Spatial Rainfall Characteristics Research Articles

Analysis of Monthly Rainfall Characteristics in Nusa Tenggara Timur and its Spatial and Temporal Shifts

The spatial characteristics of rainfall in Nusa Tenggara Timu for the periods 1961-1990 and 1991-2020 show similarities in terms of topography influencing local variations in rainfall intensity. Additionally, inland areas and the northern side of region experience higher rainfall compared to the coastal areas and the southern side. On the other hand, temporal characteristics reveal a monsoonal rainfall pattern with peak precipitation occurring in January and the lowest rainfall in August. Furthermore, there is a normal shift in rainfall patterns between the two periods, marked by a reduction in the intensity of dark colors in the 1991-2020 period compared to 1961-1990. There is also a positive shift in normal rainfall values for the months of April and December, while the remaining months experience a negative shift.

Extraction of Spatiotemporal Distribution Characteristics and Spatiotemporal Reconstruction of Rainfall Data by PCA Algorithm

Scientific analyses of urban flood risks are essential for evaluating urban flood insurance and designing drainage projects. Although the current rainfall monitoring system in China has a dense station network and high-precision rainfall data, the time series is short. In contrast, historical rainfall data have a longer sample time series but lower precision. This study introduced a PCA algorithm to reconstruct historical rainfall data. Based on the temporal and spatial characteristics of rainfall extracted from high-resolution rainfall data over the past decade, historical (6 h intervals) rainfall spatial data were reconstructed into high-resolution (1 h intervals) spatial data to satisfy the requirements of the urban flood risk analysis. The results showed that the average error between the reconstructed data and measured values in the high-value area was within 15% and in the low-value area was within 20%, representing decreases of approximately 65% and 40%, respectively, compared to traditional interpolation data. The reconstructed historical spatial rainfall data conformed to the temporal and spatial distribution characteristics of rainfall, improved the granularity of rainfall spatial data, and enabled the effective and reasonable extraction and summary of the fine temporal and spatial distribution characteristics of rainfall.

Emergence of heavy tails in streamflow distributions: the role of spatial rainfall variability

Flow events with low frequency often cause severe damage, especially if their magnitudes are higher than suggested by historical observations. The heavier right tail of streamflow distribution indicates the increasing probability of high flows. In this paper, we investigate the role played by spatially variable rainfall in enhancing the tail heaviness of streamflow distributions. We synthetically generated a wide range of spatially variable rainfall inputs and fed them to a continuous probabilistic model of the catchment water transport to simulate streamflow in five German catchments with distinct properties in size and topography. Meanwhile, we used a comparable approach to analyze rainfall and runoff records from 175 German catchments. We identified the effects of spatially variable rainfall on the tails of streamflow distributions from both simulation scenarios and data analyses. Our results show that the tail of streamflow distribution becomes heavier with increasing spatial rainfall variability only beyond a certain threshold. This finding indicates the capability of catchments to buffer growing heterogeneities of rainfall, which we term catchment resilience to increasing spatial rainfall variability. The analyses suggest that the runoff routing through the river network controls this property. In fact, both small and elongated catchments are less resilient to increasing spatial rainfall variability due to their intrinsic runoff routing characteristics. We show the links between spatial rainfall characteristics and catchment geometry and the possible occurrence of high flows. The data analyses we performed on a large set of case studies confirm the simulation results and provide confidence for the transferability of these findings.

Atmospheric circulation types controlling rainfall in the Central American Isthmus

AbstractRainfall mechanisms in the Central American Isthmus are controlled by complex physical interactions across spatial and temporal scales, which are reflected on the dynamics of atmospheric circulation patterns affecting the region. However, physical mechanisms and their relationships with thermodynamic distributions connected to overturning circulations remain elusive. Here, a set of six recurrent daily atmospheric patterns, or weather types (WT), is defined using a k‐means++ clustering algorithm on standardized fields of Convective Available Potential Energy (CAPE) and winds at 925, 850, and 200 hPa. The relationships between these weather types, their temporal characteristics, and anomalous distributions of moisture flux divergence, equivalent potential temperature (saturated and unsaturated), and observed rainfall are used to describe physical processes controlling the latter, for all seasons. Regional observed rainfall is analysed from a set of 174 automatic stations from all countries from Mexico to Panama. By modulating vertically integrated moisture fluxes, these weather types, and the different climate drivers linked to them, control the temporal and spatial rainfall characteristics in the region, especially over the Pacific side of the isthmus. During some stages of the regional rainy season, described by two weather types, thermal anomalies in convective quasi‐equilibrium characteristic of the upward branch of the Hadley cell force westerly flow over Central America, enhancing rainfall. While during other stages, the enhancement of the trades and the displacement of convection to the ITCZ area over the eastern tropical Pacific, characteristic of the midsummer drought, diminishes rainfall. This study sets the stage for a better understanding of the mechanistic relationship between these weather types and rainfall characteristics in general, like onset, demise, and duration of rainy seasons. Hence, these results can inform process‐based model diagnostics aiming at bias‐correcting climate predictions at multiple timescales.

Flood Discharge Prediction Based on Remote-Sensed Spatiotemporal Features Fusion and Graph Attention

Floods have brought a great threat to the life and property of human beings. Under the premise of strengthening flood control engineering measures and following the strategic thinking of sustainable development, many achievements have been made in flood forecasting recently. However, due to the complexity of the traditional lumped model and distributed model, the hydrologic parameter calibration process is full of difficulties, leading to a long development cycle of a reasonable hydrologic prediction model. Even for modern data-driven models, the spatial distribution characteristics of the rainfall data are also not fully mined. Based on this situation, this paper abstracts the rainfall data into the graph structure data, uses remote sensing images to extract the elevation information, introduces the graph attention mechanism to extract the spatial characteristics of rainfall, and employs long-term and short-term memory (LSTM) network to fuse the spatial and temporal characteristics for flood prediction. Through well-designed experiments, the forecasting effect of flood peak value and flood arrival time is verified. Furthermore, compared with the LSTM model and BIGRU model without spatial feature extraction, the advantages of spatiotemporal feature fusion are highlighted. The specific performance is that the RMSE (the root means square error) and R2 (coefficient of determination) of the GA-RNN model have been significantly improved. Finally, we conduct experiments on the observed ten rainfall events in the history of the target watershed. According to the hydrological prediction specifications, the model can be evaluated as a Class B flood forecasting model.

Spatial and Temporal Characteristics of Rainfall Anomalies in 1961–2010 in the Yangtze River Basin, China

Understanding rainfall anomalies and their relationship with floods in the Yangtze River Basin (YRB) is essential for evaluating flood disasters, which have a great impact on the development of agriculture and the economy. On the basis of daily rainfall data from 1961 to 2010 from 178 meteorological stations, the temporal and spatial characteristics of rainfall anomalies in the YRB were studied on an annual scale, seasonal scale, and monthly scale. The annual rainfall of the YRB showed a generally increasing trend from 1961 to 2010 (14.22 mm/10 a). By means of the Bernaola–Galvan abrupt change test and Redfit spectrum analysis, it was found that the annual average rainfall increased abruptly after 1979 and had a cycle of 2–3 years. On the seasonal scale, the rainfall in spring and autumn showed a gradually decreasing trend, especially in September, while it showed a significant increasing trend in summer and winter in the YRB. As for the monthly scale, the rainfall in the rainy season from June to July presented a clear increasing trend during the study period, which greatly enhanced the probability of floods in the YRB. Additionally, through the analysis of the spatial distribution characteristics of rainfall in the entire YRB from 1961 to 2010, it was observed that the annual rainfall amount in the YRB presented an “increase–decrease–increase” tendency from east to west, accompanied by a rain belt that continuously moved from west to east. Moreover, the rainfall characteristics in flood years were summarized, and the results revealed that the years with rainfall anomalies were more likely to have flood disasters. However, anomalies alone would not result in big floods; the spatially and temporally inhomogeneous rainfall distribution might be the primary reason for flood disasters in the entire YRB.

Using multiple indexes to analyze temporal and spatial patterns of precipitation and drought in Xinjiang, China

There is an urgent need to understand the characteristics of both precipitation and drought in arid regions of China. Different indexes may provide differing results in terms of the detection and estimation of the temporal and spatial extent of droughts. In this study, the temporal and spatial characteristics of rainfall and drought at 53 meteorological stations from 1960 to 2016 across the Xinjiang region of China were analyzed. Four precipitation-related indexes (precipitation concentration degree (PCD), precipitation concentration period (PCP), standardized precipitation index (SPI), and long-cycle drought–flood abrupt alternation index (LDFAI)) were used to investigate the spatial and temporal patterns of drought and flood. In addition, the Bayesian method and Pettitt test were used as detection tools to identify changing points in precipitation time series. The study indicated the following: (1) a wetting tendency was evident in recent years and was supported by the upward trend in SPI and inter-decadal variation in summer precipitation; (2) the spatial patterns and tendencies of PCD, PCP, and SPI were markedly different in southern and northern Xinjiang; (3) compared with the Pettitt test, use of the Bayesian method provided data closer to the real drought events; (4) it is suggested that multiple indices be used for detecting precipitation and drought characteristics as use of the SPI may lead to other indexes related to flood and drought risks being ignored.

Rainfall disaggregation for hydrological modeling: is there a need for spatial consistence?

Abstract. In this study, the influence of disaggregated rainfall products with different degrees of spatial consistence on rainfall–runoff modeling results is analyzed for three mesoscale catchments in Lower Saxony, Germany. For the disaggregation of daily rainfall time series into hourly values, a multiplicative random cascade model is applied. The disaggregation is applied on a station by station basis without consideration of surrounding stations; hence subsequent steps are then required to implement spatial consistence. Spatial consistence is represented here by three bivariate spatial rainfall characteristics that complement each other. A resampling algorithm and a parallelization approach are evaluated against the disaggregated time series without any subsequent steps. With respect to rainfall, clear differences between these three approaches can be identified regarding bivariate spatial rainfall characteristics, areal rainfall intensities and extreme values. The resampled time series lead to the best agreement with the observed ones. Using these different rainfall products as input to hydrological modeling, we hypothesize that derived runoff statistics – with emphasis on seasonal extreme values – are subject to similar differences as well. However, an impact on the extreme values' statistics of the hydrological simulations forced by different rainfall approaches cannot be detected. Several modifications of the study design using rainfall–runoff models with and without parameter calibration or using different rain gauge densities lead to similar results in runoff statistics. Only if the spatially highly resolved rainfall–runoff WaSiM model is applied instead of the semi-distributed HBV-IWW model can slight differences regarding the seasonal peak flows be identified. Hence, the hypothesis formulated before is rejected in this case study. These findings suggest that (i) simple model structures might compensate for deficiencies in spatial representativeness through parameterization and (ii) highly resolved hydrological models benefit from improved spatial modeling of rainfall.

Hydrological response of a large-scale mountainous watershed to rainstorm spatial patterns and reforestation in subtropical China

This paper aims to investigate the hydrological response of a large-scale (8973 km2) mountainous watershed to different rainstorm spatial patterns and reforestation. Based on 32 years of observations, measurements of 184 rainstorm events and 125 sediment-producing events with complete hydrographs were analyzed. The K-means clustering method was used to classify the spatial patterns of rainstorm events in accordance with their event-based spatial rainfall characteristics. The 184 rainstorm events were classified into four spatial patterns, among which the spatial features differ significantly: (I) Spatial Pattern I (SPI) includes rainstorms with a low amount of cumulative areal rainfall (27.4 mm), the highest spatial variability (0.986), and the highest frequency; (II) Spatial Pattern II (SPII) includes rainstorms of high spatial variability (0.759) and the largest amount of local maximum daily rainfall (106.8 mm); (III) Spatial Pattern III (SPIII) includes rainstorms with a medium amount of cumulative areal rainfall (58.7 mm) and low spatial variability (0.362); and (IV) Spatial Pattern IV (SPIV) includes rainstorms with the largest amount of cumulative areal rainfall (117.2 mm) and the lowest spatial variability (0.313). Vegetation cover in the upper Du watershed was significantly improved after the implementation of the Grain-for-Green project. The average area-specific sediment yields (SSY) for the four SPs were 15.4, 65.5, 55.8, and 286.2 t km−2 before reforestation and decreased to 6.0, 59.3, 43.7 and 89.9 t km−2, respectively, after reforestation. ANOVA (analysis of variance) indicated that reforestation resulted in a significant reduction in runoff coefficient under SPIII and SPIV and a significant reduction in SSY under SPI and SPIV. A hysteresis analysis suggested that the proportion of events with a clockwise loop increased from 64.9% before reforestation to 82.1% after reforestation and that complex loops became less common during 2000–2010 under SPIV, thereby implying a reduced sediment supply.

Drought monitoring and reliability evaluation of the latest TMPA precipitation data in the Weihe River Basin, Northwest China

The high resolution satellite precipitation products bear great potential for large-scale drought monitoring, especially for those regions with sparsely or even without gauge coverage. This study focuses on utilizing the latest Version-7 TRMM Multi-satellite Precipitation Analysis (TMPA 3B42V7) data for drought condition monitoring in the Weihe River Basin (0.135×106 km2). The accuracy of the monthly TMPA 3B42V7 satellite precipitation data was firstly evaluated against the ground rain gauge observations. The statistical characteristics between a short period data series (1998–2013) and a long period data series (1961–2013) were then compared. The TMPA 3B42V7-based SPI (Standardized Precipitation Index) sequences were finally validated and analyzed at various temporal scales for assessing the drought conditions. The results indicate that the monthly TMPA 3B42V7 precipitation is in a high agreement with the rain gauge observations and can accurately capture the temporal and spatial characteristics of rainfall within the Weihe River Basin. The short period data can present the characteristics of long period record, and it is thus acceptable to use the short period data series to estimate the cumulative probability function in the SPI calculation. The TMPA 3B42V7-based SPI matches well with that based on the rain gauge observations at multiple time scales (i.e., 1-, 3-, 6-, 9-, and 12-month) and can give an acceptable temporal distribution of drought conditions. It suggests that the TMPA 3B42V7 precipitation data can be used for monitoring the occurrence of drought in the Weihe River Basin.

Spatial Characteristics of Rainfall at Sparsely Distributed Station Network over the High-Latitude Mountainous Regions in Eastern Siberia

To describe the spatial characteristics of rainfall at sparsely distributed measurement network over the high-latitude mountainous regions in eastern Siberia through ground-based observation, rainfall observations were performed using non-recording standard rain gauges. Such standard rain gauges have been used over the years to measure annual rainfall at six sites from the Suntar Khayata Range to Oymyakon and 12 sites along the Kolyma Highway from Magadan to Agayakan. Relational expressions of rainfall were obtained and observation data from these gauges clearly showed that the corrected rainfall in these areas depends on altitude, that the rainfall increased slightly with an increase in altitude, and that the increased ratio of rainfall due to altitude decreased with an increase in the distance from the nearby coast.

A Global Assessment of the Spatial Distribution of Precipitation Occurrence

AbstractThe spatial distribution of precipitation occurrence has important implications for numerous applications ranging from defining cloud radiative effects to modeling hydrologic runoff, statistical downscaling, and stochastic weather generation. This paper introduces a new method of describing the spatial characteristics of rainfall and snowfall that takes advantage of the high sensitivity and high resolution of the W-band cloud precipitation radar aboard CloudSat. The resolution dependence of precipitation occurrence is described by a two-parameter exponential function defined by a shape factor that governs the variation in the distances between precipitation events and a scale length that represents the overall probability of precipitation and number density of distinct events.Geographic variations in the shape factor and scale length are consistent with large-scale circulation patterns and correlate with environmental conditions on local scales. For example, a large contrast in scale lengths between land and ocean areas reflects the more extensive, widespread nature of precipitation over land than over ocean. An analysis of warm rain in the southeast Pacific reveals a shift from frequent isolated systems to less frequent but more regularly spaced systems along a transect connecting stratocumulus and trade cumulus cloud regimes. A similar analysis during the Amazon wet season reveals a relationship between the size and frequency of convection and zonal wind direction with precipitation exhibiting a more oceanic character during periods of westerly winds. These select examples demonstrate the utility of this approach for capturing the sensitivity of the spatial characteristics of precipitation to environmental influences on both local and larger scales.

Temporal Rainfall Disaggregation with a Cascade Model: From Single-Station Disaggregation to Spatial Rainfall

Temporal rainfall disaggregation is an important tool to obtain high-resolution rainfall data, which are needed in many fields of hydrology and water resources management. The multiplicative random cascade model can be used for temporal rainfall disaggregation of daily time series. A resampling algorithm is introduced to implement spatial consistence in disaggregated time series. Spatial consistence is assumed to be represented by four bivariate and distance-dependent rainfall characteristics that complement each other. Relative diurnal cycles of the disaggregated time series are resampled with the aim to reproduce these spatial characteristics while preserving the structure generated by the cascade model. Also, to achieve a final resolution of 1 h the traditional cascade model has been modified. A modification called uniform splitting with a branching number of 3 in the first step is introduced. Results are compared with observations and an approach called diversion. In total 22 recording stations in Northern Germany with hourly resolution were used for the validation of the disaggregation procedure, starting with daily values. Investigation areas are two catchments considering different station densities. The results show that for the disaggregation, errors of time series characteristics between 3 and 12% occur. The nonexceedance curves of rainfall intensities are slightly overestimated. Extreme values are well represented. The uniform splitting method outperforms the diversion method. Spatial rainfall characteristics can be reproduced by the simulating annealing algorithm. However, with an increasing number of stations the reproduction performance declines for some rainfall characteristics. Nonexceedance curves of areal rainfall based on disaggregated and not resampled time series are generally underestimated. By application of the resampling algorithm, a better performance regarding the spatial characteristics can be achieved. The presented resampling algorithm also has the potential to be used for implementing spatial consistence for time series generated by other disaggregation models.

Analysis of human vulnerability to the extreme rainfall event on 21–22 July 2012 in Beijing, China

Abstract. The aim of this study is to characterize the extreme rainfall event on 21–22 July 2012 in Beijing, and its impact on human vulnerability. Based on the available meteorological and rainfall data from Beijing meteorological stations and Surface Weather Observation Stations, the study draws hourly rainfall maps to simulate the rainfall amount and spatial distribution. Using these maps, this paper provides a quantitative analysis of the impact of the temporal and spatial characteristics of rainfall on the vulnerability of three population groups, according to age, gender and total number of victims. The results of three linear regression models indicate the different effects of extreme rainfall parameters on victims with different characteristics. The analysis of victim data in this extreme rainfall event represents the distribution and characteristics of victims in the eight affected districts, and concludes that the "vulnerable group" are males and adults in this extreme rainfall event. This paper is an initial effort to analyze the impact of an extreme rainfall event on the vulnerability of populations with different characteristics quantitatively, which can be used by stakeholders to prioritize the extreme rainfall event impact issues, and develop contingency plans to address and prevent the human and structural damages caused by the extreme rainfall events.

서울지역 강우의 시·공간적 특성 분석

본 연구에서는 서울지역에서의 강우의 시 공간적 특성을 파악하기 위하여 크리깅 기법과 이동평균법을 적용하였다. 강우의 시간적 특성을 분석하기 위하여 가중이동평균법과 지수이동평균법을 적용하여 각각의 가중치에 따른 오차를 분석하였다. 최소오차가 발생하는 가중이동 평균법을 이용하여 서울기상대와 AWS자료를 분석한 결과, 여름강우 중 장마를 제외한 나머지 기간에 강우가 집중되고 있으며, 강우량 또한 증가하는 추세를 보였다. 강우의 공간적 특성을 분석하기 위하여 크리깅 기법을 적용하였으며, 크리깅 기법 중 spherical model이 대상지역의 집중호우에 대한 공간적 분포를 가장 잘 묘사하였다. 그리고 강우강도에 따라 매개변수를 산정하여 비교하였다. 분석결과 크리깅 기법을 적용한 면적평균강우량이 티센가중법에 의한 면적평균강우량 산정으로 인한 과대추정의 위험을 줄일 수 있을 것으로 판단된다. In this study, kriging and moving average method were applied in order to comprehend temporal and spatial characteristics of rainfall in Seoul area. Errors were estimated depending on weights of weighted moving average model and exponential moving average model for analyzing temporal characteristics of rainfall. According to the results of the analysis of rainfall database of the Seoul Meteorology Station and AWS(Automatic Weather Station) by using the weighted moving average model having minimum errors, rainfall was concentrated in the summer months except for the rainy season and tend to increase the total amount of rainfall. The kriging was applied for analyzing spatial characteristics of rainfall and the spherical model well depicted spatial distribution of urban heavy rain in target area. And parameters were calculated and analyzed in accordance with rainfall intensity. The result show area-averaged rainfall using kriging reduced risk of overestimation of area-averaged rainfall using Thiessen weighting method.

기후변화 영향을 고려한 도시지역의 확률강우량 전망

Recent inundation damage has frequently occurred due to heavy rainfall in urban area, because rainfall has locally occurred exceeding the capability of a flood control plan by the exiting design rainfall from the data of Seoul weather station. Accordingly the objective of this study is to predict new design rainfall in order to make a future flood control plan considering climate change. In this study, for considering spatial characteristics of rainfall in urban area, data of AWS was used and for retaining insufficient rainfall data, WGR model was estimated the application of target area. The results were compared with the observation data and consequently show reasonable results. In addition, to prepare for climate change, design rainfall was calculated by applying for various climate scenarios and the result would be used in order to establish future flood control plan.

AWS 자료를 이용한 우리나라의 물 공급 안전도 평가

AWS data can be used effectively to understand the rainfall characteristics in Korea. In spite of this advantage, AWS data have been used restrictively in flood control analysis and the study on water use analysis such as water balance assessment is very insufficient. In this study, AWS data are used to analyze spatial rainfall characteristics quantitatively and water balance assessment is performed based on AWS data. Water balance assessment is carried out from year 2002 to year 2010 considering water supply networks in Korea. The analysis shows that year 2009 is the driest year during 9 years (2002~2010) and the regions with low level water supply reliability are concentrated in the west coast of Jeonnam and the upper region of the Nakdong River. As a result, the regions that have a lack of available water resources such as the coastal and insular areas are vulnerable to droughts. Therefore, regional water supply and management plans are urgently needed. Additionally, AWS data, which consider rainfall characteristics of the coastal and insular areas, can be useful in water balance assessment.

Temporal and spatial characteristics of rainfall in the Lishui river basin

Based on data from 10 rainfall observation stations,hydrology statistics and correlation methods were used to analyze the spatial distribution,annual distribution and inter-annual variation of the annual average rainfall in the Lishui river basin.The general trend is that the annual average rainfall reduces gradually from the upper to the lower reaches of the River Basin,from the north-western mountain-hilly area to the south-eastern lakeside plain.Meanwhile,there is a connection between rainfall and elevation: as elevation lowers every 100 m,the annual rainfall reduces 137.76 mm;besides,the seasonal variation is quite evident,and the distribution throughout the year is uneven,with the uneven coefficient reaches 0.25.What's more,obvious inter-annual variation do exist,inter-annual variation in the middle and the lower reaches are greater than that of the upper one.Wet-dry periods during raining years last long and change greatly.It is recorded that the longest period being consistent wet is three years and four for being consistent dry.

Accuracy Assessment of Unit Hydrographs: Point versus Spatially Integrated Rainfall Input

A unit hydrograph (UH) reflects the hydrologic response of watershed processes to a rainfall event. Most UH analyses use measured rainfall from a single rain gauge even though rainfall from a single gauge may not adequately reflect either the spatial or temporal variation during a storm event. The intent of this study was to better understand factors that influence UH accuracy, especially the spatial characteristics of rainfall. Analyses were made by using runoff and rainfall data, including radar rainfall measurements, from the densely monitored Walnut Gulch watershed, Arizona. Transmission loss (TL), as a physical process, is shown to be an important factor that influences UH shape. Multiple-storm, multiple rain gauge analyses show that rainfall from a single gauge is unlikely to yield a UH that reflects the watershed response. A comparison of UHs spatially averaged by using the temporal Thiessen method agree with UHs developed by using radar rainfall measurements. Intra-watershed analyses indicate that...

Temporal and spatial characteristics of rainfall on the southwest slope of Mt. Merapi in Indonesia

Temporal and spatial characteristics of rainfall on the southwest slope of Mt. Merapi in Indonesia