyclonic circulation related with the increased moisture convergence in the coastal regions providing the favourable conditions of the convection initiation and development. The study of the characteristics and evolution process of preceding intense RREs can improve the forecasting skills and reduce the risk of urban inundation.

Monsoon Depression Amplification by Horizontal Shear and Humidity Gradients: A Shallow Water Perspective

Abstract Transient, synoptic-scale vortices produce a large fraction of total rainfall in most monsoon regions and are often associated with extreme precipitation. However, the mechanism of their amplification remains a topic of active research. For monsoon depressions, which are the most prominent synoptic-scale vortex in the Asian–Australian monsoon, recent work has suggested that meridional gradients in zonal wind in the vortex environment may produce growth through barotropic instability, while meridional gradients in environmental humidity have also been proposed to cause amplification through coupling with precipitating convection. Here, a two-dimensional shallow water model on a sphere with parameterized precipitation is used to examine the relative role played by these two environmental gradients. By systematically varying the meridional moisture gradient and meridional wind shear for both weak, quasi-linear waves and finite-amplitude isolated vortices, we show that rotational winds in the initial vortex are amplified most strongly by meridional shear of the environmental zonal wind, while vortex precipitation rates are most sensitive to environmental moisture gradients. The growth rate in the presence of both gradients is less than the sum of growth rates in the presence of isolated gradients, as the phase relation between moisture and vorticity anomalies becomes distorted with increasing shear. These results suggest that background meridional gradients in both zonal wind and environmental humidity can contribute to the amplification of vortices to monsoon depression strength, but with some degree of decoupling of the dry rotational flow and the moist convection.

First report of Colletotrichum siamense causing leaf spot on Manglietia decidua in the world.

Manglietia decidua Q. Y. Zheng is a deciduous broad-leaved plant and native to Jiangxi province, China. It is cultivated for its timber and urban landscaping (Xiong et al., 2014). In September 2019, a new foliar disease was observed on approx. 25% of 121 M. decidua trees in Jiangxi Agricultural University (N28°45'56″, E115°50'21″), Nanchang city, Jiangxi Province, China. The disease site belongs to the subtropical monsoon humid climate, with rainfall (1,600-1,700 mm) and red soil region. Initially, infection appeared on the leaf margins or tips as water-soaked, irregular lesions, then expanded to the center, developed into large black-brown, irregular necrotic lesions. Finally, the lesions fall off the leaves. To identify the pathogen, 15 diseased leaves were collected from 5 trees (3 leaves per tree) randomly. Small pieces (5 × 5 mm) cut from the lesion margins were surfaced sterilized (70% ethanol for 30 s, 3% NaOCl for 1 min, rinsed 3 times with sterile water), and placed on potato dextrose agar (PDA) at 25 °C. Among the isolated fungi, Colletotrichum-like colonies were about 91%, and 18 monoconidial isolates were obtained. Isolates HML-1, HML-4, and HML-7 were selected and preserved for further studies. Colonies on PDA were white, cottony, and grayish-white on the reverse side. Setae absent. Acervuli were brown, circular. Conidiophores were clear, septate, non-branching or branching at the base, conidiogenous cells were enteroblastic, phialidic, colorless, cylindrical, ampulliform. Conidia were elliptical, single-celled, straight, hyaline, and measured 13.3-17.9 × 4.3-5.7 µm (14.8 ± 1.2 × 4.8 ± 0.4 µm, n = 100). Appressoria were oval to irregular, dark brown, and ranged from 5.3-9.1 × 4.4-6.3 µm (7.2 ± 0.3 × 5.1 ± 0.2 µm, n=100). Morphological characteristics matched the description of Colletotrichum gloeosporioides sensu lato (Weir et al. 2012). The internal transcribed spacer regions (ITS), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), actin (ACT), chitin synthase (CHS-1), calmodulin (CAL), and beta-tubulin 2 (TUB2) were sequenced (Weir et al., 2012), and deposited in GenBank (ITS: OL757565-OL757567; ACT: OL627398-OL627400; CHS-1: OL757358-OL757360; GAPDH: OL757361-OL757363; CAL: OL757355-OL757357; TUB2: OL757364-OL757366). Six loci were concatenated, and the aligned sequences (2056 bp) were 99.9%, 99.8% homologous to C. siamense ICMP 18574 and ex-type ICMP18578, respectively. In the maximum-likelihood phylogenetic tree, the highest log likehihood was -9259.74, and 3 isolates were in the C. siamense clade. Based on the phylogeny and morphology, 3 isolates were identified as C. siamense. The pathogenicity of 3 isolates was tested on 12 M. decidua plants (variety: Yi lin ke) grown in the field. Healthy leaves were wounded slightly with a needle (Φ=0.5 mm) and inoculated with 10 µL of spore suspension (106 conidia/mL). Controls were treated with ddH2O (Si et al. 2021). All the treated leaves were covered with plastic bags to keep a high-humidity environment for 2 days. The experiments were repeated twice. Within 9 days, all the inoculated points showed similar symptoms to those observed in the field, whereas controls were asymptomatic. The same isolate was re-isolated from the lesions, whereas no fungus was isolated from control leaves. Manglietia decidua is an ancient and endangered plant, threatened with southern blight (Sclerotium rolfsii) (Yi et al. 2021a), root rot (Calonectria ilicicola) (Yi et al. 2021b). This is the first report of the newly emerging disease caused by C. siamense in the world. The potential threat should be evaluated for conservation in the future. This study provided crucial information for epidemiological studies and appropriate control strategies.

Climatology Definition of the Myanmar Southwest Monsoon (MSwM): Change Point Index (CPI)

Myanmar’s climate is heavily influenced by its geographic location and relief. Located between the Indian summer monsoon (ISM) and the East Asian summer monsoon (EASM), Myanmar’s climate is distinguished by the alternation of seasons known as the monsoon. The north-south direction of peaks and valleys creates a pattern of alternate zones of heavy and scanty precipitation during both the northeast and southwest monsoons. The majority of the rainfall has come from Myanmar’s southwest monsoon (MSwM), which is Myanmar’s rainy season (summer in global terms, June–September). This study explained both threshold-based and nonthreshold-based objective definitions of the onset and withdrawal of large-scale MSwM. The seasonal transitions in MSwM circulation and precipitation are convincingly represented by the new index, which is based on change point detection of the atmospheric moisture flow converging in the MSwM region (10–28 N, 92–102 E). A transition in vertically integrated moisture transport (VIMT), the reversal of surface winds, and an increase in precipitation may also be considered when defining MSwM onset objectively. We also define a change point of the MSwM (CPI) index for MSwM onset and withdrawal dates. The climatological mean onset of MSwM is day 135 (May 14), withdrawal is day 278 (October 4), and the total season length is 144 days. We are investigating spatial patterns of rainfall progression at and after the start of the monsoon, rather than transitions within a single region of the MSwM. The local southwest monsoon duration is well correlated with the CPI duration on interannual timescales, particularly in the peak rainfall regions, with a delay (advance) in large-scale onset or withdrawal associated with a delay (advance) of onset or withdrawal by local index. Hence, the next phase of this research is to study the maintenance and break of the monsoon to understand the underlying physical processes governing the monsoon circulation. The results of this study provide a possibility to reconstruct Myanmar’s monsoon climate dynamics, and the findings of this study can help unravel many remaining questions regarding the greater Asian monsoon system’s variability.

A deep and wide neural network to predict summer monsoon rainfall using time series data

SummaryThe importance of monsoon rainfall cannot be ignored as it affects round‐the‐year activities ranging from agricultural to industrial. Due to the nonlinear and dynamic nature of monsoon rainfall, its accurate forecast becomes a challenging task. In this paper, we propose a novel deep and wide neural network model to predict summer monsoon rainfall using historical time‐series data of 118 years. We have considered Rajasthan as our area of study, which is the largest state of India with varying atmospheric regions. Two different types of datasets are used: gridded rainfall dataset from the Indian Meteorological Department (IMD) and station rainfall data from Water Resources Department (WRD). Results obtained on both the datasets demonstrate that a single model works well in efficiently predicting summer monsoon rainfall in different geographical regions of Rajasthan, ranging from plains and plateaus to deserts and hills. We compare the results with various advanced deep learning algorithms such as 1‐dimensional convolutional neural network, long short term memory, and multilayer perceptron. The comparison results show that the proposed method clearly outperforms these algorithms in terms of its forecasting ability, which is evaluated using root mean square error and mean absolute error.

The Creep-Sliding Deformation Mechanism of the Jiaju Ancient Landslide in the Upstream of Dadu River, Tibetan Plateau, China

The Jiaju ancient landslide is a giant landslide located upstream of the Dadu River, eastern Tibetan Plateau, with a volume of approx. 7.04 × 108 m3. The Jiaju ancient landslide is complex and comprises five secondary sliding bodies, e.g., the Jiaju landslide (H01), Niexiaping landslide (H02), Xiaobawang landslide (H03), Niela landslide (H04), and Mt.-peak landslide (H05). Affected by regional neotectonic movement, heavy rainfall, river erosion, and lithology, the secondary sliding bodies of the Jiaju ancient landslide are undergoing significantly different creep-sliding deformation, which will cause great damage to villages, roads, and rivers around the sliding bodies. Combined with the SBAS-InSAR method, Sentinel-1A data from June 2018 to August 2021, remote sensing and field surveys, this study obtained the Jiaju ancient landslide deformation characteristics and deformation rate in the line-of-sight direction (VLOS), slope (VSlope), and vertical (VVertical). It is concluded that the maximum deformation rate of the Jiaju ancient landslide is significant. The maximum of VLOS, VSlope, and VVertical are −179 mm/a, −211 mm/a, and −67 mm/a, respectively. The Niela landslide (H04), Jiaju landslide (H01), and Mt.-peak landslide (H05) are very large and suffer strong deformation. Among these, the Niela landslide (H04) is in the accelerative deformation stage and at the Warn warning level, and the Jiaju landslide (H01) is in the creep deformation and attention warning level, especially heavy rainfall, which will accelerate landslide deformation and trigger reactivation. Because the geological structure is very complex for the Jiaju ancient landslide and strong neotectonic movement, under heavy rainfall, the secondary landslide creep-sliding rate of the Jiaju ancient landslide is easily accelerated and finally slides in part or as a whole, resulting in river blocking. It is suggested to strengthen the landslide deformation monitoring of the Niela landslide and Jiaju landslide and provide disaster mitigation and prevention support to the government and residents along the Dadu River watershed.

Summer Onset in Northern East Asia: Feature, Mechanism and Variability

Summer in the East Asian monsoon region is characterized by heavy rainfall and high temperature. Its onset, depicted by monsoon rainfall and/or airflow as well as surface air temperature, has been well documented. However, the onset of summer season is rarely addressed in northern East Asia (NEA) around the northern edge of the East Asian summer monsoon. This study investigates the feature, mechanism, and variability of the summer onset in NEA based on the ERA-5 reanalysis dataset for 1979–2020. Results show that, in climatology, the onset of summer in NEA occurs in pentad 31 when the spring-to-summer warming process is decelerated at the highest rate. The change in the warming rate is mainly attributed to a decrease in the diabatic heat, mostly surface sensible heat, and temperature advection plays a small role. After the onset of summer, regional low-level northwesterly winds are weakened, and a local NEA cyclonic low forms. The latter, coupled with monsoon southerly airflow to the south, advects more moisture into NEA and increases regional rainfall. Furthermore, a temperature threshold of 17 °C, the climatological regional mean surface air temperature in pentad 31, was proposed to depict summer onset in NEA. Based on the temperature threshold, the year-to-year variability of summer onset timing in NEA is revealed, ranging from pentad 29 (late May) to 34 (middle June), with the standard deviation of 1.2 pentads. It advanced by 0.6 pentads, on average, after the late 1990s. This study provides a new method to objectively quantify the timing of summer onset in East Asia, which is thermodynamically explainable and may help us to depict and monitor summer onset in different latitudes and topography.

Application of a Regionalization Method for Estimating Flash Floods: Cuautepec Basin, Mexico

A rainfall regionalization method based on variation coefficient was applied with a variant in the construction of flash flood hyetographs with several return periods using the flash flood shape of the historical event that occurred in September 2021 in the Tlalnepantla River basin, Mexico, that caused severe damage to population and its infrastructure in a few hours. The historical flash flood was simulated with a semi-distributed model in the free software HEC-HMS in order to obtain the outflow hydrograph, and the flood plains were obtained with Iber and Hec-Ras 2d software that simulate free surface flow with a two-dimensional analysis. With photographs of the site, it was possible to locate traces of water that were contrasted with they calculated depths; they were concordant. Synthetic design storms were then simulated to estimate their potential consequences on the site.

Object-based evaluation of rainfall forecasts over eastern China by eight cumulus parameterization schemes in the WRF model

Traditional pointwise verification is not fully accurate for the evaluation of rainfall forecasts due to the double-penalty problem. An alternative object-based metric, Method for Object-based Diagnostic Evaluation (MODE), was used in this study to evaluate the rainfall simulation performance of eight cumulus parameterization (CP) schemes in the Weather Research and Forecasting model. The average rainfall from May to August (MJJA) over eastern China from 2009 to 2018 and the sub-seasonal evolution of rainfall systems were mainly verified. The results showed that the heavy rainfall objects simulated by KFCuP, New Tiedtke and KSAS schemes are the closest to the observations over South China, Yangtze River Basin and North China, respectively. MODE could highlight the advantages of these schemes in the simulation of rainband physical attributes, such as centroid position, orientation, rainfall area, etc. At the sub-seasonal scale, KFCuP had the highest skill score for mimicking the observed heavy rainfall objects. To explore the reasons for the differences in rainfall simulations, the evaporation, water vapour inflow and precipitation efficiency were calculated for each scheme. It was found that members with higher precipitation generally corresponded to larger water vapour inflow and precipitation efficiency, and the water vapour inflow mainly came from the southern boundary. Further analysis found that there existed a significant positive correlation between the meridional wind and the water vapour inflow on southern boundary, which indicated that the meridional wind was an important factor affecting the regional rainfall simulation.

Secular trend in water discharge transport in the Lower Mekong River-delta: Effects of multiple anthropogenic stressors, rainfall, and tropical cyclones

The Mekong River is one of the world's most important continental rivers, and provides invaluable water resources for the survival and social development of nearly 70 million inhabitants of Southeast Asia. However, little work has been carried out on the multiforcing-induced hydrological behavior of the Lower Mekong River-delta (LMR) over the past 100 years. Here, the secular variations in water discharge were analyzed for seven gauging stations along the main stream of the LMR from the 1920s-2019, to identify the riverine hydrological mechanisms under different dynamic conditions. The results show that the water discharge delivered by the LMR to the delta decreased on both 50-year and centennial scales. Meanwhile, the daily water discharge of the LMR-delta has become more evenly distributed intra-annually, leading to “no flood in the flood season, no drought in the dry season” in this reach. While regional rainfall dominates the long-term variations in the water discharge in the LMR, episodic tropical cyclones can induce a gradual increase with enlarged spatial divergences in water discharge from the mountainous region to the delta by bringing heavy rainfall. Moreover, although the operation of the mega dams in the Upper Mekong Basin has significantly influenced the distribution of the downstream water discharge in the dry season, minor impacts can also be found in the wet season. The water consumption for irrigation was increased from the upstream to the downstream basin, which may contribute to the severe reduction in the downstream water discharge, even though typhoons induced much more runoff along the downstream reach. Considering future climate change in Southeast Asia with potential upward trends in anthropogenic stressors, it can be expected that the water discharge of the LMR-delta could worsen, and urgent countermeasures that address water resource management should be strongly considered by decision-makers in the affected countries of the Mekong River-delta.

Probable maximum precipitation analysis of high rainfall regions in India

Uttarakhand, Maharashtra, Assam & Meghalaya are the potential areas to study the precipitation, perform trend analysis and calculate the probable maximum precipitation. Probable Maximum Precipitation (PMP) has virtually zero risk of being exceeded for a given catchment area over a certain duration of time. The present work applies Hershfield Method to determine the PMP for rainfall data for the high rainfall regions of Uttarakhand, Maharashtra, Assam & Meghalaya (Assam and Meghalaya are considered as one region). Gumbel method, which is an extreme value distribution function is used to obtain the extreme value (EV) of precipitation. Further, the obtained PMP and EV values are compared with high rainfall months of La Niña years. Observation of the results showed that the obtained values from Hershfield Method are greater than the La Niña years precipitation values that have been observed till 2017, thus validating the obtained results. The outcomes from Probable Maximum Precipitation (PMP) works give insights into the extreme rainfall that can ever happen in a given catchment. The result obtained serves as indispensable input data for designing structures like dams, reservoirs, spillways, flood protection walls, sluice gates, weirs, etc. The design life of hydraulic structures is worked out using Probable Maximum Precipitation (PMF). The adopted technique and results of this study can be directly used as a design parameter for design as well as for water resources management.

Lagged response of summer precipitation to solar activity in the mid-lower reaches of the Yangtze River

In the context of more frequent extreme precipitation worldwide, the Sun’s influence on global or regional rainfall patterns has attracted much attention. Due to its vital importance to Chinese industrial and agricultural production, the precipitation property in the mid-lower reaches of the Yangtze River (MLRYR) remains a hot issue. Although previous works have implied the plausible influence of solar activity on precipitation in the mid-lower reaches of the Yangtze River, the time-lagged effect is still an open question. In this paper, we adopt the China-Z index (CZI) to represent the original precipitation data, which is proposed to monitor moisture conditions over China and is more sensitive to solar activity. We explore the lagged correlations between summer precipitation in the mid-lower reaches of the Yangtze River and solar activity. The China-Z index in June-July is negatively correlated with the sunspot number in July of the preceding year, giving a time lag of 11 months. Based on the composite analysis, we suggest that solar activity possibly modulates the precipitation by influencing the local moisture and its vertical movement through the sea-land thermal contrast and the associated East Asian summer monsoon on a much larger scale.

Large‐scale forcing over the homogeneous regions of summer rainfall anomalies in southern Africa

AbstractFor the study region (southern Africa), regional and remote large‐scale climate forcing play vital roles in the seasonal rainfall variability. Thus, uncovering the nature of the relationship between large‐scale circulations and homogeneous regions of rainfall anomalies will enhance the predictability of seasonal rainfall at specific domains in southern Africa. Considering both land and adjacent oceans in southern Africa, six austral summer homogeneous regions of rainfall anomalies were classified using the rotated principal component analysis. The analysis of the physical processes associated with the modulation of the distinct rainfall variability patterns reveals that generally, regional variations in cyclonic/anticyclonic circulations and convergence/divergence in the adjacent oceans (and landmasses) modulate the regional convergence of moisture fluxes in southern Africa. Some classified rainfall variability patterns feature homogeneous landmasses that are contiguous with the adjacent ocean, revealing land and adjacent oceans that respond coherently to the large‐scale circulation anomalies associated with the time development of the rainfall variability pattern. Further, remote climate drivers were found to be distinctively related to the regionalized rainfall anomalies, implying that the respective homogeneous rainfall regions respond differently to the large‐scale forcing induced by the (remote) climate drivers over southern Africa. Specifically, among the climate drivers that influence the hydroclimate of southern Africa, variations in the Southern Annular Mode (SAM) and the El Niño Southern Oscillation are relatively more associated with regionalized summer rainfall anomalies in southern Africa. Above‐average Nino 3.4 index (i.e., El Niño) negatively correlates with regionalized summer rainfall anomalies over large parts of southern Africa. The positive phase of the SAM positively correlates with rainfall anomaly in the homogeneous summer rainfall region comprising the subtropical parts of southern Africa and the homogeneous summer rainfall region comprising the western equatorial parts of the study region.

Multiyear La Niña Events and Multiseason Drought in the Horn of Africa

Abstract One of the primary sources of predictability for seasonal hydroclimate forecasts are sea surface temperatures (SSTs) in the tropical Pacific, including El Niño–Southern Oscillation. Multiyear La Niña events in particular may be both predictable at long lead times and favor drought in the bimodal rainfall regions of East Africa. However, SST patterns in the tropical Pacific and adjacent ocean basins often differ substantially between first- and second-year La Niñas, which can change how these events affect regional climate. Here, we demonstrate that multiyear La Niña events favor drought in the Horn of Africa in three consecutive seasons [October–December (OND), March–May (MAM), OND]. But they do not tend to increase the probability of a fourth season of drought owing to the sea surface temperatures and associated atmospheric teleconnections in the MAM long rains season following second-year La Niña events. First-year La Niñas tend to have both greater subsidence over the Horn of Africa, associated with warmer waters in the west Pacific that enhance the Walker circulation, and greater cross-continental moisture transport, associated with a warm tropical Atlantic, as compared to second-year La Niñas. Both the increased subsidence and enhanced cross-continental moisture transport favors drought in the Horn of Africa. Our results provide a physical understanding of the sources and limitations of predictability for using multiyear La Niña forecasts to predict drought in the Horn of Africa.

桢楠幼苗适应喀斯特岩溶裂隙生境及降雨时间格局变化的方式

PDF HTML阅读 XML下载 导出引用 引用提醒 桢楠幼苗适应喀斯特岩溶裂隙生境及降雨时间格局变化的方式 DOI: 10.5846/stxb202112183590 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 重庆市自然科学基金面上项目（cstc2020jcyj-msxmX0244）；中央高校基本科研业务费专项（XDJK2020B037）；国家自然科学基金项目（31500399） Phoebe zhennan S. Lee seedlings adjust the biomass allocation and root distribution to adapt to the karst fissure habitat and rainfall temporal pattern Author: Affiliation: Fund Project: General Project of Chongqing Natural Science Foundation(cstc2020jcyj-msxmX0244);Special Funds for Fundamental Scientific Research Operation of Central Universities(XDJK2020B037);National Natural Science Foundation of China(31500399) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:喀斯特生态系统是全球陆地生态系统的重要组成部分，生态环境极为脆弱。由于碳酸盐岩长期强烈的化学溶蚀作用，其基本特征体现为地表土壤和地下岩溶裂隙及洞穴的二元结构。近年来，在全球气候变化下，我国西南地区降雨格局呈现降雨频次减少且单次降雨量增加的趋势。因此，岩溶裂隙和区域降雨时间格局改变将对喀斯特地区的植物生长产生重要影响。通过模拟不同岩溶裂隙生境（S0：24 cm土壤；S1/2：12 cm土壤层+12 cm裂隙层；S3/4：6 cm土壤层+18 cm裂隙层）和不同降雨时间格局（I2d：2 d降雨间隔；I19d：19 d降雨间隔），探究二年生桢楠（Phoebe zhennan S.Lee）幼苗是否通过生物量分配及根系分布的调整来适应变化环境。结果显示：（1）短时间降雨格局下，相比全土生境，少量岩溶裂隙存在并不影响桢楠幼苗生物量的积累，然而随着岩溶裂隙层进一步增厚和降雨时间间隔延长，桢楠降低了总生物量，减少了茎且增大了根和叶的生物量分配。（2）桢楠幼苗的根系垂直分布随着深度增加而下降，且无论在何种降雨时间格局下，两种岩溶裂隙生境下桢楠均增加了岩溶裂隙之上土壤层的根系生物量分配比例。研究表明：赋存有土壤的岩溶裂隙能成为植物幼苗赖以生存的生境，但这种提供生境的能力随岩溶裂隙层增厚以及降雨时间间隔延长而减弱。桢楠幼苗以牺牲对茎生物量的分配投资为代价，提高对根系或者叶片的生物量投资，同时增大界面土层中的根系分布，来保证最大化地利用有限的土壤资源，从而适应喀斯特的岩溶裂隙（及干旱）生境。 Abstract:Karst is one of the most important fragile ecological environments in globally terrestrial ecosystems. It is basically characterized by the dual structure of surface soil and underground karst fissures and caves, due to the long-term strong chemical dissolution of carbonate rocks. In recent years, under global climate change, the rainfall pattern in southwestern China has shown a trend of decreasing rainfall frequency and greater sub-rainfall. The karst region in southwestern China, which belongs to the subtropical monsoon climate, often suffers from more obvious alternating wet and dry conditions. The underground karst fissures and variation in the temporal pattern of regional rainfall will have a significant impact on plant growth and development in this region. In this study, in order to explore whether the seedlings of Phoebe zhennan S. Lee adjust biomass allocation and root distribution to adapt to the changing environment, we simulated different karst fissure habitats (S0:24 cm soil; S1/2:12 cm soil layer+12 cm karst fractured layer; S3/4:6 cm soil layer+18 cm karst fractured layer) and different rainfall temporal patterns (I2d:rainfall interval of 2 days; I19d:rainfall interval of 19 days), and checked the plants biomass accumulation and allocation, root vertical distribution. The results showed that:(1) under the short-term rainfall pattern, compared with the whole soil habitat, the habitat with a small proportion of karst fissures did not affect the biomass accumulation of P. zhennan seedlings. With the thickening of karst fractured layer and the extension of the rainfall interval, P. zhennan reduced the total biomass, allocating less biomass to stems and more to roots and leaves. (2) The vertical distribution of root system of P. zhennan seedlings decreased with the deepen of soil layer, but increased the root biomass allocation ratio in the soil layer above the karst fissures, regardless of the rainfall temporal pattern. The results show that the fissures hosted soil can be a certain habitat for plants. However, with the thickening of fractured layer and extension of the rainfall interval, the fissures weaken the ability of the habitat. P. zhennan seedlings increase investment to root and leaf at the expense of stem biomass, and increase the root distribution in the interface soil layer above the fissures to ensure the maximum use of limited soil resources so as to adapt to the fissure (and arid) habitat in karst. 参考文献 相似文献 引证文献

Error Generation Characteristics of the Areal Rainfall Estimation Interpolation Method Using Rainfall Radar Data

This study evaluated the effects of watershed area, rain gauge density, rain gauge distribution, and rainfall movement direction on regional average rainfall estimates by comparing the spatial interpolation results. To this end, the interpolated watershed mean using radar grid data from the Ministry of Environment’s TM rain gauge point was compared with the watershed mean of all radar grids within the watershed. Results showed that eight or more rain gauges are required for accurate area average rainfall estimates in small watersheds of less than 500 km<sup>2</sup>. In addition, the inverse distance weighting method tends to underestimate area average rainfall, whereas the Thiessen method tends to overestimate it. Furthermore, as linearity of rain gauge distribution increased, the number of rainfall events with outliers increased. In particular, when the correlation coefficient exceeded 0.7, outliers appeared to rapidly increase, sharply increasing the possibility of overestimating or underestimating area average rainfall. This study clearly showed that there are limits to area-averaged rainfall estimates when using rain gauge rainfall data in small watersheds.

Regional non-stationary future extreme rainfall under changing climate over Asian Monsoon Region

An increase in the Intensity-Duration-Frequency (IDF) of rainfall extremes questions the assumption of stationarity in the design and planning of water infrastructures under changing climate. To address this, non-stationary-based approaches are widely used for assessing the extremes over time. However, the trends associated with future extreme rainfall would differ from that of the historical dataset. Therefore, the main objective of this study is to develop a non-stationary modelling approach to generate future regional IDF curves by incorporating the trend in the rainfall over Asian Monsoon Region (AMR). Daily rainfall data from (i) APHRODITE and (ii) baseline period (1951–2005) and future projections (2020−2100) simulated from 27 GCMs are used in this study. The proposed framework includes (i) selection of GCM models, (ii) Stationary (S) and Non-Stationary (NS) Generalized Extreme Value Distribution (GEVD) Models, (iii) delineation of extreme precipitation zones, (iv) performance evaluation of zone-wise models, and (v) estimation of future regional IDF curves for near-future (2020–2060), and far-future (2061–2100). Results show that the eight models and their corresponding GCM covariates cover around 90% of grids across the AMR compared to S-GEVD models among the 27 GCMs. Six extreme precipitation zones were obtained, and fitted regional models could mimic the individual station models. The change in extreme rainfall intensity for the future climate is higher for zone-1 (low extreme rainfall region), with an increase of 87–98% across different emission scenarios using the non-stationary models, whereas for zone-6 (higher extreme rainfall region) has a 60–68% increase from its stationary counterparts. For high and low emission scenarios, intensity increases up to 98% and 87% respectively for a lower return period (5-year), and 65% and 58% for a higher return period (100-year) by the end of the century.

Inter-annual and intra-annual tree-ring oxygen isotope signals in response to monsoon rainfall in northwestern Thailand

We present a new teak ( Tectona grandis L.f.) tree-ring stable oxygen isotope (δ18OTR) chronology from Mae Tuen (MT) site, Tak province, northwestern Thailand at inter-annual (167-year, A.D.1850–2016) and intra-annual (A.D.2006–2016) timescales. The inter-annual δ18OTR chronology showed a significant negative correlation ( r = −0.678, p < 0.01) with the May–October amount of regional rainfall obtained from CRU TS4.03. We established a linear regression model that explained 46.0% of the actual rainfall variance and reconstructed monsoon season rainfall back to A.D.1850. The seasonal variations in moisture conditions were reflected in inter-annual δ18OTR variability. The rainfall amount and δ18O in precipitation (δ18Op) mainly controlled intra-annual variations in teak δ18OTR. These results show that the variation in Thai teak δ18OTR is dominated by rainfall, highlighting the strength of δ18OTR as a monsoon rainfall proxy.

Deviations of satellite-measured sea surface salinity caused by environmental factors and their regional dependence

Satellite measurements have largely improved sea surface salinity (SSS) observations in the recent decade, including Soil Moisture Ocean Salinity (SMOS), Aquarius/Satélite de Aplicaciones Científicas (SAC) D, and Soil Moisture Active-Passive (SMAP). This study evaluates the deviations between the satellite SSS products and the in-situ observations (ΔS) and analyses their relationships with the environmental factors, including sea surface temperature (SST), precipitation, and wind speed. The level 3 satellite SSS generally correlates well with Argo-observed SSS but differs in the middle and high latitudes and the tropical convergence zones. The smallest ΔS appears in the subtropical open oceans, where the sea surface features warm SST, rare precipitation, and low wind speed. The variations in mean |ΔS| for the three satellites show a robust dependence on SST, precipitation, and wind, with large ΔS (outside 5%–95% interval) in particular tending to occur in areas of cold SST, heavy rainfall, and high wind speeds. The most pronounced SSS deviations occur in the middle and high latitudes (beyond 40°) due to cold SST. In particular, heavy rainfall in the subpolar regions and strong westerly winds in the mid-latitudes also make the satellite SSS measurements less accurate. In the tropical convergence zones, large SSS deviations are mainly related to heavy rainfall, showing significant surface freshening. The fresh biases related to rainfall are more significant in Level 2 SSS than in Level 3, due to the short period of the convective rainfall. In addition, surface freshening is more obvious in low wind speed scenarios, showing that the fresh skin layer induced by rain is more common on the calm ocean surface.